Restdist reads the same restriction sites format as RESTML and
computes a restriction sites distance. It can also compute a restriction
fragments distance. The original restriction fragments and restriction
sites distance methods were introduced by Nei and Li (1979). Their original
method for restriction fragments is
also available in this program, although its default methods
are my modifications of the original Nei and Li methods.
These two distances assume that the restriction sites are accidental byproducts
of random change of nucleotide sequences. For my restriction sites distance
the DNA sequences are assumed to be changing according to the Kimura
2-parameter model of DNA change (Kimura, 1980). The user can set the
transition/transversion rate for the model. For my restriction fragments
distance there is
there is an implicit assumption of a Jukes-Cantor (1969) model of change,
The user can also set the
parameter of a correction for unequal rates of evolution between sites in
the DNA sequences, using a Gamma distribution of rates among sites.
The Jukes-Cantor model is also implicit in the restriction fragments
distance of Nei and Li(1979). It
does not allow us to correct for a Gamma distribution of rates among
sites.
Restriction Sites Distance
The restriction sites distances use data coded for the presence of absence of
individual restriction sites (usually as + and - or 0 and 1). My
distance is based on the proportion, out of all sites observed in one species
or the other, which are present in both species. This is done to correct for
the ascertainment of sites, for the fact that we are not aware of many sites
because they do not appear in any species.
My distance starts by computing from the particular pair of species the fraction
n++
f = ---------------------
n++ + 1/2 (n+- + n-+)
where n++ is the number of sites contained in both species,
n+- is the number of sites contained in the first of the
two species but not in the second, and n-+ is the
number of sites contained in the second of the two species but not in the
first. This is the fraction of sites that are present in one species which are
present in both. Since the number of sites present in the two species will
often differ, the denominator is the average of the number of sites found in
the two species.
If each restriction site is s nucleotides long, the probability
that a restriction site is present in the other species, given that it is
present in a species, is
Qs,
where Q is the probability that a nucleotide has no net change as one
goes from the one species to the other. It may have changed in between; we
are interested in the probability that that nucleotide site is in the same base
in both species, irrespective of what has happened in between.
The distance is then computed by finding the branch length of a two-species
tree (connecting these two species with a single branch) such
that Q equals the s-th root of f. For this the
program computes Q for various values of branch length, iterating them
by a Newton-Raphson algorithm until the two quantities are equal.
The resulting distance should be numerically close to the original
restriction sites distance of Nei and Li (1979). It is inspired by theirs,
but theirs differs by implicitly assuming a symmetric Jukes-Cantor (1969)
model of nucleotide change, and theirs does not include a correction for
Gamma distribution of rate of change among nucleotide sites.
Restriction Fragments Distance
For restriction fragments data we use a different distance. If we
average over all restriction fragment lengths, each at its own
expected frequency, the probability that the fragment will still be
in existence after a certain amount of branch length, we must take into
account the probability that the two restriction sites at the ends of
the fragment do not mutate, and the probability that no new
restriction site occurs within the fragment in that amount of branch
length. The result for a restriction site length of s is:
Q2s
f = --------
2 - Qs
(The details of the derivation will be given in my forthcoming book
Inferring Phylogenies (to be published by Sinauer Associates
in 2001).
Given the observed fraction of restriction sites retained, f,
we can solve a quadratic equation from the above expression for
Qs. That makes it easy to obtain a value of Q,
and the branch length can then be estimated by adjusting it so the
probability of a base not changing is equal to that value.
Alternatively, if we use the Nei and Li (1979) restriction fragments
distance, this involves solving for g in the nonlinear
equation
g = [ f (3 - 2g) ]1/4
and then the distance is given by
d = - (2/r) loge(g)
where r is the length of the restriction site.
Comparing these two restriction fragments distances in a case
where their underlying DNA model is the same (which is when the
transition/transversion ratio of the modified model is set to
0.5), you will find
that they are very close to each other, differing very little at
small distances, with the modified distance become smaller than
the Nei/Li distance at larger distances. It will therefore matter
very little which one you use.
A Comment About RAPDs and AFLPs
Although these distances are designed for restriction sites
and restriction fragments data, they can be applied to RAPD and
AFLP data as well. RAPD (Randomly Amplified Polymorphic DNA)
and AFLP (Amplified Fragment Length Polymorphism) data consist
of presence or absence of individual bands on a gel. The bands
are segments of DNA with PCR primers at each end. These
primers are defined sequences of known length (often about
10 nucleotides each). For AFLPs the reolevant length is the primer
length, plus three nucleotides. Mutation in these sequences makes them no
longer be primers, just as in the case of restriction sites.
Thus a pair of 10-nucleotide primers will behave much the same
as a 20-nucleotide restriction site. You can use the restriction
sites distance as the distance between RAPD or AFLP patterns if you
set the proper value for the total length of the site to the
total length of the primers (plus 6 in the case of AFLPs).
Of course there are many possible sources of noise in these data,
including confusing fragments of similar length for each other
and having primers near each other in the genome, and these are
not taken into account in the statistical model used here.
INPUT FORMAT AND OPTIONS
The input is fairly standard, with one addition. As usual the first line of
the file gives the number of species and the number of sites, but there is also
a third number, which is the number of different restriction enzymes that were
used to detect the restriction sites. Thus a data set with 10 species and
35 different sites, representing digestion with 4 different enzymes, would
have the first line of the data file look like this:
10 35 4
The site data are in standard form. Each species starts with a species name
whose maximum length is given by the constant "nmlngth"
(whose value in the
program as distributed is 10 characters). The name should, as usual, be padded
out to that length with blanks if necessary. The sites data then follows, one
character per site (any blanks will
be skipped and ignored). Like the DNA and protein sequence data, the
restriction sites data may be either in the "interleaved" form or the
"sequential" form. Note that if you are analyzing restriction sites
data with the programs DOLLOP or MIX or other discrete character
programs, at the moment those programs do not use the "aligned" or
"interleaved" data format. Therefore you may want to avoid that format
when you have restriction sites data that you will want to feed into
those programs.
The presence of a site is indicated by a "+" and the absence by a "-". I have
also allowed the use of "1" and "0" as synonyms for "+" and "-", for
compatibility with MIX and DOLLOP which do not allow "+" and "-". If the
presence of
the site is unknown (for example, if the DNA containing it has been deleted so
that one
does not know whether it would have contained the site) then the state "?" can
be used to indicate that the state of this site is unknown.
The options are selected using an interactive menu. The menu looks like this:
Restriction site or fragment distances, version 3.6a3
Settings for this run:
R Restriction sites or fragments? Sites
G Gamma distribution of rates among sites? No
T Transition/transversion ratio? 2.000000
S Site length? 6.0
L Form of distance matrix? Square
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run? No
2 Print indications of progress of run? Yes
Y to accept these or type the letter for one to change
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The R option toggles between a restriction sites distance, which
is the default setting, and a restriction fragments distance. In
the latter case, another option appears, the N (Nei/Li) option.
This allows the user to choose the original Nei and Li (1979)
restriction fragments distance rather than my modified Nei/Li
distance, which is the default.
If the G (Gamma distribution) option is selected, the user will be
asked to supply the coefficient of variation of the rate of substitution
among sites. This is different from the parameters used by Nei and Jin, who
introduced Gamma distribution of rates in DNA distances, but
related to their parameters: their parameter a is also known as
"alpha", the shape parameter of the Gamma distribution. It is
related to the coefficient of variation by
CV = 1 / a1/2
or
a = 1 / (CV)2
(their parameter b is absorbed here by the requirement that time is scaled so
that the mean rate of evolution is 1 per unit time, which means that a = b).
As we consider cases in which the rates are less variable we should set a
larger and larger, as CV gets smaller and smaller.
The Gamma distribution option is not available when using the
original Nei/Li restriction fragments distance.
The T option is the Transition/transversion option. The user is prompted for
a real number greater than 0.0, as the expected ratio of transitions to
transversions. Note
that this is the resulting expected ratio of transitions to transversions.
The default value of the T parameter if you do not use the T
option is 2.0. The T option is not available when you choose the original
Nei/Li restriction fragment distance, which assumes a Jukes-Cantor (1969)
model of DNA change, for which the transition/transversion ratio is
in effect fixed at 0.5.
The S option selects the site length. This is set to a default
value of 6. It can be set to any positive integer. While in
the RESTML program there is an upper limit on the restriction
site length (set by memory limitations), in RESTDIST there is
no effective limit on the size of the restriction sites. A value
of 20, which might be appropriate in many cases for RAPD or AFLP
data, is typically not practical in RESTML, but it is useable in
RESTDIST.
Option L specifies that the output file will have a square matrix
of distances. It can be used to change to lower-triangular
data matrices. This will usually not be
necessary, but if the distance matrices are going to be very
large, this alternative can reduce their size by half. The
programs which are to use them should then of course be informed
that they can expect lower-triangular distance matrices.
The M, I, and 0 options are the usual Multiple data set,
Interleaved input, and screen terminal type options. These are
described in the main documentation file.
Option 1 specifies that the input data will be written out
on the output file before the distances. This is off by
default. If it is done, it will make the output file unusable
as input to our distance matrix programs.
Option 2 turns off or on the indications of the progress of the run.
The program prints out a row of dots (".") indicating the
calculation of individual distances. Since the distance matrix
is symmetrical, the program only computes the distances for the
upper triangle of the distance matrix, and then duplicates
the distance to the other corner of the matrix. Thus the rows of
dots start out of full length, and then egt shorter and shorter.
OUTPUT FORMAT
The output file contains on its first line the number of species. The
distance matrix is then printed in standard
form, with each species starting on a new line with the species name, followed
by the distances to the species in order. These continue onto a new line
after every nine distances. If the L option is used, the matrix or distances
is in lower triangular form, so that only the distances to the other species
that precede each species are printed. Otherwise the distance matrix is square
with zero distances on the diagonal. In general the format of the distance
matrix is such that it can serve as input to any of the distance matrix
programs.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the menu
selections. The output file begins by giving the number of species and the
number of characters.
The distances printed out are scaled in terms of expected numbers of
substitutions per DNA site, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate of
change, averaged over all sites analyzed, is set to 1.0. Thus when the
G option is used, the rate of change at one site may be higher than
at another, but their mean is expected to be 1.
PROGRAM CONSTANTS
The constants available to be changed are "initialv" and
"iterationsr". The constant "initialv" is the starting
value of the distance in the iterations. This will typically not need to
be changed. The constant "iterationsr" is the number of
times that the Newton-Raphson method which is used to solve the
equations for the distances is iterated. The program can be
speeded up by reducing the number of iterations from the default
value of 20, but at the possible risk of computing the distance
less accurately.
FUTURE OF THE PROGRAM
The present program does not compute the original distance of Nei and Li (1979)
for restriction sites (though it does have an option to compute their original
distance for restriction fragments). I hope to add their restriction
sites distance in the near future.
CONTENTS OF OUTPUT FILE (with all numerical options on)
(Note that when the options for displaying the input data are turned off,
the output is in a form suitable for use as an input file in the distance
matrix programs).
Note: Clique is an Old Style program. This means that it takes
some of its options information, notably the
Weights, Ancestral states and Factors
options from the input file rather than from separate files of their own
as the New Style programs in this version of PHYLIP do.
This program uses the compatibility method for unrooted two-state
characters to obtain the largest cliques of characters and the trees
which they suggest. This approach originated in the work of Le Quesne
(1969), though the algorithms were not precisely specified until the
later work of Estabrook, Johnson, and McMorris (1976a, 1976b). These
authors proved the theorem that a group of two-state characters which
were pairwise compatible would be jointly compatible. This program uses
an algorithm inspired by the Kent Fiala - George Estabrook program
CLINCH, though closer in detail to the algorithm of Bron and Kerbosch
(1973). I am indebted to Kent Fiala for pointing out that paper to me,
and to David Penny for decribing to me his branch-and-bound approach to
finding largest cliques, from which I have also borrowed. I am
particularly grateful to Kent Fiala for catching a bug in versions 2.0
and 2.1 which resulted in those versions failing to find all of the
cliques which they should. The program computes a compatibility matrix
for the characters, then uses a recursive procedure to examine all
possible cliques of characters.
After one pass through all possible cliques, the program knows the
size of the largest clique, and during a second pass it prints out the
cliques of the right size. It also, along with each clique, prints out a
the tree suggested by that clique.
INPUT, OUTPUT, AND OPTIONS
Input to the algorithm is
standard, but the "?", "P", and "B" states are not allowed. This is a
serious limitation of this program. If you want to find large cliques in
data that has "?" states, I recommend that you use MIX instead with the T
(Threshold) option and the value of the threshold set to 2.0. The theory
underlying this is given in my paper on character weighting (Felsenstein,
1981b).
The options are chosen from a menu, which looks like this:
Largest clique program, version 3.6a3
Settings for this run:
A Use ancestral states in input file? No
C Specify minimum clique size? No
O Outgroup root? No, use as outgroup species 1
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? none
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out compatibility matrix No
4 Print out tree Yes
5 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
The A (Ancestors), O (Outgroup) and M (Multiple Data Sets)
options are the usual ones, described in the main
documentation file. However, Clique being an Old Style program,
the options information for the Ancestors, Factors, and Weights
options must be specified, not in separate files, but in the input
data file. This is done by putting the letters A, F, or W on
the first line of the input file, separated by blanks from the
number of characters. The options information then follows, with the
first line of each option's information starting with its letter,
followed by at least 9 spaces or other characters to fill out to
the length of a species name before the options information occurs:
You can continue to a new line within the options information at
any time. Here is a simple example:
If you use option A (Ancestors) you should also choose it in the menu.
The compatibility matrix calculation in effect
assumes if the Ancestors option is invoked that there is in the data
another species that has all the ancestral states. This changes the
compatibility patterns in the proper way. The Ancestors option also
requires information on the ancestral states of each character to be in
the input file.
The Outgroup option will take effect only if the tree is not rooted by the
Ancestral States option.
The C (Clique Size) option indicates that
you wish to specify a minimum clique size and print out all cliques (and their
associated trees) greater than or equal to than that size. The program
prompts you for the minimum clique size.
Note that this allows you to list all cliques (each with its tree) by
simply setting the minimum clique size to 1. If you do one run and find
that the largest clique has 23 characters, you can do another run with
the minimum clique size set at 18, thus listing all cliques within 5
characters of the largest one.
Output involves a compatibility matrix (using the symbols "." and "1")
and the cliques and trees.
If you have used the F option there will be two lists of characters
for each clique, one the original multistate characters and the other the
binary characters. It is the latter that are shown on the tree. When the
F option is not used the output and the cliques reflect only the binary
characters.
The trees produced have it
indicated on each branch the points at which derived character states
arise in the characters that define the clique. There is a legend
above the tree showing which binary character is involved. Of course
if the tree is unrooted you can read the changes as going in either
direction.
The program runs very quickly but if the
maximum number of characters is large it will need a good deal of
storage, since the compatibility matrix requires ActualChars x ActualChars
boolean variables, where ActualChars is the number of characters (in the
case of the factors option the total number of true multistate characters.
ASSUMPTIONS
Basically the following assumptions are made:
Each character evolves independently.
Different lineages evolve independently.
The ancestral state is not known.
Each character has a small chance of being one which evolves
so rapidly, or is so thoroughly misinterpreted, that it
provides no information on the tree.
The probability of a single change in a character (other than
in the high rate characters) is low but not as low as the
probability of being one of these "bad" characters.
The probability of two changes in a low-rate character is much
less than the probability that it is a high-rate character.
The true tree has segments which are not so unequal in length
that two changes in a long are as easy to envisage as one
change in a short segment.
The assumptions of compatibility methods have been treated in
several of my papers (1978b, 1979, 1981b, 1988b), especially the 1981
paper. For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
A constant available for alteration at the beginning of the
program is the form width, "FormWide",
which you may want to change to make it as large as possible
consistent with the page width available on your output device,
so as to avoid the output of cliques and of trees getting wrapped
around unnecessarily.
PENNY is a program that will find all of the most parsimonious trees
implied by your data. It does so not by examining all possible trees,
but by using the more sophisticated "branch and bound" algorithm, a
standard computer science search strategy first applied to
phylogenetic inference by Hendy and Penny (1982). (J. S. Farris
[personal communication, 1975] had also suggested that this strategy,
which is well-known in computer science, might
be applied to phylogenies, but he did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem of
finding these has been shown (Graham and Foulds, 1982; Day, 1983) to be
NP-complete, which is equivalent to saying that there is no
fast algorithm that is guaranteed to solve the problem in all cases
(for a discussion of NP-completeness, see the Scientific American
article by Lewis and Papadimitriou, 1978). The result is that this
program, despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs
in the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of someone
who can let a microcomputer grind all night than for someone who
has the "benefit" of paying for time on the campus mainframe computer). IT
IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE PROGRAM
WILL TAKE ON YOUR DATA. This can be done by running it on subsets
of the species, increasing the number of species in the run until you
either are able to treat the full data set or know that the program
will take unacceptably long on it. (Making a plot of the logarithm of run
time against species number may help to project run times).
The Algorithm
The search strategy used by PENNY starts by making a tree consisting of the
first two species (the first three if the tree is to be unrooted). Then
it tries to add the next species in all possible places (there are three
of these). For each of the resulting trees it evaluates the number of
steps. It adds the next species to each of these, again in all
possible spaces. If this process would continue it would simply
generate all possible trees, of which there are a very large number even
when the number of species is moderate (34,459,425 with 10 species). Actually
it does not do this, because the trees are generated in a
particular order and some of them are never generated.
Actually the order in which trees are generated is not quite as
implied above, but is a "depth-first search". This
means that first one adds the third species in the first possible
place, then the fourth species in its first possible place, then
the fifth and so on until the first possible tree has been produced. Its
number of steps is evaluated. Then one "backtracks" by trying the
alternative placements of the last species. When these are exhausted
one tries the next placement of the next-to-last species. The
order of placement in a depth-first search is like this for a
four-species case (parentheses enclose monophyletic groups):
Make tree of first two species (A,B)
Add C in first place ((A,B),C)
Add D in first place (((A,D),B),C)
Add D in second place ((A,(B,D)),C)
Add D in third place (((A,B),D),C)
Add D in fourth place ((A,B),(C,D))
Add D in fifth place (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place (((A,D),C),B)
Add D in second place ((A,(C,D)),B)
Add D in third place (((A,C),D),B)
Add D in fourth place ((A,C),(B,D))
Add D in fifth place (((A,C),B),D)
Add C in third place (A,(B,C))
Add D in first place ((A,D),(B,C))
Add D in second place (A,((B,D),C))
Add D in third place (A,(B,(C,D)))
Add D in fourth place (A,((B,C),D))
Add D in fifth place ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species
rooted bifurcating trees, each exactly once (the parentheses each enclose
a monophyletic group). As displayed above, the backtracking
depth-first search algorithm is just another way of producing all
possible trees one at a time. The branch and bound algorithm
consists of this with one change. As each tree is constructed,
including the partial trees such as (A,(B,C)), its number of steps
is evaluated. In addition a prediction is made as to how many
steps will be added, at a minimum, as further species are added.
This is done by counting how many binary characters which are invariant in the
data up the species most recently added will ultimately show variation when
further species
are added. Thus if 20 characters vary among species A, B, and C and their
root, and if tree ((A,C),B) requires 24 steps, then if there are 8 more
characters which will be seen to vary when species D is added, we can
immediately say that no matter how we add D, the resulting tree can have no less
than 24 + 8 = 32 steps. The point of all this is that if a previously-found
tree such as ((A,B),(C,D)) required only 30 steps, then we know that
there is no point in even trying to add D to ((A,C),B). We have
computed the bound that enables us to cut off a whole line of inquiry
(in this case five trees) and avoid going down that particular branch
any farther.
The branch-and-bound algorithm thus allows us to find all most parsimonious
trees without generating all possible trees. How much of a saving this
is depends strongly on the data. For very clean (nearly "Hennigian")
data, it saves much time, but on very messy data it will still take
a very long time.
The algorithm in the program differs from the one outlined here
in some essential details: it investigates possibilities in the
order of their apparent promise. This applies to the order of addition
of species, and to the places where they are added to the tree. After
the first two-species tree is constructed, the program tries adding
each of the remaining species in turn, each in the best possible place it
can find. Whichever of those species adds (at a minimum) the most
additional steps is taken to be the one to be added next to the tree. When
it is added, it is added in turn to places which cause the fewest
additional steps to be added. This sounds a bit complex, but it is done
with the intention of eliminating regions of the search of all possible
trees as soon as possible, and lowering the bound on tree length as quickly
as possible.
The program keeps a list of all the most parsimonious
trees found so far. Whenever
it finds one that has fewer steps than
these, it clears out the list and
restarts the list with that tree. In the process the bound tightens and
fewer possibilities need be investigated. At the end the list contains
all the shortest trees. These are then printed out. It should be
mentioned that the program CLIQUE for finding all largest cliques
also works by branch-and-bound. Both problems are NP-complete but for
some reason CLIQUE runs far faster. Although their worst-case behavior
is bad for both programs, those worst cases occur far more frequently
in parsimony problems than in compatibility problems.
Controlling Run Times
Among the quantities available to be set at the
beginning of a run of PENNY, two (howoften and howmany) are of particular
importance. As PENNY goes along it will keep count of how many
trees it has examined. Suppose that howoften is 100 and howmany is 1000,
the default settings. Every time 100 trees have been examined, PENNY
will print out a line saying how many multiples of 100 trees have now been
examined, how many steps the most parsimonious tree found so far has,
how many trees of with that number of steps have been found, and a very
rough estimate of what fraction of all trees have been looked at so far.
When the number of these multiples printed out reaches the number howmany
(say 1000), the whole algorithm aborts and prints out that it has not
found all most parsimonious trees, but prints out what is has got so far
anyway. These trees need not be any of the most parsimonious trees: they are
simply the most parsimonious ones found so far. By setting the product
(howoften times howmany) large you can make
the algorithm less likely to abort, but then you risk getting bogged
down in a gigantic computation. You should adjust these constants so that
the program cannot go beyond examining the number of trees you are reasonably
willing to wait for. In their initial setting the program will
abort after looking at 100,000 trees. Obviously you may want to adjust
howoften in order to get more or fewer lines of intermediate notice of how
many trees have been looked at so far. Of course, in small cases you may
never even reach the first multiple of howoften and nothing will be printed out
except some headings and then the final trees.
The indication of the approximate percentage of trees searched so far will
be helpful in judging how much farther you would have to go to get the full
search. Actually, since that fraction is the fraction of the set of all
possible trees searched or ruled out so far, and since the search becomes
progressively more efficient, the approximate fraction printed out will
usually be an underestimate of how far along the program is, sometimes a
serious underestimate.
A constant that affects the result is
"maxtrees", which controls the
maximum number of trees that can be stored. Thus if
"maxtrees" is 25, and 32 most parsimonious trees are found,
only the first 25 of these are stored and printed out. If "maxtrees"
is increased, the program does not run any slower but requires a little
more intermediate storage space. I recommend that
"maxtrees" be kept as large as you can, provided you are willing to
look at an output with that many trees on it! Initially,
"maxtrees" is set to 100 in the distribution copy.
Methods and Options
The counting of the length of trees is done by an algorithm nearly
identical to the corresponding algorithms in MIX, and thus the remainder
of this document will be nearly identical to the MIX document. MIX
is a general parsimony program which carries out the Wagner and
Camin-Sokal parsimony methods in mixture, where each character can have
its method specified. The program defaults to carrying out Wagner
parsimony.
The Camin-Sokal parsimony method explains the data by assuming that
changes 0 --> 1 are allowed but not changes 1 --> 0. Wagner parsimony
allows both kinds of changes. (This under the assumption that 0 is the
ancestral state, though the program allows reassignment of the ancestral
state, in which case we must reverse the state numbers 0 and 1
throughout this discussion). The criterion is to find the tree which
requires the minimum number of changes. The Camin-Sokal method is due
to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
(1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
Ancestral states are known (Camin-Sokal) or unknown (Wagner).
Different characters evolve independently.
Different lineages evolve independently.
Changes 0 --> 1 are much more probable than changes 1 --> 0
(Camin-Sokal) or equally probable (Wagner).
Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the
group in question.
Other kinds of evolutionary event such as retention of polymorphism
are far less probable than 0 --> 1 changes.
Rates of evolution in different lineages are sufficiently low that
two changes in a long segment of the tree are far less probable
than one change in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
The input for PENNY is the standard input for discrete characters
programs, described above in the documentation file for the
discrete-characters programs. States "?", "P", and "B" are allowed.
Most of the options are selected using a menu:
Penny algorithm, version 3.6a3
branch-and-bound to find all most parsimonious trees
Settings for this run:
X Use Mixed method? No
P Parsimony method? Wagner
F How often to report, in trees: 100
H How many groups of 100 trees: 1000
O Outgroup root? No, use as outgroup species 1
S Branch and bound is simple? Yes
T Use Threshold parsimony? No, use ordinary parsimony
A Use ancestral states in input file? No
W Sites weighted? No
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each character No
5 Print states at all nodes of tree No
6 Write out trees onto tree file? Yes
Are these settings correct? (type Y or the letter for one to change)
The options X, O, T, A, and M are the usual Mixed Methods, Outgroup,
Threshold, Ancestral
States, and Multiple Data Sets options. They are described in the Main
documentation file and in the Discrete Characters Programs documentation
file. The O option is only acted upon if the final tree is unrooted.
The option P toggles between the Camin-Sokal parsimony criterion
and the Wagner parsimony criterion. Options F and H reset the
variables howoften (F) and howmany (H). The user is prompted for the new
values. By setting these larger the program will report its progress less
often (howoften) and will run longer (howmany times howoften). These values
default to 100 and 1000 which
guarantees a search of 100,000 trees, but these can be changed. Note that
option F in this program is not the Factors option available in some of
the other programs in this section of the package.
The A (Ancestral states) option works in the usual way, described in the
Discrete Characters Programs documentation file. If
the A option is not used, then the program will assume 0 as the
ancestral state for those characters following the Camin-Sokal method,
and will assume that the ancestral state is unknown for those characters
following Wagner parsimony. If any characters have unknown ancestral
states, and if the resulting tree is rooted (even by outgroup),
a table will be printed out
showing the best guesses of which are the ancestral states in each
character.
The S (Simple) option alters a step in PENNY which reconsiders the
order in which species are added to the tree. Normally the decision as to
what species to add to the tree next is made as the first tree is being
constructed; that ordering of species is not altered subsequently. The
S option causes it to be continually reconsidered. This will probably
result in a substantial increase in run time, but on some data sets of
intermediate messiness it may help. It is included in case it might prove
of use on some data sets.
The F (Factors)
option is not available in this program, as it would have no effect on
the result even if that information were provided in the input file.
The final output is standard: a set of trees, which
will be printed as rooted or unrooted
depending on which is appropriate, and if the user elects to see them,
tables of the number of changes
of state required in each character. If the Wagner option is in force for a
character, it may not be possible to unambiguously locate the places on
the tree where the changes occur, as there may be multiple possibilities. A
table is available to be printed out after each tree, showing for each branch
whether
there are known to be changes in the branch, and what the states are inferred
to have been at the top end of the branch. If the inferred state is a "?"
there will be multiple equally-parsimonious assignments of states; the user
must work these out for themselves by hand.
If the Camin-Sokal parsimony method (option C or S)
is invoked and the A option is also used, then the program will
infer, for any character whose ancestral state is unknown ("?") whether the
ancestral state 0 or 1 will give the fewest state changes. If these are
tied, then it may not be possible for the program to infer the
state in the internal nodes, and these will all be printed as ".". If this
has happened and you want to know more about the states at the internal
nodes, you will find helpful to use MOVE to display the tree and examine
its interior states, as the algorithm in MOVE shows all that can be known
in this case about the interior states, including where there is and is not
amibiguity. The algorithm in PENNY gives up more easily on displaying these
states.
If the A option is not used, then the program will assume 0 as the
ancestral state for those characters following the Camin-Sokal method,
and will assume that the ancestral state is unknown for those characters
following Wagner parsimony. If any characters have unknown ancestral
states, and if the resulting tree is rooted (even by outgroup),
a table will be printed out
showing the best guesses of which are the ancestral states in each
character. You will find it useful to understand the difference between
the Camin-Sokal parsimony criterion with unknown ancestral state and the Wagner
parsimony criterion.
At the beginning of the program are a series of constants,
which can be changed to help adapt the program to different computer systems.
Two are the initial values of howmany and howoften,
constants "often" and "many". Constant "maxtrees"
is the maximum number of tied trees that will be stored.
This program implements the contrasts calculation described in my 1985
paper on the comparative method (Felsenstein, 1985d). It reads in a
data set of the standard quantitative characters sort, and also a
tree from the treefile. It then forms the contrasts between species
that, according to that tree, are statistically independent. This is
done for each character. The contrasts are all standardized by
branch lengths (actually, square roots of branch lengths).
The method is explained in the 1985 paper. It assumes
a Brownian motion model. This model was introduced by Edwards and
Cavalli-Sforza (1964; Cavalli-Sforza and Edwards, 1967)
as an approximation to the evolution of gene frequencies. I have
discussed (Felsenstein, 1973b, 1981c, 1985d, 1988b) the difficulties
inherent in using it as a model for the evolution of quantitative
characters. Chief among these is that the characters do not necessarily evolve
independently or at equal rates. This program allows one to evaluate this,
if there is independent information on the phylogeny. You can
compute the variance of the contrasts for each character, as a measure of
the variance accumulating per unit branch length. You can also test
covariances of characters.
The input file is as described in the continuous characters
documentation file above, for the case of continuous quantitative
characters (not gene frequencies). Options are selected using a menu:
Continuous character comparative analysis, version 3.6a3
Settings for this run:
W within-population variation in data? No, species values are means
R Print out correlations and regressions? Yes
A LRT test of no phylogenetic component? Yes, with and without VarA
C Print out contrasts? No
M Analyze multiple trees? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
Y to accept these or type the letter for one to change
Option W makes the program expect not means of the phenotypes in each
species, but phenotypes of individual specimens. The details of
the input file format in that case are given below. In that case the
program estimates the covariances of the phenotypic change, as well as
covariances of within-species phenotypic variation. The model used is
similar to (but not identical to) that of Lynch (1990). The
algorithms used differ from the ones he
gives in that paper. They will be described in a forthcoming paper by
me. In the case that has within-species samples contrasts are used by
the program, but it does not make sense to write them out to an
output file for direct analysis. They are of two kinds, contrasts
within species and contrasts between species. The former are
affected only by the within-species phenotypic covariation, but the
latter are affected by both within- and between-species covariation.
CONTRAST infers these two kinds of covariances and writes the
estimates out.
M is similar to the usual multiple data sets input option, but is used here
to allow multiple trees to be read from the treefile, not multiple
data sets to be read from the input file. In this way you can
use bootstrapping on the data that estimated these trees, get
multiple bootstrap estimates of the tree, and then use the M
option to make multiple analyses of the contrasts and the
covariances, correlations, and regressions. In this way (Felsenstein,
1988b) you can assess the effect of the inaccuracy of the trees on
your estimates of these statistics.
R allows you to turn off or on the printing out of the statistics.
If it is off only the contrasts will be printed out (unless option
1 is selected). With only the contrasts printed out, they are in
a simple array that is in a form that many statistics packages should
be able to read. The contrasts are rows, and each row has one contrast
for each character. Any multivariate statistics package should be able
to analyze these (but keep in mind that the contrasts have, by virtue
of the way they are generated, expectation zero, so all regressions
must pass through the origin). If the W option has been set to
analyze within-species as well as between-species variation, the R
option does not appear in the menu as the regression and correlation
statistics should always be computed in that case.
As usual, the tree file has the default name intree. It
should contain the desired tree or trees. These can be
either in bifurcating form, or may have the bottommost fork be a
trifurcation (it should not matter which of these ways you present the tree).
The tree must, of course, have branch lengths.
If you have a molecular data set (for example) and also, on the same
species, quantitative measurements, here is how you can allow for the
uncertainty of yor estimate of the tree. Use SEQBOOT to generate multiple
data sets from your molecular data. Then, whichever method you use to
analyze it (the relevant ones are those that produce estimates of the
branch lengths: DNAML, DNAMLK, FITCH, KITSCH, and NEIGHBOR -- the latter
three require you to use DNADIST to turn the bootstrap data sets into
multiple distance matrices), you should use the Multiple Data Sets
option of that program. This will result in a tree file with many
trees on it. Then use this tree file with the input file containing
your continuous quantitative characters, choosing the Multiple Trees
(M) option. You will get one set of contrasts and statistics for each
tree in the tree file. At the moment there is no overall summary:
you will have to tabulate these by hand. A similar process can be
followed if you have restriction sites data (using RESTML) or
gene frequencies data.
The statistics that are printed out include the covariances between
all pairs of characters, the regressions of each character on each
other (column j is regressed on row i), and the correlations between
all pairs of characters. In assessing degress of freedom it is
important to realize that each contrast was taken to have
expectation zero, which is known because each contrast could as
easily have been computed xi-xj instead of xj-xi. Thus there is no
loss of a degree of freedom for estimation of a mean. The degrees
of freedom is thus the same as the number of contrasts, namely one
less than the number of species (tips). If you feed these contrasts
into a multivariate statistics program make sure that it knows that
each variable has expectation exactly zero.
Within-species variation
With the W option selected, CONTRAST analyzes data sets with variation within
species, using a model like that proposed by Michael Lynch (1990).
If you select the W option for within-species variation, the data
set should have this structure (on the left are the data, on the right
my comments:
number of species, number of characters
name of 1st species, # of individuals
data for individual #1
data for individual #2
name of 2nd species, # of individuals
data for individual #1
data for individual #2
data for individual #3
(and so on)
The covariances, correlations, and regressions for the "additive"
(between-species evolutionary variation) and "environmental" (within-species
phenotypic variation) are
printed out (the maximum likelihood estimates of each).
The program also estimates the within-species phenotypic variation in the
case where the between-species evolutionary covariances are forced to be
zero. The log-likelihoods of these two cases are compared and a
likelihood ratio test (LRT) is carried out. The program prints the result
of this test as a chi-square variate, and gives the number of degrees of
freedom of the LRT. You have to look up the chi-square variable on a
table of the chi-square distribution.
The log-likelihood of the data under the models with and without
between-species For the moment the program cannot handle the case where
within-species variation is to be taken into account but where only species
means are available. (It can handle cases where some species have only one
member in their sample).
We hope to fix this soon. We are also on our way to
incorporating full-sib, half-sib, or clonal groups within species, so as
to do one analysis for within-species genetic and between-species
phylogenetic variation.
The data set used as an example below is the example from a
paper by Michael Lynch (1990), his characters having been log-transformed.
In the case where there is only one specimen per species, Lynch's model
is identical to our model of within-species variation (for
multiple individuals per species it is not a subcase of his model).
DRAWTREE interactively plots an unrooted tree diagram, with many options
including orientation of tree and branches, label sizes and angles, margin
sizes. Particularly if you can use your computer screen to
preview the plot, you can very effectively adjust the details of the plotting
to get just the kind of plot you want.
To understand the working of DRAWGRAM and DRAWTREE, you should first
read the Tree Drawing Programs web page
in this documentation.
As with DRAWGRAM, to run DRAWTREE you need a compiled copy of the
program, a font file, and a tree file. The tree file has a default name
of intree. The font file has a default name of "fontfile". If there is
no file of that name, the program will ask you for the name of a font file
(we provide ones that have the names font1 through font6).
Once you decide on a favorite one of these, you could make a copy of it
and call it fontfile, and it will then be used by default.
Note that the program will get confused if the input tree file has the number
of trees on the first line of the file, so that numbr may have to be removed.
Once these choices have been made you will see the central menu of the
program, which looks like this:
Unrooted tree plotting program version 3.6a3
Here are the settings:
0 Screen type (IBM PC, ANSI)? (none)
P Final plotting device: Postscript printer
V Previewing device: X Windows display
B Use branch lengths: Yes
L Angle of labels: branch points to Middle of label
R Rotation of tree: 90.0
A Angle of arc for tree: 360.0
I Iterate to improve tree: Equal-Daylight algorithm
D Try to avoid label overlap? No
S Scale of branch length: Automatically rescaled
C Relative character height: 0.3333
F Font: Times-Roman
M Horizontal margins: 1.65 cm
M Vertical margins: 2.16 cm
# Page size submenu: one page per tree
Y to accept these or type the letter for one to change
These are the settings that control the appearance of the tree, which
has already been read in. You can either accept these as is, in which
case you would answer Y to the question and press the Return or Enter
key, or you can answer N if you want to change one, or simply type the
character corresponding to the one you want to change (if you answer N it
will just immediately ask you for that number anyway).
For a first run, particularly if previewing is available, you might accept
these default values and see what the result looks like. The program
will then tell you it is about to preview the tree and ask you to press
Return or Enter when you are ready to see this (you will probably have
to press it twice). If you are on a Windows system (and have its graphics
selected as your previewing option), on a Unix or Linux system and are
using X windows for previewing, or are on a Macintosh system, a new
window will open with the preview in it. If you are using the Tektronix
preview option the preview will appear in the window where the menu was.
On X Windows, Macintosh, and Windows you can resize the preview window,
though for some of these you may have to ask the system to redraw the
preview to see it at the new window size.
Once you are finished looking at the preview, you will want to
specify whether the program should make the final plot or change some of
the settings. This is done differently on the different previews:
In X Windows you should make the menu window the active
window. You may need to move the mouse over it, or click in it, or
click on its top bar. You do not need to try to close the preview
window yourself, and usually if you do this will cause trouble.
In Windows use the File menu in the preview window
and choose either the Change Parameters menu item, or if
you are ready to make the final plot, choose the Plot menu item.
On a Macintosh system, you can simply use the little box in
the corner of the preview window to close it. The text window for the
menu will then be active.
In PC graphics press on the Enter key. The screen with the
preview should disappear and the settings menu reappear.
With a Tektronix preview, you may need to change your screen
from a Tektronix-compatible mode to see the menu again.
Except with the Macintosh preview, the program will
now ask you if the tree is now ready to be plotted. If you answer Y (for
Yes) (or choose this option in the File menu of the preview
window in the case of Windows) the program will usually write a plot file
(with some plot options it will draw the tree on the screen). Then it will
terminate.
But if you do not say that you are ready to plot the tree,
it will go back to the above menu, allow
you to change more options, and go through the whole process again. The
easiest way to learn the meaning of the options is to try them,
particularly if previewing is available. Below I will describe them one
by one; you may prefer to skip reading this unless you are puzzled about
one of them.
THE OPTIONS
O
This is an option that allows you to change the menu window
to be an ANSI terminal or an IBM PC terminal. Generally you will not
want to change this.
P
This allows you to choose the Plotting device or file
format. We have discussed the possible choices in the
draw programs documentation web page.
V
This allows you to change the type of preView window (or
even turn off previewing. We have discussed the different possible
choices in the draw programs documentation web page.
B
Whether the tree has Branch lengths that are
being used in the diagram. If the tree that was read in had a full set
of branch lengths, it will be assumed as a default that you want to use
them in the diagram, but you can specify that they are not to be used. If
the tree does not have a full set of branch lengths then this will
be indicated, and if you try to use branch lengths the program will
refuse to allow you to do so.
L
The angle of the Labels. Initially the branches connected to
the tips will point to the middles of the labels.
If you want to change the way the labels are drawn, the program
will offer you a choice between Fixed, Middle, Radial, and Along as the
ways the angles of the labels are to be determined. If you choose
Fixed (the default), you will be asked if you want labels to be at some fixed
angle, between 90.0 and
-90.0 degrees, you can specify that. You may have to try different angles
to find one that keeps the
labels from colliding: I have not guarded against this. However there
are additional options.
The other systems for determining angles of labels are Middle (M), Radial (R)
and Along (A). Middle has the branch connected to that tip
point to the midpoint of the label.
Radial indicates that the labels are all aligned to as to
point toward the root node of the tree. Along aligns them to have the
same angle as the branch connected to that tip. This is particularly
likely to keep the labels from colliding, but it may give a misleading
impression that the final branch is long. Note that with the Radial
option, if you do not like the point from which the labels appear to
radiate, you might try re-rooting the tree (option 7).
R
The rotation of the tree. This is
initially 90.0 degrees. The angle is read out counterclockwise from the
right side of the tree, so that increasing this angle will rotate the
tree counterclockwise, and decreasing it will rotate it clockwise.
The meaning of this angle is explained further under option A.
As you rotate the tree, the appearance (and size) may change, but the
labels will not rotate if they are drawn at a Fixed angle.
A
The Angle through which the tree is plotted.
This is by default 360.0 degrees. The tree is in the shape of an
old-fashioned hand fan. The tree fans out from its root node, each of
the subtrees being allocated part of this angle, a part proportional to
how many tips the subtree contains. If the rotation of the tree is (say)
90.0 degrees (the default under option R), the fan starts at +270
degrees and runs clockwise around to -90 degrees (i.e., it starts at the
bottom of the plot and runs clockwise around until it returns to the
bottom. Thus the center of the fan runs from the root upwards (which is
why we say it is rotated to 90.0 degrees). By changing option R we can
change the direction of the fan, and by changing option A we can change
the width of the fan without changing its center line. If you want the
tree to fan out in a semicircle, a value of a bit greater than 180
degrees would be appropriate, as the tree will not completely fill the
fan. Note that using either of the iterative improvement methods
mentioned below is impossible if the angle is not 360 degrees.
I
Whether the tree angles will be Iteratively
improved. There are three methods available:
Equal Arc
This method, invented by Christopher Meacham in
PLOTREE, the predecessor to this program, starts from the root of the tree
and allocates arcs of angle to each subtree proportional to the number of
tips in it. This continues as one moves out to other nodes of the tree and
subdivides the angle allocated to them into angles for each of that node's
dependent subtrees. This method is fast, and never results in lines of the
tree crossing. It is the method used to make a starting tree for the other
two methods.
Equal Daylight
This iteratively improves an initial tree by
successively going to each interior node, looking at the subtrees (often
there are 3 of them) visible from there, and swinging them so that the
arcs of "daylight" visible between them are equal. This is not as fast as
Equal Arc but should never result in lines crossing. It gives particularly
good-looking trees, and it is the default method for this program. It will
be described in a future paper by me. This method has also been licensed to
David Swofford for use in his program PAUP*
N-Body
This assumes that there are electrical charges located
at the ends of all the branches, and that they repel each other with a force
that varies (as electrical repulsion would) as the inverse square of the
distance between them. The tree adjusts its shape until the forces balance.
This can be computationally slow, and can result in lines crossing. I find
the trees inferior to Equal Daylight, but it is worth a try.
D
Whether the program tries to avoiD overlap of the labels.
We have left this off by default, because it is a rather feeble option
that is frequently unsuccessful, and often make the trees look wierd.
Nevertheless it may be worth a try.
S
On what Scale the branch lengths will be translated
into distances on the output device. Note that when branch lengths
have not been provided, there are implicit branch lengths of 1.0 per
branch. This option will toggle back and forth between automatic
adjustment of branch lengths so that the diagram will just fit into the
margins, and you specifying how many centimeters there will be per unit
branch length. This is included so that you can plot different trees
to a common scale, showing which ones have longer or shorter branches than
others. Note that if you choose too large a value for centimeters per
unit branch length, the tree will be so big it will overrun the plotting
area and may cause failure of the diagram to display properly. Too small
a value will cause the tree to be a nearly invisible dot.
C
The Character height, measured as a fraction
of a quantity which is the horizontal space available for the tree,
divided by one less than the number of tips. You need not worry about
exactly what this is: you can always change the value (which is
initially 0.3333) to make the labels larger or smaller. On output devices
where line thicknesses can be varied, the thickness of the tree lines will
automatically be adjusted to be proportional to the character height,
which is an additional reason you may want to change character height.
F
Allows you to select the
name of the Font that you will use for the species names. This is
allowed for some of the plotter drivers (this menu item does not
appear for the others). You can
select the name of any font that is available for your plotter, for
example "Courier-Bold" or "Helvetica". The label will then be
printed using that font rather than being drawn line-by-line as it
is in the default Hershey font. In the preview of the tree, the
Hershey font is always used (which means that it may look different from
the final font). The size of the characters in the species names is
scaled according to the label heights you have selected in the menu,
whether plotter fonts or the Hershey font are used. Note that for some
plotter drivers (particular Xfig and PICT) fonts can be used only if the
species labels are horizontal or vertical (at angles of 0 degrees or
90 degrees).
M
The horizontal and vertical Margins in
centimeters. You can enter new margins (you must enter new values for
both horizontal and vertical margins, though these need not be different
from the old values). For the moment I do not allow you to specify left
and right margins separately, or top and bottom margins separately. In
a future release I hope to do so.
G
If iterative improvement is not
turned on in option I (so that we are employing the Equal Arc method), this
option appears in the menu. It controls
whether the angles of lines will be "regularized".
Regularization is on by default. It takes the angles of the branches
coming out from each node, and changes them so that they are "rounded
off". This process (which I will not fully describe) will make the
lines vertical if they are close to vertical, horizontal if they are
close to horizontal, 45 degrees if they are close to that, and so on.
It will lead to a tree in which angles look very regular. You may or
may not want that. If you are unhappy with the appearance of the tree
when using this option,
you could try rotating it slightly (option R) as that may cause some
branches to change their angle by a large amount, by having the angles
be "rounded off" to a different value.
#
The number of pages per tree. Defaults to one, but if
you need a physically large tree you may want to choose a larger
number. For example, to make a big tree for a poster, choose a larger
number of pages horizontally and vertically (the program will ask you
for these numbers), get out your scissors and paste or tape, and
go to work.
I recommend that you try all of these options (particularly if you can
preview the trees). It is of particular use to try trees with different
iteration methods (option I) and
with regularization (option G).
You will find that variety of effects can be achieved.
I would appreciate suggestions for improvements in DRAWTREE, but please
be aware that the source code is already very large and I may not be
able to implement all suggestions.
PHYLIPNEW-3.69.650/doc/main.html 0000664 0001750 0001750 00000722002 07712247475 012667 0000000 0000000
main
PHYLIP
Phylogeny Inference Package
Version 3.6(alpha3)
July, 2002
by Joseph Felsenstein
Department of Genome Sciences
University of Washington
Box 357730
Seattle, WA 98195-7730
USA
PHYLIP, the Phylogeny Inference Package, is a package of programs for
inferring phylogenies (evolutionary trees). It has been distributed since
1980, and has over 10,000 registered users, making it the most widely
distributed package of phylogeny programs. It is available free, from
its web site:
PHYLIP is available as source code in C, and also as executables for
some common computer systems. It can infer phylogenies by parsimony,
compatibility, distance matrix methods, and likelihood. It can also
compute consensus trees, compute distances between trees, draw trees,
resample data sets by bootstrapping or jackknifing, edit trees, and
compute distance matrices. It can handle data that are nucleotide
sequences, protein sequences, gene frequencies, restriction sites,
restriction fragments, distances, discrete characters, and continuous
characters.
Copyright Notice for PHYLIP
The following copyright notice is intended to cover all source code, all
documentation, and all executable programs of the PHYLIP package.
PHYLIP comes with an extensive set of documentation files. These
include the main documentation file (this one), which you should read
fairly completely. In addition there are files for groups of programs,
including ones for the molecular sequence
programs, the distance matrix
programs, the
gene frequency and continuous characters
programs, the discrete characters programs,
and the tree drawing programs. Finally,
each program has its own documentation file. References for the
documentation files are all gathered together in this main documentation
file. A good strategy is to:
Read this main documentation file.
Tentatively decide which programs are of interest to you.
Read the documentation files for the groups of programs that
contain those.
Read the documentation files for those individual programs.
What The Programs Do
Here is a short description of each of the programs. For more detailed
discussion you should definitely read the documentation file for the
individual program and the documentation file for the group of programs
it is in. In this list the name of each program is a link which will
take you to the documentation file for that program. Note that there is no
program in the PHYLIP package called PHYLIP.
Estimates phylogenies from protein sequences (input using the
standard one-letter code for amino acids) using the parsimony method, in
a variant which counts only those nucleotide changes that change the amino
acid, on the assumption that silent changes are more easily accomplished.
Estimates phylogenies by the parsimony method using nucleic acid
sequences. Allows use the full IUB ambiguity codes, and estimates
ancestral nucleotide states. Gaps treated as a fifth nucleotide state.
Can use 0/1 weights, reconstruct ancestral states, and infer branch
lengths.
Interactive construction of phylogenies from nucleic acid
sequences, with their evaluation by parsimony and compatibility and the
display of reconstructed ancestral bases. This can be used to find
parsimony or compatibility estimates by hand.
Finds all most parsimonious phylogenies for nucleic acid
sequences by branch-and-bound search. This may not be practical (depending
on the data) for more than 15 species or so.
Estimates phylogenies from nucleic acid sequence data using
the compatibility criterion, which searches for the largest number of sites
which could have all states (nucleotides) uniquely evolved on the same
tree. Compatibility is particularly appropriate when sites vary greatly in
their rates of evolution, but we do not know in advance which are the less
reliable ones.
For nucleic acid sequence data on four species, computes
Lake's and Cavender's phylogenetic invariants, which test alternative tree
topologies. The program also tabulates the frequencies of occurrence of the
different nucleotide patterns. Lake's invariants are the method which he
calls "evolutionary parsimony".
Estimates phylogenies from nucleotide sequences by maximum
likelihood. The model employed allows for unequal expected frequencies of
the four nucleotides, for unequal rates of transitions and transversions,
and for different (prespecified) rates of change in different categories of
sites, with the program inferring which sites have which rates. It also
allows different rates of change at known sites.
Same as DNAML but assumes a molecular clock. The use of the
two programs together permits a likelihood ratio test of the
molecular clock hypothesis to be made.
Estimates phylogenies from protein amino acid sequences by maximum
likelihood. The PAM or JTTF models can be employed. The program
can allow for different (prespecified) rates of change in different
categories of amino acid positions, with the program inferring which
posiitons have which rates. It also allows different rates of change
at known sites.
Same as PROML but assumes a molecular clock. The use of the
two programs together permits a likelihood ratio test of the
molecular clock hypothesis to be made.
Computes four different distances between species from nucleic
acid sequences. The distances can then be used in the distance matrix
programs. The distances are the Jukes-Cantor formula, one based on Kimura's
2-parameter method, Jin and Nei's distance which allows for rate variation
from site to site, and a maximum likelihood method using the model employed
in DNAML. The latter method of computing distances can be very slow.
Computes a distance measure for protein sequences, using
maximum likelihood estimates based on the Dayhoff PAM matrix, Kimura's 1983
approximation to it, or a model based on the genetic code plus a
constraint on changing to a different category of amino acid. Rate
variation from site to site is also allowed. The
distances can be used in the distance matrix programs.
Distances calculated from restriction sites data or
restriction fragments data. The restriction sites option is the one to
use to also make distances for RAPDs or AFLPs.
Estimation of phylogenies by maximum likelihood using
restriction sites data (not restriction fragments but presence/absence of
individual sites). It employs the Jukes-Cantor symmetrical model of
nucleotide change, which does not allow for differences of rate between
transitions and transversions. This program is very slow.
Reads in a data set, and produces multiple data sets from
it by bootstrap resampling. Since most programs in the current version of
the package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this package.
This program also allows the Archie/Faith technique of permutation of
species within characters. It can also rewrite a data set to convert
it from between the PHYLIP Interleaved and Sequential forms, and into
a preliminary version of a new XML sequence alignment format
which is under development.
Estimates phylogenies from distance matrix data under the
"additive tree model" according to which the distances are expected to
equal the sums of branch lengths between the species. Uses the
Fitch-Margoliash criterion and some related least squares criteria. Does
not assume an evolutionary clock. This program will be useful with
distances computed from molecular sequences, restriction sites or fragments
distances, with DNA hybridization measurements, and with genetic distances
computed from gene frequencies.
Estimates phylogenies from distance matrix data under the
"ultrametric" model which is the same as the additive tree model except
that an evolutionary clock is assumed. The Fitch-Margoliash criterion and
other least squares criteria are assumed. This program will be useful with
distances computed from molecular sequences, restriction sites or
fragments distances, with distances from DNA hybridization measurements,
and with genetic distances computed from gene frequencies.
An implementation by Mary Kuhner and John Yamato of Saitou and
Nei's "Neighbor Joining Method," and of the UPGMA (Average Linkage
clustering) method. Neighbor Joining is a distance matrix method producing
an unrooted tree without the assumption of a clock. UPGMA does assume a
clock. The branch lengths are not optimized by the least squares criterion
but the methods are very fast and thus can handle much larger data sets.
Estimates phylogenies from gene frequency data by maximum
likelihood under a model in which all divergence is due to genetic drift in
the absence of new mutations. Does not assume a molecular clock. An
alternative method of analyzing this data is to compute Nei's genetic
distance and use one of the distance matrix programs.
This program can also do maximum likelihoodn analysis of continuous
charactersn that evolve by a Brownian Motion model, but it assumes that
the characters evolve at equal rates and in an uncorrelated fashion, so
that it does not take into account the usual correlations of characters.
Computes one of three different genetic distance formulas
from gene frequency data. The formulas are Nei's genetic distance, the
Cavalli-Sforza chord measure, and the genetic distance of Reynolds et. al.
The former is appropriate for data in which new mutations occur in an
infinite isoalleles neutral mutation model, the latter two for a model
without mutation and with pure genetic drift. The distances are written to
a file in a format appropriate for input to the distance matrix programs.
Reads a tree from a tree file, and a data set with continuous
characters data, and produces the independent contrasts for those
characters, for use in any multivariate statistics package. Will also
produce covariances, regressions and correlations between characters for
those contrasts. Can also correct for within-species sampling variation
when individual phenotypes are available within a population.
Multistate discrete-characters parsimony method. Up to 8 states
(as well as "?") are allowed. Cannot do Camin-Sokal or Dollo Parsimony.
Can reconstruct ancestral states, use character weights, and infer branch
lengths.
Estimates phylogenies by some parsimony methods for discrete
character data with two states (0 and 1). Allows use of the
Wagner parsimony method, the Camin-Sokal parsimony method, or arbitrary
mixtures of these. Also reconstructs ancestral states and allows weighting
of characters (does not infer branch lengths).
Interactive construction of phylogenies from discrete character
data with two states (0 and 1). Evaluates parsimony and compatibility
criteria for those phylogenies and displays reconstructed states throughout
the tree. This can be used to find parsimony or compatibility estimates by
hand.
Finds all most parsimonious phylogenies for discrete-character
data with two states, for the Wagner, Camin-Sokal, and mixed parsimony
criteria using the branch-and-bound method of exact search. May be
impractical (depending on the data) for more than 10-11 species.
Estimates phylogenies by the Dollo or polymorphism parsimony
criteria for discrete character data with two states (0 and 1). Also
reconstructs ancestral states and allows weighting of characters. Dollo
parsimony is particularly appropriate for restriction sites data; with
ancestor states specified as unknown it may be appropriate for restriction
fragments data.
Interactive construction of phylogenies from discrete
character data with two states (0 and 1) using the Dollo or polymorphism
parsimony criteria. Evaluates parsimony and compatibility criteria for
those phylogenies and displays reconstructed states throughout the tree.
This can be used to find parsimony or compatibility estimates by hand.
Finds all most parsimonious phylogenies for
discrete-character data with two states, for the Dollo or polymorphism
parsimony criteria using the branch-and-bound method of exact search. May
be impractical (depending on the data) for more than 10-11 species.
Finds the largest clique of mutually compatible characters, and
the phylogeny which they recommend, for discrete character data with two
states. The largest clique (or all cliques within a given size range of
the largest one) are found by a very fast branch and bound search method.
The method does not allow for missing data. For such cases the T
(Threshold) option of PARS or MIX may be a useful alternative.
Compatibility methods are particular useful when some characters are of
poor quality and the rest of good quality, but when it is not known in
advance which ones are which.
Takes discrete multistate data with character state trees and
produces the corresponding data set with two states (0 and 1). Written by
Christopher Meacham. This program was formerly used to accomodate
multistate characters in MIX, but this is less necessary now that PARS is
available.
Plots rooted phylogenies, cladograms, and phenograms in a
wide variety of user-controllable formats. The program is interactive and
allows previewing of the tree on PC or Macintosh graphics screens,
and Tektronix or Digital graphics terminals. Final output can be
to a file formatted for one of the drawing programs, on
a laser printer (such as Postscript or PCL-compatible printers),
on graphics screens or terminals, on pen plotters (Hewlett-Packard or
Houston Instruments) or on dot matrix printers capable of graphics
(Epson, Okidata, Imagewriter, or Toshiba).
Computes the Robinson-Foulds symmetric difference distance
between trees, which allows for differences in tree topology (but does not
use branch lengths).
Computes consensus trees by the majority-rule consensus tree
method, which also allows one to easily find the strict consensus tree.
Is not able to compute the Adams consensus tree. Trees are input in a tree
file in standard nested-parenthesis notation, which is produced by many of
the tree estimation programs in the package. This program can be used as
the final step in doing bootstrap analyses for many of the methods in the
package.
Reads in a tree (with branch lengths if necessary) and allows
you to reroot the tree, to flip branches, to change species names and
branch lengths, and then write the result out. Can be used to convert
between rooted and unrooted trees, and to write the tree into a
preliminary version of a new XML tree file format which is under
development.
Running the Programs
This section assumes that you have obtained PHYLIP as compiled executables
(for Windows, Macintosh, or DOS), or have obtained the source code
and compiled it yourself (for Linux, Unix, or OpenVMS). For machines for
which compiled executables are available, there will usually be no need for
you to have a compiler or compile the programs yourself. This section
describes how to run the programs. Later in this document we will
discuss how to download and install PHYLIP (in case you are somehow
reading this without yet having done that). Normally you will only read
this document after downloading and installing PHYLIP.
A word about input files.
For all of these types of machines, it is
important to have the input files for the programs (typically data files)
prepared in advance. They can be prepared in any editor, but it is important
that they be saved in Text Only ("flat ASCII") format, not in the format that
word processors such as Microsoft Word want to write. It is up to you to read
the PHYLIP documentation files which describe the files formats that are
needed. There is a partial description in the next section of this document.
The input files can also be obtained by running a program that
produces output files in PHYLIP format (some of these programs do, and so do
programs by others such as sequence alignment programs such as ClustalW and
sequence format conversion programs such as Readseq). There is not any
input file editor available in any program in PHYLIP (you should not
simply start running one of the programs and then expect to click a mouse
somewhere to start creating a data file).
When they start running, the programs look first for input files with
particular names (such as infile, treefile, intree, or fontfile).
Exactly which file names they look for varies a bit from program to program,
and you should read the documentation file for the particular program to
find out. If you have files with those names the programs will use them
and not ask you for the file name. If they do not find files of those
names, the programs will say that they cannot find a file of that name, and
ask you to type in the file name.
For example, if DnaML looks
for the file infile and does not find one of that name,
it prints the message:
dnaml: can't find input file "infile"
Please enter a new file name>
This does not mean that an error
has occurred. All you need to do is to type in the name of the file.
The program looks for the input files in the same directory that the
program is in (a directory is the same thing as a "folder"). In Windows, Linux, Unix, or MSDOS, if you are asked for the
file name you can type in the path to the file, as part of the name (thus,
if the file is in the directory above the current one, you can type in
a file name such as ../myfile.dna). If you do not know what a
"directory" is, or what "above" means, then you are a member of the new
generation who just clicks the mouse and assumes that a list of file names
will magically appear. (Typically members of this generation have no idea
where the files are on their system, and accumulate enormous amounts of
unnecessary clutter in their file systems.) In this case you should ask
someone to explain directories to you.
Running the programs on a Windows machine.
Double-click on the icon for
the program. A window should open with a menu in it. Further dialog with the
program occurs
by typing on the keyboard in response to what you see in the window. The
programs can be interrupted either by typing Control-C (which means to
press down on the Ctrl key while typing the letter C), or by using
the mouse to open the File menu in the upper-left corner of the program's
window area and then select Quit. Other than this, most PHYLIP programs
make no use of the mouse. The tree-drawing programs Drawtree and Drawgram
do allow use of the mouse to select some options.
Running the programs on a Macintosh.
Double-click on the icon for
the program. A window should open. Further dialog with the program occurs
by typing on the keyboard in response to what you see in the window. The
programs can be interrupted by using
the mouse to open the File menu in the upper-left corner of the program's
window area and then select Quit. Alternatively, you can use the
Command-Q key combination.
When you use Quit, the program will ask you whether you want to save
a file whose name is the program name (often followed by .out -- for
example, if you are using DNAML it will ask you if you want to save file
Dnaml.out. This file is simply a record of everything that
displayed on the program window, and you usually will not want to save it.
Pressing the Enter key or selecting the Do Not Save button with
the mouse will keep this from being saved.
If you encounter memory limitations on a Macintosh, and determine that
this is not due to a problem with the format of the input file, as it
often will be, you may be able to solve it by raising the limits of the
stack and heap sizes of the program. To do this click on the program
and then select Get Info from the Finder File menu.
This will open a window which can be made to show the memory limits
of the program. These can be changed by selecting them and typing in
larger numbers. This may relieve nagging memory problems. If it does
not, consult your local documentation and suspect problems with your
input file format.
Running the programs on a Unix system.
Type the name of the program
in lower-case letters (such as dnaml). To interrupt the program while
it is running, type Control-C (which means to press down on the Ctrl key
while typing the letter C).
Running the programs in MSDOS.
Type the name of the program
in lower-case letters (such as dnaml). To interrupt the program while
it is running, type Control-C (which means to press down on the Ctrl key
while typing the letter C).
Running the programs in background or under control of a command file
In running the programs, you may sometimes want to put them in background
so you can proceed with other work. On systems with a windowing environment
they can be put in their own window, and commands like the Unix and Linux
nice command used to make
them have lower priority so that they do not interfere with interactive
applications in other windows. This part of the discussion will
assume either a Windows system or a Unix or Linux system. I will
note when the commands work on one of these systems but not the other.
Running jobs in background on Macintosh systems is an arcane art into whose
mysteries I have not been initiated (or perhaps no one has been initiated).
If there is no windowing
environment, on a Unix or Linux system you will want to use an
ampersand (&) after the command file name when invoking it to put the
job in the background. You will have to put all the responses to the
interactive menu of the program into a file and tell the background job
to take its input from that file.
On Windows systems there is no & or nice command
but input and output redirection and command files work fine, with the sole
difference that the a file of commands must have a name ending in
.BAT, such as FOOFILE.BAT.
For example: suppose you want to run DNAPARS in a background, taking its
input data from a file called sequences.dat, putting its interactive
output to file called screenout, and using a file called input as
the place to store the interactive input. The file input need only
contain two lines:
sequences.dat
Y
which is what you would have typed to run the program interactively, in
response to the program's request for an input file name if it did not
find a file named infile, in in response the the menu.
To run the program in background, in Unix or Linux you would simply give the command:
dnapars < input > screenout &
These run the program with input responses coming from input and
interactive output being put into file screenout. The usual output
file and tree file will also be created by this run (keep that in mind
as if you run any other PHYLIP program from the same directory while
this one is running in background you may overwrite the output file from
one program with that from the other!).
If you wanted to give the program lower priority, so that it would
not interfere with other work, and you have Berkeley Unix type job control
facilities in your Unix or Linux (and you usually do), you can use the
nice command:
nice +10 dnapars < input > screenout &
which lowers the priority of the run. To also time the run and put the
timing at the end of screenout, you can do this:
nice +10 ( time dnapars < input ) >& screenout &
which I will not attempt to explain.
On Unix or Linux systems
you may also want to explore putting the interactive output into the
null file /dev/null so as to not be bothered with it (but then you
cannot look at it to see why something went wrong). If you have problems
with creating output files that are too large, you may want to
explore carefully the turning off of options in the programs you run.
If you are doing several runs in one, as for example when you do a
bootstrap analysis using SEQBOOT, DNAPARS (say), and CONSENSE, you
can use an editor to create a "command file" with these commands:
This is the Unix or Linux version -- in the MSDOS version, the renaming
of files and the appending of output to the file screenout is
handled differently.
On Unix or Linux the command file might be named something like
foofile, and on Windows systems might be named foofile.bat.
On Unix or Linux the command file must be given
execute permission by using the command chmod +x foofile followed
by the command rehash. The job that foofile describes
can be run in background on Unix or Linux by giving the command
foofile &
On Windows systems it can be run by
clicking on the icon of the command file. Its icon will have a little gear
symbol.
Note that you must also have the interactive input
commands for SEQBOOT (including the random number seed), DNAPARS, and
CONSENSE in the separate files input1, input2, and input3.
Note that when PHYLIP programs attempt to open a new output file (such as
outfile, outtree, or plotfile, if they see
a file of that name already in existence they will ask you if you want to
overwrite it, and offer alternatives including writing to another file,
appending information to that file, or quitting the program without writing to
the file. This means that in writing batch files it is important to know
whether there will be a prompt of this sort. You must know in advance
whether the file will exist. You may want to put in your batch file a
command that tests for the existence of a pre-existing output file and
if so, removes it. You might even want to put in a command that creates a
file of that name, so that you can be sure it is there! Either way,
you will then know whether to put into your file of keyboard responses the
proper response to the inquiry about overwriting that output file.
Preparing Input Files
The input files for PHYLIP programs must be prepared separately - there is
no data editor within PHYLIP. You can use a word processor (or text
editor) to prepare them yourself, or you can use a program that produces
a PHYLIP-format output. Sequence alignment programs such as ClustalW
commonly have an option to produce PHYLIP files as output, and some
other phylogeny programs, such as MacClade and TreeView, are capable of
producing a PHYLIP-format file.
The format of the input files is discussed below, and you should also
read the other PHYLIP documentation relevant to the particular type of
data that you are using, and the particular programs you want to run, as
there will be more details there.
It is very important that the input files be in "Text Only" or "flat
ASCII" format. This means that they contain only printable ASCII/ISO
characters, and not any unprintable characters. Many word processors such
as Microsoft Word save their files in a format that contains unprintable
characters, unless you tell them not to. For Microsoft Word you can
select Save As from its File menu, and choose Text Only
as the file format. This can also be done in WordPad utility in Windows .
Other word processors will have equivalent
options. Text editors such as the vi and emacs editors on
Unix and Linux, Windows Notepad, the SimpleText editor in MacOS, or the pico
editor that comes with the pine
mailer program, produce their files in Text Only format and should not
cause any trouble.
Input and output files
For most of the PHYLIP programs, information comes from a series of
input files, and ends up in a series of output files:
The programs interact with the user by presenting a menu. Aside from the
user's choices from the menu, they read
all other input from files. These files have default names. The program
will try to find a file of that name - if it does not, it will ask the
user to supply the name of that file.
Input data such as DNA sequences
comes from a file whose default name is infile. If the user
supplies a tree, this is in a file whose default name is intree.
Values of weights for the characters are in weights, and the
tree plotting program need some digitized fonts which are supplied in
fontfile (all these are default names).
For example, if DnaML looks
for the file infile and does not find one of that name,
it prints the message:
dnaml: can't find input file "infile"
Please enter a new file name>
This simply means that it wants you to type in the name of the
input file.
Two programs in the package works differently according to an older ("Old
Style") system. These are CLIQUE and FACTOR. The information on ancestral
states is supplied in the data file whose
default name is infile, and for FACTOR the Factors
information is written into the output file rather than being put into a
separate file called factors. See the documentation
page for CLIQUE
and the documentation page for FACTOR
for information on these differences. By the time of the final 3.6
release we hope to have these last Old Style programs converted to the new
system.
Data file format
I have tried to adhere to a rather stereotyped input and output
format. For the parsimony, compatibility and maximum likelihood programs,
excluding the distance matrix methods, the simplest version of the input
data file looks something like this:
The first line of the input file contains the number of species and the
number of characters (in this case sites). These are in free format, separated
by blanks. The information for each species follows, starting with a
ten-character species name (which can include blanks and some punctuation
marks), and continuing with the characters for that species. The name should
be on the same line as the first character of the data for that species.
(I will use the term "species" for the tips of the trees, recognizing
that in some cases these will actually be populations or individual gene
sequences).
The name should be ten characters in length, filled out to the full
ten characters by blanks if shorter. Any printable ASCII/ISO character is
allowed in the name, except for parentheses ("(" and ")"), square
brackets ("[" and "]"), colon (":"), semicolon (";") and comma (",").
If you forget to extend the names to ten characters in length by blanks,
the program will get out of synchronization with the contents of the data
file, and an error message will result.
In the
discrete-character programs, DNA sequence programs and protein sequence
programs the characters are each a
single letter or digit, sometimes separated by blanks. In
the continuous-characters programs they are real numbers with decimal points,
separated by blanks:
Latimeria 2.03 3.457 100.2 0.0 -3.7
The conventions about continuing the data beyond one line per species are
different between the molecular sequence programs and the others. The
molecular sequence programs can take the data in "aligned" or "interleaved"
format, in which we first have some lines giving the first part of each of the
sequences, then some
lines giving the next part of each, and so on. Thus the sequences might
look like this:
Note that in these sequences we have a blank every
ten sites to make them easier to read: any such blanks are allowed. The blank
line which separates the two groups of lines (the ones
containing sites 1-20 and ones containing sites 21-39) may or may not
be present, but if it is, it should be a line of zero length and not contain
any extra blank
characters (this is because of a limitation of the current versions
of the programs). It is important that the number of sites in each
group be the same for all species (i.e., it will not be possible to run
the programs successfully if the first species line contains 20 bases, but
the first line for the second species contains 21 bases).
Alternatively, an option can be selected in the menu to take the data in
"sequential" format, with all of the data for the first species,
then all of the characters for the next species, and so on. This is also
the way that the discrete characters programs and the gene frequencies
and quantitative characters programs want to read the data. They do not
allow the interleaved format.
In the sequential format, the character data can run on to a new line at any
time (except in the middle of a species name or, in the case of continuous
character and distance matrix programs where you cannot go to a new line in
the middle of a real number). Thus it is legal to have:
Archaeopt 001100
1101
or even:
Archaeopt
0011001101
though note that the full ten characters of the species name must
then be present: in the above case there must be a blank after the "t". In all
cases it is possible to put internal blanks between any of the character
values, so that
Archaeopt 0011001101 0111011100
is allowed.
Note that you can convert molecular sequence data between the interleaved
and the sequential data formats by using the Rewrite option of the D
menu item in SEQBOOT.
If you make an error in the format of the input file, the programs can
sometimes detect that
they have been fed an illegal character or illegal numerical value and issue
an error message such as BAD CHARACTER STATE:, often printing out the
bad value, and sometimes the number of the species and character in which it
occurred. The program will then stop shortly after. One of the things which
can lead to a bad value is the omission of something earlier in the file, or
the insertion of something superfluous, which cause the reading of the file to
get out of synchronization. The program then starts reading things it
didn't expect, and concludes that they are in error. So if you see this error
message, you may also want
to look for the earlier problem that may have led to the program becoming
confused about what it is reading.
Some options are described below, but you should also read the documentation
for the groups of the programs and for the individual programs.
The Menu
The menu is straightforward. It typically looks like this (this one is for
DNAPARS):
DNA parsimony algorithm, version 3.6
Setting for this run:
U Search for best tree? Yes
S Search option? More thorough search
V Number of trees to save? 100
J Randomize input order of sequences? No. Use input order
O Outgroup root? No, use as outgroup species 1
T Use Threshold parsimony? No, use ordinary parsimony
N Use Transversion parsimony? No, count all steps
W Sites weighted? No
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each site No
5 Print sequences at all nodes of tree No
6 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
If you want to accept the default settings (they are shown in the above case)
you can simply type Y followed by pressing on the Enter key.
If you want to change any of the options, you should type the letter
shown to the left of its entry in the menu. For example, to set a threshold
type T. Lower-case letters will also work. For many of the options
the program will ask for supplementary information, such as the value of
the threshold.
Note the Terminal type entry, which you will find on all menus. It
allows you to specify which type of terminal your screen is. The options
are an IBM PC screen, an ANSI standard terminal, or none.
Choosing zero (0) toggles
among these three options in cyclical order, changing each time the 0
option is chosen. If one of them is right for your terminal the screen will be
cleared before the menu is displayed. If none works, the none option
should probably be chosen. The programs should start with a terminal option
appropriate for your computer, but if they do not, you can change the
terminal type manually. This is particularly important in program RETREE
where a tree is displayed on the screen - if the terminal type is set to the
wrong value, the tree can look very strange.
The other numbered options control which information the program will
display on your screen or on the output files. The option to Print
indications of progress of run will show information such as the names of
the species as they are successively added to the tree, and the
progress of rearrangements. You will usually want to see these as
reassurance that the program is running and to help you estimate how long
it will take. But if you are running the program "in background" as can be
done on multitasking and multiuser systems, and do not have the
program running in its own window, you may want to turn this option off so
that it does not disturb your use of the computer while the program is
running.
The Output File
Most of the programs write their output onto a file called (usually) outfile, and a representation of the trees found onto a file called
outtree.
The exact contents of the output file vary from program to program and also
depend on which menu options you have selected. For many programs, if you
select all possible output information, the output will consist of
(1) the name of the program and its
version number, (2) some of the input information printed out, and (3) a series of
phylogenies, some with associated information indicating how much change
there was in each character or on each part of the tree. A typical rooted tree
looks like this:
The interpretation of the tree is fairly straightforward: it "grows"
from left to right. The numbers at the forks are arbitrary and are used (if
present) merely to identify the forks. For many of the programs the tree
produced is unrooted. Rooted and unrooted trees are printed in nearly the
same form, but the unrooted ones are accompanied by the
warning message:
remember: this is an unrooted tree!
to indicate that this is an unrooted tree and to warn against
taking the position of its root too seriously. Mathematicians still call
an unrooted tree a tree, though some systematists unfortunately use the term
"network" for an unrooted tree. This conflicts with standard mathematical
usage, which reserves the name "network" for a completely different kind of
graph). The root of this tree could be anywhere, say on the line leading
immediately to Mouse. As an exercise,
see if you can tell whether the following tree is or is not a different
one from the above:
(it is not different). It is important also to realize that the
lengths of the segments of the printed tree may not be significant: some
may actually represent branches of zero length, in the sense that there is no
evidence that
those branches are nonzero in length. Some of the diagrams of trees attempt
to print branches approximately proportional to estimated
branch lengths, while in others the lengths are purely conventional and
are presented just to make the topology visible. You will have to look closely
at the documentation that accompanies each program to see what it presents
and what is known about the lengths of the branches on the tree. The above
tree attempts to represent branch lengths approximately in the diagram. But
even in those cases, some of the smaller branches are likely to be
artificially lengthened to make the tree topology clearer. Here is what
a tree from DNAPARS looks like, when no attempt is made to make the
lengths of branches in the diagram proportional to estimated branch
lengths:
+--Human
+--5
+--4 +--Chimp
! !
+--3 +-----Gorilla
! !
+--2 +--------Orang
! !
+--1 +-----------Gibbon
! !
--6 +--------------Mouse
!
+-----------------Bovine
remember: this is an unrooted tree!
When a tree has branch lengths, it will be accompanied by a table showing
for each branch the numbers (or names) of the nodes at each end of the
branch, and the length of that branch. For the first tree shown above,
the corresponding table is:
Ignoring the asterisks and the approximate confidence limits, which will be
described in the documentation file for DNAML, we can see that the table
gives a more precise idea of what the lengths of all the branches are.
Similar tables exist in distance matrix and likelihood programs, as well
as in the parsimony programs DNAPARS and PARS.
Some of the parsimony programs in the package can print out a table
of the number of steps that different characters (or sites) require on
the tree. This table may not be obvious at first. A typical example looks like
this:
The numbers across the top and down the side indicate which site
is being referred to. Thus site 23 is column "3" of row "20"
and has 1 step in this case.
There are many other kinds of information that can appear in the
output file, They vary from program to program, and we leave their
description to the documentation files for the specific programs.
The Tree File
In output from most programs,
a representation of the tree is also written into the tree file
outtree. The tree is specified by nested pairs
of parentheses, enclosing
names and separated by commas. We will describe how this works
below. If there are any blanks in the names,
these must be replaced by the underscore character "_". Trailing blanks
in the name may be omitted. The pattern of the parentheses indicates
the pattern of the tree by having each pair of parentheses enclose all
the members of a monophyletic group. The tree file could look like this:
In this tree the first fork separates the lineage leading to
Mouse and Bovine from the lineage leading to the rest. Within the
latter group there is a fork separating Gibbon from the rest, and so on.
The entire tree is enclosed in an outermost pair of parentheses. The tree ends
with a semicolon. In some programs such as DNAML, FITCH, and CONTML,
the tree will be unrooted. An unrooted tree should have its
bottommost fork have a
three-way split, with three groups separated by two commas:
(A,(B,(C,D)),(E,F));
Here the three groups at the bottom node are A, (B,C,D), and
(E,F). The single three-way split corresponds to one of the interior
nodes of the unrooted tree (it can be any interior node of the tree). The
remaining forks are encountered as you move out from that first node.
In newer programs, some are able to tolerate these other forks being
multifurcations (multi-way splits).
You should check the documentation files
for the particular programs you are using to see in which of these forms
you can expect the user tree to be in. Note that many of the programs
that actually estimate an unrooted tree (such as DNAPARS) produce trees in the
treefile in rooted form! This is done for reasons of arbitrary internal bookkeeping. The placement of the root is arbitrary. We are working toward
having all programs be able to read all trees, whether rooted or unrooted,
multifurcating or bifurcating, and having them do the right thing with
them. But this is a long-term goal and it is not yet achieved.
For programs that infer branch lengths, these are given in the trees in the
tree file as real numbers following a colon, and placed immediately
after the group descended from that branch. Here is a typical tree
with branch lengths:
Note that the tree may continue to a new line at any time except in the
middle of a name or the middle of a branch length, although in trees
written to the tree file this will only be done after a comma.
These representations of trees are a subset of the standard adopted
on 24 June 1986 at the annual meetings of the Society for the Study of
Evolution by an informal committee (its final session in Newick's
lobster restaurant - hence its name, the Newick standard)
consisting of Wayne Maddison (author of MacClade), David Swofford (PAUP),
F. James Rohlf (NTSYS-PC), Chris Meacham (COMPROB and the original
PHYLIP tree drawing programs), James Archie,
William H.E. Day, and me. This standard is a generalization of
PHYLIP's format, itself based on a well-known representation of trees in
terms of parenthesis patterns which is due to the famous mathematician
Arthur Cayley, and which has been around for over a century. The
standard is now employed by most phylogeny computer programs but unfortunately
has yet to be decribed in a formal published description. Other
descriptions by me and by Gary Olsen can be accessed using the Web at:
Most of the programs allow various options that alter the amount of
information the program is provided or what is done with the
information. Options are selected in the menu.
Common options in the menu
A number of the options from the menu, the U (User tree), G (Global),
J (Jumble), O (Outgroup), W (Weights),
T (Threshold), M (multiple data sets), and the tree output options, are used
so widely that it is best to discuss them in this document.
The U (User tree) option. This option toggles between the default
setting, which allows the program to search for the best tree, and the
User tree setting, which reads a tree or trees ("user trees") from the input
tree file and evaluates them. The input tree file's
default name is intree. In a few cases the trees should
be preceded by a line giving the number of trees:
while in most cases the initial line with the number of trees is not
required. This is an inconsistency in the programs that we are intending
to eliminate soon. Some programs require rooted trees, some unrooted
trees, and some can handle multifurcating trees. You should read
the documentation for the particular program to find out which it
requires. Program RETREE can be used to convert trees among
these forms (on saving a tree from RETREE, you are asked whether
you want it to be rooted or unrooted).
In using the user tree option, check the pattern of parentheses
carefully. The programs do not always detect
whether the tree makes sense, and if it does not there will probably be
a crash (hopefully, but not inevitably, with an error message indicating
the nature of the problem). Trees written out by programs are
typically in the proper form.
Some of the programs require that the user trees be preceded by line with the
number of user trees. Some require that they not be preceded by
this line, and many can tolerate either. I have tried to note for
each of these programs which of these forms of the user tree file
is appropriate. We hope to bring all programs to the same user tree file
format as soon as possible.
The G (Global) option. In the programs which construct trees (except for
NEIGHBOR, the "...PENNY" programs and CLIQUE, and of course
the "...MOVE" programs where you construct the trees yourself),
after all species have been added to the tree a rearrangements phase
ensues. In most of these programs the rearrangements are automatically
global, which in this case means that subtrees will be removed from the tree
and put back on in all possible ways so as to have a better chance of
finding a better tree. Since this can be time consuming (it roughly
triples the time taken for a run) it is left as an option in some of the
programs, specifically CONTML, FITCH, and DNAML. In these programs
the G menu option toggles between the default of local rearrangement and
global rearrangement. The rearrangements are explained more below.
The J (Jumble) option. In most of the tree construction programs
(except for the "...PENNY" programs and CLIQUE), the exact
details of the search of different trees depend on the order of input of
species. In these programs J option enables you to tell the program to use
a random number
generator to choose the input order of species. This option is toggled on
and off by
selecting option J in the menu. The program will then prompt you for
a "seed" for the random number generator. The seed should be an integer
between 1 and 32767, and should of form 4n+1,
which means that it must give a remainder of 1 when divided by 4. This can be
judged by looking at the last two digits of the number. Each different seed
leads to a different sequence of addition of species. By simply changing the
random number seed and re-running the programs one can look for other, and
better trees. If the seed entered is not odd, the program will not proceed,
but will prompt for another seed.
The Jumble option also causes the program to ask you how many times you
want to restart the process. If you answer 10, the program will
try ten different orders of species in constructing the trees, and the
results printed out will reflect this entire search process (that is,
the best trees found among all 10 runs will be printed out, not the
best trees from each individual run).
Some people have asked what are good values of the random number seed.
The random number seed is used to start a process of choosing "random"
(actually pseudorandom) numbers, which behave as if they were
unpredictably randomly chosen between 0 and 232-1 (which is
4,294,967,296). You could put in the number 133 and find that the
next random number was 1,876,973,009. As they are effectively
unpredictable, there is no such thing as a choice that is better than
any other, provided that the numbers are of the form 4n+1. However
if you re-use a random number seed, the sequence of random numbers
that result will be the same as before, resulting in exactly the same
series of choices, which may not be what you want.
The O (Outgroup) option. This specifies which species is to be used
to root the tree by having it become the outgroup. This option is
toggled on and off by choosing O in the menu (the alphabetic
character O, not the digit 0). When it is on, the program will
then prompt for the
number of the outgroup (the species being taken in the numerical order that
they occur in the input file). Responding by typing 6 and then an
Enter character indicates that the sixth species in the data
is the outgroup. Outgroup-rooting will not be attempted if the
data have already established a root for the tree from some other
consideration, and may not be if it is a user-defined tree,
despite your invoking the option. Thus programs such as DOLLOP that
produce only rooted trees do not allow the Outgroup option. It is also
not available in KITSCH, DNAMLK, or CLIQUE. When it is used, the tree as
printed out is still listed as being an
unrooted tree, though the outgroup is connected to the bottommost node
so that it is easy to visually convert the tree into rooted form.
The T (Threshold) option. This sets a threshold forn the
parsimony programs such that if the
number of steps counted in a character is higher than the threshold, it
will be taken to be the threshold value rather than the actual number of
steps. The default is a threshold so high that it will never be
surpassed (in which case the steps whill simply be counted). The T
menu option toggles on and off asking the user to
supply a threshold. The use of thresholds to obtain methods intermediate
between parsimony and compatibility methods is described in my 1981b paper.
When the T option is in force, the program
will prompt for the numerical threshold value. This will be a positive
real number greater than 1. In programs MIX, MOVE, PENNY, PROTPARS,
DNAPARS, DNAMOVE, and DNAPENNY, do not use threshold values less
than or equal to 1.0, as they have no meaning and lead to a tree which
depends only on considerations such as the input order of species and not at
all on the character state data! In programs DOLLOP, DOLMOVE, and DOLPENNY
the threshold should never be 0.0 or less, for the same
reason. The T option is an
important and underutilized one: it is, for example, the only way in this
package (except for program DNACOMP) to do a compatibility analysis when there
are missing data. It is a method of de-weighting characters that evolve
rapidly. I wish more people were aware of its properties.
The M (Multiple data sets) option. In menu programs there is an
M menu
option which allows one to toggle on the multiple data sets option. The
program will ask you how many data sets it should expect. The data sets
have the same format as the first data set. Here is a (very small) input file
with two five-species data sets:
The main use of this option will be to allow all of the methods in these
programs to be bootstrapped. Using the program SEQBOOT one can take any
DNA, protein, restriction sites, gene frequency or binary character data set and
make multiple data sets by bootstrapping. Trees can be produced for all of
these using the M option. They will be written on the tree output file if
that option is left in force. Then the program CONSENSE can be used with
that tree file as its input file. The result is a majority rule consensus
tree which can be used to make confidence intervals. The present version
of the package allows, with the use of SEQBOOT and CONSENSE and the M option,
bootstrapping of many of the methods in the package.
Programs DNAML, DNAPARS and PARS can also take multiple weights
instead of multiple data sets. They can then do bootstrapping by
reading in one data set, together with a file of weights that show how
the characters (or sites) are reweighted in each bootstrap sample. Thus a
site that is omitted in a bootstrap sample has effectively been given
weight 0, while a site that has been duplicated has effectively been
given weight 2. SEQBOOT has a menu selection to produce the file of
weights information automatically, instead of producing a file of
multiple data sets.
The W (Weights) option. This signals the program that, in
addition to the data set, you want to read in a series of weights that
tell how many times each character is to be counted. If the weight
for a character is zero (0) then that character is in effect to
be omitted when the tree is evaluated. If it is (1) the
character is to be counted once. Some programs allow weights greater than
1 as well. These have the effect that the character is counted as
if it were present that many times, so that a weight of 4 means that the
character is counted 4 times.
The values 0-9 give weights 0 through 9, and the
values A-Z give weights 10 through 35. By use of the weights we can
give overwhelming weight to some characters, and drop others from the
analysis. In the molecular sequence programs only two values of the
weights, 0 or 1 are allowed.
The weights are used to analyze subsets of the characters, and also can be
used for resampling of the data as in bootstrap and jackknife resampling.
For those programs that allow weights to be greater than 1, they can also
be used to emphasize information from some characters more strongly than
others. Of course, you must have some rationale for doing this.
The weights are provided as a sequence of digits. Thus they might be
10011111100010100011110001100
The weights are to be provided in an input file
whose default name is weights. In programs such as SEQBOOT
that can also output a file of weights, the input weights have a default
file name of inweights, and the output file name has a default
file name of outweights.
Weights can be used to analyze different subsets of characters (by weighting
the rest as zero). Alternatively, in the discrete characters programs
they can be used to force a certain
group to appear on the phylogeny (in effect confining consideration to only
phylogenies containing that group). This is done by adding an imaginary
character that has 1's for the members of the group, and 0's
for all the
other species. That imaginary character is then given the highest weight
possible: the result will be that any phylogeny that does not contain that
group will be penalized by such a heavy amount that it will not (except in
the most unusual circumstances) be considered. Of course, the new character
brings extra steps to the tree, but the number of these can be calculated
in advance and subtracted out of the total when reporting the results. This
use of weights is an important one, and one sadly ignored
by many users who could profit from it. In the case of molecular sequences
we cannot use weights this way, so that to force a given group to appear we
have to add a large extra segment of sites to the molecule, with (say) A's
for that group and C's for every other species.
The option to write out the trees into a tree file. This specifies that you
want the program to write
out the tree not only on its usual output, but also onto a file in
nested-parenthesis notation (as described above). This option is sufficiently
useful that it is turned on by default in all programs that allow it. You
can optionally turn it off if you wish, by typing the appropriate number
from the menu (it varies from program to program). This option is useful for
creating tree files that can be directly read into the programs, including
the consensus tree and tree distance programs, and the tree plotting programs.
The output tree file has a default name of outtree.
The (0) terminal type option . (This is the digit 0, not
the alphabetic character O). The program will default to
one particular assumption about your terminal (except in the case of
Macintoshes, the default will be an ANSI compatible terminal). You can
alternatively select it to be either an IBM PC, or nothing.
This affects the ability of the programs to clear the screen when they
display their menus, and the graphics characters used to display trees
in the programs DNAMOVE, MOVE, DOLMOVE, and RETREE. If you are running an
MSDOS system and have the ANSI.SYS driver installed in your CONFIG.SYS
file, you may find that the screen clears correctly even with the default
setting of ANSI.
The Algorithm for Constructing Trees
All of the programs except FACTOR, DNADIST, GENDIST, DNAINVAR, SEQBOOT,
CONTRAST, RETREE, and the plotting and
consensus tree programs act to construct an estimate of a phylogeny. MOVE,
DOLMOVE, and DNAMOVE let you construct it yourself by hand. All of
the rest but NEIGHBOR, the "...PENNY" programs and CLIQUE make use of
a common approach involving additions and rearrangements. They are
trying to minimize or maximize some quantity over the space of all
possible evolutionary trees. Each program contains a part that, given
the topology of the tree, evaluates the quantity that is being minimized
or maximized. The straightforward approach would be to evaluate all
possible tree topologies one after another and pick the one which,
according to the criterion being used, is best. This would not be
possible for more than a small number of species, since the number of
possible tree topologies is enormous. A review of the literature on the
counting of evolutionary trees will be found one of my papers
(Felsenstein, 1978a).
Since we cannot search all topologies, these programs are not
guaranteed to always find the best tree, although they seem to do quite
well in practice. The strategy they employ is as follows: the species
are taken in the order in which they appear in the input file. The
first two (in some programs the first three) are taken and a tree
constructed containing only those. There is only one possible topology for
this tree. Then the next species is taken, and we consider where it
might be added to the tree. If the initial tree is (say) a rooted tree
with two species and we want the resulting three-species tree to be a
bifurcating tree, there are only three places where we could add the
third species. Each of these is tried, and each time the resulting tree is
evaluated according to the criterion. The best one is chosen to be the
basis for further operations. Now we consider adding the fourth
species, again at each of the five possible places that would result in
a bifurcating tree. Again, the best of these is accepted.
Local Rearrangements
The process continues in this manner, with one important exception. After
each species is added, and before the next
is added, a number of rearrangements of the tree are tried, in an effort
to improve it. The algorithms move through the tree, making all
possible local rearrangements of the tree. A local rearrangement involves an
internal segment of the tree in the following manner. Each internal
segment of the tree is of this form (where T1, T2, and T3 are subtrees
- parts of the tree that can contain further forks and tips):
the segment we are discussing being indicated by the asterisks. A local
rearrangement consists of switching the subtrees T1 and T3 or T2 and T3,
so as to obtain one of the following:
Each time a local rearrangement is successful in finding a better tree,
the new arrangement is accepted. The phase of local rearrangements does
not end until the program can traverse the entire tree, attempting local
rearrangements, without finding any that improve the tree.
This strategy of adding species and making local rearrangements will look
at about (n-1)x(2n-3) different topologies, though if
rearrangements are frequently successful the number may be larger. I
have been describing the strategy when rooted trees are being
considered. For unrooted trees there is a precisely similar strategy,
though the first tree constructed may be a three-species tree and the
rearrangements may not start until after the addition of the fifth
species.
Though we are not guaranteed to have found the best tree topology,
we are guaranteed that no nearby topology (i. e. none accessible by a
single local rearrangement) is better. In this sense we have reached a
local optimum of our criterion. Note that the whole process is
dependent on the order in which the species are present in the input
file. We can try to find a different and better solution by reordering
the species in the input file and running the program again (or, more
easily, by using the J option). If none of
these attempts finds a better solution, then we have some indication
that we may have found the best topology, though we can never be certain
of this.
Note also that a new topology is never accepted unless it is better
than the previous one, so that the rearrangement process can never fall
into an endless loop. This is also the way ties in our criterion are
resolved, namely by sticking with the tree found first. However, the tree
construction programs other than CLIQUE, CONTML, FITCH,
and DNAML do keep a record of all trees found that are tied with the best one
found. This gives you some immediate idea of which parts of the tree can be
altered without affecting the quality of the result.
Global Rearrangements
A feature of most of the programs, such as PROTPARS, DNAPARS,
DNACOMP, DNAML, DNAMLK, RESTML, KITSCH, FITCH, CONTML, MIX, and DOLLOP,
is "global" optimization of the tree. In four of these (CONTML,
FITCH, DNAML and DNAMLK) this is an option, G. In the others it
automatically applies. When
it is present there is an additional stage to the search for the best tree.
Each possible subtree is removed from the tree from the tree and added back in
all possible places. This process continues until all subtrees can be removed
and added again without any improvement in the tree. The purpose of this
extra rearrangement is to make it less likely that one or more a species gets
"stuck" in a suboptimal region of the space of all possible trees. The use of
global optimization results in approximately a tripling (3 x ) of the run-time,
which is why I have left it as an option in some of the slower programs.
What PHYLIP calls "global" rearrangements are more properly called
SPR (subtree pruning and regrafting) by Swofford et. al. (1996) as distinct
from the NNI (nearest neighbor interchange) rearrangements that PHYLIP
also uses, and the TBR (tree bisection and reconnection) rearrangements
that it does not use.
The programs doing global optimization print out a dot "." after each group is
removed and re-added to the tree, to give the user some sign that the
rearrangements are proceeding. A new line of dots is started whenever a new
round of global rearrangements is started following an improvement in the
tree. On the line before the dots are printed there is printed a bar of
the form "!---------------!" to show how many dots
to expect. The dots will
not be printed out at a uniform rate, but the later dots, which represent
removal of larger groups from the tree and trying them consequently in fewer
places, will print out more quickly. With some compilers each row of dots may
not be printed out until it is complete.
It should be noted that PENNY, DOLPENNY, DNAPENNY and CLIQUE use a more
sophisticated strategy of "depth-first search" with a "branch and bound"
search method that guarantees that all
of the best trees will be found. In the case
of PENNY, DOLPENNY and DNAPENNY there can be a considerable sacrifice of
computer time if the number of species is greater than about ten: it is a
matter for you to consider whether it is worth it for you to guarantee finding
all the most parsimonious trees, and that depends on how much free computer
time you have! CLIQUE finds all largest cliques, and does so without undue
burning of computer time. Although all of these problems that have been
investigated fall into the
category of "NP-hard" problems that in effect do not have a rapid solution,
the cases that cause this trouble for the largest-cliques algorithm in
CLIQUE apparently are not biologically realistic and do not occur in actual
data.
Multiple Jumbles
As just mentioned, for most of these programs the search depends on the order
in which the species are entered into the tree. Using the J (Jumble)
option you can supply a random number seed which will allow the program to put
the species in in a random order. Jumbling can be
done multiple times. For example, if you tell the program to do it
10 times, it will go through the tree-building process 10 times, each with a
different random order of adding species. It will keep a record of the trees
tied for best over the whole process. In other words, it does not just
record the best trees from each of the 10 runs, but records the best ones
overall. Of course this is slow, taking 10 times longer than a single run.
But it does give us a much greater chance of finding all of the most
parsimonious trees. In the terminology of Maddison (1991) it
can find different "islands" of trees. The present algorithms do not
guarantee us to find all trees in a given "island" from a single run, so
multiple runs also help explore those "islands" that are found.
Saving multiple tied trees
For the parsimony and compatibility programs, one can have a perfect tie
between two or more trees. In these programs these trees are all
saved. For the newer parsimony programs such as DNAPARS and PARS,
global rearrangement is carried out on all of these tied trees. This can
be turned off in the menu.
For trees with criteria which are real numbers, such as the distance
matrix programs FITCH and KITSCH, and the likelihood programs DNAML,
DNAMLK, CONTML, and RESTML, it is difficult to get an exact tie between
trees. Consequently these programs save only the single best tree
(even though the others may be only a tiny bit worse).
Strategy for Finding the Best Tree
In practice, it is advisable to use the Jumble option to evaluate many
different orderings of the input species. It is advisable to use the
Jumble option and specify that it be done many times (as many as ten)
to use different orderings
of the input species).
People who want a magic "black box" program whose results they do
not have to question (or think about) often are upset that these
programs give results that are dependent on the order in which the species
are entered in the data. To me this property is an advantage, for it
permits you to try different searches for better trees, simply by
varying the input order of species. If you do not use the multiple Jumble
option, but do multiple individual runs instead, you
can easily decide which to pay most attention to - the one or ones that
are best according to the criterion employed (for example, with parsimony,
the one out of the runs that results in the tree with the fewest changes).
In practice, in a single run, it usually seems best to put species that are
likely to be sources of confusion in the topology last, as by the time they are
added the arrangement of the earlier species will have stabilized into a
good configuration, and then the last few species will by fitted into
that topology. There will be less chance this way of a poor initial
topology that would affect all subsequent parts of the search. However,
a variety of arrangements of the input order of species should be tried,
as can be done if the J option is used,
and no species should be kept in a fixed place in the order of input.
Note that the results of the "...PENNY" programs and CLIQUE
are not sensitive to the input order of species, and NEIGHBOR is only
slightly sensistive to it, so that multiple Jumbling is not possible
with those programs. Note also that with global search, which
is standard in many programs and in others is an
option, each group (including
each individual species) will be removed and re-added in all possible
positions, so that a species causing confusion will have more chance of moving
to a new location than it would without global rearrangement.
A Warning on Interpreting Results
Probably the most important thing to keep in mind while running any of the
parsimony or compatibility programs is not
to overinterpret the result. Many users treat the set of most parsimonious
trees as if it were a confidence interval. If a group appears in all of the
most parsimonious trees then they treat it as well established. Unfortunately
the confidence interval on phylogenies appears to be much
larger than the set of all most parsimonious trees (Felsenstein, 1985b).
Likewise, variation of result among different methods will not be a good
indicator of the size of the confidence interval. Consider a simple data set
in which, out of 100 binary characters, 51 recommend the unrooted tree
((A,B),(C,D)) and 49 the tree ((A,D),(B,C)). Many different
methods will all give the same result on
such a data set: they will estimate the tree as ((A,B),(C,D)).
Nevertheless it is
clear that the 51:49 margin by which this tree is favored is not statistically
significantly different from 50:50. So consistency among different methods
is a poor guide to statistical significance.
Relative Speed of Different
Programs and Machines
Relative speed of the different programs
C compilers differ in efficiency of the code they generate,
and some deal with some features of the language better than with
others. Thus a program which is unusually fast on one computer may be
unusually slow on another. Nevertheless, as a rough guide to relative
execution speeds, I have tested the programs on three data sets, each of
which has 10 species and 40 characters. The first is an imaginary one
in which all characters are compatible - ("The Willi Hennig Memorial
Data Set" as J. S. Farris once called ones like it). The second is the binary
recoded form of the fossil horses data set of Camin and Sokal (1965).
The third data set has data that is completely random: 10 species and 20
characters that have a 50% chance that each character state is 0 or
1 (or A or G). The data sets thus range from a completely
compatible one in which there is no homoplasy (paralellism or convergence),
through the horses data set, which requires 29 steps where the possible
minimum number would be 20, to the random data set, which requires 49 steps.
We can thus see how this increasing messiness of the data affects running
times. The three data sets have all had 20 sites of A's added to the
end of each sequence, so as to prevent likelihood or distance matrix programs
from having infinite branch lengths (the test data sets used for timing
previous versions of PHYLIP wsere the same except that they lacked these
20 extra sites).
Here are the nucleotide sequence versions of the three data sets:
10 40
A CACACACAAAAAAAAAAACAAAAAAAAAAAAAAAAAAAAA
B CACACAACAAAAAAAAAACAAAAAAAAAAAAAAAAAAAAA
C CACAACAAAAAAAAAAAACAAAAAAAAAAAAAAAAAAAAA
D CAACAAAACAAAAAAAAACAAAAAAAAAAAAAAAAAAAAA
E CAACAAAAACAAAAAAAACAAAAAAAAAAAAAAAAAAAAA
F ACAAAAAAAACACACAAAACAAAAAAAAAAAAAAAAAAAA
G ACAAAAAAAACACAACAAACAAAAAAAAAAAAAAAAAAAA
H ACAAAAAAAACAACAAAAACAAAAAAAAAAAAAAAAAAAA
I ACAAAAAAAAACAAAACAACAAAAAAAAAAAAAAAAAAAA
J ACAAAAAAAAACAAAAACACAAAAAAAAAAAAAAAAAAAA
10 40
A CACACAACCAAACAAACCACAAAAAAAAAAAAAAAAAAAA
B AAACCACACACACAAACCCAAAAAAAAAAAAAAAAAAAAA
C ACAAAACCAAACCACCCACAAAAAAAAAAAAAAAAAAAAA
D AAAAACACAACACACCAAACAAAAAAAAAAAAAAAAAAAA
E AAACAACCACACACAACCAAAAAAAAAAAAAAAAAAAAAA
F CCCAAACACCCCCAAAAAACAAAAAAAAAAAAAAAAAAAA
G ACACCCCCACACCCACCAACAAAAAAAAAAAAAAAAAAAA
H AAAACAACAACCACCCCACCAAAAAAAAAAAAAAAAAAAA
I ACACAACAACACAAACAACCAAAAAAAAAAAAAAAAAAAA
J CCAAAAACACCCAACCCAACAAAAAAAAAAAAAAAAAAAA
Here are the timings of many of the version 3.6 programs on these three data
sets as run after being compiled by Gnu C and run on a
266 MHz Pentium MMX computer under Linux.
Hennigian Data
Horses Data
Random Data
PROTPARS
0.133
0.167
0.308
DNAPARS
0.163
0.191
0.573
DNAPENNY
0.300
0.196
36.68
DNACOMP
0.081
0.073
0.127
DNAML
2.19
2.53
2.73
DNAMLK
5.40
6.13
7.21
PROML
44.79
90.46
68.49
PROMLK
171.01
183.61
239.34
DNAML
2.19
2.53
2.73
DNAINVAR
0.002
0.002
0.002
DNADIST
0.029
0.024
0.033
PROTDIST
1.095
1.089
1.107
RESTML
3.55
3.18
5.15
RESTDIST
0.012
0.010
0.010
FITCH
0.20
0.31
0.24
KITSCH
0.055
0.061
0.058
NEIGHBOR
0.003
0.004
0.005
CONTML
0.380
0.368
0.396
GENDIST
0.008
0.009
0.008
PARS
0.201
0.263
0.729
MIX
0.064
0.078
0.123
PENNY
0.038
0.087
15.93
DOLLOP
0.134
0.141
0.233
DOLPENNY
0.051
0.241
101.29
CLIQUE
0.010
0.015
0.020
In all cases the programs were run under the default options without compiler
switches, except as
specified here. The
data sets used for the discrete characters programs have 0's and 1's
instead of A's and C's. For CONTML the A's and C's
were made into 0.0's and 1.0's and considered as 40 2-allele loci.
For the distance programs 10 x 10 distance matrices were
computed from the three data sets.
For the restriction sites programs A and C were changed into
+ and -. It does not
make much sense to benchmark MOVE, DOLMOVE, or DNAMOVE, although when there
are many characters and many species the response time after each
alteration of the tree should be proportional to the product of the number of
species and the number of characters. For DNAML and DNAMLK the frequencies
of the four bases were
set to be equal rather than determined empirically as is the default. For
RESTML the number of enzymes was set to 1.
In most cases, the benchmark was made more accurate by analyzing 10 data
sets using the M (Multiple data sets) option and dividing the resulting
time by 10. Times were determined as user times using the Linux time
command. Several patterns will be apparent from this. The algorithms (MIX,
DOLLOP, CONTML, FITCH, KITSCH, PROTPARS, DNAPARS, DNACOMP, and
DNAML, DNAMLK, RESTML) that use the above-described addition strategy have
run times that do not depend strongly on the messiness of the data. The only
exception to this is that if a data set such as the Random data requires
extra rounds of global rearrangements it takes longer. The
programs differ greatly in run time: the likelihood programs RESTML, DNAML and
CONTML are quite a bit slower than the others. The protein sequence parsimony
program, which has to do a considerable amount of bookkeeping to keep track of
which amino acids can mutate to each other, is also relatively slow.
Another class of algorithms includes PENNY, DOLPENNY, DNAPENNY and CLIQUE.
These are branch-and-bound methods: in principle they should have execution
times that rise exponentially with the number of species and/or
characters, and they might be much more sensitive to messy data. This is
apparent with PENNY, DOLPENNY, and DNAPENNY, which go from being reasonably
fast with clean data to very slow with messy data. DOLPENNY is particularly
slow on messy data - this is because this algorithm cannot make use of some of
the lower-bound calculations that are possible with DNAPENNY and PENNY. CLIQUE
is very fast on all
data sets. Although in theory it should bog down if the number of cliques in
the data is very large, that does not happen with random data, which in
fact has few cliques and those small ones. Apparently the "worst-case"
data sets that cause exponential run time are much rarer for CLIQUE than for
the other branch-and-bound methods.
NEIGHBOR is quite fast compared to FITCH and KITSCH, and should make it
possible to run much larger cases, although the results are expected to be
a bit rougher than with those programs.
Speed with different numbers of species
How will the speed depend on the number of species and the number
of characters? For the sequential-addition algorithms, the speed should
be proportional to somewhere between the cube of the number of species and
the square of the number of species, and to the number
of characters. Thus a case that has, instead of 10 species and 20
characters, 20 species and 50 characters would take (in the cubic case)
2 x 2 x 2 x 2.5 = 20
times as long. This implies that cases with more than 20 species will
be slow, and cases with more than 40 species very slow. This places a
premium on working on small subproblems rather than just dumping a whole
large data set into the programs.
An exception to these rules will be some of the DNA programs that use an
aliasing device to save execution time. In these programs execution time
will not necessarily increase proportional to the number of sites,
as sites that show the same pattern of nucleotides will be detected
as identical and the calculations for them will be done only once, which does
not lead to more execution time. This is particularly
likely to happen with few species and many sites, or with data sets that have
small amounts of evolutionary divergence.
For programs FITCH and KITSCH, the distance matrix is square, so
that when we double the number of species we also double the number of
"characters", so that running times will go up as the fourth power of
the number of species rather than the third power. Thus a 20-species
case with FITCH is expected to run sixteen times more slowly than a 10-species
case.
For programs like PENNY and CLIQUE the run times will rise faster
than the cube of the number of species (in fact, they can rise faster
than any power since these algorithms are not guaranteed to work in
polynomial time). In practice, PENNY will frequently bog down above 11
species, while CLIQUE easily deals with larger numbers.
For NEIGHBOR the speed should vary only as the square of the number of
species, so a case twice as large will take only four times as long. This
will make it an attractive alternative to FITCH and KITSCH for large data
sets.
Note: If you are unsure of how long a program will take, try it first on
a few species, then work your way up until you get a feel for the speed
and for what size programs you can afford to run.
Execution time is not the most important criterion for a program,
particularly as computer time gets much cheaper than your time or a
programmer's time. With workstations on which background jobs can be run
all night, execution speed is not overwhelmingly relevant. Some of us have been
conditioned by an earlier era of computing to consider execution speed
paramount. But ease of use, ease of adaptation to your computer system,
and ease of modification are much more important in practice, and in
these respects I think these programs are adequate. Only if you are
engaged in 1960's style mainframe computing, or if you have very large
amounts of data is minimization of execution
time paramount.
Nevertheless it would have been nice to have made the programs
faster. The present speeds are a compromise between speed and
effectiveness: by making them slower and trying more rearrangements in the
trees, or by enumerating all possible trees, I could have made the programs
more likely to find the best tree. By trying fewer rearrangements I
could have speeded them up, but at the cost of finding worse trees. I
could also have speeded them up by writing critical sections in assembly
language, but this would have sacrificed ease of distribution to new
computer systems. There are also some options included in these programs that
make it
harder to adopt some of the economies of bookkeeping that make other programs
faster. However to some extent I have simply made the decision not to spend
time trying to speed up program bookkeeping when there were new likelihood and
statistical methods to be developed.
Relative speed of different machines
It is interesting to compare different machines using DNAPARS as the
standard task. One can rate a machine on the DNAPARS benchmark by summing the
times for all three of the data sets. Here are relative total timings over
all three data sets (done with various versions of DNAPARS) for some machines,
taking a Pentium MMX 266 notebook computer running Linux with gcc as the
standard. Benchmarks from versions 3.4 and 3.5 of the program are
included (respectively the Pascal and C versions whose timings are in
parentheses. They are compared only with each other and are scaled to the
rest of the timings using the joint runs on the 386SX and the Pentium MMX 266.
This use of separate standards is necessary not
because of different languages but because different versions of the package
are being compared. Thus, the "Time" is the ratio of the Total to that for
the Pentium, adjusted by the scalings of machines using 3.4 and 3.5 when
appropriate. The Relative Speed is the reciprocal of the Time.
Machine
Operating System
Compiler
Total
Time
Relative Speed
Toshiba T1100+
MSDOS
Turbo Pascal 3.01A
(269)
1758.2
0.0005688
Apple Mac Plus
MacOS
Lightspeed Pascal 2
(175.84)
1149.3
0.0008701
Toshiba T1100+
MSDOS
Turbo Pascal 5.0
(162)
1058.9
0.0009443
Macintosh Classic
MacOS
Think Pascal 3
(160)
1045.8
0.0009562
Macintosh Classic
MacOS
Think C
(43.0)
795.6
0.0012569
IBM PS2/60
MSDOS
Turbo Pascal 5.0
(58.76)
384.00
0.002604
80286 (12 Mhz)
MSDOS
Turbo Pascal 5.0
(47.09)
307.77
0.003249
Apple Mac IIcx
MacOS
Think Pascal 3
(42)
274.44
0.003644
Apple Mac SE/30
MacOS
Think Pascal 3
(42)
274.44
0.003644
Apple Mac IIcx
MacOS
Lightspeed Pascal 2
(39.84)
260.44
0.003840
Apple Mac IIcx
MacOS
Lightspeed Pascal 2#
(39.69)
259.33
0.003856
Zenith Z386 (16MHz)
MSDOS
Turbo Pascal 5.0
(38.27)
256.67
0.003896
Macintosh SE/30
MacOS
Think C
(13.6)
251.56
0.003975
386SX (16 MHz)
MSDOS
Turbo Pascal 6.0
(34)
222.41
0.004496
386SX (16 MHz)
MSDOS
Microsoft Quick C
(12.01)
222.41
0.004496
Sequent-S81
DYNIX
Silicon Valley Pascal
(13.0)
84.89
0.011780
VAX 11/785
Unix
Berkeley Pascal
(11.9)
77.77
0.012857
80486-33
MSDOS
Turbo Pascal 6.0
(11.46)
74.89
0.013353
Sun 3/60
SunOS
Sun C
(3.93)
72.67
0.013761
NeXT Cube (68030)
Mach
Gnu C
(2.608)
48.256
0.02072
Sequent S-81
DYNIX
Sequent Symmetry C
(2.604)
48.182
0.02075
VAXstation 3500
Unix
Berkeley Pascal
(7.3)
47.777
0.02093
Sequent S-81
DYNIX
Berkeley Pascal
(5.6)
36.600
0.02732
Unisys 7000/40
Unix
Berkeley Pascal
(5.24)
34.244
0.02920
VAX 8600
VMS
DEC VAX Pascal
(3.96)
25.889
0.03863
Sun SPARC IPX
SunOS
Gnu C version 2.1
(1.28)
23.689
0.04221
VAX 6000-530
VMS
DEC C
(0.858)
15.867
0.06303
VAXstation 4000
VMS
DEC C
(0.809)
14.978
0.06677
IBM RS/6000 540
AIX
XLP Pascal
(2.276)
14.866
0.06726
NeXTstation(040/25)
Mach
Gnu C
(0.75)
13.867
0.07212
Sun SPARC IPX
SunOS
Sun C
(0.68)
12.580
0.07951
486DX (33 MHz)
Linux
Gnu C #
(0.63)
11.666
0.08571
Sun SPARCstation-1
Unix
Sun Pascal
(1.7)
11.111
0.09000
DECstation 5000/200
Unix
DEC Ultrix C
(0.45)
8.333
0.12000
Sun SPARC 1+
SunOS
Sun C
(0.40)
7.400
0.13513
DECstation 3100
Unix
DEC Ultrix Pascal
(0.77)
5.022
0.1991
IBM 3090-300E
AIX
Metaware High C
(0.27)
5.000
0.2000
DECstation 5000/125
Unix
DEC Ultrix C
(0.267)
4.933
0.2027
DECstation 5000/200
Unix
DEC Ultrix C
(0.256)
4.733
0.2113
Sun SPARC 4/50
SunOS
Sun C
(0.249)
4.607
0.2171
DEC 3000/400 AXP
Unix
DEC C
(0.224)
4.144
0.2413
DECstation 5000/240
Unix
DEC Ultrix C
(0.1889)
3.496
0.2861
SGI Iris R4000
Unix
SGI C
(0.184)
3.404
0.2937
IBM 3090-300E
VM
Pascal VS
(0.464)
3.022
0.3309
DECstation 5000/200
Unix
DEC Ultrix Pascal
(0.39)
2.533
0.3947
Pentium 120
Linux
Gnu C
1.848
1.994
0.5016
Pentium Pro 180
Linux
Gnu C
1.009
1.088
0.9353
Pentium 266 MMX
Linux
Gnu C (PHYLIP 3.5)
(0.054)
1.0
1.0
Pentium 266 MMX
Linux
Gnu C
0.927
1.0
1.0
Pentium 200
Linux
Gnu C
0.853
0.9202
1.2647
SGI PowerChallenge
Irix
Gnu C
0.844
0.9297
1.0756
DEC Alpha 400 4/233
DUNIX
Digital C (cc -fast)
0.730
0.7875
1.2699
Pentium II 500
Linux
Gnu C
0.368
0.4053
2.467
Compaq/Digital Alpha 500au
DUNIX
Digital C (cc -fast)
0.167
0.1805
5.541
This benchmark not only reflects integer performance of these machines
(as DNAPARS has few floating-point operations) but also the efficiency
of the compilers. Some of the machines (the DEC 3000/400 AXP
and the IBM RS/6000, in particular) are much faster than this benchmark
would indicate. The numerical programs benchmark below gives them a
fairer test. The Compaq/Digital Alpha 500au times are exaggerated because,
although their compiles are optimized for that processor, the Pentium
compiles are not similarly optimized.
Note that parallel machines like the Sequent and the SGI PowerChallenge are not
really as slow as indicated by the data here, as these runs did nothing to take
advantage of their parallelism.
These benchmarks have now extended over 13 years, and in the DNAPARS
benchmark they extend over a range of 8000-fold in speed!
The experience of our laboratory, which seems typical, is that
computer power grows by a factor of about 1.85 per year. This is
roughly consistent with these benchmarks.
For a picture of speeds for a more numerically intensive program,
here are benchmarks using DNAML, with the Pentium MMX 266
as the standard. Some of the timings, the ones in parentheses, are
using PHYLIP version 3.5, and those are compared to that version run on
the Pentium 266. Runs using the PHYLIP 3.4 Pascal version are adjusted
using the 386SX timings where both were run. Numbers are
total run times (total user time in the case of Unix) over all three data sets.
Machine
Operating System
Compiler
Seconds
Time
Relative Speed
386SX 16 Mhz
PCDOS
Turbo Pascal 6
(7826)
181.18
0.005519
386SX 16 Mhz
PCDOS
Quick C
(6549.79)
181.18
0.005519
Compudyne 486DX/33
Linux
Gnu C
(1599.9)
44.26
0.022595
SUN Sparcstation 1+
SunOS
Sun C
(1402.8)
38.805
0.025770
Everex STEP 386/20
PCDOS
Turbo Pascal 5.5
(1440.8)
33.356
0.029980
486DX/33
PCDOS
Turbo C++
(1107.2)
30.628
0.032650
Compudyne 486DX/33
PCDOS
Waterloo C/386
(1045.78)
28.929
0.034567
Sun SPARCstation IPX
SunOS
Gnu C
(960.2)
26.562
0.037648
NeXTstation(68040/25)
Mach
Gnu C
(916.6)
25.355
0.039439
486DX/33
PCDOS
Waterloo C/386
(861.0)
23.817
0.041986
Sun SPARCstation IPX
SunOS
Sun C
(787.7)
21.790
0.045893
486DX/33
PCDOS
Gnu C
(650.9)
18.006
0.05554
VAX 6000-530
VMS
DEC C
(637.0)
17.621
0.05675
DECstation 5000/200
Unix
DEC Ultrix RISC C
(423.3)
11.710
0.08540
IBM 3090-300E
AIX
Metaware High C
(201.8)
5.582
0.17914
Convex C240/1024
Unix
C
(101.6)
2.8105
0.35581
DEC 3000/400 AXP
Unix
DEC C
(98.29)
2.7189
0.36779
Pentium 120
Linux
Gnu C
25.26
3.3906
0.29493
Pentium Pro 180
Linux
Gnu C
18.88
2.5342
0.3946
Pentium 200
Linux
Gnu C
16.51
2.2161
0.4512
SGI PowerChallenge
IRIX
Gnu C
12.446
1.6706
0.5985
Pentium MMX 266
Linux
Gnu C (PHYLIP 3.5)
(36.15)
1.0
1.0
DEC Alpha 400 4/233
Linux
Gnu C (cc -fast)
8.0418
1.0792
0.9266
Pentium MMX 266
Linux
Gnu C
7.45
1.0
1.0
Pentium II 500
Linux
Gnu C
6.02
0.8081
1.2375
Compaq/Digital Alpha 500au
Linux
Gnu C (cc -fast)
0.9383
0.1259
7.940
As before, the parallel machines such as the Convex and the SGI PowerChallenge
were only run using one processor, which does not take into account the
gain that could be obtained by parallelizing the programs. The speed of the
Compaq/Digital Alpha 500au is exaggerated because it was compiled in a way
optimized for its processor, while the Pentium compiles were not.
You are invited to send me figures for your machine for
inclusion in future tables. Use the data sets above and compute the total
times for DNAPARS and for DNAML for the three data sets (setting the
frequencies of the four bases to 0.25 each for the DNAML runs). Be sure to
tell me the name and version of your compiler, and the version of PHYLIP you
tested.
If the times are too small to be measured accurately, obtain the times
for ten data sets (the Multiple data sets option) and divide by 10.
General Comments on Adapting
the Package to Different Computer Systems
In the sections following you will find instructions on how to adapt the
programs to different computers and compilers. The programs should compile
without alteration on most versions of C. They use the "malloc" library
or "calloc" function to allocate memory so that the upper limits on how many
species or how many sites or characters they can run is set by the system memory
available to that memory-allocation function.
In the document file for each program, I have supplied a small
input example, and the output it produces, to help you check whether the
programs are running properly.
Compiling the programs
If you have not been able to get executables for PHYLIP, you should be
able to make your own. This is easy under Unix and Linux, but more
difficult if you have a Macintosh or a Windows system. If you have the
latter, we stringly recommend you download and use the PowerMac and
Windows executables that we distribute. If you do that, you will not need
to have any compiler or to do any compiling. I get a certain number of
inquiries each year from confused users who are not sure what a compiler
is but think they need one. After downloading the executables they
contact me and complain that they did not find a compiler included in the
package, and would I please e-mail them the compiler. What they really
need to do is use the executables and forget about compiling them.
Some users may also need to compile the programs in order to modify them.
The instructions below will help with this.
I will discuss how to compile PHYLIP using one of a number of widely-used
compilers. After these I will comment on compiling PHYLIP on other, less
widely-used systems.
Unix and Linux
In Unix and Linux (which is Unix in all important functional respects, if
not in all
legal respects) it is easy to compile PHYLIP yourself, which is why we have
generally not bothered to distribute executables for Unix. Unix (and Linux)
systems generally have a C compiler and have the make utility. We
distribute with the PHYLIP source code a Unix-compatible Makefile.
After you have finished unpacking the Documentation and Source Code
archive, you will find that you have created a directory phylip
in which there are three
subdirectories, called exe, src, and doc.
There is also an HTML web page, phylip.html. The exe
directory
will be empty, src contains the source code files, including the
Makefile. Directory doc contains the documentation files.
Enter the src directory. Before you compile, you will want to
look at the makefile and see whether you want to alter the compilation
command. There are careful instructions in the Makefile telling you how to
do this. To compile all the programs just type:
make install
You will then see the compiling commands as they happen, with
occasional warning messages. If these are warnings, rather than errors,
they are not too serious. A typical warning would be like this:
dnaml.c:1204: warning: static declaration for re_move follows non-static
After a time the compiler will finish compiling. If you have done a
make install the system will then move the executables into the
exe subdirectory and also save space by erasing all the relocatable
object files that were produced in the process. You should be left with
useable executables in the exe directory, and the src
directory should be as before. To run the executables, go into the
exe directory and type the program name (say dnaml).
The names of the
executables will be the same as the names of the C programs, but without the
.c suffix. Thus dnaml.c compiles to make an executable called dnaml.
A typical Unix or Linux installation would put the directory phylip
in /usr/local. The name of the executables directory EXEDIR
could be changed to be /usr/local/bin, so that the make install
command puts the executables there. If the users have /usr/local/bin
in their paths, the programs would be found when their names are typed.
The font files font1 through font6 could also be
placed there. A batch script containing the lines
could be used to establish links in the user's working directory so that
Drawtree and Drawgram would find these font files when users
type a name such as font1 when the program asks
them for a font file name. The
documentation web pages are in subdirectory doc of the
main PHYLIP directory, except for one, phylip.html which is
in the main PHYLIP directory. It has a table of all of the documentation
pages, including this one. If users create a bookmark to that page
it can be used to access all of the other documentation pages.
To compile just one program, such as DNAML, type:
make dnaml
After this compilation, dnaml will be in the src
subdirectory. So will some rrelocatable object code files that
were used to create the executable. These have names ending in
.o - they can safely be deleted.
If you have problems with the compilation command, you can edit the
Makefile. It has careful explanations at its front of how you
might want to do so. For example, you might want to change the C
compiler name cc to the name of the Gnu C compiler, gcc.
This can be done by removing the comment character # from the
front of one line, and placing it at the front of a nearby line.
How to do so should be clear from the material at the beginning of the
Makefile. We have included sample lines for using the gcc
compiler and for using the Cygwin Gnu C++ environment on Windows, as
well as the default of cc.
Some older C compilers (notably the Berkeley C compiler which is
included free with some Sun systems) do not adhere to the ANSI C
standard (because they were written before it was set down).
They have trouble with the function prototypes which are in
our programs. We have included an #ifndef preprocessor
command to eliminate the problem, if you use the switch -DOLDC
when compiling. Thus with these compilers you need only use this in
your C flags (in the Makefile) and compilers such as Berkeley C
will cause no trouble.
Macintosh PowerMacs
Compiling with Metrowerks Codewarrior on Macintosh PowerMacs...
We shall assume that you have a recent version of the Metrowerks
Codewarrior C++
compiler. This description, and the project files that we provide,
assume Codewarrior 5.3. We also assume some familiarity with
the use of the Codewarrior compiler and its Integrated Development
Environment (IDE).
Start with our src directory (folder) that contains the C source
code files such as dnaml.c and also the Codewarrior resource
files such as dnaml.rsrc, which are provided by us.
Creating the project file. We will use DnaML as our example.
We have provided a full set of project files in the
self-extracting Macintosh archive.
If you have them then you do not need
to do the items on the following list:
Start up the Codewarrior IDE integrated development environment.
Create a new project file by choosing New... on the File
menu.
Type in the project name dnaml.proj
On the Project menu on the left side of the New window, double-click on MacOS C/C++ Stationery
In the New project window that opens, click on the triangle
to the left of Standard Console.
Move the slider at the right of the window down until you reach
SIOUX-WASTE
Click on the triangle to the left of SIOUX-WASTE. This opens
another list of choices below.
Click on the menu item SIOUX-WASTE C PPC. Press the OK button. After a bit a window dnaml.proj will open.
Click on the triangle to the left of the Sources menu item. A
template item called HelloWorld.c will open.
Select HelloWorld.c.
Open the Edit menu at the top of the Mac screen and select
Clear. A box will open asking if you want to remove HelloWorld.c from the project.
Select OK.
If the dnaml.c file came from the self-extracting Macintosh
archive that we distribute, it should show a yellow-and-back-striped Metrowerks
icon (if not, as when you get it from some other form of our distribution,
you may have to pass it through a program like Microsoft Word, making
sure to save it as a Text Only file, to get
Metrowerks to be able to see it as a potential source code file).
Drag the dnaml.c file onto the Sources item in your
dnaml.proj window.
Drop it onto Sources so that it appears under the Sources choice.
This may take a few tries -- if it appears above Sources grab it
and move it again.
Now add the other files that must be compiled with dnaml.c.
These can be identified by looking at our Makefile -- for DnaML
they are seq.c, phylip.c, seq.h, and phylip.h. Each of them needs to be added to the project file in the same way that
dnaml.c was.
Drag dnaml.rsrc into Sources in the same way. It
doesn't matter whether it appears before or after dnaml.c.
Go to the Edit menu and select the PPC Std C SIOUX-WASTE Settings item. A window of that name will then open.
Under the Target item you will see a PPC Target item.
Select it. A PPC Target window will open to the right.
Change the name in the File Name box to be PHYLIP
Change the ???? in the Creator box to (say) PHYD
Change the Preferred Heap Size to 1024.
Under Language Settings in the left-hand menu of the window,
select C/C++ Language. A window called C/C++ Language
will open to the immediate right.
Click on Require Function Prototypes to deselect that setting.
Click on the Save button at the lower-right of the project
settings window.
Close the PPC Std C SIOUX-WASTE Settings window using the usual
box in the upper-left corner.
On your Desktop you should now find a folder PHYLIP.
If it has a
file called HelloWorld.c you may want to discard that file.
In that PHYLIP folder you will find a file dnaml.proj.
Double-click on that project file. If the Metrowerks is not already open,
it should open now.
If a window called Project Messages opens and there is a
complaint in it about access paths being wrong, you should fix these by
selecting the Reset project entry paths item in the Project
menu.
Select the Make item in the Project menu.
In the Project menu, select Make
Compiling a program once its resource file is available..
If the resource files are all available (as they should be), you did not need
to do any of the above. Usually users will have no need to compile
the programs, but occasionally they may want to change a setting or
add a feature. In that case the Metrowerks Codewarrior compiler can be
used. We have provided support for compiling the programs in its
most recent version, version 5.3. The following discussion will
assume that you have obtained and installed the compiler.
You should find in the source code directory
src a subdirectory called mac which contains the
Metrowerks Codewarrior compiler "project files" (with names ending in
.proj, as well as the resource files (which end in .rsrc
for each program. You can get into this subdirectory, activate the
Metrowerks compiler, and open the appropriate project file. To
compile the program, simply make sure that the project file is an
active window, and type Command-M (which is to say, hold down
the Command key while typing M). Alternatively,
pull down the Project window and select Make. The
program should then compile, possibly with ignorable warning messages.
Windows systems
Compiling with Microsoft Visual C++
Microsoft Visual C++ is used to compile the executables we distribute
Windows. It can compile using a Makefile. We have supplied this
in the source code distrubution as Makefile.msvc.
You will need to preserve the Unix Makefile by renaming it to, say,
Makefile.unix, then make a copy of Makefile.msvc
and call it Makefile.
Setting the path.
Before using nmake you will need to have the paths
set properly. For this, use the Start menu to open Command or
a Dos Prompt first. To set the path type
set MSVC=Path
where Path is where Microsoft Visual Studio is installed
(e.g. it might be in c:\Microsoft Visual Studio).
However the path you type should not have any spaces in it.
This means that you may have to use the directory's
DOS filename. In general to get a DOS name you take the first six letters of
the directory name and follow them by ~1. For example,
Microsoft Visual Studio will have a DOS name
Micros~1, Program Files will be Progra~1).
Depending on what other
file are in the directory the DOS name may be the first six letters followed
by ~2,~3,~4, etc... (e.g. Micros~3 or Progra~5).
It may take some
experimentation to figure it out. With older Versions of Windows (pre-win2000)
it may be possible to just right click on the directory icon and select
Properties to get the DOS name.
Once you have set MSVC, type
PATH=%PATH%;%MSVC%\VC98\bin
Then the Makefile will need to be edited. The line
MSVCPATH=c:\Micros~1\VC98
will need to be changed so that
It points to whereever Microsoft Visual Studio is installed followed by
\VC98.
Using the Makefile. The Makefile is invoked using the
nmake command. If you simply type nmake you
will get a list of possible make commands. For example,
to compile a single program such as Dnaml but not
install it, type make dnaml. To compile and install all
programs type make install. We have supplied all the
support files and icons needed for the compilations. They are
in subdirectory msvc of the main source code
directory.
Compiling with Borland C++
Borland C++ can be downloaded for free from Inprise (Borland)
(see their site
http://www.borland.com
It can compile using a Makefile. We have supplied this
in the source code distrubution as Makefile.bcc.
You will need to preserve the Unix Makefile by renaming it to, say,
Makefile.unix, then make a copy of Makefile.bcc
and call it Makefile. The Makefile is invoked using the
make command. If you simply type make you
will get a list of possible make commands. For example,
to compile a single program such as Dnaml but not
install it, type make dnaml. To compile and install all
programs type make install. We have supplied all the
the support files and icons needed for the compilations. They
are in subdirectory bcc of the main source code
directory. We have had to supply a complete
second set of the resource files with names *.brc
because Borland resource files have a minor incompatibility
with Microsoft Visual C++ resource files.
If this does not work the PATH may need to be set manually.
This can be done by opening a Command or DOS window using the Start
menu. To set the path, type
set BORLAND=Path
Where Path is where Borland is installed, such as
C:\Progra~1\Borland.
Then type
PATH=%PATH%;%BORLAND%\CBUILD~1\Bin
Compiling with Metrowerks Codewarrior for Windows
As with Macintosh systems, Metrowerks Codewarrior requires
you to have project files for each program you compile.
For Metrowerks Codewarrior for Windows we are not providing the projects
themselves, but we are providing
projects which have been exported as XML files. To open one of these one
cannot just click on
File/Open but instead on the menu option File/Import Project.
Metrowerks will then ask you for the project name.
Type in the name of the program (e.g. dnaml). Once this is done Metrowerks will
act like this is a regular project file.
We have supplied a complete set of these XML project files in the
source code distribution. They are in subdirectory metro
of the main source code directory. This is supplied with the
source code distribution for Windows (it is not in the source
code distributions for other platforms).
For Metrowerks Codewarrior for Windows we are not providing the projects
themselves, but we are providing
projects which have been exported as XML files. To open one of these one
cannot just click on
File/Open but instead on the menu option File/Import Project.
Metrowerks will then ask you for the project name.
Type in the name of the program (e.g. dnaml). Once this is done Metrowerks will
act like this is a regular project file.
To compile the program
pull down the Project menu and select Make. The
program should then compile, possibly with ignorable warning messages.
For the moment we are not giving here the details of
how to create these projects yourself -- you usually will not need
to, as you have the project files we have supplied.
Compiling with Cygnus Gnu C++
Cygnus Solutions (now a part of Red Hat, Inc.) has adapted the Gnu C compiler
to Windows systems and
provided an environment, CygWin, which mimics Unix for compiling.
This is available for purchase from them, and they also make it
available to be downloaded for free. The download is large. To get it, go
to their download site at
http://sources.redhat.com/cygwin/download.html and follow the
instructions there. It is a bit
difficult to figure out how to download it -- you need to download
their setup.exe program and then it will download the rest
when it is run. You will need a lot of disk space for it.
Once you have
installed the free Cygnus environment and the associated Gnu C compiler
on your Windows system, compiling PHYLIP is essentially identical to
what one does for Unix or Linux. In PHYLIP's src directory,
change the name of our Unix Makefile to something like
Makefile.unx (so as to keep it around). There is a special
Makefile for the Cygwin
compiler called Makefile.cyg. Make a copy of it called
Makefile.
This Makefile should contain a compiling command:
CC = gcc
Now enter the Cygwin environment (which you can do using the Windows
Start menu and its Programs menu item. There should be
a Cygnus menu choice within that submenu, which you can use to
start the Cygnus environment. This puts you in an imitation of a Unix
shell.
On entering the CygWin environment you will find yourself in one of the
subdirectories of the CygWin directory. Change to the directory where the
PHYLIP programs have been put (for example by issuing the command
cd c:/phylip
You should then be able to compile PHYLIP
by issuing the appropriate make command, such as make install.
If you have modified one of our source code files such as dnaml.c,
it would be wise to
have saved the original version of it first as, say, dnaml.c0.
To associate an icon with a program (say DnaML), you need an icon
file (say dna.ico which contains the icon in standard format.
There should also be a file called dnaml.rc which contains the single
line:
dnaml ICON "dna.ico"
We have provided a subdirectory icons in the src
subdirectory, containing a full set of icons and a full set of resource
files (*.rc).
Our Cygwin Makefile will automatically invoke them.
VMS VAX systems
We have not tried to compile version 3.6 on an OpenVMS system but the
following instructions should work.
On the OpenVMS operating system with DEC VAX VMS C the programs will compile
without alteration. The commands for compiling a typical program
(DNAPARS, which depends on the separately compiled files phylip.c
and seq.c) are:
$ DEFINE LNK$LIBRARY SYS$LIBRARY:VAXCRTL
$ CC DNAPARS.C
$ CC PHYLIP.C
$ CC SEQ.C
$ LINK DNAPARS,PHYLIP,SEQ
Once you use this $ DEFINE statement during a given interactive session,
you need not repeat it again as the symbol LNK$LIBRARY is thereafter
properly defined. The compilation process leaves a file DNAPARS.OBJ
in your directory: this can
be discarded. The executable program is named DNAPARS.EXE. To run the program
one then uses the command:
$ R DNAPARS
The compiler defaults to the filenames INFILE., OUTFILE., and
TREEFILE..
If the input file INFILE. does not exist the program will prompt you to
type in its name. Note that some commands on VMS such as TYPE OUTFILE
will fail because the name of the file that it will attempt to type out will be not
OUTFILE. but OUTFILE.LIS. To get it to type the write file you
would have to instead issue the command TYPE OUTFILE..
When you are
using the interactive previewing feature of DRAWGRAM (or DRAWTREE) on
a Tektronix or DEC ReGIS compatible terminal, you will want before
running the program to have issued the command:
$ SET TERM/NOWRAP/ESCAPE
so that you do not run into trouble from the VMS line length limit of
255 characters or the filtering of escape characters.
To know which files to compile together, look at the entries in the
Makefile.
VMS systems are rapidly disappearing, so we will not devote much
effort to get PHYLIP working on them.
Parallel computers
As parallel computers become more common, the issue of how to compile
PHYLIP for them has become more pressing. People have been compiling
PHYLIP for vector machines and parallel machines for many years. We
have not made a version for parallel machines because there is still
no standard parallel programming environment on such machines (or rather,
there are many standards, so that one cannot find one that makes
a parallel execution version of PHYLIP practical). However the
MPI Message Passing Interface is spreading rapidly, and we will
probably support it in future versions of PHYLIP.
Although the underlying algorithms of most programs,
which treat sites independently, should be amenable to vector and
parallel processors,
there are details of the code which might best be changed.
In certain of the programs (Dnaml, Dnamlk,
Proml, Promlk) I have put a special
comment statement next to the loops in the program where
the program will spend most of its time, and which are the places
most likely to benefit from parallelization. This comment statement is:
/* parallelize here */
In particular
within these innermost loops of the programs there are often scalar quantities
that are used for temporary bookkeeping. These quantities, such as
sum1, sum2, zz, z1, yy, y1, aa, bb, cc, sum, and denom in procedure makenewv
of DNAML (and similar quantities in procedure nuview) are there to
minimize the number of array references. For vectorizing and parallelizing
compilers it will
be better to replace them by arrays so that processing can occur
simultaneously.
If you succeed in making a parallel version of PHYLIP we would like to
know how you did it. In particular, if you can prepare a web page which
describes how to do it for your computer system, we would like to have it
for inclusion in our PHYLIP web pages. Please e-mail it to me. We hope to
have a set of pages that give detailed instructions on how to make parallel
version of PHYLIP on various kinds of machines. Alternatively, if we
are given your modified version of the program we may be able to
figure out how to make modifications to our source code to allow
users to compile the program in a way which makes those modifications.
Other computer systems
As you can see from the variety of different systems on which these
programs have been successfully run, there are no serious
incompatibility problems with most computer systems. PHYLIP in various
past Pascal versions has also been compiled on 8080 and Z80 CP/M Systems, Apple
II systems running UCSD Pascal, a variety of minicomputer systems such as
DEC PDP-11's and HP 1000's, on 1970's era mainframes such as CDC
Cyber systems, and so on. In a later era
it was also compiled on IBM 370 mainframes, and of course on DOS and
Windows systems and on Macintosh and PowerMacintosh systems.
We have gradually
accumulated experience on a wider variety of C compilers. If you succeed in
compiling the C version of PHYLIP on a different machine or a different
compiler, I would like to
hear the details so that I can consider including the instructions in a future version
of this manual.
Frequently Asked Questions
This set of Frequently Asked Questions, and their answers, is from the
PHYLIP web site. A more up-to-date version can be found there, at:
"It doesn't work! It doesn't work!! It says can't find infile.
Actually, it's working just fine. Many of the programs look for an input file called infile,
and if one of that name is not present in the current directory, they then ask
you to type in the name of the input file. That's all that it's doing. This
is done so that
you can get the program to read the file without you having to type in its
name, by making a copy of your input file and calling it infile.
If you don't do that, then the program issues this message. It looks
alarming, but really all that it is trying to do is to get you to type in
the name of the input file. Try giving it the name of the input file.
"The program reads my data file and then says it's has
a memory allocation error!"
This is what tends to happen if there is a problem with the format of the data
file, so that the programs get confused and think they need to set aside memory
for 1,000,000 species or so. The result is a "memory allocation error". Check the data file format against the documentation:
make sure that the data files have not been saved in the format of
your word processor (such as Microsoft Word) but in a "flat ASCII" or "text only"
mode. Note that adding memory to your computer is not the
way to solve this problem -- you probably have plenty of memory
to run the program once the data file is in the correct format.
"On our Macintosh, larger data files fail to run."
We have set the memory allowances on the Macintosh executables
to be generous, but not too big. You therefore may need to
increase them. Use the Get Info item on the Finder File menu.
"I opened the program but I don't see where to create
a data file!"
The programs (there are more than one) use data
files that have been created outside of the program. They do not have any
data editor within them. You can create a data file by using an editor,
such as Microsoft Word, EMACS, vi, SimpleText, Notepad, etc. But be sure
not to save the file in Microsoft Word's own format. It should be saved in
Text Only format. You can use the documentation files, including the examples
at the end of those files, to figure out the format of the input file.
Documentation files such as main.html, sequence.html,
distance.html and many others should be consulted. Many users
create their data files by having their alignment program (such as
ClustalW), output its alignments in PHYLIP format. Many alignment programs
have options to do that.
menu while the program is selected.
"I ran PHYLIP, and all it did was say it was extracting a bunch of files!"
There is no executable program
named PHYLIP in the PHYLIP package! But in some cases
(especially the Windows distribution) there is a file called
phylip.exe.
That file is an archive of documentation and source code. Once you have
run it and extracted the files in it, so that they are in the directory,
running it again will just do the extraction again, which is unnecessary.
Similarly for the archive files for the Windows executables, which
have names like phylipwx.exe and phylipwy.exe.
They are run only once to extract their contents.
"One program makes an output file and then the next program crashes while reading it!"
Did you rename the file? If a program makes a file called outfile, and then the
next program is told to use outfile as its input file, terrible things will
happen. The second program first opens outfile as an output file, thus
erasing it. When it then tries to read from this empty outfile
a psychological
crisis ensues. The solution is simply to rename outfile before trying to
use it as an input file.
"I make a file called infile and then the program can't find it!"
Let me guess. You are using Windows, right? You made your file in Word or
in Notepad or WordPad, right? If you made a file in one of these editors, and
saved it, not in Word format, but in Text Only format, then you were doing the
right thing. But when you told the operating system to save the file as
infile, it actually didn't. It saved it as
infile.txt. Then just to make
life harder for you, the operating system is set up by default to not show
that three-letter extension to the file name. Next to its icon it will show
the name infile. So you think, quite reasonably, that
there is a file called infile. But there isn't a file of that
name, so the program, quite reasonably, can't find a file called
infile. If you want to check what the actual file name is, use
the Properties
menu item of the File item on your folder (in Windows versions, anyway).
You should be able to get the program to work by telling it that the file name
is INFILE.TXT.
"Consense gives wierd branch lengths! How do I
get more reasonable ones?"
Consense gives branch lengths which are simply the numbers of replicates
that support the branch. This is not a good reflection of how long those
branches are estimated to be. The best way to put better branch lengths on a
consensus tree is to use it as a User Tree in a program that will estimate
branch lengths for it. You may need to convert it to being an unrooted tree,
using Retree, first. If the original program you were using was a parsimony
program, which does not estimate branch lengths, you may instead have to make
some distances between your species (using, for example, DnaDist), and use
Fitch to put branch lengths on the user tree. Here is the sequence of
steps you should go through:
Take the tree and use Retree to make sure it is Unrooted (just
read it into Retree and then save it, specifying Unrooted)
Use the unrooted tree as a User Tree (option U) in one of
our programs (such as Fitch or DnaML). If you use Fitch, you also
need to use one of the distance programs such as DnaDist to
compute a set of distances to serve as its input.
Specify that the branch lengths
of the tree are not to be used but should be re-estimated. This
is actually the default.
"DrawTree (or DrawGram) doesn't work: it can't find the font file!"
Six font files, called font1 through font6, are
distributed with the executables
(and with the source code too). The program looks for a copy of one of them
called fontfile. If you haven't made such a copy called
fontfile it then asks
you for the name of the font file. If they are in the current directory, just
type one of font1 through font6. The reason for
having the program look for fontfile
is so that you can copy your favorite font file, call the copy
fontfile,
and then it will be found automatically without you having to type the name of
the font file each time.
"Can DrawGram draw a scale beside the tree? Print the branch lengths as numbers?"
It can't do either of these. Doing so would make the program more complex, and
it is not obvious how to fit the branch length numbers into a tree that has
many very short internal branches. If you want these scales or numbers,
choose an output plot file format (such as Postscript, PICT or PCX) that can be read by
a drawing program such as Adobe Illustrator, Freehand, Canvas, CorelDraw,
or MacDraw.
Then you can add the scales and branch length numbers yourself by hand. Note
the menu option in DrawTree and DrawGram that specifies the tree size to be
a given number of centimeters per unit branch length.
"How can I get DrawGram or DrawTree to print the bootstrap values
next to the branches?"
When you do bootstrapping and use Consense, it prints the bootstrap
values in its output file (both in a table of sets, and on the diagram
of the tree which it makes). These are also in the output tree file of
Consense. There they are in place of branch lengths. So to get them to
be on the output of DrawGram or DrawTree, you must write the tree in the
format of a drawing program and use it to put the values in by hand, as
mentioned in the answer to the previous question.
"I have an HP Laserjet and can't get DrawGram to print on it"
DRAWGRAM and DRAWTREE produce a plot file (called plotfile): they
do not send it to the printer. It is up to you to get the plot file to
the printer. If you are running Windows or DOS this can probably be done
with the MSDOS command COPY/B PLOTFILE PRN:, unless your printer
is a networked printer. The /B
is important. If it is omitted the copy command will strip off the
highest bit of each byte, which can cause the printing to fail or produce
garbage.
"DNAML won't read the treefile that is produced by DNAPARS!"
That's because the DnaPars tree file is a rooted tree, and DnaML wants an
unrooted tree. Try using Retree to change the file to be an unrooted tree
file.
"In bootstrapping, SEQBOOT makes too large a file"
If there are 1000 bootstrap replicates, it will make a file
1000 times as long as your original data set. But for many methods
there is another way that uses much less file space. You can use
SEQBOOT to make a file of multiple sets of weights, and use those
together with the original data set to do bootstrapping.
"In bootstrapping, the output file gets too big."
When running a program such as NEIGHBOR or DNAPARS with multiple data
sets (or multiple weights) for purposes of bootstrapping,
the output file is usually not needed, as it
is the output tree file that is used next. You can use the menu
of the program to turn off the writing of trees into the
output file. The trees will still be written into the tree file.
"Why doesn't NEIGHBOR read my DNA sequences correctly?"
Because it wants
to have as input a distance matrix, not sequences. You have to use DNADIST to
make the distance matrix first.
How to make it do various things
"How do I bootstrap?"
The general method of bootstrapping
involves running SEQBOOT to make multiple bootstrapped data sets out of your
one data set, then running one of the tree-making programs with the Multiple
data sets option to analyze them all, then running CONSENSE to make a majority
rule consensus tree from the resulting tree file. Read the documentation of
SEQBOOT to get further information. Before, only parsimony methods could be
bootstrapped. With this new system almost any of the tree-making methods in
the package can be bootstrapped. It is somewhat more tedious but you will find
it much more rewarding.
"How do I specify a multi-species outgroup
with your parsimony programs?"
It's not a feature but is not too hard to do in many of the programs. In
parsimony programs like MIX, for which the W (Weights) and A (Ancestral states)
options are available, and weights can be larger than 1, all you need to do is:
(a)
In MIX, make up an extra character with states 0 for all the outgroups
and 1 for all the ingroups. If using DNAPARS the ingroup can have (say)
G and the outgroup A.
(b)
Assign this character an enormous weight (such as Z for 35) using the W
option, all other characters getting weight 1, or whatever weight they had
before.
(c)
If it is available, Use the A (Ancestral states) option to designate that
for that new character the state found in the outgroup is the ancestral
state.
(d)
In MIX do not use the O (Outgroup) option.
(e)
After the tree is found, the designated ingroup should have been held
together by the fake character. The tree will be rooted somewhere in the
outgroup (the program may or may not have a preference for one place in
the outgroup over another). Make sure that you subtract from the total
number of steps on the tree all steps in the new character.
In programs like DNAPARS, you cannot use this method as weights of sites
cannot be greater than 1. But you do an analogous trick, by adding a
largish number of extra sites to the data, with one nucleotide state ("A")
for the ingroup and another ("G") for the outgroup. You will then have to
use RETREE to manually reroot the tree in the desired place.
"How do I force certain groups to remain monophyletic in your
parsimony programs?"
By the same method as in the previous question, using multiple fake characters, any number of
groups of species can be forced to be monophyletic. In MOVE, DOLMOVE, and
DNAMOVE you can specify whatever outgroups you want without going to this
trouble.
"How can I reroot one of the trees written out by PHYLIP?"
Use the program
RETREE. But keep in mind whether the tree inferred by the original program was
already rooted, or whether you are free to reroot it.
"What do I do about deletions and insertions in my sequences?"
The
molecular sequence programs will accept sequences that have gaps (the "-"
character). They do various things with them, mostly not optimal. DNAPARS
counts "gap" as if it were a fifth nucleotide state (in addition to A, C, G,
and T). Each site counts one change when a gap arises or disappears. The
disadvantage of this treatment is that a long gap will be overweighted, with
one event per gapped site. So a gap of 10 nucleotides will count as being as
much evidence as 10 single site nucleotide substitutions. If there are not
overlapping gaps, one way to correct this is to recode the first site in the
gap as "-" but make all the others be "?" so the gap only counts as one event.
Other programs such as DNAML and DNADIST count gaps as equivalent to unknown
nucleotides (or unknown amino acids) on the grounds that we don't know what
would be there if something were there. This completely leaves out the
information from the presence or absence of the gap itself, but does not bias
the gapped sequence to be close to or far from other gapped or ungapped
sequences.
So it is not necessary to remove gapped regions from your
sequences, unless the presence of gaps indicates that the region is
badly aligned.
"How can I produce distances for my data set which
has 0's and 1's?"
You can't do it in a simple and general
way, for a straightforward reason. Distance methods must correct the
distances for superimposed changes. Unless we know specifically how to
do this for your particular characters, we cannot accomplish the
correction. There are many formulas we could use, but we can't choose
among them without much more information. There are issues of superimposed
changes, as well as heterogeneity of rates of change in different
characters. Thus we have not provided a distance program for 0/1 data.
It is up to you to figure out what is an appropriate stochastic model
for your data and to find the right distance formulas.
"I have RFLP fragment data: which programs should I
use?"
This is more difficult question than you may imagine.
Here is quick tour of the issues:
You can code fragments are 0 and 1 and use a parsimony program. It is
not obvious in advance whether 0 or 1 is ancestral, though it is likely that
change in one direction is more likely than change in the other for each
fragment. One can use either Wagner parsimony (programs MIX,
PENNY or MOVE) or use Dollo parsimony
(DOLLOP, DOLPENNY or DOLMOVE)
with the ancestral states all set as unknown ("?").
You can use a distance matrix method using the RFLP distance of Nei and
Li (1979). Their restriction fragment distance is available in our
program RestDist.
You should be very hesitant to bootstrap RFLP's. The individual
fragments do not evolve independently: a single nucleotide substitution
can eliminate one fragment and create two (or vice versa).
For restriction sites (rather than fragments) life is a bit
easier: they evolve nearly independently so bootstrapping is possible
and RESTML can be used. Also directionality of change
is less ambiguous when parsimony is used.
"Why don't your parsimony programs print out branch lengths?"
Well, DNAPARS and PARS can. The others have not yet been upgraded to the
same level. The longer answer is that it is because
there are problems defining the branch lengths. If you look closely at the
reconstructions of the states of the hypothetical ancestral nodes for almost
any data set and almost any parsimony method you will find some ambiguous
states on those nodes. There is then usually an ambiguity as to which branch
the change is actually on. Other parsimony programs resolve this in one or
another arbitrary fashion, sometimes with the user specifying how (for example,
methods that push the changes up the tree as far as possible or down it as far
as possible). Our older programs leave it to the user to do this. In
DNAPARS and PARS we use an algorithm discovered by Hochbaum and Pathria (1997)
(and independently by Wayne Maddison) to compute branch lengths that average
over all possible placements of the changes. But these branch lengths, as
nice as they are, do not correct for mulitple superimposed changes. Few
programs available from others currently correct the branch lengths for
multiple changes of state that may have overlain each other. One possible way
to get branch lengths with nucleotide sequence data is to take the tree
topology that you got, use RETREE to convert it to be unrooted, prepare a
distance matrix from your data using DNADIST, and then use FITCH with that tree
as User Tree and see what branch lengths it estimates.
"Why can't your programs handle unordered multistate characters?"
In this 3.6 release there is a program PARS which does parsimony for
undordered multistate characters with up to 8 states, plus ?. The
other the discrete characters parsimony programs can only handle two states,
0 and 1.
This is mostly because I have not yet had time to modify them to do so - the
modifications would have to be extensive. Ultimately I hope to get these done.
If you have four or fewer states and need a feature that is not in PARS,
you could recode your states to look like nucleotides
and use the parsimony programs in the molecular sequence section of PHYLIP, or
you could use one of the excellent parsimony programs produced by others.
Background information needed:
"What file format do I use for the sequences?"
"How do I use the programs? I can't find any documentation!"
These are discussed in the documentation files. Do you have them? If you
have a copy of this page you probably do. They are
in a separate archive from the executables (they are in the Documentation and
Sources archives, which you should definitely fetch). Input file formats
are discussed in main.html, in sequence.html, distance.html,
contchar.html, discrete.html, and the documentation files for the
individual programs.
"Where can I find out how to infer
phylogenies?
There are few books yet. For molecular data you could use one of these:
Graur, D. and W.-H. Li. 2000. Fundamentals of Molecular
Evolution. Sinauer Associates, Sunderland, Massachusetts. (or the earlier edition
by Li and Graur).
Page, R. D. P. and E. C. Holmes. 1998. Molecular Evolution:
A Phylogenetic Approach. Blackwell, Oxford.
Nei, M. and S. Kumar. 2000. Molecular Evolution and
Phylogenetics. Oxford University Press, Oxford.
In addition, one of these three review articles may help:
Swofford, D. L., G. J. Olsen, P. J. Waddell, and D. M. Hillis. 1996.
Phylogenetic inference. pp. 407-514 in Molecular Systematics, 2nd ed.,
ed. D. M. Hillis, C. Moritz, and B. K. Mable. Sinauer Associates, Sunderland,
Massachusetts.
Felsenstein, J. 1988. Phylogenies from molecular sequences: inference and
reliability. Annual Review of Genetics22: 521-565.
Felsenstein, J. 1988. Phylogenies and quantitative
characters. Annual Review of Ecology and Systematics19: 445-471.
My own book on phylogenies is due to be published in late 2002. It
will be called "Inferring Phylogenies". For information on whether it has
been published you should check the
Sinauer Associates web site.
Questions about distribution and citation:
"If I copied PHYLIP from a friend without you knowing, should I try
to keep you from finding out?"
No. It is to your advantage and mine for you to
let me know. If you did not get PHYLIP "officially" from me or from someone
authorized by me, but copied a friend's version, you are not in my database of
users. You may also have an old version which has since been
substantially improved. I don't mind you "bootlegging"
PHYLIP (it's free anyway), but
you should realize that you may have copied an outdated version. If you are reading this
Web page,
you can get the latest version just as quickly over Internet.
It will help both of us if you get
onto my mailing list. If you are on it, then I will give your name to other
nearby users when they ask for the names of nearby users, and they are urged to contact you and
update your copy. (I benefit by getting a better feel for how many
distributions there have been, and having a better mailing list to use to give
other users local people to contact). Use the registration form which
can be accessed through our web site's registration page.
"How do I make a citation to the PHYLIP package in the paper I am
writing?"
One way is like this:
Felsenstein, J. 2002. PHYLIP (Phylogeny Inference Package) version 3.6a3.
Distributed by the author. Department of Genome Sciences, University of
Washington, Seattle.
or if the editor for whom you are writing insists that the citation must be to
a printed publication, you could cite a notice for version 3.2 published in
Cladistics:
For a while a printed version of the PHYLIP documentation was available and one
could cite that. This is no longer true. Other than that, this is difficult,
because I have never written a paper announcing PHYLIP! My 1985b paper in
Evolution on the bootstrap method contains a
one-paragraph Appendix describing the availability of this package, and that
can also be cited as a reference for the package, although it was
distributed since 1980 while the bootstrap paper is 1985. A paper on PHYLIP
is needed mostly to give people something to cite, as word-of-mouth, references
in other people's papers, and electronic newsgroup postings have spread the
word about PHYLIP's existence quite effectively.
"Can I make copies of PHYLIP available to the students in
my class?"
Generally, yes. Read the Copyright notice near the front of
this main documentation page. If you charge money for PHYLIP,
or use it in a service for which you charge money, you will need
to negotiate a royalty. But you can make it freely available
and you do not need to get any special permission from us to do so.
"How many copies of PHYLIP have been distributed?"
On
27 September, 1996 we reached 5,000 registered installations worldwide.
(By now we are well over 15,000 but have lost count for
the moment). Of course there are
many more people who have got copies from friends. PHYLIP is the most widely
distributed phylogeny package. (This situation may reverse itself rapidly
once PAUP* is fully released. During the years it was in full distribution,
PAUP was ahead in phylogenies published, and the availability of distance and
likelihood methods in PAUP* are making it very popular.)
In recent years magnetic tape distribution and e-mail distribution of
PHYLIP have disappeared,
and there has been a big decrease of diskette distributions (down to only
one or two per year). But all this has
been more than offset by, first, an explosion of distributions by anonymous ftp
over Internet, and then a bigger explosion of World Wide Web distributions and
registrations (about 6 registrations per day at the moment).
Questions about documentation
"Where can I get a printed version of the PHYLIP documents?"
For the
moment, you can only get a printed version by printing it yourself. For
versions 3.1 to 3.3 a printed version was sold by Christopher Meacham and Tom
Duncan, then at the University Herbarium of the University of California at
Berkeley. But they have had to discontinue this as it was too much work. You
should be able to print out the documentation files on almost any printer and
make yourself a printed version of whichever of them you need.
"Why have I been dropped from your newsletter mailing list?"
You haven't.
The newsletter was dropped. It simply was too hard to mail it out to such a
large mailing list. The last issue of the newsletter was Number 9 in May,
1987. The Listserver News Bulletins that we tried for a while have also been dropped
as too hard to keep up to date. I am hoping that our World Wide Web site will take their place.
Additional Frequently Asked Questions, or:
"Why didn't it occur to you to ...
... allow the options to be set on the command line?
We could in Unix and Linux, or somewhat differently in Windows. But
there are so many options that this would be difficult, especially
when the options require additional information to be supplied such as
rates of evolution for many categories of sites. You may be asking this
question because you want to automate the operation of PHYLIP programs
using batch files (command files) to run in background. If that is the
issue, see the section of this main documentation page on
"Running the programs in background or under control of a command file".
It explains how to set the options using input redirection and a file
that has the menu responses as keystrokes.
... write these programs in Pascal?"
These programs started out
in Pascal in 1980. In 1993 we released both Pascal and C versions. The
present version (3.6) and
future versions will be C-only. I make fewer mistakes in Pascal and do
like the language better than C, but C has overtaken Pascal and Pascal
compilers are starting to be hard to find on some machines. Also C is a
bit better standardized which makes the number of modifications a user
has to make to adapt the programs to their system much less.
... write these programs in Java?"
Well, we might. It is not completely clear which of two contenders,
C++ and Java, will become more widespread, and which one will gradually
fade away. Whichever one is more successful, we will probably want to use
for future versions of PHYLIP. As the C compilers that are used to
compile PHYLIP are usually also able to compile C++, we will be moving in
that direction, but with constant worrying about whether to convert PHYLIP
to Java instead.
... forgot about all those inferior systems and just develop PHYLIP for Unix?"
This is self-answering, since the same people first said I should
just develop it for Apple II's, then for CP/M Z-80's, then for IBM PCDOS,
then for Macintoshes or for Sun
workstations, and then for Windows. If I had listened to them and done any one of these, I would
have had a very hard time adapting the package to any of the other ones once
these folks changed their mind (and most of them did)!
... write these programs in PROLOG
(or Ada, or Modula-2, or SIMULA, or BCPL, or PL/I, or APL, or LISP)?"
These are all languages I have considered. All
have advantages, but they are not really widespread (as are C and C++).
... include in the package a program to do the Distance Wagner method, (or
successive approximations character weighting,
or transformation series analysis)?"
In most cases where I have not
included other methods, it is because I decided that they had no substantial
advantages over methods that were included (such as the programs FITCH,
KITSCH, NEIGHBOR, the T option of MIX and DOLLOP, and the "?" ancestral
states option of the discrete characters parsimony programs).
... include in the package ordination methods and more
clustering algorithms?"
Because this is not a clustering package, it's a
package for phylogeny estimation. Those are different tasks with different
objectives and mostly different methods. Mary Kuhner and Jon Yamato have,
however,
included in NEIGHBOR an option for UPGMA clustering, which will be very
similar to KITSCH in results.
... include in the package a program to do nucleotide sequence
alignment?"
Well, yes, I should
have, and this is scheduled to be in future releases. But multiple sequence
alignment programs, in the era after Sankoff, Morel, and Cedergren's 1973
classic paper, need to use substantial computer horsepower to estimate the
alignment and the tree together (but see Karl Nicholas's program
GeneDoc or Ward Wheeler and David Gladstein's MALIGN, as
well as more approximate methods of tree-based alignment used in
ClustalW or TreeAlign).
(Fortunately) obsolete questions
(The following four questions, once
common, have finally disappeared, I am pleased to report).
"Why didn't it occur to you to ...
... let me log in to your computer in Seattle
and copy the files out over a phone line?"
No thanks. It would cost you for a lot of
long-distance telephone time, plus a half hour of my time and yours in which
I had to explain to you how to log in and do the copying.
... send me a listing of your program?"
Damn it, it's not "a program",
it's 35 programs, in a great many files. What were you
thinking of doing, having 1800-line programs typed in by slaves at your
end? If you were going to go to all that trouble why not try network
transfer? If you have these then you can print out all the
listings you want to and add them to the huge stack of printed output in
the corner of your office.
... write a magnetic tape in our computer center's favorite format
(inverted Lithuanian EBCDIC at 998 bpi)?"
Because the ANSI standard
format is the most widely used one, and even though your computer center
may pretend it can't read a tape written this way, if you sniff around
you will find a utility to read it. It's just a lot easier for me to
let you do that work. If I tried to put the tape into your format, I
would probably get it wrong anyway.
... give us a version of these in FORTRAN?"
Because the
programs are far easier to write and debug in C or Pascal, and cannot
easily be
rewritten into FORTRAN (they make extensive use of recursive calls and
of records and pointers). In any case, C is widely available. If you don't
have a C compiler or don't know
how to use it, you are going to have to learn a language like C or
Pascal sooner or later, and the sooner the better.
New Features in This Version
Version 3.6 has many new features:
Faster (well, less, slow) likelihood programs.
The DNA and protein likelihood and distance programs allow
for rate variation between sites using a gamma distribution of
rates among sites, or using a gamma distribution plus a given
fraction of sites which are assumed invariant.
A new multistate discrete characters parsimony program, PARS, that
handles unordered multistate characters.
The DNAPARS and PARS parsimony programs can infer multifurcating
trees, which sensibly reduces the number of tied trees they find.
A new protein sequence likelihood program, PROML,
and also a version, PROMLK which assumes a molecular clock.
A new restriction sites and restriction fragments distance program,
RESTDIST, that can also be used to compute distances for RAPD and
AFLP data. It also allows for gamma-distributed rate variation among
DNA sites.
In the DNA likelihood programs, you can now specify different
categories of rates of change (such as rates for first, second, and
third positions of a coding sequence) and assign them to specific sites.
This is in addition to the ability of the program to use the Hidden Markov
Model mechanism to allow rates of change to vary across sites in a way that
does not ask you to assign which rate goes with which site.
The input files for many of the programs are now
simpler, in that they do not contain options information such as specification
of weights and categories. That information is now provided in separete
files with default names such as weights and categories.
The DNA likelihood programs can now evaluate multifurcating
user trees (option U).
All programs that read in user-defined trees now do so from a separate
file, whose default name is intree, rather than requiring them to
be in the input file as before.
The DNA likelihood programs can infer the sequence at ancestral
nodes in the interior of the tree.
DNAPARS can now do transversion parsimony.
The bootstrapping program SEQBOOT now can, instead of producing a
large file containing multiple data sets, be asked instead
to produce a weights file with multiple sets of weights. Many
programs in this release can analyze those multiple weights together with
the original data set, which saves disk space.
The bootstrapping program SEQBOOT can pass weights and categories
information through to a multiple weights file or a multiple categories
file.
SEQBOOT can also convert sequence files from Interleaved to
Sequential form, or back.
SEQBOOT can also write a sequence data file into a preliminary version of
a new XML format which is being defined for sequence alignments,
for use by programs that need XML input
(none of the current PHYLIP programs yet need this format, but it
will be useful in the future).
RETREE can now write tree out into a preliminary version of a new XML tree
file format which is in the process of being defined.
The Kishino-Hasegawa-Templeton (KHT) test which compares user-defined
trees (option U) is now joined by the Shimodaira-Hasegawa (SH) test
(Shimodaira and Hasegawa, 1999) which corrects for comparisons among
multiple tests. This avoids a statistical problem with multiple user trees.
CONTRAST can now carry out an analysis that takes into account
within-species variation, according to a model similar (but not
identical) to that introduced by Michael Lynch (1990)
A new program, TREEDIST, computes the Robinson-Foulds symmetric
difference distance among trees. This measures the number of branches in
the trees that are present in one but not the other.
FITCH and KITSCH now have an option to make trees by the
minimum evolution distance matrix method.
The protein parsimony program PROTPARS now allows you to choose among
a number of different genetic codes such as mitochondrial codes.
The consensus tree program CONSENSE
can compute the Ml family of consensus tree methods, which
generalize the Majority Rule consensus tree method. It can
also compute our extended Majority Rule consensus (which is
Majority Rule with some additional groups added to resolve the
tree more completely), and it can also compute the original
Majority Rule consensus tree method which does not add these
extra groups. It can also
compute the Strict consensus.
The tree-drawing programs DRAWGRAM and DRAWTREE have a number of new
options of kinds of file they can produce, including Windows Bitmap files,
files for the Idraw and FIG X windows drawing programs, the POV ray-tracer,
and even VRML Virtual Reality Markup Language files that will enable you
to wander around the tree using a VRML plugin for your browser, such as
Cosmo Player.
DRAWTREE now uses my new Equal Daylight Algorithm to draw unrooted
trees. This gives a much better-looking tree. Of course, competing programs
such as TREEVIEW and PAUP draw trees that look just as good - because they
too have started to use my method (with my encouragement). DRAWTREE also
can use another algorithm, the n-body method.
The tree-drawing programs can now produce trees across multiple
pages, which is handy for looking at trees with very large numbers
of tips, and for producing giant diagrams by pasting together
multiple sheets of paper.
There are many more, lesser features added as well.
Coming Attractions, Future Plans
There are some obvious deficiencies in this version. Some of these
holes will be filled in the next few releases (leading to version
4.0). They include:
A program to align molecular sequences on a predefined User Tree may
ultimately be included. This will allow alignment and phylogeny
reconstruction to procede iteratively by successive runs of two programs, one
aligning on a tree and the other finding a better tree based on that alignment.
In the shorter run a simple two-sequence alignment program may be included.
An interactive "likelihood explorer" for DNA sequences will be written.
This will allow, either with or without the assumption of a molecular
clock, trees to be varied interactively so that the user can get a much
better feel for the shape of the likelihood surface. Likelihood will be
able to be plotted against branch lengths for any branch.
If possible we will find some way of correcting for purine/pyrimidine
richness variations among species, within the framework of the maximum
likelihood programs. That they maximum likelihood programs do not allow
for base composition variation is their major limitation at the moment.
The Hidden Markov Model (regional rates) option of DNAML and DNAMLK will
be generalized to allow
for rates at sites to gradually change as one moves along the tree,
in an attempt to implement Fitch and Markowitz's (1970) notion of "covarions".
Obviously we need to start thinking about a more visual mouse/windows
interface, but only if that can be used on X windows, Macintoshes, and
Windows.
Program PENNY and its relatives will improved so as to run faster
and find all most parsimonious trees more quickly.
A more sophisticated compatibility program should be included, if I can
find one.
An "evolutionary clock" version of CONTML will be done, and the same
may also be done for RESTML.
We are gradually generalizing the tree structures in the programs to
infer multifurcating trees as well as bifurcating ones.
We should be able to have any program read any tree and know what to do
with it, without the user having to fret about whether an unrooted tree was
fed to a program that needs a rooted tree.
We are economizing on the size of the source code, and enforcing some
standardization of it, by putting frequently used routines in separate
files which can be linked into various programs. This will enforce
a rather complete standardization of our code.
We will move our code to an object-oriented
language, most lkely C++. One could describe the language that version
3.4 was written in as "Pascal", version 3.5 as "Pascal written in C",
version 3.6 as "C written in C", and maybe version 4.0 as "C++ written
in C" and then 4.1 as "C++ written in C++". At least that scenario
is one possibility.
Much of the future development of the package will be in the DNA and protein
likelihood programs and the distance matrix programs. This is for several
reasons. First, I am more interested in those problems. Second, collection of
molecular data is increasing rapidly, and those programs have the most promise
for future development
for those data.
Endorsements
Here are some comments people have made in print about PHYLIP. Explanatory
material in square brackets is my own. They fall naturally into two groups:
From the pages of Cladistics:
"Under no circumstances can we recommend PHYLIP/WAG [their name for the
Wagner parsimony option of MIX]."
Luckow, M. and R. A. Pimentel (1985)
"PHYLIP has not proven very effective in implementing parsimony (Luckow and
Pimentel, 1985)."
J. Carpenter (1987a)
"... PHYLIP. This is the computer program where every newsletter concerning
it is mostly bug-catching, some of which have been put there by previous
corrections. As Platnick (1987) documents, through dint of much labor useful
results may be attained with this program, but I would suggest an
easier way: FORMAT b:"
J. Carpenter (1987b)
"PHYLIP is bug-infested and both less effective and orders of
magnitude slower than other programs ...."
"T. N. Nayenizgani" [J. S. Farris] (1990)
"Hennig86 [by J. S. Farris] provides such substantial improvements over
previously available programs (for both mainframes and microcomputers) that
it should now become the tool of choice for practising systematists."
N. Platnick (1989)
... and in the pages of other journals:
"The availability, within PHYLIP of distance, compatibility, maximum likelihood,
and generalized `invariants' algorithms (Cavender and Felsenstein, 1987) sets
it apart from other packages .... One of the strengths of PHYLIP is its
documentation ...."
Michael J. Sanderson (1990)
(Sanderson also criticizes PHYLIP for slowness and inflexibility of its
parsimony algorithms, and compliments other packages on their strengths).
"This package of programs has gradually become a basic necessity to anyone
working seriously on various aspects of phylogenetic inference .... The package
includes more programs than any other known phylogeny package. But it is not
just a collection of cladistic and related programs. The package has great
value added to the whole, and for this it is unique and of extreme
importance .... its various strengths are in the great array of methods
provided ...."
Bernard R. Baum (1989)
(note also W. Fink's critical remarks (1986) on version 2.8 of PHYLIP).
References for the Documentation Files
In the documentation files that follow I frequently refer to papers
in the literature. In order to centralize the references they are given
in this section. The chapter by David Swofford,
Gary Olsen, Peter Waddell, and David Hillis
(1996) is also an excellent review of the issues in phylogeny
reconstruction.
If you want to find further papers beyond these, my
Quarterly Review of Biology review of 1982 and my Annual Review of Genetics
review of 1988 list many further references.
Adams, E. N. 1972. Consensus techniques and the comparison of
taxonomic trees. Systematic Zoology21: 390-397.
Adams, E. N. 1986. N-trees as nestings: complexity, similarity, and
consensus. Journal of Classification3: 299-317.
Archie, J. W. 1989. A randomization test for phylogenetic information in
systematic data. Systematic Zoology38: 219-252.
Barry, D., and J. A. Hartigan. 1987. Statistical analysis of hominoid
molecular evolution. Statistical Science2: 191-210.
Baum, B. R. 1989. PHYLIP: Phylogeny Inference Package. Version 3.2. (Software
review). Quarterly Review of Biology64: 539-541.
Bron, C., and J. Kerbosch. 1973. Algorithm 457: Finding all cliques
of an undirected graph. Communications of the Association for Computing Machinery16: 575-577.
Camin, J. H., and R. R. Sokal. 1965. A method for deducing branching
sequences in phylogeny. Evolution19: 311-326.
Carpenter, J. 1987a. A report on the Society for the Study of Evolution
workshop "Computer Programs for Inferring Phylogenies". Cladistics3:
363-375.
Carpenter, J. 1987b. Cladistics of cladists. Cladistics3: 363-375.
Cavalli-Sforza, L. L., and A. W. F. Edwards. 1967. Phylogenetic
analysis: models and estimation procedures. Evolution32: 550-570
(also American Journal of Human Genetics19: 233-257).
Cavender, J. A. and J. Felsenstein. 1987. Invariants of phylogenies in a
simple case with discrete states. Journal of Classification4: 57-71.
Churchill, G.A. 1989. Stochastic models for heterogeneous DNA sequences.
Bulletin of Mathematical Biology51: 79-94.
Conn, E. E. and P. K. Stumpf. 1963. Outlines of Biochemistry. John Wiley
and Sons, New York.
Day, W. H. E. 1983. Computationally difficult parsimony problems in
phylogenetic systematics. Journal of Theoretical Biology103:
429-438.
Dayhoff, M. O. and R. V. Eck. 1968. Atlas of Protein Sequence
and Structure 1967-1968. National Biomedical Research Foundation,
Silver Spring, Maryland.
Dayhoff, M. O., R. M. Schwartz, and B. C. Orcutt. 1979. A model of
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Credits
Over the years various granting agencies have contributed to the
support of the PHYLIP project (at first without knowing it). They are:
Years
Agency
Grant or Contract Number
1999-2002
NSF
BIR-9527687
1999-2002
NIH NIGMS
R01 GM51929-04
1999-2001
NIH NIMH
R01 HG01989-01
1995-1999
NIH NIGMS
R01 GM51929-01
1992-1995
National Science Foundation
DEB-9207558
1992-1994
NIH NIGMS Shannon Award
2 R55 GM41716-04
1989-1992
NIH NIGMS
1 R01-GM41716-01
1990-1992
National Science Foundation
BSR-8918333
1987-1990
National Science Foundation
BSR-8614807
1979-1987
U.S. Department of Energy
DE-AM06-76RLO2225 TA DE-AT06-76EV71005
I am particularly grateful to program administrators William Moore,
Irene Eckstrand, Peter Arzberger, and Conrad Istock, who have
gone beyond the call of duty to make sure that PHYLIP continued.
Booby prizes for funding are awarded to:
The people at the U.S. Department of Energy who, in 1987, decided they
were "not interested in phylogenies",
The members of the Systematics Panel of NSF who twice (in 1989 and 1992)
positively recommended that my applications not be funded. I am very
grateful to program director William Moore for courageously overruling
their decision the first time. The 1992 NSF Systematics Panel could claim
no credit for PHYLIP whatsoever.
The members of the 1992 Genetics Study Section of NIH who rated my
proposal in the 53rd percentile (I don't know if that's 53rd from
the top or the bottom, but does it matter?), thus denying it funding. I am,
however, grateful to the NIGMS administrators, especially Irene Eckstrand,
who supported giving me
a "Shannon award" partially funding my work for a period in spite of this
rating.
The original Camin-Sokal parsimony program and the polymorphism parsimony
program were written by me in 1977 and 1978. They were Pascal versions of
earlier FORTRAN programs I wrote in 1966 and 1967 using the same algorithm to
infer phylogenies under the Camin-Sokal and polymorphism parsimony
criteria. Harvey Motulsky worked for me as a programmer in 1971 and wrote
FORTRAN programs to carry out the Camin-Sokal, Dollo, and polymorphism
methods (he is known these days as the author of the scientific
graphing package GraphPad). But most of the early work on PHYLIP other than my own was by Jerry
Shurman and Mark Moehring. Jerry Shurman worked for me in the summers of
1979 and 1980, and Mark Moehring worked for me in the summers of 1980 and
1981. Both wrote original versions of many of the other programs, based on
the original versions of my Camin-Sokal parsimony program and POLYM. These
formed the basis of Version 1 of the Package, first distributed in October,
1980.
Version 2, released in the spring of 1982, involved a fairly complete rewrite
by me of many of those programs. Hisashi Horino for
version 3.3 reworked some parts of the programs CLIQUE and CONSENSE
to make their output more comprehensible, and has added some code to the
tree-drawing programs DRAWGRAM and DRAWTREE as well. He also worked on
some of the Drawtree and Drawgram driver code.
My more recent part-time programmers Akiko Fuseki, Sean Lamont,
Andrew Keeffe, Daniel Yek, Dan Fineman, Patrick Colacurcio,
Mike Palczewski, and Doug Buxton gave
me substantial help with the current release, and their excellent work is
greatly appreciated. Akiko in particular did much of the hard work of adding
new features and changing old ones in the 3.4 and 3.5 releases,
centralized many of the C routines in support files, and is responsible for the
new versions of DNAPARS and PARS. Andrew
prepared the Macintosh version, wrote RETREE, added the ray-tracing
and PICT code to the DRAW programs and has since done much other work. Sean
was central to the conversion to
C, and tested it extensively. My postdoctoral fellow
Mary Kuhner and her associate Jon Yamato created NEIGHBOR, the
neighbor-joining and UPGMA program, for the current release, for which I am
also grateful (Naruya Saitou and Li Jin kindly encouraged us to use some of the
code from their own implementation of this method).
I am very grateful to over 200
users for algorithmic suggestions, complaints about features (or lack of
features), and information about the behavior of their operating systems
and compilers. A list of some of their names will be found at the credits page
on the PHYLIP web site.
A major contribution to this package has been made by others
writing programs or parts of programs. Chris Meacham contributed the
important program FACTOR, long demanded by users, and the even more
important ones PLOTREE and PLOTGRAM. Important parts of the code in
DRAWGRAM and DRAWTREE were taken over from those two programs.
Kent Fiala wrote
function "reroot" to do outgroup-rooting, which was an essential part of many
programs in earlier versions. Someone at the Western Australia Institute of
Technology suggested the name PHYLIP (by writing it the label on the
outside of a magnetic tape), but they all seem to deny having done
so (and I've lost the relevant letter).
The distribution of the package also owes much to Buz Wilson and Willem Ellis,
who put a lot of effort into the early distributions of the PCDOS and
Macintosh versions respectively. Christopher Meacham and Tom Duncan for three
versions distributed a printed version of these documentation files (they are no
longer able to do so), and I am
very grateful to them for those efforts. William H.E. Day and F. James Rohlf
have been very helpful in setting up the listserver news bulletin service which
succeeded the PHYLIP newsletter for a time.
I also wish to thank the people who have made computer resources available to
me, mostly in the loan of use of microcomputers. These include Jeremy
Field, Clem Furlong, Rick Garber, Dan Jacobson, Rochelle Kochin, Monty Slatkin,
Jim Archie, Jim Thomas, and George Gilchrist.
I should also note the computers used to develop this package:
These include a CDC 6400, two DECSystem 1090s, my trusty old SOL-20, my
old Osborne-1, a VAX 11/780, a VAX 8600, a MicroVAX I, a DECstation
3100, my old Toshiba 1100+, my
DECstation 5000/200, a DECstation 5000/125, a Compudyne 486DX/33, a
Trinity Genesis 386SX, a Zenith Z386, a Mac Classic, a DEC Alphastation 400
4/233, a Pentium 120, a Pentium 200, a PowerMac 6100, and a Macintosh G3.
(One of the reasons
we have been successful in achieving compatibility between different computer
systems is that I have had to run them myself under so many different operating
systems and compilers).
Other Phylogeny Programs Available Elsewhere
A comprehensive list of phylogeny programs is maintained at the PHYLIP
web site on the Phylogeny Programs pages:
Here we will simply mention some of the major general-purpose programs. For
many more and much more, see those web pages.
PAUP* A comprehensive program with parsimony, likelihood, and
distance matrix methods. It competes with PHYLIP to be responsible for
the most trees published. Written by David Swofford and distributed by
Sinauer Associates of Sunderland, Massachusetts.
It is described in a web pages for
the Macintosh version,the Windows version,
and
the Unix/OpenVMS version.
Current prices are $100 for the Macintosh version, $85 for the
Windows version, and $150 for Unix versions for many kinds of workstations.
MacClade An interactive Macintosh and PowerMac program to
rearrange trees and watch the changes in the fit of the trees to
data as judged by parsimony. MacClade has a great many features including
a spreadsheet data editor and many different descriptive statistics
for different kinds of data. It is particularly designed to export and
import data to and from PAUP*.
MacClade is available for $100 from Sinauer Associates, of Sunderland,
Massachusetts. It is described in a web page at
http://www.sinauer.com/detail.php?id=4707.
MacClade is also described on its
Web page, at http://phylogeny.arizona.edu/macclade/macclade.html.
MEGA A Windows and DOS program by Sudhir Kumar of Arizona State University
(written together with Koichiro Tamura and Masatoshi Nei while he was a
student in Nei's lab at Pennsylvania
State University). It can carry out parsimony and distance matrix methods
for DNA sequence data. Version 2.1 for Windows
can be downloaded from
the MEGA web site
at http://www.megasoftware.net.
PAML Ziheng Yang of the Department of Genetics and Biometry at
University College, London has written this package of programs to
carry out likelihood analysis of DNA and protein sequence data. PAML is
particularly strong in the options for coping with variability of rates
of evolution from site to site, though it is less able than some other
packages to search effectively for the best tree. It is available as
C source code and as PowerMac and Windows executables from its web site at
http://abacus.gene.ucl.ac.uk/software/paml.html.
TREE-PUZZLE This package by Korbinian Strimmer and Arndt von Haeseler
was begun when they were at the Uviversität Munchen in Germany.
TREE-PUZZLE can carry out likelihood
methods for DNA and protein data, searching by the strategy of
"quartet puzzling" which they invented. It can also compute distances.
It superimposes trees estimated
from many quartets of species. TREE-PUZZLE is available for Unix, Macintoshes,
or Windows from their web site at
http://www.tree-puzzle.de/.
DAMBE A package written by Xuhua Xia, then of the
Department of
Ecology and Biodiversity of the University of Hong Kong.
Its initials stand for Data Analysis in Molecular Biology and Evolution.
DAMBE is a general-purpose package for DNA and protein sequence phylogenies.
It can read and
convert a number of file formats, and has many features for
descriptive statistics, and can compute a number of commonly-used
distance matrix measures and infer phylogenies by parsimony, distance,
or likelihood methods, including bootstrapping and jackknifing. There are
a number of kinds of statistical tests of trees available and it
can also display phylogenies. DAMBE includes a copy of ClustalW as well;
DAMBE consists of Windows95 executables. It is available from its
web site at http://web.hku.hk/~xxia/software/software.htm.
Xia has now moved to the Department of Biology of the University of Ottawa,
Canada, and I suspect the DAMBE web site will soon follow him there.
MOLPHY A package of programs for carrying out likelihood analysis
of DNA and protein data, written by Jun Adachi and Masami Hasegawa of the
Institute of Statistical Mathematics in Tokyo, Japan. The source code
is available from them at
the MOLPHY web site at
http://www.ism.ac.jp/software/ismlib/softother.e.html, and
Windows executables are available from Russell Malmberg's web site at
http://dogwood.botany.uga.edu/malmberg/software.html.
Hennig86 A fast parsimony program by J. S. Farris of the
Naturhistoriska Riksmuseet in Stockholm, Sweden for discrete characters
data (it can handle DNA if its states are recoded to be digits).
Reputed to be faster than PAUP*.
The program is distributed as an executable and costs $50, plus $5
mailing costs ($10 outside of of the U.S.). The user's name should be stated,
as copies are personalized as a copy-protection measure. It is
distributed by Arnold Kluge, Amphibians and Reptiles, Museum of Zoology,
University of
Michigan, Ann Arbor, Michigan 48109-1079, U.S.A. (akluge@umich.edu) and
by Diana Lipscomb at George Washington University (BIODL@gwuvm.gwu.edu).
RnA J. S. Farris's very fast program which uses parsimony
to carry out jackknifing resampling of DNA sequence data. This would be
nearly equivalent in properties to bootstrapping if the jackknifing were
sampling random halves of the data, but Farris prefers to have each
jackknife sample delete a fraction 1/e of the data, which will give
most groups too much support (he would disagree with this statement).
RnA is available from Arnold Kluge, Amphibians and Reptiles, Museum of Zoology,
University of
Michigan, Ann Arbor, Michigan 48109-1079, U.S.A. (akluge@umich.edu)
and Diana Lipscomb
at George Washington University (BIODL@gwuvm.gwu.edu) who may be
contacted for details. The cost is about $30 US.
NONA Pablo Goloboff, of the Instituto Miguel Lillo in
Tucuman, Argentina has written these very fast parsimony programs, capable
of some relevant forms of weighted parsimony, which can handle either
DNA sequence data or discrete characters. It is available as shareware
from http://www.cladistics.com/aboutNona.htm
There is a 30 day free trial, after which
NONA must be purchased separately by sending a check for $40.00 to
either directly to the the author, or to: James M. Carpenter, Attn: NONA,
Division of Invertebrate Zoology, American Museum of Natural History,
Central Park West at 79th Street, New York, NY 10024.
TNT This program, by Pablo Goloboff, J. S. Farris, and Kevin Nixon,
is for searching large data sets for most parsimonious trees.
The authors are respectively at the Instituto Miguel Lillo in Tucuman,
Argentina, the Naturhistoriska Riksmuseet in Stockholm, Sweden, and the
Hortorium, Cornell University, Ithaca, New York.
TNT is described
as faster than other methods, though not faster than NONA for small to
medium data sets. Its distribution status is somewhat uncertain. The site
http://www.cladistics.com/aboutTNT.html
describes it as unavailable,
while the web site http://www.cladistics.com/webtnt.html makes a beta version
available for download. The program downloaded is free but needs a password to
function, which the user should obtain from Pablo Goloboff (see the latter
web page for details).
These are only a few of the more than 194 different phylogeny packages that
are now available (as of January, 2001 - the number keeps increasing). The
others are described (and web links and ftp addresses provided) at my
Phylogeny Programs web pages at the address given above.
How You Can Help Me
Simply let me know of any problems you have had adapting the
programs to your computer. I can often make "transparent" changes that, by
making the code avoid the wilder, woolier, and less standard parts of
C, not only help others who have your machine but even improve the
chance of the programs functioning on new machines. I would like fairly
detailed information on what gave trouble, on what operating system,
machine, and (if relevant) compiler, and what had to be done to make the
programs work. I am sometimes able to do some over-the-telephone
trouble-shooting, particularly
if I don't have to pay for the call, but electronic mail is a the best
way for me to be asked about problems, as you can include your
input and output files so I can see what is going on (please do not
send them as Attachments, but as part of the body of a message). I'd really
like these programs to be
able to run with only routine changes on absolutely everything, down to
and possibly including the Amana Touchmatic Radarange Microwave Oven
which was an Intel 8080 system (in fact, early versions of this package did
run successfully on Intel 8080 systems running the CP/M operating system).
A PalmPilot version is contemplated too.
I would also like to know timings of programs from the package, when
run on the three test input files provided above, for various computer and
compiler combinations, so that I can provide this information in the
section on speeds of this document.
For the phylogeny plotting programs DRAWGRAM and DRAWTREE,
I am particularly interested in knowing what has to be done
to adapt them for other graphic file formats.
You can also be helpful to PHYLIP users in your part of the world by
helping them get the latest version of PHYLIP from our web site
and by helping them with any
problems they may have in getting PHYLIP working on their data.
Your help is appreciated. I am always happy to hear suggestions
for features and programs that ought to be incorporated in the package,
but please do not be upset if I turn out to have already considered the
particular possibility you suggest and decided against it.
In Case of Trouble
Read The (documentation) Files Meticulously ("RTFM"). If that doesn't solve the
problem, please check the Frequently Asked Questions web page at the
PHYLIP web site:
If none of these answers your question, get in touch with me. My electronic mail address
is given below. If you do ask about a problem, please specify the program
name, version of the package, computer operating system, and
send me your data file so I can test the problem. Do not
send your data file as an e-mail Attachment but instead
as the body of a message. I read the e-mail on a Unix system, which makes
it impossible to read some formats of attachments without
running around to other machines and moving the files there. This
is one of my least favorite activities, so please do not use attachments.
Also it will help if you
have the relevant output and documentation files so that you
can refer to them in any correspondence. I can also be reached by telephone
by calling me in my office:
+1-(206)-543-0150, or at home: +1-(206)-526-9057 (how's that for user
support!). If I cannot be reached at either place, a message can be left at
the office of
the Department of Genome Sciences, (206)-221-7377 but I prefer strongly that I not
call you, as in any phone consultation the least you can do is pay the phone
bill. Better yet, use electronic mail.
Particularly if you are in a part of the world distant from me, you may also
want to try to get in touch with other users of PHYLIP nearby. I can also,
if requested, provide a list of nearby users.
Joe Felsenstein
Department of Genome Sciences
University of Washington
Box 357730
Seattle, Washington 98195-7730, U.S.A.
This program computes any one of three measures of genetic distance from a set
of gene frequencies in different populations (or species). The three are
Nei's genetic distance (Nei, 1972), Cavalli-Sforza's chord measure (Cavalli-
Sforza and Edwards, 1967) and Reynolds, Weir, and Cockerham's (1983) genetic
distance. These are written to an output file in a format that can be read by
the distance matrix phylogeny programs FITCH and KITSCH.
The three measures have somewhat different assumptions. All assume that all
differences between populations arise from genetic drift. Nei's distance is
formulated for an infinite isoalleles model of mutation, in which there is a
rate of neutral mutation and each mutant is to a completely new alleles. It
is assumed that all loci have the same rate of neutral mutation, and that the
genetic variability initially in the population is at equilibrium between
mutation and genetic drift, with the effective population size of each
population remaining constant.
Nei's distance is:
__ __
\ \
/_ /_ p1mi p2mi
m i
D = - ln ( ------------------------------------- ).
__ __ __ __
\ \ \ \
[ /_ /_ p1mi2]1/2 [ /_ /_ p2mi2]1/2
m i m i
where m is summed over loci, i over alleles at the m-th locus, and where
p1mi
is the frequency of the i-th allele at the m-th locus in population 1.
Subject to the above assumptions, Nei's genetic distance is expected, for a
sample of sufficiently many equivalent loci, to rise linearly with time.
The other two genetic distances assume that there is no mutation, and that all
gene frequency changes are by genetic drift alone. However they do not
assume that population sizes have remained constant and equal in all
populations. They cope with changing population size by having expectations
that rise linearly not with time, but with the sum over time of 1/N, where N
is the effective population size. Thus if population size doubles, genetic
drift will be taking place more slowly, and the genetic distance will be
expected to be rising only half as fast with respect to time. Both genetic
distances are different estimators of the same quantity under the same model.
Cavalli-Sforza's chord distance is given by
__ __ __
\ \ \
D2 = 4 /_ [ 1 - /_ p1mi1/2 p 2mi1/2] / /_ (am - 1)
m i m
where m indexes the loci, where i is summed over the alleles at the m-th
locus, and where a is the number of alleles at the m-th locus. It can be
shown that this distance always satisfies the triangle
inequality. Note that as given here it is divided by the number of degrees
of freedom, the sum of the numbers of alleles minus one. The quantity which
is expected to rise linearly with amount of
genetic drift (sum of 1/N over time) is D squared, the quantity computed
above, and that is what is written out into the distance matrix.
Reynolds, Weir, and Cockerham's (1983) genetic distance is
__ __
\ \
/_ /_ [ p1mi - p2mi]2
m i
D2 = --------------------------------------
__ __
\ \
2 /_ [ 1 - /_ p1mi p2mi ]
m i
where the notation is as before and D2 is the quantity that is
expected to rise linearly with cumulated genetic drift.
Having computed one of these genetic distances, one which you feel is
appropriate to the biology of the situation, you can use it as the input to
the programs FITCH, KITSCH or NEIGHBOR. Keep in mind that the statistical
model in
those programs implicitly assumes that the distances in the input table have
independent errors. For any measure of genetic distance this will not be true,
as bursts of random genetic drift, or sampling events in drawing the sample of
individuals from each population, cause fluctuations of gene frequency that
affect many distances simultaneously. While this is not expected to bias the
estimate of the phylogeny, it does mean that the weighing of evidence from all
the different distances in the table will not be done with maximal
efficiency. One issue is which value of the P
(Power) parameter should be used. This depends on how the variance of a
distance rises with its expectation. For Cavalli-Sforza's chord distance, and
for the Reynolds et. al. distance it can be shown that the variance of the
distance will be proportional to the square of its expectation; this suggests
a value of 2 for P, which the default value for FITCH and KITSCH
(there is no P option in NEIGHBOR).
If you think that the pure genetic drift model is appropriate, and are thus
tempted to use the Cavalli-Sforza or Reynolds et. al. distances, you might
consider using the maximum likelihood program CONTML instead. It will
correctly weigh the evidence in that case. Like those genetic distances, it
uses approximations that break down as loci start to drift all the way to
fixation. Although Nei's distance will not break down in that case, it
makes other assumptions about equality of substitution rates at all loci and
constancy of population sizes.
The most important thing to remember is that genetic distance is not an
abstract, idealized measure of "differentness". It is an estimate of a
parameter (time or cumulated inverse effective population size) of the
model which is thought to have generated the differences we see. As an
estimate, it has statistical properties that can be assessed, and we should
never have to choose between genetic distances based on their aesthetic
properties, or on the personal prestige of their originators. Considering them
as estimates
focuses us on the questions which genetic distances are intended to answer,
for if there are none there is no reason to compute them. For further
perspective on genetic distances, I recommend my own paper evaluating
Reynolds, Weir, and Cockerham (1983), and the material in Nei's book (Nei,
1987).
INPUT FORMAT
The input to this program is standard and is as described in the Gene
Frequencies and Continuous
Characters Programs documentation file above. It consists of the number of
populations (or species), the number of loci,
and after that a line containing the numbers of alleles at each of the
loci. Then the gene frequencies follow in standard format.
The options are selected using a menu:
Genetic Distance Matrix program, version 3.6a3
Settings for this run:
A Input file contains all alleles at each locus? One omitted at each locus
N Use Nei genetic distance? Yes
C Use Cavalli-Sforza chord measure? No
R Use Reynolds genetic distance? No
L Form of distance matrix? Square
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print indications of progress of run? Yes
Y to accept these or type the letter for one to change
The A (All alleles) option is described in the Gene Frequencies and
Continuous Characters Programs documentation file. As with CONTML, it is
the signal that all alleles are represented in the gene frequency input,
without one being left out per locus. C, N, and R are the signals to
use the Cavalli-Sforza, Nei, or Reynolds et. al. genetic distances
respectively. The Nei distance is the default, and it will be computed
if none of these options is explicitly invoked. The L option is the signal
that the distance matrix is to be written out in Lower triangular form.
The M option is the usual Multiple Data Sets option, useful for
doing bootstrap analyses with the distance matrix programs. It allows
multiple data sets, but does not allow multiple sets of weights (since
there is no provision for weighting in this program).
OUTPUT FORMAT
The output file simply contains on its first line the number of species (or
populations). Each
species (or population) starts a new line, with its name printed out
first, and then and there are up to nine
genetic distances printed on each line, in the standard format used as input
by the distance matrix programs. The output, in its default form, is
ready to be used in the distance matrix programs.
CONSTANTS
The constants
available to be changed by the user if the program is recompiled are
"namelength" the length of a species name, set to 10 in the distribution
and "epsilon" which defines a small quantity that is used when checking
whether allele frequencies at a locus sum to more than one: if all
alleles are input (option A) and the sum differs from 1 by more than epsilon,
or if not all alleles are input and the sum is greater than 1 by more
then epsilon, the program will see this as an error and stop. You may
find this causes difficulties if you gene frequencies have been rounded.
I have tried to keep epsilon from being too small to prevent such problems.
RUN TIMES
The program is quite fast and the user should effectively never be limited by
the amount of time it takes. All that the program has to do is read in the
gene frequency data and then, for each pair of species, compute a genetic
distance formula for each pair of species. This should require an amount of
effort proportional to the total number of alleles over loci, and to the
square of the number of populations.
FUTURE OF THIS PROGRAM
The main change that will be made to this program in the future is to add
provisions for taking into account the sample size for each population. The
genetic distance formulas have been modified by their inventors to correct for
the inaccuracy of the estimate of the genetic distances, which on the whole
should artificially increase the distance between populations by a small
amount dependent on the sample sizes. The main difficulty with doing this is
that I have not yet settled on a format for putting the sample size in the
input data along with the gene frequency data for a species or population.
I may also include other distance measures, but only if I think their use is
justified. There are many very arbitrary genetic distances, and I am
reluctant to include most of them.
This program uses nucleotide sequences to compute a distance matrix, under
four different models of nucleotide substitution. It can also
compute a table of similarity between the nucleotide sequences.
The distance for each
pair of species estimates the total branch length between the two species, and
can be used in the distance matrix programs FITCH, KITSCH or NEIGHBOR. This
is an alternative to use of the sequence data itself in the maximum likelihood
program DNAML or the parsimony program DNAPARS.
The program reads in nucleotide sequences and writes an output file containing
the distance matrix, or else a table of similarity between sequences.
The four models of nucleotide substitution are those
of Jukes and Cantor (1969), Kimura (1980), the F84 model (Kishino and Hasegawa,
1989; Felsenstein and Churchill, 1996), and the model underlying the
LogDet distance (Barry and Hartigan, 1987; Lake, 1994;
Steel, 1994; Lockhart et. al., 1994).
All except the LogDet distance can be made to allow for
for unequal rates of substitution at different sites, as Jin and Nei
(1990) did for the Jukes-Cantor model.
The program correctly takes
into account a variety of sequence ambiguities, although in cases where they
exist it can be slow.
Jukes and Cantor's (1969) model assumes that there is independent change at
all sites, with equal probability. Whether a base changes is independent of
its identity, and when it changes there is an equal probability of ending up
with each of the other three bases. Thus the transition probability matrix
(this is a technical term from probability theory and has nothing to do with
transitions as opposed to transversions) for a short period of time dt is:
To: A G C T
---------------------------------
A | 1-3a a a a
From: G | a 1-3a a a
C | a a 1-3a a
T | a a a 1-3a
where a is u dt, the product of the rate of substitution per unit time (u)
and the length dt of the time interval. For longer periods of time this
implies that the probability that two sequences will differ at a given site
is:
p = 3/4 ( 1 - e- 4/3 u t)
and hence that if we observe p, we can compute an estimate of the branch
length ut by inverting this to get
ut = - 3/4 loge ( 1 - 4/3 p )
The Kimura "2-parameter" model is almost as symmetric as this, but allows
for a difference between transition and transversion rates. Its transition
probability matrix for a short interval of time is:
To: A G C T
---------------------------------
A | 1-a-2b a b b
From: G | a 1-a-2b b b
C | b b 1-a-2b a
T | b b a 1-a-2b
where a is u dt, the product of the rate of transitions per unit time and dt
is the length dt of the time interval, and b is v dt, the product of half the
rate of transversions (i.e., the rate of a specific transversion)
and the length dt of the time interval.
The F84 model incorporates different rates of transition
and transversion, but also allowing for different frequencies of the four
nucleotides. It is the model which is used in DNAML, the maximum likelihood
nucelotide sequence phylogenies program in this package. You will find the
model described in the document for that program. The transition
probabilities for this model are given by Kishino and Hasegawa (1989),
and further explained in a paper by me and Gary Churchill (1996).
The LogDet distance allows a fairly general model of substitution. It
computes the distance from the determinant of the empirically observed
matrix of joint probabilities of nucleotides in the two species. An
explanation of it is available in the chapter by Swofford et, al. (1996).
The first three models are closely related. The DNAML model reduces to
Kimura's
two-parameter model if we assume that the equilibrium frequencies of the four
bases are equal. The Jukes-Cantor model in turn is a special case of the
Kimura 2-parameter model where a = b. Thus each model is a special case of
the ones that follow it, Jukes-Cantor being a special case of both of the
others.
The Jin and Nei (1990) correction for variation in rate of evolution from
site to site can be adapted to all of the first three models.
It assumes that the rate of substitution varies from site to site
according to a gamma distribution, with a coefficient of variation that
is specified by the user. The user is asked for it when choosing this option
in the menu.
Each distance that is calculated is an estimate, from that particular pair of
species, of the divergence time between those two species. For the Jukes-
Cantor model, the estimate is computed using the formula for ut given above,
as long as the nucleotide symbols in the two sequences are all either A, C, G,
T, U, N, X, ?, or - (the latter four indicate a deletion or an unknown
nucleotide. This estimate is a maximum likelihood estimate for that
model. For the Kimura 2-parameter model, with only these nucleotide symbols,
formulas special to that estimate are also computed. These are also,
in effect, computing the maximum likelihood estimate for that model. In
the Kimura case it depends on the
observed sequences only through the sequence length and the observed number of
transition and transversion differences between those two sequences. The
calculation in that case is a maximum likelihood estimate and will differ
somewhat from the estimate obtained from the formulas in Kimura's original
paper. That formula was also a maximum likelihood estimate, but with the
transition/transversion ratio estimated empirically, separately for each pair
of sequences. In the present case, one overall preset transition/transversion
ratio is used which makes the computations harder but achieves greater
consistency between different comparisons.
For the
F84 model, or for any of the models where one or both sequences contain at
least one of the other ambiguity codons such as Y, R, etc., a maximum
likelihood calculation is also done using code which was originally written
for DNAML. Its disadvantage is that it is slow. The resulting
distance is in effect a maximum likelihood estimate of the divergence time
(total branch length between) the two sequences. However the present
program will be much faster than versions earlier than 3.5, because I have
speeded up the iterations.
The LogDet model computes the distance from the determinant of the
matrix of co-occurrence of nucleotides in the two species, according to
the formula
D = - 1/4(loge(|F|) - 1/2loge(fA1fC1fG1fT1fA2fC2fG2fT2))
Where F is a matrix whose (i,j) element is the fraction
of sites at which base i occurs in one species and base j
occurs in the other. fji is the fraction of sites at
which species i has base j.
The LogDet distance cannot cope with ambiguity codes. It must have
completely defined sequences. One limitation of the LogDet distance is
that it may be infinite sometimes, if there are too many changes between
certain pairs of nucleotides. This can be particularly noticeable with
distances computed from bootstrapped sequences.
Note that there is an
assumption that we are looking at all sites, including those
that have not changed at all. It is important not to restrict attention
to some sites based on whether or not they have changed; doing that
would bias the distances by making them too large, and that in turn
would cause the distances
to misinterpret the meaning of those sites that
had changed.
For all of these
distance methods, the program allows us to specify
that "third position" bases have a different rate of substitution than first and
second positions, that introns have a different rate than exons, and so on. The
Categories option which does this allows us to make up to
9 categories of sites and specify different rates of change for them.
In addition to the four distance calculations, the program can also
compute a table of similarities between nucleotide sequences. These values
are the fractions of sites identical between the sequences.
The diagonal values are 1.0000. No attempt is made to count similarity
of nonidentical nucleotides, so that no credit is given for having
(for example) different purines at corresponding
sites in the two sequences. This option has been requested by many
users, who need it for descriptive purposes. It is not intended that
the table be used for inferring the tree.
INPUT FORMAT AND OPTIONS
Input is fairly standard, with one addition. As usual the first line of the
file gives the number of species and the number of sites.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion --
neither is dot (".").
The options are selected using an interactive menu. The menu looks like this:
Nucleic acid sequence Distance Matrix program, version 3.6a3
Settings for this run:
D Distance (F84, Kimura, Jukes-Cantor, LogDet)? F84
G Gamma distributed rates across sites? No
T Transition/transversion ratio? 2.0
C One category of substitution rates? Yes
W Use weights for sites? No
F Use empirical base frequencies? Yes
L Form of distance matrix? Square
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
Y to accept these or type the letter for one to change
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The D option selects one of the four distance methods, or the
similarity table. It toggles among the
five methods. The default method, if none is specified, is the F84
model.
If the G (Gamma distribution) option is selected, the user will be
asked to supply the coefficient of variation of the rate of substitution
among sites. This is different from the parameters used by Nei and Jin but
related to them: their parameter a is also known as "alpha",
the shape parameter of the Gamma distribution. It is
related to the coefficient of variation by
CV = 1 / a1/2
or
a = 1 / (CV)2
(their parameter b is absorbed here by the requirement that time is scaled so
that the mean rate of evolution is 1 per unit time, which means that a = b).
As we consider cases in which the rates are less variable we should set a
larger and larger, as CV gets smaller and smaller.
The F (Frequencies) option appears when the Maximum Likelihood distance is
selected. This distance requires that the program be provided with the
equilibrium frequencies of the four bases A, C, G, and T (or U). Its default
setting is one which may save users much time. If you
want to use the empirical frequencies of the bases, observed in the input
sequences, as the base frequencies, you simply use the default setting of
the F option. These empirical
frequencies are not really the maximum likelihood estimates of the base
frequencies, but they will often be close to those values (what they are is
maximum likelihood estimates under a "star" or "explosion" phylogeny).
If you change the setting of the F option you will be prompted for the
frequencies of the four bases. These must add to 1 and are to be typed on
one line separated by blanks, not commas.
The T option in this program does not stand for Threshold,
but instead is the Transition/transversion option. The user is prompted for
a real number greater than 0.0, as the expected ratio of transitions to
transversions. Note
that this is not the ratio of the first to the second kinds of events,
but the resulting expected ratio of transitions to transversions. The exact
relationship between these two quantities depends on the frequencies in the
base pools. The default value of the T parameter if you do not use the T
option is 2.0.
The C option allows user-defined rate categories. The user is prompted
for the number of user-defined rates, and for the rates themselves,
which cannot be negative but can be zero. These numbers, which must be
nonnegative (some could be 0),
are defined relative to each other, so that if rates for three categories
are set to 1 : 3 : 2.5 this would have the same meaning as setting them
to 2 : 6 : 5.
The assignment of rates to
sites is then made by reading a file whose default name is "categories".
It should contain a string of digits 1 through 9. A new line or a blank
can occur after any character in this string. Thus the categories file
might look like this:
122231111122411155
1155333333444
The L option specifies that the output file is to have the distance
matrix in lower triangular form.
The W (Weights) option is invoked in the usual way, with only weights 0
and 1 allowed. It selects a set of sites to be analyzed, ignoring the
others. The sites selected are those with weight 1. If the W option is
not invoked, all sites are analyzed.
The Weights (W) option
takes the weights from a file whose default name is "weights". The weights
follow the format described in the main documentation file.
The M (multiple data sets) option will ask you whether you want to
use multiple sets of weights (from the weights file) or multiple data sets
from the input file.
The ability to use a single data set with multiple weights means that
much less disk space will be used for this input data. The bootstrapping
and jackknifing tool Seqboot has the ability to create a weights file with
multiple weights. Note also that when we use multiple weights for
bootstrapping we can also then maintain different rate categories for
different sites in a meaningful way. You should not use the multiple
data sets option without using multiple weights, you should not at the
same time use the user-defined rate categories option (option C).
The options 0 is the usual one. It is described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
OUTPUT FORMAT
As the
distances are computed, the program prints on your screen or terminal
the names of the species in turn,
followed by one dot (".") for each other species for which the distance to
that species has been computed. Thus if there are ten species, the first
species name is printed out, followed by nine dots, then on the next line
the next species name is printed out followed by eight dots, then the
next followed by seven dots, and so on. The pattern of dots should form
a triangle. When the distance matrix has been written out to the output
file, the user is notified of that.
The output file contains on its first line the number of species. The
distance matrix is then printed in standard
form, with each species starting on a new line with the species name, followed
by the distances to the species in order. These continue onto a new line
after every nine distances. If the L option is used, the matrix or distances
is in lower triangular form, so that only the distances to the other species
that precede each species are printed. Otherwise the distance matrix is square
with zero distances on the diagonal. In general the format of the distance
matrix is such that it can serve as input to any of the distance matrix
programs.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the menu
selections. The output file begins by giving the number of species and the
number of characters, and the identity of the distance measure that is
being used.
If the C (Categories) option is used a table of the relative rates of
expected substitution at each category of sites is printed, and a listing
of the categories each site is in.
There will then follow the equilibrium frequencies of the four bases.
If the Jukes-Cantor or Kimura distances are used, these will necessarily be
0.25 : 0.25 : 0.25 : 0.25. The output then shows
the transition/transversion ratio that was specified or
used by default. In the case of the Jukes-Cantor distance this will always
be 0.5. The transition-transversion parameter (as opposed to the ratio)
is also printed out: this is used within the program and can be ignored.
There then follow the data sequences, with the base sequences printed in
groups of ten bases along the lines of the Genbank and EMBL formats.
The distances printed out are scaled in terms of expected numbers of
substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate of
change, averaged over all sites analyzed, is set to 1.0
if there are multiple categories of sites. This means that whether or not
there are multiple categories of sites, the expected fraction of change
for very small branches is equal to the branch length. Of course,
when a branch is twice as
long this does not mean that there will be twice as much net change expected
along it, since some of the changes may occur in the same site and overlie or
even reverse each
other. The branch lengths estimates here are in terms of the expected
underlying numbers of changes. That means that a branch of length 0.26
is 26 times as long as one which would show a 1% difference between
the nucleotide sequences at the beginning and end of the branch. But we
would not expect the sequences at the beginning and end of the branch to be
26% different, as there would be some overlaying of changes.
One problem that can arise is that two or more of the species can be so
dissimilar that the distance between them would have to be infinite, as
the likelihood rises indefinitely as the estimated divergence time
increases. For example, with the Jukes-Cantor model, if the two sequences
differ in 75% or more of their positions then the estimate of dovergence
time would be infinite. Since there is no way to represent an infinite
distance in the output file, the program regards this as an error, issues an
error message indicating which pair of species are causing the problem, and
stops. It might be that, had it continued running, it would have also run
into the same problem with other pairs of species. If the Kimura
distance is being used there may be no error message; the program may
simply give a large distance value (it is iterating towards
infinity and the value is just where the iteration stopped). Likewise
some maximum likelihood estimates may also become large for the same
reason (the sequences showing more divergence than is expected even with
infinite branch length). I hope in the future to add more warning
messages that would alert the user the this.
If the similarity table is selected, the table that is produced is not
in a format that can be used as input to the distance matrix programs.
it has a heading, and the species names are also put at the tops of the
columns of the table (or rather, the first 8 characters of each species
name is there, the other two characters omitted to save space). There
is not an option to put the table into a format that can be read by
the distance matrix programs, nor is there one to make it into a table
of fractions of difference by subtracting the similarity values from 1.
This is done deliberately to make it more difficult for the use to
use these values to construct trees. The similarity values are
not corrected for multiple changes, and their use to construct trees
(even after converting them to fractions of difference) would be
wrong, as it would lead to severe conflict between the distant
pairs of sequences and the close pairs of sequences.
PROGRAM CONSTANTS
The constants that are available to be changed by the user at the beginning
of the program include
"maxcategories", the maximum number of site
categories, "iterations", which controls the number of times
the program iterates the EM algorithm that is used to do the maximum
likelihood distance, "namelength", the length of species names in
characters, and "epsilon", a parameter which controls the accuracy of the
results of the iterations which estimate the distances. Making "epsilon"
smaller will increase run times but result in more decimal places of
accuracy. This should not be necessary.
The program spends most of its time doing real arithmetic.
The algorithm, with separate and independent computations
occurring for each pattern, lends itself readily to parallel processing.
CONTENTS OF OUTPUT FILE (with all numerical options on)
(Note that when the options for displaying the input data are turned off,
the output is in a form suitable for use as an input file in the distance
matrix programs).
MIX is a general parsimony program which carries out the Wagner and
Camin-Sokal parsimony methods in mixture, where each character can have
its method specified separately. The program defaults to carrying out Wagner
parsimony.
The Camin-Sokal parsimony method explains the data by assuming that
changes 0 --> 1 are allowed but not changes 1 --> 0. Wagner parsimony
allows both kinds of changes. (This under the assumption that 0 is the
ancestral state, though the program allows reassignment of the ancestral
state, in which case we must reverse the state numbers 0 and 1
throughout this discussion). The criterion is to find the tree which
requires the minimum number of changes. The Camin-Sokal method is due
to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
(1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
Ancestral states are known (Camin-Sokal) or unknown (Wagner).
Different characters evolve independently.
Different lineages evolve independently.
Changes 0 --> 1 are much more probable than changes 1 --> 0
(Camin-Sokal) or equally probable (Wagner).
Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the
group in question.
Other kinds of evolutionary event such as retention of polymorphism
are far less probable than 0 --> 1 changes.
Rates of evolution in different lineages are sufficiently low that
two changes in a long segment of the tree are far less probable
than one change in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
INPUT FORMAT
The input for MIX is the standard input for discrete characters
programs, described above in the documentation file for the
discrete-characters programs. States "?", "P", and "B" are allowed.
The options are selected using a menu:
Mixed parsimony algorithm, version 3.6a3
Settings for this run:
U Search for best tree? Yes
X Use Mixed method? No
P Parsimony method? Wagner
J Randomize input order of species? No. Use input order
O Outgroup root? No, use as outgroup species 1
T Use Threshold parsimony? No, use ordinary parsimony
A Use ancestral states in input file? No
W Sites weighted? No
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each character No
5 Print states at all nodes of tree No
6 Write out trees onto tree file? Yes
Are these settings correct? (type Y or the letter for one to change)
The options U, X, J, O, T, A, and M are the usual User Tree, miXed
methods, Jumble, Outgroup,
Ancestral States, and Multiple Data Sets options, described either
in the main documentation file or in the Discrete Characters Programs
documentation file. The
user-defined trees supplied if you use the U option must be given as rooted
trees with two-way splits (bifurcations). The O option is acted upon only if
the final tree is unrooted and is not a user-defined tree. One of the
important uses of the the O option is to root the tree so that if there are
any characters in which the ancestral states have not been specified, the
program will print out a table showing which ancestral states require the
fewest steps. Note that when any of the characters has Camin-Sokal parsimony
assumed for it, the tree is rooted and the O option will have no effect.
The option P toggles between the Camin-Sokal parsimony criterion
and the default Wagner parsimony criterion. Option X invokes
mixed-method parsimony. If the A option is invoked, the ancestor is not
to be counted as one of the species.
The F (Factors)
option is not available in this program, as it would have no effect on
the result even if that information were provided in the input file.
OUTPUT FORMAT
Output is standard: a list of equally parsimonious trees, which will be printed
as rooted or unrooted depending on which is appropriate, and, if the
user chooses, a table of the
number of changes of state required in each character. If the Wagner option is
in force for a character, it may not be possible to unambiguously locate the
places on the tree where the changes occur, as there may be multiple
possibilities. If the user selects menu option 5, a table is printed out
after each tree, showing for each
branch whether there are known to be changes in the branch, and what the states
are inferred to have been at the top end of the branch. If the inferred state
is a "?" there will be multiple equally-parsimonious assignments of states; the
user must work these out for themselves by hand.
If the Camin-Sokal parsimony method
is invoked and the Ancestors option is also used, then the program will
infer, for any character whose ancestral state is unknown ("?") whether the
ancestral state 0 or 1 will give the fewest state changes. If these are
tied, then it may not be possible for the program to infer the
state in the internal nodes, and these will all be printed as ".". If this
has happened and you want to know more about the states at the internal
nodes, you will find helpful to use MOVE to display the tree and examine
its interior states, as the algorithm in MOVE shows all that can be known
in this case about the interior states, including where there is and is not
amibiguity. The algorithm in MIX gives up more easily on displaying these
states.
If the A option is not used, then the program will assume 0 as the
ancestral state for those characters following the Camin-Sokal method,
and will assume that the ancestral state is unknown for those characters
following Wagner parsimony. If any characters have unknown ancestral
states, and if the resulting tree is rooted (even by outgroup),
a table will also be printed out
showing the best guesses of which are the ancestral states in each
character. You will find it useful to understand the difference between
the Camin-Sokal parsimony criterion with unknown ancestral state and the Wagner
parsimony criterion.
If the U (User Tree) option is used and more than one tree is supplied, the
program also performs a statistical test of each of these trees against the
best tree. This test, which is a version of the test proposed by
Alan Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences
invented by Kishino and Hasegawa (1989), and uses the mean and variance of
step differences between trees, taken across characters. If the mean
is more than 1.96 standard deviations different then the trees are declared
significantly different. The program
prints out a table of the steps for each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the step differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one. It
is important to understand that the test assumes that all the binary
characters are evolving independently, which is unlikely to be true for
many suites of morphological characters.
If the U (User Tree) option is used and more than one tree is supplied, the
program also performs a statistical test of each of these trees against the
best tree. This test, which is a version of the test proposed by
Alan Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences
invented by Kishino and Hasegawa (1989), and uses the mean and variance of
step differences between trees, taken across characters. If the mean
is more than 1.96 standard deviations different then the trees are declared
significantly different. The program
prints out a table of the steps for each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the step differences at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one. It
is important to understand that the test assumes that all the binary
characters are evolving independently, which is unlikely to be true for
many suites of morphological characters.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sums of steps across
characters are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected number of steps,
numbers of steps for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the lowest number of steps exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the number of steps for each tree, the differences of
each from the lowest one, the variance of that quantity as determined by
the differences of the numbers of steps at individual characters,
and a conclusion as to
whether that tree is or is not significantly worse than the best one.
At the beginning of the program is a constant, maxtrees,
the maximum number of trees which the program will store for output.
The program is descended from earlier programs SOKAL and WAGNER which have
long since been removed from the PHYLIP package, since MIX has all their
capabilites and more.
MOVE is an interactive parsimony program, inspired by Wayne Maddison and
David Maddison's marvellous program MacClade, which is written for Apple
Macintosh computers. MOVE reads in a data set which is prepared in almost the
same format as one for the mixed method parsimony program MIX. It allows
the user to choose an initial tree, and displays this tree on the screen. The
user can look at different characters and the way their states are
distributed on that tree, given the most parsimonious reconstruction of state
changes for that particular tree. The user then can specify how the tree is to
be rearraranged, rerooted or written out to a file. By looking at different
rearrangements of the tree the user can manually search for the most
parsimonious tree, and can get a feel for how different characters are affected by changes in the tree topology.
This program is compatible with fewer computer systems than the other
programs in PHYLIP. It can be adapted to PCDOS systems or to
any system whose screen or terminals emulate DEC VT100
terminals (such as Telnet programs for logging in to remote computers over a
TCP/IP network,
VT100-compatible windows in the X windowing system, and any
terminal compatible with ANSI standard terminals).
For any other screen types, there is a generic option which does
not make use of screen graphics characters to display the character
states. This will be less effective, as the states will be less
easy to see when displayed.
The input data file is set up almost identically to the data files for
MIX.
The user interaction starts with the program presenting a menu. The
menu looks like this:
Interactive mixed parsimony algorithm, version 3.6a3
Settings for this run:
X Use Mixed method? No
P Parsimony method? Wagner
A Use ancestral states? No
F Use factors information? No
O Outgroup root? No, use as outgroup species 1
W Sites weighted? No
T Use Threshold parsimony? No, use ordinary parsimony
U Initial tree (arbitrary, user, specify)? Arbitrary
0 Graphics type (IBM PC, ANSI, none)? (none)
S Width of terminal screen? 80
L Number of lines on screen? 24
Are these settings correct? (type Y or the letter for one to change)
The P (Parsimony method) option selects among Wagner parsimony
and Camin-Sokal parsimony. If X (miXed methods) is selected the
P menu item disappears, as it is then irrelevant.
The X (miXed methods), A (Ancestors), F (Factors),
O (Outgroup), T (Threshold), and 0 (Graphics type) options are the usual
ones and are described in the main documentation page and in the
discrete characters program documentation page. The L option allows
the program to take advantage of larger screens if available.
The U (initial tree) option allows the user to choose whether
the initial tree is to be arbitrary, interactively specified by the user, or
read from a tree file. Typing U causes the program to change among the
three possibilities in turn. I
would recommend that for a first run, you allow the tree to be set up
arbitrarily (the default), as the "specify" choice is difficult
to use and the "user tree" choice requires that you have available a tree file
with the tree topology of the initial tree.
Its default name is intree. The program will ask you for its name if
it looks for the input tree file and does not find one of this name.
If you wish to set up some
particular tree you can also do that by the rearrangement commands specified
below. The T (threshold) option allows a continuum of methods between
parsimony and compatibility. Thresholds less than or equal to 1.0 do not
have any
meaning and should not be used: they will result in a tree dependent only on
the input order of species and not at all on the data!
Note that the usual W (Weights) option is not available in MOVE. We
hope to add it soon.
The F (Factors)
option is available in this program. It is only used to inform the program
which
groups of characters are to be counted together in computing the number of
characters compatible with the tree. Thus if three binary characters are all
factors of the same multistate character, the multistate character will
be counted as compatible with the tree only if all three factors are compatible
with it.
After the initial menu is displayed and the choices are made,
the program then sets up an initial tree and displays it. Below it will be a
one-line menu of possible commands, which looks like this:
NEXT? (Options: R # + - S . T U W O F C H ? X Q) (H or ? for Help)
If you type H or ? you will get a single screen showing a description of each
of these commands in a few words. Here are slightly more detailed
descriptions:
R
("Rearrange"). This command asks for the number of a node which is to be
removed from the tree. It and everything to the right of it on the tree is to
be removed (by breaking the branch immediately below it). The command also
asks for the number of a node below which that group is to be inserted. If an
impossible number is given, the program refuses to carry out the rearrangement
and asks for a new command. The rearranged tree is displayed: it will often
have a different number of steps than the original. If you wish to undo a
rearrangement, use the Undo command, for which see below.
#
This command, and the +, - and S commands described below, determine
which character has its states displayed on the branches of
the trees. The initial tree displayed by the program does not show
states of sites. When # is typed, the program does not ask the user which
character is to be shown but automatically shows the states of the next
binary character that is not compatible with the tree (the next character that
does not
perfectly fit the current tree). The search for this character "wraps around"
so that if it reaches the last character without finding one that is not
compatible with the tree, the search continues at the first character; if no
incompatible character is found the current character is shown, and if no
current
character is shown then the first character is shown. The display takes
the form of
different symbols or textures on the branches of the tree. The state of each
branch is actually the state of the node above it. A key of the symbols or
shadings used for states 0, 1 and ? are shown next to the tree. State ? means
that either state 0 or state 1 could exist at that point on the tree, and that
the user may want to consider the different possibilities, which are usually
apparent by inspection.
+
This command is the same as # except that it goes forward one character,
showing the states of the next character. If no character has been shown,
using + will
cause the first character to be shown. Once the last character has been
reached, using + again will show the first character.
-
This command is the same as + except that it goes backwards, showing the
states of the previous character. If no character has been shown, using - will
cause the last character to be shown. Once character number 1 has been
reached, using - again will show the last character.
S
("Show"). This command is the same as + and - except that it causes
the program to ask you for the number of a character. That character is
the one whose states will be displayed. If you give the character number as 0,
the program will go back to not showing the states of the characters.
. (dot)
This command simply causes the current tree to be redisplayed. It is of
use when the tree has partly disappeared off of the top of the screen owing to
too many responses to commands being printed out at the bottom of the screen.
T
("Try rearrangements"). This command asks for the name of a node. The
part of the tree at and above that node is removed from the tree. The program
tries to re-insert it in each possible location on the tree (this may take some
time, and the program reminds you to wait). Then it prints out a summary. For
each possible location the program prints out the number of the node to the
right of the
place of insertion and the number of steps required in each case. These are
divided into those that are better, tied, or worse than the current tree. Once
this summary is printed out, the group that was removed is inserted into its
original position. It is up to you to use the R command to actually carry out
any the arrangements that have been tried.
U
("Undo"). This command reverses the effect of the most recent
rearrangement, outgroup re-rooting, or flipping of branches. It returns to the
previous tree topology. It will be of great use when rearranging the tree and
when a rearrangement proves worse than the preceding one -- it permits you to
abandon the new one and return to the previous one without remembering its
topology in detail.
W
("Write"). This command writes out the current tree onto a tree output
file. If the file already has been written to by this run of MOVE, it will
ask you whether you want to replace the contents of the file, add the tree to
the end of the file, or not write out the tree to the file. The tree
is written in the standard format used by PHYLIP (a subset of the
Newick standard). It is in the proper format to serve as the
User-Defined Tree for setting up the initial tree in a subsequent run of the
program. Note that if you provided the initial tree topology in a tree file
and replace its contents, that initial tree will be lost.
O
("Outgroup"). This asks for the number of a node which is to be the
outgroup. The tree will be redisplayed with that node
as the left descendant of the bottom fork. Under some options (for example the
Camin-Sokal parsimony method or the Ancestor state options), the number of
steps required on the tree may change on re-rooting. Note that it is possible to
use this to make a multi-species group the outgroup (i.e., you can give the
number of an interior node of the tree as the outgroup, and the program will
re-root the tree properly with that on the left of the bottom fork).
F
("Flip"). This asks for a node number and then flips the two branches at
that node, so that the left-right order of branches at that node is
changed. This does not actually change the tree topology (or the number of
steps on that tree) but it does change the appearance of the tree.
.br
C
("Clade"). When the data consist of more than 12 species (or more than
half the number of lines on the screen if this is not 24), it may be
difficult to display the tree on one screen. In that case the tree
will be squeezed down to
one line per species. This is too small to see all the interior states of the
tree. The C command instructs the program to print out only that part of the
tree (the "clade") from a certain node on up. The program will prompt you for
the number of this node. Remember that thereafter you are not looking at the
whole tree. To go back to looking at the whole tree give the C command again
and enter "0" for the node number when asked. Most users will not want to use
this option unless forced to.
H
("Help"). Prints a one-screen summary of what the commands do, a few
words for each command.
?
("huh?"). A synonym for H. Same as Help command.
X
("Exit"). Exit from program. If the current tree has not yet been saved
into a file, the program will ask you whether it should be saved.
Q
("Quit"). A synonym for X. Same as the eXit command.
ADAPTING THE PROGRAM TO YOUR COMPUTER AND TO YOUR TERMINAL
As we have seen, the initial menu of the program allows you to choose
among three screen types (PC, ANSI, and none).
If you want to
avoid having to make this choice every time, you can change
some of the
constants in the file phylip.h to have the terminal type initialize
itself in the proper way, and recompile.
The constants that need attention are ANSICRT and IBMCRT.
Currently these are both set to "false" on Macintosh and on Unix/Linux
systems, and IBMCRT is set to "true" on Windows systems. If your system
has an ANSI compatible terminal, you might want to find the
definition of ANSICRT in phylip.h and set it to "true", and
IBMCRT to "false".
MORE ABOUT THE PARSIMONY CRITERION
MOVE uses as its numerical criterion the Wagner and
Camin-Sokal parsimony methods in mixture, where each character can have
its method specified separately. The program defaults to carrying out Wagner
parsimony.
The Camin-Sokal parsimony method explains the data by assuming that changes 0
--> 1 are allowed but not changes 1 --> 0. Wagner parsimony allows both kinds
of changes. (This under the assumption that 0 is the ancestral state, though
the program allows reassignment of the ancestral state, in which case we must
reverse the state numbers 0 and 1 throughout this discussion). The criterion
is to find the tree which requires the minimum number of changes. The Camin-
Sokal method is due to Camin and Sokal (1965) and the Wagner method to Eck and
Dayhoff (1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
Ancestral states are known (Camin-Sokal) or unknown (Wagner).
Different characters evolve independently.
Different lineages evolve independently.
Changes 0 --> 1 are much more probable than changes 1 --> 0 (Camin-Sokal)
or equally probable (Wagner).
Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the group in
question.
Other kinds of evolutionary event such as retention of
polymorphism are far less probable than 0 --> 1 changes.
Rates of
evolution in different lineages are sufficiently low that two changes in a long
segment of the tree are far less probable than one change in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
Below is a test data set, but we cannot show the
output it generates because of the interactive nature of the program.
This program uses protein sequences to compute a distance matrix, under
four different models of amino acid replacement. It can also
compute a table of similarity between the amino acid sequences.
The distance for each
pair of species estimates the total branch length between the two species, and
can be used in the distance matrix programs FITCH, KITSCH or NEIGHBOR. This
is an alternative to use of the sequence data itself in the
parsimony program PROTPARS.
The program reads in protein sequences and writes an output file containing
the distance matrix or similarity table. The four models of amino acid
substitution are
one which is based on the Jones, Taylor and Thornton (1992) model of
amino acid change, one based on the PAM matrixes of Margaret Dayhoff, one due to
Kimura (1983) which approximates it based simply on the fraction of
similar amino acids, and one based on a model in which the amino acids are
divided up into groups, with change occurring based on the genetic code
but with greater difficulty of changing between groups. The program correctly
takes into account a variety of sequence ambiguities.
The four methods are:
(1) The Dayhoff PAM matrix. This uses Dayhoff's PAM 001 matrix from
Dayhoff (1979), page 348. The PAM model is an empirical one that
scales probabilities of change from one amino acid to another in
terms of a unit which is an expected 1% change between two amino acid
sequences. The PAM 001 matrix is used to make a transition probability
matrix which allows prediction of the probability of changing from any
one amino acid to any other, and also predicts equilibrium amino acid
composition. The program assumes that these probabilities are correct
and bases its computations of distance on them. The distance that is
computed is scaled in units of expected fraction of amino acids
changed. This is a unit of 100 PAM's.
(2) The Jones-Taylor-Thornton model. This is similar to the Dayhoff
PAM model, except that it is based on a recounting of the number of
observed changes in amino acids by Jones, Taylor, and Thornton (1992).
They used a much larger sample of protein sequences than did Dayhoff.
The distance is scaled in units of the expected fraction of amino acids
changed (100 PAM's). Because its sample is so much larger this
model is to be preferred over the original Dayhoff PAM model. It
is the default model in this program.
(3) Kimura's distance. This is a rough-and-ready distance formula for
approximating PAM distance by simply measuring the fraction of amino
acids, p, that differs between two sequences and computing the
distance as (Kimura, 1983)
D = - loge ( 1 - p - 0.2 p2 ).
This is very quick to do but has some obvious limitations. It does not
take into account which amino acids differ or to what amino acids
they change, so some information is lost. The units of the distance
measure are fraction of amino acids differing, as also in the case of
the PAM distance. If the fraction of amino acids differing gets larger
than 0.8541 the distance becomes infinite.
(4) The Categories distance. This is my own concoction. I imagined
a nucleotide sequence changing according to Kimura's 2-parameter model,
with the exception that some changes of amino acids are less likely than
others. The amino acids are grouped into a series of categories. Any
base change that does not change which category the amino acid is in is
allowed, but if an amino acid changes category this is allowed only a
certain fraction of the time. The fraction is called the "ease" and
there is a parameter for it, which is 1.0 when all changes are allowed
and near 0.0 when changes between categories are nearly impossible.
In this option I have allowed the user to select the Transition/Transversion
ratio, which of several genetic codes to use, and which categorization
of amino acids to use. There are three of them, a somewhat random sample:
(a)
The George-Hunt-Barker (1988) classification of amino acids,
(b)
A classification provided by my colleague Ben Hall when I asked him for one,
(c)
One I found in an old "baby biochemistry" book (Conn and Stumpf, 1963),
which contains most of the biochemistry I was ever taught, and all that I ever
learned.
Interestingly enough, all of them are consisten with the same linear
ordering of amino acids, which they divide up in different ways. For the
Categories model I have set as default the George/Hunt/Barker classification
with the "ease" parameter set to 0.457 which is approximately the value
implied by the empirical rates in the Dayhoff PAM matrix.
The method uses, as I have noted, Kimura's (1980) 2-parameter model of DNA
change. The Kimura "2-parameter" model allows
for a difference between transition and transversion rates. Its transition
probability matrix for a short interval of time is:
To: A G C T
---------------------------------
A | 1-a-2b a b b
From: G | a 1-a-2b b b
C | b b 1-a-2b a
T | b b a 1-a-2b
where a is u dt, the product of the rate of transitions per unit time and dt
is the length dt of the time interval, and b is v dt, the product of half the
rate of transversions (i.e., the rate of a specific transversion)
and the length dt of the time interval.
Each distance that is calculated is an estimate, from that particular pair of
species, of the divergence time between those two species. The Kimura
distance is straightforward to compute. The other two are considerably
slower, and they look at all positions, and find that distance which
makes the likelihood highest. This likelihood is in effect the length of
the internal branch in a two-species tree that connects these two
species. Its likelihood is just the product, under the model, of the
probabilities of each position having the (one or) two amino acids that
are actually found. This is fairly slow to compute.
The computation proceeds from an eigenanalysis (spectral decomposition)
of the transition probability matrix. In the case of the PAM 001 matrix
the eigenvalues and eigenvectors are precomputed and are hard-coded
into the program in over 400 statements. In the case of the Categories
model the program computes the eigenvalues and eigenvectors itself, which
will add a delay. But the delay is independent of the number of species
as the calculation is done only once, at the outset.
The actual algorithm for estimating the distance is in both cases a
bisection algorithm which tries to find the point at which the derivative
os the likelihood is zero. Some of the kinds of ambiguous amino acids
like "glx" are correctly taken into account. However, gaps are treated
as if they are unkown nucleotides, which means those positions get dropped
from that particular comparison. However, they are not dropped from the
whole analysis. You need not eliminate regions containing gaps, as long
as you are reasonably sure of the alignment there.
Note that there is an
assumption that we are looking at all positions, including those
that have not changed at all. It is important not to restrict attention
to some positions based on whether or not they have changed; doing that
would bias the distances by making them too large, and that in turn
would cause the distances
to misinterpret the meaning of those positions that
had changed.
The program can now correct distances for unequal rates of change at different
amino acid positions. This correction, which was introduced for DNA
sequences by Jin and Nei (1990), assumes that the distribution of rates
of change among amino acid positions follows a Gamma distribution. The
user is asked for the value of a parameter that determines the amount of
variation of rates among amino acid positions. Instead of the more
widely-known coefficient alpha, PROTDIST uses the coefficient of variation
(ratio of the standard deviation to the mean) of rates among amino acid
positions. . So if there is 20% variation in rates, the CV is
is 0.20. The square of the C.V. is also the reciprocal of the
better-known "shape parameter", alpha, of the Gamma
distribution, so in this case the shape parameter alpha = 1/(0.20*0.20)
= 25. If you want to achieve a particular value of alpha, such as 10,
you will want to use a CV of 1/sqrt(100) = 1/10 = 0.1.
In addition to the four distance calculations, the program can also
compute a table of similarities between amino acid sequences. These values
are the fractions of amino acid positions identical between the sequences.
The diagonal values are 1.0000. No attempt is made to count similarity
of nonidentical amino acids, so that no credit is given for having
(for example) different hydrophobic amino acids at the corresponding
positions in the two sequences. This option has been requested by many
users, who need it for descriptive purposes. It is not intended that
the table be used for inferring the tree.
INPUT FORMAT AND OPTIONS
Input is fairly standard, with one addition. As usual the first line of the
file gives the number of species and the number of sites. There follows the
character W if the Weights option is being used.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
After that are the lines (if any) containing the information for the
W option, as described below.
The options are selected using an interactive menu. The menu looks like this:
Protein distance algorithm, version 3.6a3
Settings for this run:
P Use JTT, PAM, Kimura or categories model? Jones-Taylor-Thornton matrix
G Gamma distribution of rates among positions? No
C One category of substitution rates? Yes
W Use weights for positions? No
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
Are these settings correct? (type Y or the letter for one to change)
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The G option chooses Gamma distributed rates of evolution across amino
acid psoitions. The program will pronmpt you for the Coefficient of Variation
of rates. As is noted above, thi is 1/sqrt(alpha) if alpha is the more
familiar "shape coefficient" of the Gamma distribution. If the G option
is not selected, the program defaults to having no variation of rates
among sites.
The options M and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
The P option selects one of the four distance methods, or the
similarity table. It toggles among these
five methods. The default method, if none is specified, is the
Jones-Taylor-Thornton model. If the Categories distance is selected
another menu option, T, will appear allowing the user
to supply the Transition/Transversion ratio that should be assumed
at the underlying DNA level, and another one, C, which allows the
user to select among various nuclear and mitochondrial genetic codes.i
The transition/transversion ratio can be any number from 0.5 upwards.
The W (Weights) option is invoked in the usual way, with only weights 0
and 1 allowed. It selects a set of sites to be analyzed, ignoring the
others. The sites selected are those with weight 1. If the W option is
not invoked, all sites are analyzed.
OUTPUT FORMAT
As the
distances are computed, the program prints on your screen or terminal
the names of the species in turn,
followed by one dot (".") for each other species for which the distance to
that species has been computed. Thus if there are ten species, the first
species name is printed out, followed by one dot, then on the next line
the next species name is printed out followed by two dots, then the
next followed by three dots, and so on. The pattern of dots should form
a triangle. When the distance matrix has been written out to the output
file, the user is notified of that.
The output file contains on its first line the number of species. The
distance matrix is then printed in standard
form, with each species starting on a new line with the species name, followed
by the distances to the species in order. These continue onto a new line
after every nine distances. The distance matrix is square
with zero distances on the diagonal. In general the format of the distance
matrix is such that it can serve as input to any of the distance matrix
programs.
If the similarity table is selected, the table that is produced is not
in a format that can be used as input to the distance matrix programs.
it has a heading, and the species names are also put at the tops of the
columns of the table (or rather, the first 8 characters of each species
name is there, the other two characters omitted to save space). There
is not an option to put the table into a format that can be read by
the distance matrix programs, nor is there one to make it into a table
of fractions of difference by subtracting the similarity values from 1.
This is done deliberately to make it more difficult for the use to
use these values to construct trees. The similarity values are
not corrected for multiple changes, and their use to construct trees
(even after converting them to fractions of difference) would be
wrong, as it would lead to severe conflict between the distant
pairs of sequences and the close pairs of sequences.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the menu
selections. The output file begins by giving the number of species and the
number of characters, and the identity of the distance measure that is
being used.
In the Categories model of substitution,
the distances printed out are scaled in terms of expected numbers of
substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate of
change is set to 1.0. For the Dayhoff PAM and Kimura models the
distance are scaled in terms of the expected numbers of amino acid
substitutions per site. Of course, when a branch is twice as
long this does not mean that there will be twice as much net change expected
along it, since some of the changes may occur in the same site and overlie or
even reverse each
other. The branch lengths estimates here are in terms of the expected
underlying numbers of changes. That means that a branch of length 0.26
is 26 times as long as one which would show a 1% difference between
the protein (or nucleotide) sequences at the beginning and end of the
branch. But we
would not expect the sequences at the beginning and end of the branch to be
26% different, as there would be some overlaying of changes.
One problem that can arise is that two or more of the species can be so
dissimilar that the distance between them would have to be infinite, as
the likelihood rises indefinitely as the estimated divergence time
increases. For example, with the Kimura model, if the two sequences
differ in 85.41% or more of their positions then the estimate of divergence
time would be infinite. Since there is no way to represent an infinite
distance in the output file, the program regards this as an error, issues a
warning message indicating which pair of species are causing the problem, and
computes a distance of -1.0.
PROGRAM CONSTANTS
The constants that are available to be changed by the user at the beginning
of the program include
"namelength", the length of species names in
characters, and "epsilon", a parameter which controls the accuracy of the
results of the iterations which estimate the distances. Making "epsilon"
smaller will increase run times but result in more decimal places of
accuracy. This should not be necessary.
The program spends most of its time doing real arithmetic. Any software or
hardware changes that speed up that arithmetic will speed it up by a nearly
proportional amount.
TEST DATA SET
(Note that although these may look like DNA sequences, they are being
treated as protein sequences consisting entirely of alanine, cystine,
glycine, and threonine).
CONTENTS OF OUTPUT FILE (with all numerical options on )
(Note that when the numerical options are not on, the output file produced is
in the correct format to be used as an input file in the distance matrix
programs).
(c) Copyright 1986-2000 by The University of
Washington. Written by Joseph Felsenstein. Permission is granted to copy
this document provided that no fee is charged for it and that this copyright
notice is not removed.
These programs estimate phylogenies from protein
sequence or nucleic acid sequence data. PROTPARS uses a parsimony method
intermediate between Eck and Dayhoff's
method (1966) of allowing transitions between all amino acids and counting
those, and Fitch's (1971) method of counting the number of nucleotide changes
that would be needed to evolve the protein sequence. DNAPARS uses the
parsimony method allowing changes between all bases
and counting the number of those. DNAMOVE is an interactive parsimony
program allowing the user to rearrange trees by hand and see where
characters states change. DNAPENNY
uses the branch-and-bound method to search for all most
parsimonious trees in the nucleic acid sequence case. DNACOMP
adapts to nucleotide sequences the compatibility (largest clique)
approach. DNAINVAR does not directly estimate a phylogeny, but computes Lake's
(1987) and Cavender's (Cavender and Felsenstein, 1987) phylogenetic invariants,
which are quantities whose values depend on the phylogeny. DNAML does a
maximum likelihood estimate of the phylogeny (Felsenstein, 1981a). DNAMLK
is similar to DNAML but assumes a molecular clock. DNADIST
computes distance measures between pairs of species from nucleotide sequences,
distances that can then be used by the distance matrix programs FITCH and
KITSCH. RESTML does a maximum likelihood estimate from restriction
sites data. SEQBOOT allows you to read in a data set and then produce
multiple data sets from it by bootstrapping, delete-half jackknifing, or
by permuting within sites. This
then allows most of these methods to be bootstrapped or jackknifed, and
for the Permutation Tail Probability Test of Archie (1989) and Faith and
Cranston (1991) to be carried out.
The input and output format for RESTML is described in
its document files. In general its input format is similar to
those described here, except that the one-letter codes for restriction sites
is specific to that program and is described in that document file. Since
the input formats for the eight DNA sequence and two protein sequence
programs apply to more than one program, they are described here. Their
input formats are standard, making use of the IUPAC standards.
.sp 2
.ce
INTERLEAVED AND SEQUENTIAL FORMATS
The sequences can continue over multiple lines; when this is done the
sequences must be either in "interleaved" format, similar to the
output of alignment programs, or "sequential" format. These are
described in the main document file. In sequential format all
of one sequence is given, possibly on multiple lines, before the next starts.
In interleaved format the first part of the file should contain the first
part of each of the sequences, then possibly a line containing nothing
but a carriage-return character, then the second part of each sequence,
and so on. Only the first parts of the sequences should be preceded by
names. Here is a hypothetical example of interleaved format:
5 42
Turkey AAGCTNGGGC ATTTCAGGGT
Salmo gairAAGCCTTGGC AGTGCAGGGT
H. SapiensACCGGTTGGC CGTTCAGGGT
Chimp AAACCCTTGC CGTTACGCTT
Gorilla AAACCCTTGC CGGTACGCTT
GAGCCCGGGC AATACAGGGT AT
GAGCCGTGGC CGGGCACGGT AT
ACAGGTTGGC CGTTCAGGGT AA
AAACCGAGGC CGGGACACTC AT
AAACCATTGC CGGTACGCTT AA
while in sequential format the same sequences would be:
5 42
Turkey AAGCTNGGGC ATTTCAGGGT
GAGCCCGGGC AATACAGGGT AT
Salmo gairAAGCCTTGGC AGTGCAGGGT
GAGCCGTGGC CGGGCACGGT AT
H. SapiensACCGGTTGGC CGTTCAGGGT
ACAGGTTGGC CGTTCAGGGT AA
Chimp AAACCCTTGC CGTTACGCTT
AAACCGAGGC CGGGACACTC AT
Gorilla AAACCCTTGC CGGTACGCTT
AAACCATTGC CGGTACGCTT AA
Note, of course, that a portion of a sequence like this:
300 AAGCGTGAAC GTTGTACTAA TRCAG
is perfectly legal, assuming that the species name has gone before, and is
filled out to full length by blanks. The above
digits and blanks will be ignored, the sequence being taken as starting
at the first base symbol (in this case an A). This should enable you to
use output from many multiple-sequence alignment programs with only
minimal editing.
In interleaved format
the present versions of the programs may sometimes have difficulties with the
blank lines between groups of lines, and if so you might want to retype
those lines, making sure that they have only a carriage-return and no blank
characters on them, or you may perhaps have to eliminate them. The symptoms
of this problem are that the programs complain that the sequences are not
properly aligned, and you can find no other cause for this complaint.
INPUT FOR THE DNA SEQUENCE PROGRAMS
The input format for the DNA sequence programs is
standard: the data have A's, G's, C's and T's (or U's). The first line of the
input file contains the number of species and the number of sites. As
with the other programs, options information may follow this. Following this,
each species starts on a new line. The first 10
characters of that line are the species name. There then follows
the base sequence of that species, each character
being one of the letters A, B, C, D, G, H, K, M, N, O, R, S, T, U, V,
W, X, Y, ?, or - (a period was also previously allowed but it is no longer
allowed, because it sometimes is used in different senses in other
programs). Blanks will be ignored, and so will numerical
digits. This allows GENBANK and EMBL sequence entries to be read with
minimum editing.
These characters can be either upper or lower case. The algorithms
convert all input characters to upper case (which is how they
are treated). The characters constitute the IUPAC (IUB) nucleic acid code
plus some slight
extensions. They enable input of nucleic acid sequences taking full account
of any ambiguities in the sequence.
Symbol
Meaning
A
Adenine
G
Guanine
C
Cytosine
T
Thymine
U
Uracil
Y
pYrimidine
(C or T)
R
puRine
(A or G)
W
"Weak"
(A or T)
S
"Strong"
(C or G)
K
"Keto"
(T or G)
M
"aMino"
(C or A)
B
not A
(C or G or T)
D
not C
(A or G or T)
H
not G
(A or C or T)
V
not T
(A or C or G)
X,N,?
unknown
(A or C or G or T)
O
deletion
-
deletion
INPUT FOR THE PROTEIN SEQUENCE PROGRAMS
The input for the protein sequence programs is fairly standard. The first
line contains the
number of species and the number of amino acid positions (counting any
stop codons that you want to include). These are followed on the same line
by the options. The only options which
need information in the input file are U (User Tree) and W (Weights). They are
as described in the main documentation file. If the W (Weights) option is
used there must be a W in the first line of the input file.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The protein sequences are given by the one-letter code used by
the late Margaret Dayhoff's group in the Atlas of Protein Sequences,
and consistent with the IUB standard abbreviations.
In the present version it is:
Symbol
Stands for
A
ala
B
asx
C
cys
D
asp
E
glu
F
phe
G
gly
H
his
I
ileu
J
(not used)
K
lys
L
leu
M
met
N
asn
O
(not used)
P
pro
Q
gln
R
arg
S
ser
T
thr
U
(not used)
V
val
W
trp
X
unknown amino acid
Y
tyr
Z
glx
*
nonsense (stop)
?
unknown amino acid or deletion
-
deletion
where "nonsense", and "unknown" mean respectively a nonsense (chain
termination) codon and an amino acid whose identity has not been
determined. The state "asx" means "either asn or asp",
and the state "glx" means "either gln or glu" and the state "deletion"
means that alignment studies indicate a deletion has happened in the
ancestry of this position, so that it is no longer present. Note that
if two polypeptide chains are being used that are of different length
owing to one terminating before the other, they can be coded as (say)
HIINMA*????
HIPNMGVWABT
since after the stop codon we do not definitely know that
there has been a deletion, and do not know what amino acid would
have been there. If DNA studies tell us that there is
DNA sequence in that region, then we could use "X" rather than "?". Note
that "X" means an unknown amino acid, but definitely an amino acid,
while "?" could mean either that or a deletion. Otherwise one will usually
want to use "?" after a stop codon, if one does not know what amino acid is
there. If the DNA sequence has been observed there, one probably ought to
resist putting in the amino acids that this DNA would code for, and one should
use "X" instead, because under the assumptions implicit in this either the
parsimony or the distance
methods, changes to any noncoding sequence are much easier than
changes in a coding region that change the amino acid
Here are the same one-letter codes tabulated the other way 'round:
Amino acid
One-letter code
ala
A
arg
R
asn
N
asp
D
asx
B
cys
C
gln
Q
glu
E
gly
G
glx
Z
his
H
ileu
I
leu
L
lys
K
met
M
phe
F
pro
P
ser
S
thr
T
trp
W
tyr
Y
val
V
deletion
-
nonsense (stop)
*
unknown amino acid
X
unknown (incl. deletion)
?
THE OPTIONS
The programs allow options chosen from their menus. Many of these are as described in the
main documentation file, particularly the options J, O, U, T, W,
and Y. (Although T has a different meaning in the programs DNAML and
DNADIST than in the others).
The U option indicates that
user-defined trees are provided at the end of the input file. This
happens in the usual way, except that for PROTPARS, DNAPARS, DNACOMP, and
DNAMLK, the trees must be strictly
bifurcating, containing only two-way splits, e. g.: ((A,B),(C,(D,E)));. For
DNAML and RESTML it must have a trifurcation at its base,
e. g.: ((A,B),C,(D,E));. The
root of the tree may in those cases be placed arbitrarily, since the trees
needed are actually unrooted, though they look different when printed out. The
program RETREE should enable you to reroot the trees without having to
hand-edit or retype them. For
DNAMOVE the U option is not available (although
there is an equivalent feature which uses rooted user trees).
A feature of the nucleotide sequence programs other than DNAMOVE
is that they save time and computer memory space by recognizing sites
at which the pattern of bases is the same, and doing their computation only
once. Thus if we have only four species but a large number of sites, there
are (ignoring ambiguous bases) only about 256 different patterns of
nucleotides (4 x 4 x 4 x 4) that can occur. The programs automatically
count how many occurrences there are of each and then only needs to do as much
computation as would be
needed with 256 sites, even though the number of sites is actually much
larger. If there are ambiguities (such as Y or R nucleotides), these are also
handled correctly, and do not cause trouble. The programs store the full
sequences but reserve other space for bookkeeping only for the distinct
patterns. This saves space. Thus the programs will run very effectively
with few species and many sites. On larger numbers of species,
if rates of evolution are small, many of the sites will be invariant
(such as having all A's) and thus will mostly have one of four patterns. The
programs will in this way automatically avoid doing duplicate
computations for such sites.
PHYLIPNEW-3.69.650/doc/contchar.html 0000664 0001750 0001750 00000016443 07712247475 013551 0000000 0000000
contchar
version 3.6
Gene Frequencies and Continuous Character Data Programs
The programs in this group
use gene frequencies and quantitative character values. One (CONTML)
constructs maximum likelihood estimates of the phylogeny, another
(GENDIST) computes genetic distances for use in the distance matrix
programs, and the third (CONTRAST) examines correlation of traits as
they evolve along a given phylogeny.
When the gene frequencies data are used in CONTML or GENDIST, this
involves the following assumptions:
Different lineages evolve independently.
After two lineages split, their characters change
independently.
Each gene frequency changes by genetic drift, with or without mutation
(this varies from method to method).
Different loci or characters drift independently.
How these assumptions affect the methods will be seen in my papers on
inference of phylogenies from gene frequency and continuous character
data (Felsenstein, 1973b, 1981c, 1985c).
The input formats are fairly similar to the discrete-character
programs, but with one difference. When CONTML is used in the gene-frequency
mode (its usual, default mode), or when GENDIST is used,
the first line contains the number of species (or
populations) and the number of loci and the options information.
There then follows a line which
gives the numbers of alleles at each locus, in order. This must be
the full number of alleles, not the number of alleles which will be input:
i. e. for a two-allele locus the number should be 2, not 1. There
then follow the species (population) data, each species beginning
on a new line. The first 10 characters are taken as the name, and
thereafter the values of the individual characters are read free-format,
preceded and separated by blanks. They can go to a new line if desired,
though of course not in the middle of a number. Missing data is not
allowed - an important limitation. In the default configuration, for
each locus, the numbers should be
the frequencies of all but one allele. The menu option A (All) signals that
the frequencies of all alleles are provided in the input data -- the
program will then automatically ignore the last of them. So without the
A option, for a
three-allele locus there should be two numbers, the frequencies of
two of the alleles (and of course it must always be the same
two!). Here is a typical data set without the A option:
The first line has the number of species (or populations) and the number
of loci. The second line has the number of alleles for each of the 3 loci.
The species lines have names (filled out to 10 characters with blanks)
followed by the gene frequencies of the 2 alleles for the first locus, the
3 alleles for the second locus, and the 2 alleles for the third locus.
You can start a new line after any of these allele frequencies, and
continue to give the frequencies on that line (without repeating the
species name).
If all alleles of a locus are given, it is important to have them add up
to 1. Roundoff of the frequencies may cause the program to conclude that
the numbers do not sum to 1, and stop with an error message.
While many compilers may be more tolerant, it is probably wise to
make sure that each number, including the first, is preceded by a blank,
and that there are digits both preceding and following any decimal
points.
CONTML and CONTRAST also treat quantitative characters (the
continuous-characters mode in CONTML, which is option C). It is assumed
that each character is evolving according to a Brownian motion model, at the
same rate, and independently. In
reality it is almost always impossible to guarantee this. The issue is
discussed at length
in my review article in Annual Review of Ecology and Systematics (Felsenstein,
1988a), where I point out the difficulty of transforming the characters so
that they are not only genetically independent but have independent selection
acting on them. If you are going to use CONTML to model evolution of
continuous characters, then you should at least make some attempt to remove
genetic correlations between the characters (usually all one can do is remove
phenotypic correlations by transforming the characters so that there is no
within-population covariance and so that the within-population
variances of the characters are equal -- this is equivalent to using
Canonical Variates). However, this will only guarantee that one has
removed phenotypic covariances between characters. Genetic covariances
could only be removed by knowing the coheritabilities of the characters,
which would require genetic experiments, and selective covariances
(covariances due to covariation of selection pressures) would require
knowledge of the sources and extent of selection pressure in all variables.
CONTRAST is a program designed to infer, for a given phylogeny that is
provided to the program, the covariation between characters in a data
set. Thus we have a program in this set that allow us to take information
about the covariation and rates of evolution of characters and make an
estimate of the phylogeny (CONTML), and a program that takes an estimate of the
phylogeny and infers the variances and covariances of the character
changes. But we have no program that infers both the phylogenies and
the character covariation from the same data set.
In the quantitative characters mode, a typical small data set would be:
Note that in the latter case, there is no line giving the numbers
of alleles at each locus. In this latter case no square-root
transformation of the coordinates is done: each is assumed to give
directly the position on the Brownian motion scale.
For further discussion of options and modifiable constants in CONTML,
GENDIST, and CONTRAST see the documentation files for those programs.
PHYLIPNEW-3.69.650/doc/dnainvar.html 0000664 0001750 0001750 00000040371 07712247475 013547 0000000 0000000
dnainvar
version 3.6
DNAINVAR -- Program to compute Lake's and Cavender's
phylogenetic invariants from nucleotide sequences
This program reads in nucleotide sequences for four species and computes
the phylogenetic invariants discovered by James Cavender (Cavender and
Felsenstein, 1987) and James Lake (1987). Lake's method is also
called by him "evolutionary parsimony". I prefer Cavender's more
mathematically precise term "invariants", as the method bears somewhat
more relationship to likelihood methods than to parsimony. The invariants
are mathematical
formulas (in the present case linear or quadratic) in the EXPECTED
frequencies of site patterns which are zero for all trees of a given
tree topology, irrespective of branch lengths. We can consider at a given
site that if there
are no ambiguities, we could have for four species the nucleotide patterns
(considering the same site across all four species) AAAA, AAAC, AAAG, ...
through TTTT, 256 patterns in all.
The invariants are formulas in the expected pattern frequencies, not
the observed pattern frequencies. When they are computed using the
observed pattern frequencies, we will
usually find that they are not precisely zero even when the model is correct
and we have the correct tree topology. Only as the number of nucleotides
scored becomes infinite will the observed pattern frequencies approach their
expectations; otherwise, we must do a statistical test of the invariants.
Some explanation of invariants will be found in the above papers, and also
in my recent review article on statistical aspects of inferring phylogenies
(Felsenstein, 1988b). Although invariants have some important advantages,
their validity also depends on symmetry assumptions that may not be satisfied.
In the discussion below suppose that the possible unrooted phylogenies are
I: ((A,B),(C,D)), II: ((A,C),(B,D)), and III: ((A,D),(B,C)).
Lake's Invariants, Their Testing and Assumptions
Lake's invariants are fairly simple to describe: the patterns involved are
only those in which there are two purines and two pyrimidines at a site.
Thus a site with AACT would affect the invariants, but a site with AAGG would
not. Let us use (as Lake does)
the symbols 1, 2, 3, and 4, with the proviso that 1 and 2
are either both of the purines or both of the pyrimidines; 3 and 4 are the
other two nucleotides. Thus 1 and 2 always differ by a transition; so do
3 and 4. Lake's invariants, expressed in terms of expected frequencies, are
the three quantities:
(1) P(1133) + P(1234) - P(1134) - P(1233),
(2) P(1313) + P(1324) - P(1314) - P(1323),
(3) P(1331) + P(1342) - P(1341) - P(1332),
He showed that invariants (2) and (3) are zero under Topology I, (1) and (3)
are zero under topology II, and (1) and (2) are zero under Topology III. If,
for example, we see a site with pattern ACGC, we can start by setting 1=A.
Then 2 must be G. We can then set 3=C (so that 4 is T). Thus its pattern
type, making those substitutions, is 1323. P(1323) is the expected
probability of the type of pattern which includes ACGC, TGAG, GTAT, etc.
Lake's invariants are easily tested with observed frequencies. For example,
the first of them is a test of whether there are as many sites of types 1133
and 1234 as there are of types 1134 and 1233; this is easily tested with a
chi-square test or, as in this program, with an exact binomial test. Note
that with several invariants to test, we risk overestimating the significance
of results if we simply accept the nominal 95% levels of significance
(Li and Guoy, 1990).
Lake's invariants assume that each site is evolving independently, and that
starting from any base a transversion is equally likely to end up at each of
the two possible bases (thus, an A undergoing a transversion is equally likely
to end up as a C or a T, and similarly for the other four bases from which one
could start. Interestingly, Lake's results do not assume that rates of
evolution are the same at all sites. The result that the total of 1133 and 1234
is expected to be the same as the total of 1134 and 1233 is unaffected by the
fact that we may have aggregated the counts over classes of sites evolving at
different rates.
Cavender's Invariants, Their Testing and Assumptions
Cavender's invariants (Cavender and Felsenstein, 1987) are for the case of
a character with two states. In the nucleic acid case we can classify
nucleotides into two states, R and Y (Purine and Pyrimidine) and then use the
two-state results. Cavender starts, as before, with the pattern frequencies.
Coding purines as R and pyrimidines as Y, the patterns types are RRRR, RRRY,
and so on until YYYY, a total of 16 types. Cavender found quadratic functions
of the expected frequencies of these 16 types that were expected to be zero
under a given phylogeny, irrespective of branch lengths. Two invariants
(called K and L) were found for each tree topology. The L invariants are
particularly easy to understand. If we have the tree topology ((A,B),(C,D)),
then in the case of two symmetric states, the event that A and B have the same
state should be independent of whether C and D have the same state, as the
events determining these happen in different parts of the tree. We can set
up a contingency table:
C = D C =/= D
------------------------------
|
A = B | YYYY, YYRR, YYYR, YYRY,
| RRRR, RRYY RRYR, RRRY
|
A =/= B | YRYY, YRRR, YRYR, YRRY,
| RYYY, RYRR RYYR, RYRY
and we expect that the events C = D and A = B will be independent. Cavender's
L invariant for this tree topology is simply the negative of the crossproduct
difference,
P(A=/=B and C=D) P(A=B and C=/=D) - P(A=B and C=D) P(A=/=B and C=/=D).
One of these L invariants is defined for each of the three tree topologies.
They can obviously be tested simply by doing a chi-square test on the
contingency table. The one corresponding to the correct topology should be
statistically indistinguishable from zero. Again, there is a possible
multiple tests problem if all three are tested at a nominal value of 95%.
The K invariants are differences between the L invariants. When one of the
tables is expected to have crossproduct difference zero, the other two are
expected to be nonzero, and also to be equal. So the difference of their
crossproduct differences can be taken; this is the K invariant. It is not
so easily tested.
The assumptions of Cavender's invariants are different from those of
Lake's. One obviously need not assume anything about the frequencies of, or
transitions among, the two different purines or the two different
pyrimidines. However one does need to assume independent events at each site,
and one needs to assume that the Y and R states are symmetric, that the
probability per unit time that a Y changes into an R is the same as the
probability that an R changes into a Y, so that we expect equal frequencies
of the two states. There is also an assumption that all sites are changing
between these two states at the same expected rate. This assumption is not
needed for Lake's invariants, since expectations of sums are equal to
sums of expectations, but for Cavender's it is, since products of expectations
are not equal to expectations of products.
It is helpful to have both sorts of invariants available; with further work we
may appreciate what other invaraints there are for various models of nucleic
acid change.
INPUT FORMAT
The input data for DNAINVAR is standard. The first line of the input file
contains the
number of species (which must always be 4 for this version of DNAINVAR)
and the number of sites.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The options are selected using an interactive menu. The menu looks like this:
Nucleic acid sequence Invariants method, version 3.6a3
Settings for this run:
W Sites weighted? No
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out the counts of patterns Yes
4 Print out the invariants Yes
Y to accept these or type the letter for one to change
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The options W, M and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
OUTPUT FORMAT
The output consists first (if option 1 is selected) of a reprinting of the
input data, then (if option 2 is on) tables
of observed pattern frequencies and pattern type frequencies. A table will
be printed out, in alphabetic order AAAA through TTTT of all the patterns
that appear among the sites and the number of times each appears. This table
will be invaluable for computation of any other invariants. There follows
another table, of pattern types, using the 1234 notation, in numerical
order 1111 through 1234, of the number of times each type of pattern appears.
In this computation all sites at which there are any ambiguities or deletions
are omitted. Cavender's invariants could actually be computed from sites
that have only Y or R ambiguities; this will be done in the next release of
this program.
If option 3 is on the invariants are then printed out,
together with their statistical
tests. For Lake's invariants the two sums which are expected to be equal are
printed out, and then the result of an one-tailed exact binomial test which
tests whether the difference is expected to be this positive or more. The P
level is given (but remember the multiple-tests problem!).
For Cavender's L invariants the contingency tables are given. Each is tested
with a one-tailed chi-square test. It is possible that the expected numbers
in some categories could be too small for valid use of this test; the program
does not check for this. It is also possible that the chi-square could be
significant but in the wrong direction; this is not tested in the current
version of the program. To check it beware of a chi-square greater than 3.841
but with a positive invariant. The invariants themselves are computed, as the
difference of cross-products. Their absolute magnitudes are not important,
but which one is closest to zero may be indicative. Significantly nonzero
invariants should be negative if the model is valid. The K invariants, which
are simply differences among the L invariants, are also printed out without
any test on them being conducted. Note that it is possible to use the
bootstrap utility SEQBOOT to create multiple data sets, and from the
output from sunning all of these get the empirical variability of these
quadratic invariants.
PROGRAM CONSTANTS
The constants
that are defined at the beginning of the program include
"maxsp",
which must always be 4 and should not be changed.
The program is very fast, as it has rather little work to do; these methods
are just a little bit beyond the reach of hand tabulation. Execution speed
should never be a limiting factor.
FUTURE OF THE PROGRAM
In a future version I hope to allow for Y and R codes in the calculation of
the Cavender invariants, and to check for significantly negative cross-product
differences in them, which would indicate violation of the model. By
then there should be more known about invariants for larger number of species,
and any such advances will also be incorporated.
TEST SET OUTPUT (run with all numerical options turned on)
Nucleic acid sequence Invariants method, version 3.6a3
4 species, 13 sites
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta ..G..C.... ..C
Gamma C.TT.C.T.. C.A
Delta GGTA.TT.GG CC.
Pattern Number of times
AAAC 1
AAAG 2
AACC 1
AACG 1
CCCG 1
CCTC 1
CGTT 1
GCCT 1
GGGT 1
GGTA 1
TCAT 1
TTTT 1
Symmetrized patterns (1, 2 = the two purines and 3, 4 = the two pyrimidines
or 1, 2 = the two pyrimidines and 3, 4 = the two purines)
1111 1
1112 2
1113 3
1121 1
1132 2
1133 1
1231 1
1322 1
1334 1
Tree topologies (unrooted):
I: ((Alpha,Beta),(Gamma,Delta))
II: ((Alpha,Gamma),(Beta,Delta))
III: ((Alpha,Delta),(Beta,Gamma))
Lake's linear invariants
(these are expected to be zero for the two incorrect tree topologies.
This is tested by testing the equality of the two parts
of each expression using a one-sided exact binomial test.
The null hypothesis is that the first part is no larger than the second.)
Tree Exact test P value Significant?
I 1 - 0 = 1 0.5000 no
II 0 - 0 = 0 1.0000 no
III 0 - 0 = 0 1.0000 no
Cavender's quadratic invariants (type L) using purines vs. pyrimidines
(these are expected to be zero, and thus have a nonsignificant
chi-square, for the correct tree topology)
They will be misled if there are substantially
different evolutionary rate between sites, or
different purine:pyrimidine ratios from 1:1.
Tree I:
Contingency Table
2 8
1 2
Quadratic invariant = 4.0
Chi-square = 0.23111 (not significant)
Tree II:
Contingency Table
1 5
1 6
Quadratic invariant = -1.0
Chi-square = 0.01407 (not significant)
Tree III:
Contingency Table
1 2
6 4
Quadratic invariant = 8.0
Chi-square = 0.66032 (not significant)
Cavender's quadratic invariants (type K) using purines vs. pyrimidines
(these are expected to be zero for the correct tree topology)
They will be misled if there are substantially
different evolutionary rate between sites, or
different purine:pyrimidine ratios from 1:1.
No statistical test is done on them here.
Tree I: -9.0
Tree II: 4.0
Tree III: 5.0
PHYLIPNEW-3.69.650/doc/pars.html 0000664 0001750 0001750 00000025354 07712247475 012716 0000000 0000000
pars
PARS is a general parsimony program which carries out the Wagner
parsimony method with multiple states. Wagner parsimony
allows changes among all states. The criterion is to find the tree which
requires the minimum number of changes.
The Wagner method was originated by Eck and Dayhoff (1966) and by Kluge and
Farris (1969). Here are its assumptions:
Ancestral states are unknown unknown.
Different characters evolve independently.
Different lineages evolve independently.
Changes to all other states are equally probable (Wagner).
These changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the
group in question.
Other kinds of evolutionary event such as retention of polymorphism
are far less probable than these state changes.
Rates of evolution in different lineages are sufficiently low that
two changes in a long segment of the tree are far less probable
than one change in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
INPUT FORMAT
The input for PARS is the standard input for discrete characters
programs, described above in the documentation file for the
discrete-characters programs, except that multiple states (up to 9 of them)
are allowed. Any characters other than "?" are allowed as states, up to a
maximum of 9 states. In fact, one can
use different symbols in different columns of the data matrix,
although it is rather unlikely that you would want to do that.
The symbols you can use are:
The digits 0-9,
The letters A-Z and a-z,
The symbols "!\"#$%&'()*+,-./:;<=>?@\[\\]^_`\{|}~
(of these, probably only + and - will be of interest to most users).
But note that these do not include blank (" "). Blanks in the
input data are simply skipped by the program, so that they can be used to
make characters into groups for ease of viewing.
The "?" (question mark) symbol has special meaning. It is allowed in the
input but is not available as the symbol of a state. Rather, it means that
the state is unknown.
PARS can handle both bifurcating and multifurcating trees. In doing its
search for most parsimonious trees, it adds species not only by creating new
forks in the middle of existing branches, but it also tries putting them at
the end of new branches which are added to existing forks. Thus it searches
among both bifurcating and multifurcating trees. If a branch in a tree
does not have any characters which might change in that branch in the most
parsimonious tree, it does not save that tree. Thus in any tree that
results, a branch exists only if some character has a most parsimonious
reconstruction that would involve change in that branch.
It also saves a number of trees tied for best (you can alter the number
it saves using the V option in the menu). When rearranging trees, it
tries rearrangements of all of the saved trees. This makes the algorithm
slower than earlier programs such as MIX.
The options are selected using a menu:
Discrete character parsimony algorithm, version 3.6
Setting for this run:
U Search for best tree? Yes
S Search option? More thorough search
V Number of trees to save? 100
J Randomize input order of sequences? No. Use input order
O Outgroup root? No, use as outgroup species 1
T Use Threshold parsimony? No, use ordinary parsimony
W Sites weighted? No
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each site No
5 Print character at all nodes of tree No
6 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
The Weights (W) option
takes the weights from a file whose default name is "weights". The weights
follow the format described in the main documentation file, with integer
weights from 0 to 35 allowed by using the characters 0, 1, 2, ..., 9 and
A, B, ... Z.
The User tree (option U) is read from a file whose default name is
intree.
The trees can be multifurcating. They must be preceded in the file by a
line giving the number of trees in the file.
The options J, O, T, and M are the usual Jumble, Outgroup,
Threshold parsimony, and Multiple Data Sets options,
described either
in the main documentation file or in the Discrete Characters Programs
documentation file.
The M (multiple data sets option) will ask you whether you want to
use multiple sets of weights (from the weights file) or multiple data sets.
The ability to use a single data set with multiple weights means that
much less disk space will be used for this input data. The bootstrapping
and jackknifing tool Seqboot has the ability to create a weights file with
multiple weights.
The O (outgroup) option will have no effect if the U (user-defined tree)
option is in effect.
The T (threshold) option allows a continuum of methods
between parsimony and compatibility. Thresholds less than or equal to 1.0 do
not have any meaning and should
not be used: they will result in a tree dependent only on the input
order of species and not at all on the data!
OUTPUT FORMAT
Output is standard: if option 1 is toggled on, the data is printed out,
with the convention that "." means "the same as in the first species".
Then comes a list of equally parsimonious trees.
Each tree has branch lengths. These are computed using an algorithm
published by Hochbaum and Pathria (1997) which I first heard of from
Wayne Maddison who invented it independently of them. This algorithm
averages the number of reconstructed changes of state over all sites a
over all possible most parsimonious placements of the changes of state
among branches. Note that it does not correct in any way for multiple
changes that overlay each other.
If option 2 is
toggled on a table of the
number of changes of state required in each character is also
printed. If option 5 is toggled
on, a table is printed
out after each tree, showing for each branch whether there are known to be
changes in the branch, and what the states are inferred to have been at the
top end of the branch. This is a reconstruction of the ancestral sequences
in the tree. If you choose option 5, a menu item D appears which gives you
the opportunity to turn off dot-differencing so that complete ancestral
sequences are shown. If the inferred state is a "?",
there will be multiple
equally-parsimonious assignments of states; the user must work these out for
themselves by hand.
If option 6 is left in its default state the trees
found will be written to a tree file, so that they are available to be used
in other programs.
If the U (User Tree) option is used and more than one tree is supplied, the
program also performs a statistical test of each of these trees against the
best tree. This test, which is a version of the test proposed by
Alan Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences
due to Kishino and Hasegawa (1989), and
uses the mean and variance of
step differences between trees, taken across sites. If the mean
is more than 1.96 standard deviations different then the trees are declared
significantly different. The program
prints out a table of the steps for each tree, the differences of
each from the best one, the variance of that quantity as determined by
the step differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
It is important to understand that the test assumes that all the discrete
characters are evolving independently, which is unlikely to be true for
many suites of morphological characters.
Option 6 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined
trees are written to the output tree file.
Discrete character parsimony algorithm, version 3.6
One most parsimonious tree found:
+Epsilon
+---------3
+----2 +--------------Delta
| |
| +Gamma
|
1---------Beta
|
+Alpha
requires a total of 8.000
between and length
------- --- ------
1 2 0.166667
2 3 0.333333
3 Epsilon 0.000000
3 Delta 0.500000
2 Gamma 0.000000
1 Beta 0.333333
1 Alpha 0.000000
steps in each site:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0| 1 1 1 2 2 1
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
1 110110
1 2 yes .0....
2 3 yes 0.1...
3 Epsilon no ......
3 Delta yes ...001
2 Gamma no ......
1 Beta yes ...00.
1 Alpha no ......
This program carries out the Fitch-Margoliash and Least Squares methods,
plus a variety of others of the same family, with the assumption that all
tip species are contemporaneous, and that there is an evolutionary clock
(in effect, a molecular clock). This means that branches of the tree cannot
be of arbitrary length, but are constrained so that the total
length from the root of
the tree to any species is the same. The quantity minimized is the same
weighted sum of squares described in the Distance Matrix Methods documentation
file.
The options are set using the menu:
Fitch-Margoliash method with contemporary tips, version 3.6a3
Settings for this run:
D Method (F-M, Minimum Evolution)? Fitch-Margoliash
U Search for best tree? Yes
P Power? 2.00000
- Negative branch lengths allowed? No
L Lower-triangular data matrix? No
R Upper-triangular data matrix? No
S Subreplicates? No
J Randomize input order of species? No. Use input order
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
Most of the options are described in the Distance Matrix Programs documentation
file.
The D (methods) option allows choice between the Fitch-Margoliash
criterion and the Minimum Evolution method (Kidd and Sgaramella-Zonta, 1971;
Rzhetsky and Nei, 1993). Minimum Evolution (not to be confused with
parsimony) uses the Fitch-Margoliash criterion to fit branch lengths to each
topology, but then chooses topologies based on their total branch length
(rather than the goodness of fit sum of squares). There is no
constraint on negative branch lengths in the Minimum Evolution method;
it sometimes gives rather strange results, as it can like solutions
that have large negative branch lengths, as these reduce the total
sum of branch lengths!
Note that the User Trees (used by option U) must be
rooted trees (with a bifurcation at their base). If you take a user
tree from FITCH and try to evaluate it in KITSCH, it must first be
rooted. This can be done using RETREE. Of the options
available in FITCH, the O option is
not available, as KITSCH estimates a rooted tree which cannot be
rerooted, and the G option is not
available, as global rearrangement is the default condition anyway. It
is also not possible to specify that specific branch lengths of a user tree
be retained when it is read into KITSCH, unless all of them are present. In
that case the tree should be properly clocklike. Readers who wonder why
we have not provided the feature of holding some of the user tree branch
lengths constant while iterating others are invited to tell us how they
would do it. As you consider particular possible patterns of branch
lengths you will find that the matter is not at all simple.
If you use a User Tree (option U) with branch lengths with KITSCH, and the
tree is not clocklike, when two branch lengths give conflicting positions
for a node, KITSCH will use the first of them and ignore the other. Thus
the user tree:
((A:0.1,B:0.2):0.4,(C:0.06,D:0.01):43);
is nonclocklike, so it will be treated as if it were actually the tree:
((A:0.1,B:0.1):0.4,(C:0.06,D:0.06):44);
The input is exactly the same as described in the Distance Matrix Methods
documentation file. The output is a rooted tree, together with the sum of
squares, the number of tree topologies searched, and, if the power P is at
its default value of 2.0, the Average Percent Standard Deviation is also
supplied. The lengths of the branches of the tree are given in a table,
that also shows for each branch the time at the upper end of the
branch. "Time" here really means cumulative branch length from the root, going
upwards (on the printed diagram, rightwards). For each branch, the
"time" given is for the node at the right (upper) end of the branch. It
is important to realize that the branch lengths are not exactly proportional to
the lengths drawn on the printed tree diagram! In particular, short
branches are exaggerated in the length on that diagram so that they are
more visible.
The method may be considered as providing an estimate of the
phylogeny. Alternatively, it can be considered as a phenetic clustering of
the tip species. This method minimizes an objective function, the sum of
squares,
not only setting the levels of the clusters so as to do so, but rearranging
the hierarchy of clusters to try to find alternative clusterings that
give a lower overall sum of squares. When the power option P is set to a
value of P = 0.0, so that we are minimizing a simple sum of squares
of the differences between the observed distance matrix and the expected one,
the method is very close in spirit to Unweighted Pair Group Arithmetic Average
Clustering (UPGMA), also called Average-Linkage Clustering. If the topology of
the tree is fixed and there turn out to be no branches of negative length, its
result should be the same as UPGMA in that case. But since it tries
alternative topologies and (unless
the N option is set) it combines nodes that otherwise could result in a reversal
of levels, it is possible for it to give a different, and better, result than
simple sequential clustering. Of course UPGMA itself is available as an
option in program NEIGHBOR.
The U (User Tree) option requires a bifurcating tree, unlike FITCH, which
requires an unrooted tree with a trifurcation at its base. Thus the tree
shown below would be written:
((D,E),(C,(A,B)));
If a tree with a trifurcation at the base is by mistake fed into the U option
of KITSCH then some of its species (the entire rightmost furc, in fact) will be
ignored and too small a tree read in. This should result in an error message
and the program should stop. It is important to understand the
difference between the User Tree formats for KITSCH and FITCH. You may want
to use RETREE to convert a user tree that is suitable for FITCH into one
suitable for KITSCH or vice versa.
An important use of this method will be to do a formal statistical test of
the evolutionary clock hypothesis. This can be done by comparing the sums
of squares achieved by FITCH and by KITSCH, BUT SOME CAVEATS ARE
NECESSARY. First, the assumption is that the observed distances are truly
independent, that no original data item contributes to more than one of them
(not counting the two reciprocal distances from i to j and from j to i). THIS
WILL NOT HOLD IF THE DISTANCES ARE OBTAINED FROM GENE FREQUENCIES, FROM
MORPHOLOGICAL CHARACTERS, OR FROM MOLECULAR SEQUENCES. It may be invalid even
for immunological distances and levels of DNA hybridization, provided that the
use of common standard for all members of a row or column allows an error in
the measurement of the standard to affect all these distances
simultaneously. It will also be invalid if the numbers have been collected in
experimental groups, each measured by taking differences from a common standard
which itself is measured with error. Only if the numbers in different cells
are measured from independent standards can we depend on the statistical
model. The details of the test and the assumptions are discussed in my review
paper on distance methods (Felsenstein, 1984a). For further and sometimes
irrelevant controversy on these matters see the papers by Farris (1981,
1985, 1986) and myself (Felsenstein, 1986, 1988b).
A second caveat is that the distances must be expected to rise linearly with
time, not according to any other curve. Thus it may be necessary to transform
the distances to achieve an expected linearity. If the distances have an upper
limit beyond which they could not go, this is a signal that linearity may
not hold. It is also VERY important to choose the power P at a value
that results in the standard deviation of the variation of the observed from the
expected distances being the P/2-th power of the expected distance.
To carry out the test, fit the same data with both FITCH and KITSCH,
and record the two sums of squares. If the topology has turned out the
same, we have N = n(n-1)/2 distances which have been fit with
2n-3
parameters in FITCH, and with n-1 parameters in KITSCH. Then the
difference between S(K) and S(F) has d1 = n-2
degrees of freedom. It is
statistically independent of the value of S(F), which has
d2 = N-(2n-3)
degrees of freedom. The ratio of mean squares
[S(K)-S(F)]/d1
----------------
S(F)/d2
should, under the
evolutionary clock, have an F distribution with n-2 and
N-(2n-3) degrees of
freedom respectively. The test desired is that the F ratio is in the upper
tail (say the upper 5%) of its distribution. If the S (subreplication)
option is in
effect, the above degrees of freedom must be modified by noting that
N is not n(n-1)/2 but is the sum of the numbers of replicates of all
cells in the distance matrix read in, which may be either square or
triangular. A further explanation of the
statistical test of the clock is given in a paper of mine (Felsenstein, 1986).
The program uses a similar tree construction method to the other programs
in the package and, like them, is not guaranteed to give the best-fitting
tree. The assignment of the branch lengths for a given topology is a
least squares fit, subject to the constraints against negative branch lengths,
and should not be able to be improved upon. KITSCH runs more quickly than
FITCH.
The constant
available for modification at the beginning of the program is
"epsilon", which defines a small quantity needed in
some of the calculations. There is no feature saving multiply trees
tied for best,
because exact ties are not expected, except in cases where it should be
obvious from the tree printed out what is the nature of the tie (as when an
interior branch is of length zero).
This program implements a maximum likelihood method for restriction sites
data (not restriction fragment data). This program is one of the slowest
programs in this package, and can be very tedious to run. It is
possible to have the program search for the maximum likelihood tree.
It will be more practical for some users (those that do not have
fast machines) to use the U (User Tree)
option, which takes less run time, optimizing branch lengths and computing
likelihoods for particular tree topologies suggested by the user. The
model used here is essentially identical to that used by Smouse and Li (1987)
who give explicit expressions for computing the likelihood for three-species
trees. It does not place prior probabilities on trees as they do. The present
program extends their approach to multiple species by
a technique which, while it does not give explicit expressions for likelihoods,
does enable their computation and the iterative improvement of branch
lengths. It also allows for multiple restriction enzymes. The algorithm
has been described in a paper (Felsenstein, 1992). Another relevant
paper is that of DeBry and Slade (1985).
The assumptions of the present model are:
Each restriction site evolves independently.
Different lineages evolve independently.
Each site undergoes substitution at an expected rate which we specify.
Substitutions consist of replacement of a nucleotide by one of the
other three nucleotides, chosen at random.
Note that if the existing base is, say, an A, the chance of it being
replaced by a G is 1/3, and so is the chance that it is replaced by
a T. This means that there can be no difference in the (expected)
rate of transitions and transversions. Users who are upset at this
might ponder the fact that a version allowing different rates of
transitions and transversions would run an estimated 16 times
slower. If it also allowed for unequal frequencies of the four bases,
it would run about 300,000 times slower! For the moment, until a better
method is available, I guess I'll stick with this one!
INPUT FORMAT AND OPTIONS
Subject to these assumptions, the program is an approximately
correct maximum likelihood method. The
input is fairly standard, with one addition. As usual the first line of the
file gives the number of species and the number of sites, but there is also
a third number, which is the number of different restriction enzymes that were
used to detect the restriction sites. Thus a data set with 10 species and
35 different sites, representing digestion with 4 different enzymes, would
have the first line of the data file look like this:
10 35 4
The first line of the data file will also contain a letter W following
these numbers (and separated from them by a space) if the Weights option
is being used. As with all programs using the weights option, a line or lines
must then follow, before the data, with the weights for each site.
The site data are in standard form. Each species starts with a species name
whose maximum length is given by the constant "nmlngth"
(whose value in the
program as distributed is 10 characters). The name should, as usual, be padded
out to that length with blanks if necessary. The sites data then follows, one
character per site (any blanks will
be skipped and ignored). Like the DNA and protein sequence data, the
restriction sites data may be either in the "interleaved" form or the
"sequential" form. Note that if you are analyzing restriction sites
data with the programs DOLLOP or MIX or other discrete character
programs, at the moment those programs do not use the "aligned" or
"interleaved" data format. Therefore you may want to avoid that format
when you have restriction sites data that you will want to feed into
those programs.
The presence of a site is indicated by a "+" and the absence by a "-". I have
also allowed the use of "1" and "0" as synonyms for "+" and "-", for
compatibility with MIX and DOLLOP which do not allow "+" and "-". If the
presence of
the site is unknown (for example, if the DNA containing it has been deleted so
that one
does not know whether it would have contained the site) then the state "?" can
be used to indicate that the state of this site is unknown.
User-defined trees may follow the
data in the usual way. The trees must be unrooted, which means that at their
base they must have a trifurcation.
The options are selected by a menu, which looks like this:
Restriction site Maximum Likelihood method, version 3.6
Settings for this run:
U Search for best tree? Yes
A Are all sites detected? No
S Speedier but rougher analysis? Yes
G Global rearrangements? No
J Randomize input order of sequences? No. Use input order
L Site length? 6
O Outgroup root? No, use as outgroup species 1
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
The U, J, O, M, and 0 options are the usual ones, described in the main
documentation file. The user trees for option U are read from a file whose
default name is intree. The I option selects between Interleaved and
Sequential input data formats, and is described in the documentation file for
the molecular sequences programs.
The G
(global search) option causes, after the last species is added to the tree,
each possible group to be removed and re-added. This improves the result,
since the position of every species is reconsidered. It approximately triples
the run-time of the program.
The two options specific to this program are the A, and L options. The L
(Length) option allows the user to specify the length in bases of the
restriction sites. Allowed values are 1 to 8 (the
constant "maxcutter" in file phylip.h
controls the maximum allowed value). At the
moment the program assumes that all sites have the same length (for example,
that all enzymes are 6-base-cutters). The default value for this parameter is
6, which will be used if the L option is not invoked. A desirable future
development for the package would be allowing the L parameter to be different
for every site. It would also be desirable to allow for ambiguities in the
recognition site, since some enzymes recognize 2 or 4 sequences. Both of these
would require fairly complicated programming or else slower execution times.
The A (All) option specifies that all sites are detected, even those for which
all of the species have the recognition sequence absent (character state
"-"). The default condition is that it is assumed that such sites will not
occur in the data. The likelihood computed when the A option is not used is
the probability of the pattern of sites given that tree and conditional on the
pattern not being all absences. This will be realistic for most data, except
for cases in which the data are extracted from sites data for a larger number
of species, in which case some of the site positions could have all absences in
the subset of species. In such cases an effective way of analyzing the data
would be to omit those sites and not use the A option, as such positions, even
if not absolutely excluded, are nevertheless less likely than random to have
been incorporated in the data set.
The W (Weights) option, which is invoked in the input file rather than in
the menu, allows the user to select a subset of sites to
be analyzed. It is invoked in the usual way, except that only weights
0 and 1 are allowed. If the W option is not used, all sites will be
analyzed. If the Weights option is used, there must be a W in the first
line of the input file.
OUTPUT FORMAT
The output starts by giving the number of species, and the number of sites. If
the default condition is used instead of the A option the program states that
it is assuming that sites absent in all species have been omitted. The value
of the site length (6 bases, for example) is also given.
If option 2 (print out data) has been selected,
there then follow the restriction site sequences, printed in
groups of ten sites. The trees found are printed as an unrooted
tree topology (possibly rooted by outgroup if so requested). The
internal nodes are numbered arbitrarily for the sake of
identification. The number of trees evaluated so far and the log
likelihood of the tree are also given.
A table is printed
showing the length of each tree segment, as well as (very) rough confidence
limits on the length. As with DNAML, if a confidence limit is
negative, this indicates that rearrangement of the tree in that region
is not excluded, while if both limits are positive, rearrangement is
still not necessarily excluded because the variance calculation on which
the confidence limits are based results in an underestimate, which makes
the confidence limits too narrow.
In addition to the confidence limits,
the program performs a crude Likelihood Ratio Test (LRT) for each
branch of the tree. The program computes the ratio of likelihoods with and
without this branch length forced to zero length. This done by comparing the
likelihoods changing only that branch length. A truly correct LRT would
force that branch length to zero and also allow the other branch lengths to
adjust to that. The result would be a likelihood ratio closer to 1. Therefore
the present LRT will err on the side of being too significant.
One should also
realize that if you are looking not at a previously-chosen branch but at all
branches, that you are seeing the results of multiple tests. With 20 tests,
one is expected to reach significance at the P = .05 level purely by
chance. You should therefore use a much more conservative significance level,
such as .05 divided by the number of tests. The significance of these tests
is shown by printing asterisks next to
the confidence interval on each branch length. It is important to keep
in mind that both the confidence limits and the tests
are very rough and approximate, and probably indicate more significance than
they should. Nevertheless, maximum likelihood is one of the few methods that
can give you any indication of its own error; most other methods simply fail to
warn the user that there is any error! (In fact, whole philosophical schools
of taxonomists exist whose main point seems to be that there isn't any
error, that the "most parsimonious" tree is the best tree by definition and
that's that).
The log likelihood printed out with the final tree can be used to perform
various likelihood ratio tests. Remember that testing one tree topology
against another is not a simple matter, because two different tree topologies
are not hypotheses that are
nested one within the other. If the trees differ by only one branch
swap, it seems to be conservative to test the difference between their
likelihoods with one degree of freedom, but other than that little is known and
more work on this is needed.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the
rates at different sites, the
program also performs a statistical test of each of these trees against the
one with highest likelihood. If there are two user trees, the test
done is one which is due to Kishino and Hasegawa (1989), a version
of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of
log-likelihood differences between trees, taken across sites. If the two
trees' means are more than 1.96 standard deviations different
then the trees are
declared significantly different. This use of the empirical variance of
log-likelihood differences is more robust and nonparametric than the
classical likelihood ratio test, and may to some extent compensate for the
any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods across
sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the highest log-likelihood exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the log-likelihoods of each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the log-likelihood differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
The branch lengths printed out are scaled in terms of expected numbers of
base substitutions, not counting replacements of a base by itself. Of course,
when a branch is twice as long this does not mean that there will be twice as
much net change expected along it, since some of the changes occur in the same
site and overlie or even reverse each other. Confidence limits on the branch
lengths are also given. Of course a negative value of the branch length is
meaningless, and a confidence limit overlapping zero simply means that the
branch length is not necessarily significantly different from zero. Because of
limitations of the numerical algorithm, branch length estimates of zero will
often print out as small numbers such as 0.00001. If you see a branch length
that small, it is really estimated to be of zero length.
Another possible source of confusion is the existence of negative values for
the log likelihood. This is not really a problem; the log likelihood is not a
probability but the logarithm of a probability, and since probabilities never
exceed 1.0 this logarithm will typically be negative. The log likelihood is
maximized by being made more positive: -30.23 is worse than -29.14. The log
likelihood will not always be negative since a combinatorial constant has been
left out of the expression for the likelihood. This does not affect the tree
found or the likelihood ratios (or log likelihood differences) between trees.
THE ALGORITHM
The program uses a Newton-Raphson algorithm to update one branch length at a
time. This is faster than the EM algorithm which was described in my
paper on restriction sites maximum likelihood (Felsenstein, 1992). The
likelihood that is being
maximized is the same one used by Smouse and Li (1987) extended for multiple
species.
moving down on the likelihood surface. You may have to "tune" the value of
extrapol to suit your data.
PROGRAM CONSTANTS
The constants include "maxcutter" (set in phylip.h),
the maximum length of an enzyme
recognition site. The memory used by the program will be approximately
proportional to this value, which is 8 in the distribution copy.
The program also uses constants
"iterations" and "smoothings", and decreasing "epsilon". Reducing
"iterations" and "smoothings" or increasing "epsilon"
will result in faster execution but a worse result. These values will
not usually have to be changed.
The program spends most of its time doing real arithmetic. The algorithm, with
separate and independent computations
occurring at each site, lends itself readily to parallel processing.
A feature of the algorithm is that it saves time by recognizing sites at which
the pattern of presence/absence is the same, and does that computation only
once. Thus if we have only four species but a large number of sites, there are
only about (ignoring ambiguous bases) 16 different patterns of presence/absence
(2 x 2 x 2 x 2) that can occur. The program automatically counts
occurrences of each and does the computation for each pattern only once, so
that it only needs to do as much computation as would be needed with at most
16 sites, even though the number of sites is actually much larger. Thus
the program will run very effectively with few species and many sites.
PAST AND FUTURE OF THE PROGRAM
This program was developed by modifying DNAML version 3.1 and also adding
some of the modifications that were added to DNAML version 3.2, with which
it shares many of its data structures and much of its strategy. Version
3.6 changed from EM iterations of branch lengths, which involved arbitrary
extrapolation factors, to the Newton-Raphson algorithm, which improved the
speed of the program (though only from "very slow" to "slow").
There are a number of obvious directions in which the program needs to be
modified in the future. Extension to allow for different rates of transition
and transversion is straightforward, but would slow down the program
considerably, as I have mentioned above. I have not included in the program
any provision for saving and printing out
multiple trees tied for highest likelihood, in part because an exact tie is
unlikely.
CONSENSE reads a file of computer-readable trees and prints
out (and may also write out onto a file) a consensus tree. At the moment
it carries out a family of consensus tree methods called the
Ml
methods (Margush and McMorris, 1981). These include strict consensus and
majority rule consensus. Basically the
consensus tree consists of monophyletic groups
that occur as often as possible in the data. If a group occurs in more than
a fraction l of all the input trees it will definitely
appear in the consensus tree.
The tree printed out has at each fork a number indicating how many times the
group which consists of the species to the right of (descended from) the fork
occurred. Thus if we read in 15 trees and find that a fork has the number
15, that group occurred in all of the trees. The strict consensus tree
consists of all groups that occurred 100% of the time, the rest of the
resolution being ignored. The tree printed out here includes groups down
to 50%, and below it until the tree is fully resolved.
The majority rule consensus tree consists of all groups that occur more than
50% of the time. Any other percentage level between 50% and 100% can also
be used, and that is why the program in effect
carries out a family of methods. You
have to decide on the percentage level, figure out for yourself what number
of occurrences that would be (e.g. 15 in the above case for 100%), and
resolutely ignore any group below that number. Do not use numbers at or below
50%, because some groups occurring (say) 35% of the time will not be shown
on the tree. The collection of all groups that occur 35% or more of the
time may include two groups that are mutually self contradictory and cannot
appear in the same tree. In this program, as the default method I have
included groups that occur
less than 50% of the time, working downwards in their frequency of occurrence,
as long as they continue to resolve the tree and do not contradict more
frequent groups. In this respect the method is similar to the Nelson consensus
method (Nelson, 1979) as explicated by Page (1989) although it is not identical
to it.
The program can also carry out Strict consensus, Majority Rule consensus
without the extension which adds groups until the tree is fully
resolved, and other members of the Ml family, where the
user supplied the fraction of times the group must appear in the input
trees to be included in the consensus tree.
For the moment the program cannot carry out any other
consensus tree method, such as Adams consensus (Adams, 1972, 1986) or methods
based on
quadruples of species (Estabrook, McMorris, and Meacham, 1985).
INPUT, OUTPUT, AND OPTIONS
Input is a tree file (called intree)
which contains a series of trees in the Newick
standard form -- the form used when many of the programs in this package
write out tree files. Each tree starts on a new line. Each tree can have
a weight, which is a real number and is located in comment brackets "["
and "]" just before the final ";" which
ends the description of the tree. When the input trees have weights
(like [0.01000]) then the total number of trees will be the total of those
weights, which is often a number like 1.00. When the a tree doesn't have
a weight it will each be assigned a weight of 1. This means that when we have
tied trees (as from a parsimony program) three alternative tied trees will
be counted as if each was 1/3 of a tree.
Note that this program can correctly
read trees whether or not they are bifurcating: in fact they can be
multifurcating at any level in the tree.
The options are selected from a menu, which looks like this:
Majority-rule and strict consensus tree program, version 3.6
Settings for this run:
C Consensus type (strict, MR, MRe, Ml) Majority Rule (extended)
O Outgroup root: No, use as outgroup species 1
R Trees to be treated as Rooted: No
T Terminal type (IBM PC, ANSI, none): none
1 Print out the sets of species: Yes
2 Print indications of progress of run: Yes
3 Print out tree: Yes
4 Write out trees onto tree file: Yes
Are these settings correct? (type Y or the letter for one to change)
Option C (Consensus method) selects which of four methods the
program uses. The program defaults to using the extended Majority
Rule method. Each time the C option is chosen the program moves on
to another method, the others being in order Strict, Majority Rule,
and Ml. Here are descriptions of the methods. In each
case the fraction of times a set appears among the input trees
is counted by weighting by the weights of the trees (the numbers
like [0.6000] that appear at the ends of trees in some
cases).
Strict
A set of species must appear in all input trees
to be included in the strict consensus tree.
Majority Rule (extended)
Any set of species that appears
in more than 50% of the trees is included. The program then
considers the other sets of species in order of the frequency with
which they have appeared, adding to the consensus tree any which are
compatible with it until the tree is fully resolved. This is the
default setting.
Ml
The user is asked for a fraction between
0.5 and 1, and the program then includes in the consensus tree any
set of species that occurs among the input trees more than that
fraction of then time. The Strict consensus and the Majority Rule
consensus are extreme cases of the Ml consensus, being
for fractions of 1 and 0.5 respectively.
Majority Rule
A set of species is included in the
consensus tree if it is present in more than half of the
input trees.
Option R (Rooted) toggles between the default assumption that the input trees
are unrooted trees and the selection that
specifies that the tree is to be treated as a rooted tree and not
re-rooted. Otherwise the tree will be treated as outgroup-rooted and will
be re-rooted automatically at the first species encountered on the first
tree (or at a species designated by the Outgroup option).
Option O is the usual Outgroup rooting option. It is in effect only if
the Rooted option selection is not in effect. The trees will be re-rooted
with a species of your choosing. You will be asked for the number of the
species that is to be the outgroup. If we want to outgroup-root the tree on
the line leading to a
species which appears as the third species (counting left-to-right) in the
first computer-readable tree in the input file, we would invoke select
menu option O and specify species 3.
Output is a list of the species (in the order in which they appear in the
first tree, which is the numerical order used in the program), a list
of the subsets that appear in the consensus tree, a list of those that
appeared in one or another of the individual
trees but did not occur frequently enough to get into the consensus tree,
followed by a diagram showing the consensus tree. The lists of subsets
consists of a row of symbols, each either "." or "*". The species
that are in the set are marked by "*". Every ten species there is
a blank, to help you keep track of the alignment of columns. The
order of symbols corresponds to the order of species in the species
list. Thus a set that consisted of the second, seventh, and eighth out
of 13 species would be represented by:
.*....**.. ...
Note that if the trees are unrooted the final tree will have one group,
consisting of every species except the Outgroup (which by default is the
first species encountered on the first tree), which always appears. It
will not be listed in either of the lists of sets, but it will be shown in
the final tree as occurring all of the time. This is hardly surprising:
in telling the program that this species is the outgroup we have specified
that the set consisting of all of the others is always a monophyletic set. So
this is not to be taken as interesting information, despite its dramatic
appearance.
Option 2 in the menu gives you the option of turning off the writing of
these sets into the output file. This may be useful if you are primarily
interested in getting the tree file.
Option 3 is the usual tree file option. If this is on (it is by default)
then the final tree will be written onto an output tree file (whose default
name is "outtree"). Note that the lengths on the tree on the output tree file
are not branch lengths but the number of times that
each group appeared in the input trees. This
number is the sum of the weights of the trees in which it appeared, so that
if there are 11 trees, ten of them having weight 0.1 and one weight 1.0,
a group that appeared in the last tree and in 6 others would be shown as
appearing 1.6 times and its branch length will be 1.6.
CONSTANTS
The program uses the consensus tree algorithm originally designed for
the bootstrap programs. It is quite fast, and execution time is unlikely
to be limiting for you (assembling the input file will be much more of a
limiting step). In the future, if possible, more consensus tree methods
will be incorporated (although the current methods are the ones needed
for the component analysis of bootstrap estimates of phylogenies, and in
other respects I also think that the
present ones are among the best).
Majority-rule and strict consensus tree program, version 3.6
Species in order:
A
B
H
D
J
G
E
F
I
C
Sets included in the consensus tree
Set (species in order) How many times out of 9.00
.......**. 9.00
..******** 9.00
..***....* 6.00
..****.*** 6.00
..***..... 6.00
..*.*..... 4.00
..***..*** 2.00
Sets NOT included in consensus tree:
Set (species in order) How many times out of 9.00
.....**... 3.00
.....****. 3.00
..**...... 3.00
.....***** 3.00
..*.****** 2.00
.....*.**. 2.00
..****...* 2.00
....****** 2.00
...******* 1.00
Majority rule consensus (extended to resolve tree)
CONSENSUS TREE:
the numbers at the forks indicate the number
of times the group consisting of the species
which are to the right of that fork occurred
among the trees, out of 9.00 trees
+-------------------------------------------------------A
|
| +-----------------------------------------E
| |
| | +------I
| | +----------------9.0-|
| | | +------F
| +--9.0-| |
| | | +--2.0-| +-------------D
| | | | | +--6.0-|
| | | | | | | +------J
| | | | +--6.0-| +--4.0-|
+------| +--6.0-| | +------H
| | |
| | +--------------------C
| |
| +----------------------------------G
|
+------------------------------------------------B
remember: this is an unrooted tree!
This program implements the maximum likelihood method for protein amino
acid sequences under the constraint that the trees estimated must be
consistent with a molecular clock. The molecular clock is the
assumption that the tips of the tree are all equidistant, in branch
length, from its root. This program is indirectly related to PROML.
It uses the Dayhoff probability model of change between amino acids.
Its algorithmic details are not yet published, but many of them are
similar to DNAMLK.
The assumptions of the model are:
Each position in the sequence evolves independently.
Different lineages evolve independently.
Each position undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of occurrence)
which we specify.
All relevant positions are included in the sequence, not just those that
have changed or those that are "phylogenetically informative".
The probabilities of change between amino acids are given by the
model of Dayhoff (Dayhoff and Eck, 1968; Dayhoff et. al., 1979).
Note the assumption that we are looking at all positions, including those
that have not changed at all. It is important not to restrict attention
to some positions based on whether or not they have changed; doing that
would bias branch lengths by making them too long, and that in turn
would cause the method to misinterpret the meaning of those positions that
had changed.
This program uses a Hidden Markov Model (HMM)
method of inferring different rates of evolution at different amino acid
positions. This
was described in a paper by me and Gary Churchill (1996). It allows us to
specify to the program that there will be
a number of different possible evolutionary rates, what the prior
probabilities of occurrence of each is, and what the average length of a
patch of positions all having the same rate. The rates can also be chosen
by the program to approximate a Gamma distribution of rates, or a
Gamma distribution plus a class of invariant positions. The program computes the
likelihood by summing it over all possible assignments of rates to positions,
weighting each by its prior probability of occurrence.
For example, if we have used the C and A options (described below) to specify
that there are three possible rates of evolution, 1.0, 2.4, and 0.0,
that the prior probabilities of a position having these rates are 0.4, 0.3, and
0.3, and that the average patch length (number of consecutive positions
with the same rate) is 2.0, the program will sum the likelihood over
all possibilities, but giving less weight to those that (say) assign all
positions to rate 2.4, or that fail to have consecutive positions that have the
same rate.
The Hidden Markov Model framework for rate variation among positions
was independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of
rates; we allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant positions.
This feature effectively removes the artificial assumption that all positions
have the same rate, and also means that we need not know in advance the
identities of the positions that have a particular rate of evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each positions (for example, we might want
amino acid positions in the active site of a protein to change more slowly
than other positions. This is done with the categories input file and the
C option. We then specify (using the menu) the relative rates of evolution of
amino acid positions
in the different categories. For example, we might specify that positions
in the active site
evolve at relative rates of 0.2 compared to 1.0 at other positions. If we
are assuming that a particular position maintains a cysteine bridge to another,
we may want to put it in a category of positions (including perhaps the
initial position of the protein sequence which maintains methionine) which
changes at a rate of 0.0.
If both user-assigned rate categories and Hidden Markov Model rates
are allowed, the program assumes that the
actual rate at a position is the product of the user-assigned category rate
and the Hidden Markov Model regional rate. (This may not always make
perfect biological sense: it would be more natural to assume some upper
bound to the rate, as we have discussed in the Felsenstein and Churchill
paper). Nevertheless you may want to use both types of rate variation.
INPUT FORMAT AND OPTIONS
Subject to these assumptions, the program is a
correct maximum likelihood method. The
input is fairly standard, with one addition. As usual the first line of the
file gives the number of species and the number of amino acid positions.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter amino acid code. The sequences must
either be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The options are selected using an interactive menu. The menu looks like this:
Amino acid sequence
Maximum Likelihood method with molecular clock, version 3.6a3
Settings for this run:
U Search for best tree? Yes
P JTT or PAM amino acid change model? Jones-Taylor-Thornton model
C One category of substitution rates? Yes
R Rate variation among sites? constant rate of change
G Global rearrangements? No
W Sites weighted? No
J Randomize input order of sequences? No. Use input order
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
5 Reconstruct hypothetical sequences? No
Are these settings correct? (type Y or the letter for one to change)
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The options U, W, J, O, M, and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
The R (Hidden Markov Model rates) option allows the user to
approximate a Gamma distribution of rates among positions, or a
Gamma distribution plus a class of invariant positions, or to specify how
many categories of
substitution rates there will be in a Hidden Markov Model of rate
variation, and what are the rates and probabilities
for each. By repeatedly selecting the R option one toggles among
no rate variation, the Gamma, Gamma+I, and general HMM possibilities.
If you choose Gamma or Gamma+I the program will ask how many rate
categories you want. If you have chosen Gamma+I, keep in mind that
one rate category will be set aside for the invariant class and only
the remaining ones used to approximate the Gamma distribution.
For the approximation we do not use the quantile method of Yang (1995)
but instead use a quadrature method using generalized Laguerre
polynomials. This should give a good approximation to the Gamma
distribution with as few as 5 or 6 categories.
In the Gamma and Gamma+I cases, the user will be
asked to supply the coefficient of variation of the rate of substitution
among positions. This is different from the parameters used by Nei and Jin
(1990) but
related to them: their parameter a is also known as "alpha",
the shape parameter of the Gamma distribution. It is
related to the coefficient of variation by
CV = 1 / a1/2
or
a = 1 / (CV)2
(their parameter b is absorbed here by the requirement that time is scaled so
that the mean rate of evolution is 1 per unit time, which means that a = b).
As we consider cases in which the rates are less variable we should set a
larger and larger, as CV gets smaller and smaller.
If the user instead chooses the general Hidden Markov Model option,
they are first asked how many HMM rate categories there
will be (for the moment there is an upper limit of 9,
which should not be restrictive). Then
the program asks for the rates for each category. These rates are
only meaningful relative to each other, so that rates 1.0, 2.0, and 2.4
have the exact same effect as rates 2.0, 4.0, and 4.8. Note that an
HMM rate category
can have rate of change 0, so that this allows us to take into account that
there may be a category of amino acid positions that are invariant. Note that
the run time
of the program will be proportional to the number of HMM rate categories:
twice as
many categories means twice as long a run. Finally the program will ask for
the probabilities of a random amino acid position falling into each of these
regional rate categories. These probabilities must be nonnegative and sum to
1. Default
for the program is one category, with rate 1.0 and probability 1.0 (actually
the rate does not matter in that case).
If more than one HMM rate category is specified, then another
option, A, becomes
visible in the menu. This allows us to specify that we want to assume that
positions that have the same HMM rate category are expected to be clustered
so that there is autocorrelation of rates. The
program asks for the value of the average patch length. This is an expected
length of patches that have the same rate. If it is 1, the rates of
successive positions will be independent. If it is, say, 10.25, then the
chance of change to a new rate will be 1/10.25 after every position. However
the "new rate" is randomly drawn from the mix of rates, and hence could
even be the same. So the actual observed length of patches with the same
rate will be a bit larger than 10.25. Note below that if you choose
multiple patches, there will be an estimate in the output file as to
which combination of rate categories contributed most to the likelihood.
Note that the autocorrelation scheme we use is somewhat different
from Yang's (1995) autocorrelated Gamma distribution. I am unsure
whether this difference is of any importance -- our scheme is chosen
for the ease with which it can be implemented.
The C option allows user-defined rate categories. The user is prompted
for the number of user-defined rates, and for the rates themselves,
which cannot be negative but can be zero. These numbers, which must be
nonnegative (some could be 0),
are defined relative to each other, so that if rates for three categories
are set to 1 : 3 : 2.5 this would have the same meaning as setting them
to 2 : 6 : 5.
The assignment of rates to amino acid positions
is then made by reading a file whose default name is "categories".
It should contain a string of digits 1 through 9. A new line or a blank
can occur after any character in this string. Thus the categories file
might look like this:
122231111122411155
1155333333444
With the current options R, A, and C the program has a good
ability to infer different rates at different positions and estimate
phylogenies under a more realistic model. Note that Likelihood Ratio
Tests can be used to test whether one combination of rates is
significantly better than another, provided one rate scheme represents
a restriction of another with fewer parameters. The number of parameters
needed for rate variation is the number of regional rate categories, plus
the number of user-defined rate categories less 2, plus one if the
regional rate categories have a nonzero autocorrelation.
The G (global search) option causes, after the last species is added to
the tree, each possible group to be removed and re-added. This improves the
result, since the position of every species is reconsidered. It
approximately triples the run-time of the program.
The User tree (option U) is read from a file whose default name is
intree. The trees can be multifurcating. This allows us to test the
hypothesis that a given branch has zero length.
If the U (user tree) option is chosen another option appears in
the menu, the L option. If it is selected,
it signals the program that it
should take any branch lengths that are in the user tree and
simply evaluate the likelihood of that tree, without further altering
those branch lengths. In the case of a clock, if some branches have lengths
and others do not, the program does not estimate the lengths of those that
do not have lengths given in the user tree. If any of the branches
do not have lengths, the program re-estimates the lengths of all of them.
This is done because estimating some and not others is hard in the
case of a clock.
The W (Weights) option is invoked in the usual way, with only weights 0
and 1 allowed. It selects a set of positions to be analyzed, ignoring the
others. The positions selected are those with weight 1. If the W option is
not invoked, all positions are analyzed.
The Weights (W) option
takes the weights from a file whose default name is "weights". The weights
follow the format described in the main documentation file.
The M (multiple data sets) option will ask you whether you want to
use multiple sets of weights (from the weights file) or multiple data sets
from the input file.
The ability to use a single data set with multiple weights means that
much less disk space will be used for this input data. The bootstrapping
and jackknifing tool Seqboot has the ability to create a weights file with
multiple weights. Note also that when we use multiple weights for
bootstrapping we can also then maintain different rate categories for
different positions in a meaningful way. You should not use the multiple
data sets option without using multiple weights, you should not at the
same time use the user-defined rate categories option (option C).
The algorithm used for searching among trees is faster than it was in
version 3.5, thanks to using a technique invented by David Swofford
and J. S. Rogers. This involves not iterating most branch lengths on most
trees when searching among tree topologies, This is of necessity a
"quick-and-dirty" search but it saves much time.
OUTPUT FORMAT
The output starts by giving the number of species, the number of amino
acid positions.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of positions is printed, as well
as the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the menu
option to print them out, with the base sequences printed in
groups of ten amino acids. The
trees found are printed as a rooted
tree topology. The
internal nodes are numbered arbitrarily for the sake of
identification. The number of trees evaluated so far and the log
likelihood of the tree are also given. The branch lengths in the diagram are
roughly proportional to the estimated branch lengths, except that very short
branches are printed out at least three characters in length so that the
connections can be seen.
A table is printed
showing the length of each tree segment, and the time (in units of
expected amino acid substitutions per position) of each fork in the tree,
measured from the root of the tree. I have not attempted in include
code for approximate confidence limits on branch points, as I have done
for branch lengths in PROML, both because of the extreme crudeness of
that test, and because the variation of times for different forks would be
highly correlated.
The log likelihood printed out with the final tree can be used to perform
various likelihood ratio tests. One can, for example, compare runs with
different values of the relative rate of change in the active site and in
the rest of the protein to determine
which value is the maximum likelihood estimate, and what is the allowable range
of values (using a likelihood ratio test, which you will find described in
mathematical statistics books). One could also estimate the base frequencies
in the same way. Both of these, particularly the latter, require multiple runs
of the program to evaluate different possible values, and this might get
expensive.
This program makes possible a (reasonably) legitimate
statistical test of the molecular clock. To do such a test, run PROML
and PROMLK on the same data. If the trees obtained are of the same
topology (when considered as unrooted), it is legitimate to compare
their likelihoods by the likelihood ratio test. In PROML the likelihood
has been computed by estimating 2n-3 branch lengths, if their are n tips
on the tree. In PROMLK it has been computed by estimating n-1 branching
times (in effect, n-1 branch lengths). The difference in the number of
parameters is (2n-3)-(n-1) = n-2. To perform the test take the
difference in log likelihoods between the two runs (PROML should be the
higher of the two, barring numerical iteration difficulties) and double
it. Look this up on a chi-square distribution with n-2 degrees of
freedom. If the result is significant, the log likelihood has been
significantly increased by allowing all 2n-3 branch lengths to be
estimated instead of just n-1, and molecular clock may be rejected.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the
rates at different amino acid positions, the
program also performs a statistical test of each of these trees against the
one with highest likelihood. If there are two user trees, the test
done is one which is due to Kishino and Hasegawa (1989), a version
of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of
log-likelihood differences between trees, taken across amino acid
positions. If the two
trees' means are more than 1.96 standard deviations different
then the trees are
declared significantly different. This use of the empirical variance of
log-likelihood differences is more robust and nonparametric than the
classical likelihood ratio test, and may to some extent compensate for the
any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods across
amino acid positions are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the highest log-likelihood exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the log-likelihoods of each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the log-likelihood differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one. However
the test is not available if we assume that there
is autocorrelation of rates at neighboring positions (option A) and is not
done in those cases.
The branch lengths printed out are scaled in terms of expected numbers of
amino acid substitutions, scaled so that the average rate of
change, averaged over all the positions analyzed, is set to 1.0.
if there are multiple categories of positions. This means that whether or not
there are multiple categories of positions, the expected fraction of change
for very small branches is equal to the branch length. Of course,
when a branch is twice as
long this does not mean that there will be twice as much net change expected
along it, since some of the changes occur in the same position and overlie or
even reverse each
other. The branch length estimates here are in terms of the expected
underlying numbers of changes. That means that a branch of length 0.26
is 26 times as long as one which would show a 1% difference between
the amino acid sequences at the beginning and end of the branch. But we
would not expect the sequences at the beginning and end of the branch to be
26% different, as there would be some overlaying of changes.
Because of limitations of the numerical
algorithm, branch length estimates of zero will often print out as small
numbers such as 0.00001. If you see a branch length that small, it is really
estimated to be of zero length.
Another possible source of confusion is the existence of negative values for
the log likelihood. This is not really a problem; the log likelihood is not a
probability but the logarithm of a probability. When it is
negative it simply means that the corresponding probability is less
than one (since we are seeing its logarithm). The log likelihood is
maximized by being made more positive: -30.23 is worse than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what amino acid position
categories contributed the most to the final likelihood. This combination of
HMM rate categories need not have contributed a majority of the likelihood,
just a plurality. Still, it will be helpful as a view of where the
program infers that the higher and lower rates are. Note that the
use in this calculations of the prior probabilities of different rates,
and the average patch length, gives this inference a "smoothed"
appearance: some other combination of rates might make a greater
contribution to the likelihood, but be discounted because it conflicts
with this prior information. See the example output below to see
what this printout of rate categories looks like.
A second list will also be printed out, showing for each position which
rate accounted for the highest fraction of the likelihood. If the fraction
of the likelihood accounted for is less than 95%, a dot is printed instead.
Option 3 in the menu controls whether the tree is printed out into
the output file. This is on by default, and usually you will want to
leave it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees
which are written onto the output tree file, rather than the trees
printed on the output file. To keep the output file from becoming too
large, it may be wisest to use option 3 to prevent trees being
printed onto the output file.
Option 4 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined
trees are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated
at each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species which
are the input sequences).
The symbol printed out is for the amino acid which accounts for the
largest fraction of the likelihood at that position.
In that table, if a position has an amino acid which
accounts for more than 95% of the likelihood, its symbol printed in capital
letters (W rather than w). One limitation of the current
version of the program is that when there are multiple HMM rates
(option R) the reconstructed amino acids are based on only the single
assignment of rates to positions which accounts for the largest amount of the
likelihood. Thus the assessment of 95% of the likelihood, in tabulating
the ancestral states, refers to 95% of the likelihood that is accounted
for by that particular combination of rates.
PROGRAM CONSTANTS
The constants defined at the beginning of the program include "maxtrees",
the maximum number of user trees that can be processed. It is small (100)
at present to save some further memory but the cost of increasing it
is not very great. Other constants
include "maxcategories", the maximum number of position
categories, "namelength", the length of species names in
characters, and three others, "smoothings", "iterations", and "epsilon", that
help "tune" the algorithm and define the compromise between execution speed and
the quality of the branch lengths found by iteratively maximizing the
likelihood. Reducing iterations and smoothings, and increasing epsilon, will
result in faster execution but a worse result. These values
will not usually have to be changed.
The program spends most of its time doing real arithmetic.
The algorithm, with separate and independent computations
occurring for each pattern, lends itself readily to parallel processing.
PAST AND FUTURE OF THE PROGRAM
This program was developed in version 3.6 by Lucas Mix by combining code
from DNAMLK and from PROML.
CONTENTS OF OUTPUT FILE (with all numerical options on)
(It was run with HMM rates having gamma-distributed rates
approximated by 5 rate categories,
with coefficient of variation of rates 1.0, and with patch length
parameter = 1.5. Two user-defined rate categories were used, one for
the first 6 positions, the other for the last 7, with rates 1.0 : 2.0.
Weights were used, with sites 1 and 13 given weight 0, and all others
weight 1.)
Amino acid sequence
Maximum Likelihood method with molecular clock, version 3.6a3
5 species, 13 sites
Site categories are:
1111112222 222
Sites are weighted as follows:
0111111111 111
Jones-Taylor-Thornton model of amino acid change
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta ..G..C.... ..C
Gamma C.TT.C.T.. C.A
Delta GGTA.TT.GG CC.
Epsilon GGGA.CT.GG CCC
Discrete approximation to gamma distributed rates
Coefficient of variation of rates = 1.000000 (alpha = 1.000000)
State in HMM Rate of change Probability
1 0.264 0.522
2 1.413 0.399
3 3.596 0.076
4 7.086 0.0036
5 12.641 0.000023
Expected length of a patch of sites having the same rate = 1.500
Site category Rate of change
1 1.000
2 2.000
+-----------------Epsilon
+-----------------------------------------4
+--3 +-----------------Delta
! !
--2 +-----------------------------------------------------------Gamma
!
! +--------------------------Beta
+--------------------------------1
+--------------------------Alpha
Ln Likelihood = -138.46858
Ancestor Node Node Height Length
-------- ---- ---- ------ ------
root 2
2 3 0.00010 0.00010
3 4 6.92817 6.92807
4 Epsilon 9.99990 3.07173
4 Delta 9.99990 3.07173
3 Gamma 9.99990 9.99980
2 1 5.47444 5.47444
1 Beta 9.99990 4.52546
1 Alpha 9.99990 4.52546
Combination of categories that contributes the most to the likelihood:
3333333333 333
Most probable category at each site if > 0.95 probability ("." otherwise)
.......... ...
Probable sequences at interior nodes:
node Reconstructed sequence (caps if > 0.95)
2 .AeDesDDdd eSe
3 .AeDesDDDd eSe
4 .GEDssDEDD ESs
Epsilon GGGATCTCGG CCC
Delta GGTATTTCGG CCT
Gamma CATTTCGTCA CAA
1 .AeDEdDDds sSE
Beta AAGGTCGCCA AAC
Alpha AACGTGGCCA AAT
PHYLIPNEW-3.69.650/doc/draw.html 0000664 0001750 0001750 00000123211 07712247475 012675 0000000 0000000
main
DRAWTREE and DRAWGRAM are interactive tree-plotting programs that take a
tree description in a file and read it, and then let you interactively make
various settings and then plot the tree on a laser printer, plotter,
or dot matrix printer. In many cases (with Macintosh or PC graphics,
with X windows, or with a Tektronix-compatible graphics terminal)
you can preview the resulting tree. This allows you to modify the tree
until you like the result, then plot the result. DRAWTREE plots
unrooted trees and DRAWGRAM plots rooted cladograms and phenograms. On
good laser printers or as files for good drawing programs both can produce
fully publishable
results. On dot matrix printers the results look grainy but are good
enough for overhead transparencies or slides for presentations.
These programs are descended from PLOTGRAM and PLOTREE written by
Christopher Meacham. I have incorporated his code for fonts and his
plotter drivers, and in DRAWTREE have used some of his code for drawing
unrooted trees. In both programs I have also included some plotter driver
code by David Swofford, Julian Humphries and George D.F. "Buz" Wilson,
to all of whom I am very grateful. Mostly, however, they consist of my own
code and that of my programmers. The font files are printable-character
recodings of the public-domain Hershey fonts, recoded by Christopher Meacham.
This document will describe the features common to both programs. The
documents for DRAWTREE and DRAWGRAM describe the particular choices you
can make in each of those programs. The Appendix to this documentation file
contains some pieces of C code that can be inserted to make the program
handle another plotting device -- the plotters by Calcomp.
A Short Introduction
To use DRAWTREE and DRAWGRAM, you must have
(1)
The compiled version of the program. If you have not obtained a
version of PHYLIP precompiled for your machine, you will have to take
the source code given here and modify it for your C
compiler and then compile it. This is not too hard: it is discussed below.
(2)
A tree file. Trees are described in the nested-parenthesis notation
used throughout PHYLIP and standardized in an informal meeting of
program authors in Durham, New Hampshire in June, 1986. Trees for
both programs may be either bifurcating or multifurcating, and may
either have or not have branch lengths. Tree files produced by
the PHYLIP programs are in this form. There is further description of the
tree file format later in this document.
(3)
A font file. There are six font files distributed with PHYLIP:
these consist of three Roman, two Italic, and one Russian Cyrillic font,
all from the public-domain
Hershey Fonts, in ASCII readable form. The details of font
representation need not concern you; all you need to do is to copy the
font file corresponding to the font you want into the appropriate
directory under the appropriate file name, and let the program use it.
Or you can let the program ask you for the name of the font file, which
it will do if it does not find one itself.
The six fonts are, respectively, a one- and a two-stroke sans-serif
Roman font, a three-stroke serifed Roman font, a two- and a three-
stroke serifed Italic font, and a two-stroke Cyrillic font for the Russian
language. If this is not clear just try them all. Note that for some
printers several built-in fonts such as Times-Roman and Courier can be used
too.
(4)
A plotting device, and if possible a screen on which you can preview
the plot. The programs work with Postscript-compatible laser printers,
laser printers compatible with the PCL printer language of the Hewlett-Packard
Laserjet series,
IBM PC graphics screens,
the PICT format for the MacDraw drawing program,
the PCX file format for the PC Paintbrush painting program,
the file format for the freeware X-windows drawing programs xfig and
idraw,
the X Bitmap format for X-windows,
plotters including Hewlett-Packard models, dot matrix printers including
models by Epson and Apple, graphics terminals from DEC and Tektronix,
the input format for the freeware ray-tracing (3-dimensional rendering)
programs POV and rayshade,
and, strangest and most wonderful of all,
the Virtual Reality Markup Language (VRML) which is a file format that is
used by freely-available virtual reality programs like Cosmo Player.
You can choose the plotting and previewing
devices from a menu at run time, and these can be different. There are
places in the source code for the program where you can insert code for
a new plotter, should you want to do that.
Once you have all these, the programs should be fairly self explanatory,
particular if you can preview your plots so that you can discover the
meaning of the different options by trying them out.
Once you have a compiled version of the appropriate program, say
DRAWGRAM, and a file called (say) treefile with the tree in it, and
a font file (say font2 which you have copied as a file called
fontfile),
all you do is run the program DRAWGRAM. It should automatically read the
font and tree files, and will allow you to change the graphics devices. Then
it will let you see the options it has chosen, and ask you if you
want to change these. Once you have modified those that you want to,
you can tell it to accept those. The program will then allow you to
preview the tree on your screen, if you have told it that you have
an appropriate graphics screen. After
previewing the tree, the program will want to know whether you are ready to
plot the tree. In Windows you answer this using the File menu of the preview
window. In X Windows and Macintosh systems you can close the preview
window by clicking on its corner. Whether or not you close it, if you
get back to the text window that had the menus, and it accepts typing in
that window, you will be asked whether you want to accept the plot as is.
If you say no, it will once again allow you to change options and
will the allow you to preview the tree again, and so on as many times
as you want. If you say yes, then it will write a file called (say)
plotfile. If you then copy this file to your printer or plotter,
it should result in a beautifully plotted tree. If the final plotting
device is a Macintosh or PC graphics screen, it may not write a plot file
but will plot directly on the screen.
Having read the above, you may be ready to run the program. Below you
Will find more information about representation of trees in the tree
file, on the different kinds of graphics devices supported by this
program, and on how to recompile these programs.
Trees
The Newick Standard for representing trees in computer-readable
form makes use of the correspondence between trees and nested
parentheses, noticed in 1857 by the famous English mathematician Arthur
Cayley. If we have this rooted tree:
A D
\ E /
\ C / /
\ ! / /
\ ! / /
B \!/ /
\ o /
\ ! /
\ ! /
\ ! /
\ ! /
\!/
o
!
!
then in the tree file it is represented by the following sequence of printable
characters, starting at the beginning of the file:
(B,(A,C,E),D);
The tree ends with a semicolon. Everything after the semicolon in the
input file is ignored, including any other trees. The bottommost node
in the tree is an interior node, not a tip. Interior nodes are
represented by a pair of matched parentheses. Between them are
representations of the nodes that are immediately descended from that
node, separated by commas. In the above tree, the immediate
descendants are B, another interior node, and D. The other interior
node is represented by a pair of parentheses, enclosing representations
of its immediate descendants, A, C, and E.
Tips are represented by their names. A name can be any string of
printable characters except blanks, colons, semcolons, parentheses, and
square brackets. In the programs a maximum of 20 characters are allowed
for names: this limit can easily be increased by recompiling the program
and changing the constant
declaration for "MAXNCH" in phylip.h.
Because you may want to include a blank in a name, it is assumed that
an underscore character ("_") stands for a blank; any of these in a
name will be converted to a blank when it is read in. Any name may also
be empty: a tree like
(,(,,),);
is allowed. Trees can be multifurcating at any level (while in many
of the programs multifurcations of user-defined trees are not allowed
or restricted to a trifurcation at the bottommost level, these programs
do make any such restriction).
Branch lengths can be incorporated into a tree by putting a real
number, with or without decimal point, after a node and preceded by
a colon. This represents the length of the branch immediately
below that node. Thus the above tree might have lengths
represented as:
(B:6.0,(A:5.0,C:3.0,E:4.0):5.0,D:11.0);
These programs will be able to make use of this information only if
lengths exist for every branch, except the one at the bottom of
the tree.
The tree starts on the first line of the file, and can continue to
subsequent lines. It is best to proceed to a new line, if at all,
immediately after a comma. Blanks can be inserted at any point except
in the middle of a species name or a branch length.
The above description is of a subset of the Newick Standard. For
example, interior nodes can have names in that standard, but if
any are included the present programs will omit them.
To help you understand this tree representation, here are some trees
in the above form:
The Newick Standard was adopted June 26, 1986 by an informal
committee meeting during the Society for the Study of Evolution
meetings in Durham, New Hampshire and consisting of James Archie,
William H.E. Day, Wayne Maddison, Christopher Meacham, F. James Rohlf,
David Swofford, and myself. A web page describing it will be found
at
http://evolution.gs.washington.edu/phylip/newicktree.html.
Plotter file formats
When the programs run they have a menu which allows you to set (on its
option P) the final plotting device, and another menu which allows you
to set the type of preview screen. The
choices for previewing are a subset of those available for plotting,
and they can be different (the most useful combination will usually be a
previewing graphics screen with a hard-copy plotter or a drawing program
graphics file format).
The plotting device menu looks like this:
type: to choose one compatible with:
L Postscript printer file format
M PICT format (for drawing programs)
J HP Laserjet PCL file format
W MS-Windows Bitmap
F FIG 2.0 drawing program format
A Idraw drawing program format
Z VRML Virtual Reality Markup Language file
P PCX file format (for drawing programs)
K TeKtronix 4010 graphics terminal
X X Bitmap format
V POVRAY 3D rendering program file
R Rayshade 3D rendering program file
H Hewlett-Packard pen plotter (HPGL file format)
D DEC ReGIS graphics (VT240 terminal)
E Epson MX-80 dot-matrix printer
C Prowriter/Imagewriter dot-matrix printer
T Toshiba 24-pin dot-matrix printer
O Okidata dot-matrix printer
B Houston Instruments plotter
U other: one you have inserted code for
Choose one:
Here are the choices, with some comments on each:
Postscript printer file format. This means that the program will
generate a file containing Postscript commands as its plot file. This
can be printed on any Postscript-compatible laser printer. The page
size is assumed to be 8.5 by 11 inches, but as plotting is within this
limit A4 metric paper should work well too. This is the best
quality output option. For this printer the menu options in DRAWGRAM
and DRAWTREE that allow you to select one of the built-in fonts will
work. The programs default to Times-Roman when this plotting option
is in effect. I have been able to use fonts Courier, Times-Roman, and
Helvetica. The others have eluded me for some reason known only to those
who really understand Postscript.
If your laser printer, supposedly
Postcript-compatible, refuses to print the plot file, you might
consider whether the first line of the plot file, which starts with %!
needs to be altered somehow or eliminated. If your Laserwriter is hooked to
a Macintosh it will be necessary
to persuade it to print the plot file.
In recent versions of the Macintosh operating systems this can supposedly
be done by dragging the file icon onto the printer icon on the desktop.
In earlier versions of the MacOS operating system you might have to use
a utility called the Laserwriter Font Utility, which was distributed with the
operating system.
PICT format (for drawing programs). This file format is read by
many drawing programs (an early example was MacDraw). It has support for
some fonts, though if fonts are used the species names can only be drawn
horizontally or vertically, not at other angles in between. The control over
line widths is a bit rough also, so that some lines at different angles
may turn out to be different widths when you do not want them to be.
If you are working on a Macintosh system and have not been able to persuade
it to print a Postscript file, this option may be the best solution, as you
could then read the file into a drawing program and then order it to print
the resulting screen. The PICT file format has font support, and the
default font for this plotting option is set to Times. You can also
choose font attributes for the labels such as Bold, Italic, Outline, and
Shadowed.
HP Laserjet PCL file format. Hewlett-Packard's extremely popular line
of laser printers has been emulated by many other brands of laser printer,
so that this format is compatible with more printers than any other.
One limitation of the PCL4
command language for these printers is that it does not have primitive
operations for drawing arbitrary diagonal lines. This means that they must
be treated by these programs as if they were dot matrix printers with a
great many dots. This makes output files large, and output can be slow.
The user will be asked to choose
the dot resoluton (75, 150, or 300 dots per inch). The 300 dot per inch
setting should not be used if the laser printer's memory is less than
512k bytes. The quality of output is also not as good as it might
be so that the Postscript file format will usually produce better results even
at the same resolution. I am
grateful to Kevin Nixon for inadvertently pointing out that on Laserjets one
does not have to dump the complete bitmap of a page to plot a tree.
MS-Windows Bitmap. This file format is used by most Windows
drawing and paint programs, including Windows Paint which comes with the
Windows operating system. It asks you to choose the height and width
of the graphic image in pixels. For the moment, the image is set to be
a monochrome image which can only be black or white. We hope to change
that soon, but note that by pasting the image into a copy of Paint that
is set to have a color image of the appropriate size, one can get a version
whose color can be changed. Note also that Windows Bitmap files can be
used as "wallpaper" images for the background of a desktop.
IBM PC graphics screens. The code for this in the programs is available
in the precompiled PC executables or if you compile the programs
yourself in C. The graphics modes supported are CGA, EGA, VGA,
Hercules, and AT&T (Olivetti).
This option is also available for previewing plots, and
in either previewing or final plotting it draws directly on the screen
and does not make a plot file.
FIG 2.0 drawing program format. This is the file format of the
free drawing program Xfig, available for X-windows systems on Unix or
Linux systems. Xfig
can be obtained fromhttp://duke.usask.ca/~macphed/soft/fig/
You should also get transfig, which contains the fig2dev program which converts
xfig output to the various printer languages. Transfig is on the same machine
in
The present format
does not write the species labels in fonts recognized by
Xfig but draws them with lines. This often makes the names look rather
bumpy. We hope to change this soon.
Idraw drawing program format. Idraw is a free drawing program for
X windows systems (such as Unix and Linux systems). Its interface is
loosely based on MacDraw, and I find it much more useable than Xfig.
Though it was unsupported for a number of years, it has more recently
been actively supported by Scott Johnston, of
Vectaport, Inc. (http://www.vectaport.com). He has produced, in his ivtools package, a number
of specialized versions of Idraw, and he also distributes the original
Idraw as part of it. Linux executables for all these are available from
Vectaport, or from various archive machines.
The Idraw file format that our programs produce can be read into Idraw, or
can be imported into the other Ivtools programs. The file format saved
from Idraw (or which can be exported from the other Ivtools programs)
is Postscript, and if one does not print directly from Idraw one can
simply send the file to the printer. But the format we produce is missing
some of the header information and will not work directly as a Postscript
file. However if you read it into Idraw and then save it (or import it into
one of the other Ivtools programs and then export it) you will get a Postscript
version that is fully useable.
DRAWGRAM and DRAWTREE have font support in their Idraw file format options.
The default font is Times-Bold but you can also enter the name of any
other font that is supported by your Postscript printer. Idraw labels
can be rotated to any angle.
VRML Virtual Reality Markup Language file. This is by far the most
interesting plotting file format. VRML files describe objects in 3-dimensional
space with lighting on them. A number of freely available "virtual reality
browsers" such as Cosmo Player can read VRML files.
A list of available virtual reality browsers and browser plugins
can be found at http://www.web3d.org/vrml/browpi.htm.
These allow you to
wander around looking at the tree from various angles, including from
behind! At the moment our VRML output is primitive, with labels that
always look the same no matter what angle you look at them from, and
with a "sun" that is always behind you. The tree is made of three-dimensional
tubes but is basically flat. We hope to change these soon. What's
next? Trees whose branches stick out in three dimensions? Animated trees
whose forks rotate slowly?
A video game involving combat among schools of systematists?
PCX file format (for drawing programs). A bitmap format that was
formerly much used on the PC platform, this has been largely superseded by
the Windows Bitmap (BMP) format, but it is still useful. This file format
is simple and is read by many other programs as well. The user must
choose one of three resolutions for the file, 640x480, 800x600, or 1024x768.
The file is a monochrome paint file. Our PCX format is correct but is not
read correctly by versions of Microsoft Paint (PBrush) that are running on
systems that have loaded Word97.
Tektronix 4010 graphics terminal. The plot file will contain commands
for driving the Tektronix series of graphics terminals. Other
graphics terminals were compatible with the Tektronix 4010 and its
immediate descendants. The PCDOS version of the public domain communications
program Kermit, versions 2.30 and later, can emulate a Tektronix
graphics terminal if the command "set terminal tek" is given. Of course
that assumes that you are communicating with another computer. There are
also similar terminal emulation programs for Macintoshes that emulate
Tektronix graphics. On workstations with X windows you can use one option of
the "xterm" utility to create a Tektronix-compatible window. On Sun
workstations there used to be a
Tektronix emulator you can run called "tektool" which can be used to
view the trees. The Tektronix option is also available in our programs
for previewing the plots, in which case the plotting commands will be not be
written into a file but will be sent directly to your terminal.
X Bitmap format. This produces an X-bitmap for the X Windows system
on Unix or Linux systems,
which can be displayed on X screens. You will be asked for the
size of the bitmap (e.g., 16x16, or 256x256, etc.). This format
cannot be printed out without further format conversion but is
usable for backgrounds of windows ("wallpaper"). This can be a very
bulky format if you choose a large bitmap. The bitmap is a structure
that can actually be compiled into a C program (and thus built in to it),
if you should have some reason for doing that.
POVRAY 3D rendering program file. This produces a file for the
free ray-tracing program POVRay (Persistence of Vision Raytracer),
which is available athttp://www.povray.org/.
It shows a tree floating above a flat landscape. The tree is flat but
made out of tubes (as are the letters of the species names). It
casts a realistic shadow across the landscape. lit from over the left
shoulder of the viewer. You will be asked to confirm the colors of the
tree branches, the species names, the background, and the bottom plane.
These default to Blue, Yellow, White, and White respectively.
Rayshade 3D rendering program file. The input format for the
free ray-tracing program "rayshade" which is
available
at http://www-graphics.stanford.edu/~cek/rayshade/rayshade.html
for many kinds of systems. Rayshade
takes files of this format and turns them into color scenes in "raw"
raster format (also called "MTV" format after a raytracing
program of that name). If you get the pbmplus package
(available fromhttp://sourceforge.net/projects/netpbm/).
and compile it on your system
you can use the "mtvtoppm" and "ppmtogif" programs to convert this
into the widely-used GIF raster format. (the pbmplus package will also
allow you to convert into tiff, pcx and many other formats) The
resultant image will show a tree floating above a landscape, rendered
in a real-looking 3-dimensional scene with shadows and illumination.
It is possible to use Rayshade to
make two scenes that together are a stereo pair. When producing
output for Rayshade you will be asked by the DRAWGRAM or DRAWTREE
whether you want to reset the values for the colors you want for the
tree, the species names, the background, and the desired resolution.
Hewlett-Packard pen plotter (HPGL file format).
This means that the program will generate a
file as its plot file which uses the HPGL graphics language. Hewlett-Packard
7470, 7475, and many other plotters are compatible with this. The
paper size is again assumed to be 8.5 by 11 inches (again, A4 should
work well too). It is assumed that there are two pens, a finer one for
drawing names, and the HPGL commands will call for switching between
these. The Hewlett-Packard Laserjet III printer can emulate an HP plotter,
and this feature is included in its PCL5 command language (but not in the
PCL4 command languages of earlier Hewlett-Packard models). As plotters
are now rare the main use of HPGL will be when they are emulated by
laser printers, but other file formats such as PCL and Postscript will be
better choices in those cases.
DEC ReGIS graphics (VT240 terminal). The DEC ReGIS standard is
used by the VT240 and VT340 series terminals by DEC (Digital Equipment
Corporation). There used to be many graphics terminals that emulate the
VT240 or VT340 as well. The DECTerm windows in many versions
of Digital's (now Compaq's) DECWindows windowing system do so.
This option is available in our programs for
previewing trees as well. In preview mode it does not write a plot file
but sends the commands directly to the screen; in final mode it writes a
plot file. In DEC's version of Unix, Ultrix version 4.1 and later,
the windowing system allows DEC ReGIS graphics as a default.
Epson MX-80 dot-matrix printer. This file format is for the dot-matrix
printers by Epson (starting with the MX80 and continuing on to many other
models), as well as the IBM Graphics printers. The code here plots in
double-density graphics mode. Many of the later models are capable of
higher-density graphics but not with every dot printed. This
density was chosen for reasonably wide compatibility. Many other dot-matrix
printers on the market have graphics modes compatible with the
Epson printers. I cannot guarantee that the plot files generated by
these programs will be compatible with all of these, but they do work on
Epsons. They have also worked, in our hands, on IBM Graphics Printers. There
used to be many printers that claimed compatibility with these too, but I
do not know whether it will work on all of them. If you have trouble
with any of these you might consider trying in the epson option of
procedure initplotter to put in a fprintf statement
that writes to plotfile an escape sequence that changes line spacing.
As dot matrix printers are rare these days, I suspect this option will
not get much testing.
Prowriter/Imagewriter dot-matrix printer.
The trading firm C. Itoh distributed this line of
dot-matrix printers, which was made by Tokyo Electric (TEC) and also was
sold by NEC under the product number PC8023. These were 9-pin dot matrix
printers. In a slightly modified form they were also the Imagewriter
printer sold by Apple for their Macintosh line. The same escape codes
seem to work on both machines, the Apple version being a serial
interface version. They are not related to the IBM Proprinter, despite
the name.
Toshiba 24-pin dot-matrix printer.
The 24-pin printers from Toshiba were covered
by this option. These included the P1340, P1350, P1351, P351, 321, and
later models. For a 24-pin printer the plot file can get fairly large
as it contains a bit map of the image and there are more bits with a
24-pin image. Printing was usually slow.
Okidata dot-matrix printer.
The ML81, 82, 83 and ML181, 182, 183 line of dot-matrix
printers from Okidata had their own graphics codes and those are dealt
with by this option. The later Okidata ML190 series emulated IBM Graphics
Printers so that you would not want to use this option for them but the option
for that printer.
Houston Instruments plotter. The Houston Instruments line of plotters
were also known as Bausch and Lomb plotters. The code in the
programs for these has not been tested recently; I would appreciate
anyone who tries it out telling me whether it works. I do not have
access to such a plotter myself, and doubt most users will come across one.
Conversion from these formats to others is also possible.
There is a free program by Jef Poskanzer called "PBMPLUS" that interconverts
many bitmap formats (see above under Rayshade).
Drivers for Preview of Plots
Plots may be previewed in a number of formats which are chosen using the
menu option. Previewing defaults to different drivers depending on which
kind of system you are running the programs on. For Unix or Linux systems
it defaults to X Windows, for Windows systems to Windows graphics, and
for Macintosh systems to macintosh graphics screens.
We have already mentioned (above) some of the options that are also used
for previewing. These include:
MSDOS Graphics Screens. These were mentioned
above as possible output images.
Macintosh graphics screens. Using the windowing features of
Codewarrior C from Metrowerks, our Macintosh executables
open a graphics window and draw preview trees in it. We have
not provided this option for final plotting of the tree.
The window is about 2/3 the height of the desktop screen and has the tree drawn
in black on a white background.
After the preview appears, you can dismiss the window by closing it
using the usual little box in its corner, or by typing Command-Q.
X Windows display. Our Unix and Linux code tries to do previews
in X Windows. We hope that the Unix/Linux Makefle will find the correct
libraries to link from. An X window appears with the preview of the tree
in it. To dismiss this window one needs to put the mouse over the
text window that had the menus in it (or click on them) and then type Y
or N to plot the tree or return to the menu.
MS Windows display. The executables produced using the Cygwin
Gnu C++ compiler should produce this graphics preview window. The preview
window can be dismissed using its File menu. In its menu the Change
Parameters otion will lead you back to the text menu to make more
changes, and the Plot option will cause the final plot file to be written.
The Quit option will interrupt the program, causing no plot file to b produced.
Normally you will not want to use that option.
Tektronix 4010 graphics terminal. This previewing option was
described above as a final plot option.
DEC ReGIS graphics (VT240 terminal). This previewing option was
described above as a final plot option.
Problems Copying Files to Printers
A problem may arose in how to get the plot files to the plotting device
or printer. One has to copy them directly, but one should be careful to
not let your serial or parallel port strip off the high-order bits in the
bytes if you are using one of the options that generate nonprintable
characters. This will be true for most of the dot matrix printers and
for bitmaps dumped to an HP Laserjet-compatible printer. This can be
a problem under Unix or MSDOS. If, for example, you have a dot-matrix
printer connected to a parallel port under PCDOS, to copy the file
PLOTFILE to the printer without losing the high-order bits, you must use
the /B switch on the COPY command:
COPY/B PLOTFILE PRN:
The VAX VMS Line Length Problem
A problem that may occur under some operating systems, particularly the
VMS operating system for Digital VAXes, is having a plot file with lines
that exceed some operating system limit such as 255 characters. This can
happen if you are using the Tektronix option.
You should set your terminal type with the
command
$ SET TERM/NOWRAP/ESCAPE
which will allow Tektronix and DEC ReGIS
plots to successfully appear on your terminal. That way, if you have a
terminal capable of plotting one of these kinds of plots, the operating
system will not interfere with the process. It will not be possible to
use files of Tektronix commands as final plot files, however, as the TYPE
command usually used to get them to appear on the screen does not allow
lines longer than 2048 bytes, and Tektronix plots are single lines longer
than that.
Other problems and opportunities
Another problem is adding labels (such as vertical scales and branch
lengths) to the plots produced by this program. This may require you to
use the BMP, PICT, Idrawm, Xfig, PCX or Postscript file format and use a draw
or paint program to add them.
I would like to add more fonts. The present fonts are recoded versions of
the Hershey fonts. They are legally publicly distributable. Most other font
families on the market are not public domain and I cannot
afford to license them for distribution. Some people have noticed that the
Hershey fonts, which are drawn by a series of straight lines, have noticeable
angles in what are supposed to be curves, when they are printed on modern
laser printers and looked at closely. This is less a problem than one might
think since, fortunately, when scientific journals print a tree it is usually
shrunk so small that these imperfections (and often the tree itself)
are hard to see!
One more font that could be added from the Hershey font collection would be a
Greek font. If Greek users would
find that useful I could add it, but my impression is that they publish
mostly in English anyway.
Writing Code for a new Plotter, Printer or File Format
The C version of these programs consists of two C programs, "drawgram.c"
and "drawtree.c". Each of these has common sections of code compiled
into it called
"draw.c", "draw2.c" and a common header file, "draw.h". In addition
the Macintosh version requires two more files, "interface.c" and
"interface.h". All of the graphics commands that are common to both
programs will be found in "draw.c" and "draw2.c". The following instructions
for writing your own code to drive a different kind of printer,
plotter, or graphics file format, require you only to make changes in
"drawgraphics.c". The two programs can then be recompiled.
If you want to write code for other printers, plotters, or vector
file formats, this is not
too hard. The plotter option "U" is provided as a place for you to insert
your own code. Chris Meacham's system was to draw everything, including the
characters in the names and all curves, by drawing a series of straight
lines. Thus you need only master your plotter's commands for drawing
straight lines. In function "plotrparms"
you must set up the values of
variables "xunitspercm" and "yunitspercm", which are the number of units in
the x and y directions per centimeter, as well as variables "xsize" and
"ysize" which are the size of the plotting area in centimeters in the x
direction and the y direction. A variable "penchange" of a user-defined type
is set to "yes" or "no" depending on whether the commands to change the pen
must be issued when switching between plotting lines and drawing
characters. Even though dot-matrix printers do not have pens, penchange
should be set to "yes" for them. In function "plot" you must issue commands
to draw a line from the current
position (which is at (xnow, ynow) in the plotter's units) to the position
(xabs, yabs), under the
convention that the lower-left corner of the plotting area is (0.0, 0.0). In
functions "initplotter" and "finishplotter"
you must issue commands to
initialize the plotter and to finish plotting, respectively. If the pen is
to be changed an appropriate piece of code must be inserted in
function "penchange".
For dot matrix printers and raster graphics matters are a bit more complex. The
functions "plotrparms", "initplotter", "finishplotter" and "plot"
still respectively set up the parameters for the plotter, initialize it,
finish a plot, and plot one line. But now the plotting consists of drawing
dots into a two-dimensional array called "stripe". Once the plot is
finished this array is printed out. In most cases the array is not as tall
as a full plot: instead it is a rectangular strip across it. When the
program has finished drawing in ther strip, it prints it out and then
moves down the plot to the next strip. For example, for Hewlett-Packard
Laserjets we have defined the strip as 2550 dots wide and 20 dots deep. When
the program goes to draw a line, it draws it into the strip and ignores
any part of it that falls outside the strip. Thus the program does a complete
plotting into the strip, then prints it, then moves down the diagram by (in
this case) 20 dots, then does a complete plot into that strip, and so on.
To work with a new raster or dot matrix format, you will have to define the
desired width of a strip ("strpwide"), the desired depth ("strpdeep"), and
how many lines of bytes must be printed out to print a strip. For example
Toshiba P351 printers in graphics mode print strips of dots 1350 bits wide
by 24 bits deep, each column of 24 bits printing out as consecutive four bytes
with 6 bits each. In that case, one prints out a
strip by printing up to 1350 groups of 4 bytes. "strpdiv" is 4, and
"strpwide" is 1350, and "strpdeep" is 24. Procedure "striprint"
is the one that prints out a strip, and has special-case code for the
different printers and file formats. For file formats, all of which
print out a single row of dots at a time, the variable "strpdiv" is not
used. The variable "dotmatrix" is set to
"true" or "false" in function "plotrparms"
according to whether or not "strpdiv" is to be used. Procedure "plotdot"
sets a single dot in the array "strip" to 1 at position (xabs, yabs). The
coordinates run from 1 at the top of the plot to larger numbers as we
proceed down the page. Again, there is special-case code for different
printers and file formats in that
function.
You will probably want to read the code for some of the dot matrix or file
format options if you want to write code for one of them. Many of them
have provision for printing only part of a line, ignoring parts of it that
have no dots to print.
I would be happy to obtain the resulting code from you to consider
adding it to this listing so we can cover more kinds of plotters, printers,
and file formats.
APPENDIX 1.
Code to drive some other graphics devices.
These pieces of code are to be
inserted in the places reserved for the "Y" plotter option. The variables
necessary to run this
have already been incorporated into the
programs.
Calcomp plotters:
Calcomp's industrial-strength plotters are not as much a fixture of
University computer centers as they one were, but just in case you need to
use one, this code should work:
A global declaration needed near the front of drawtree.c:
This program infers an unrooted phylogeny from protein sequences, using a
new method intermediate between the approaches of Eck and Dayhoff (1966) and
Fitch (1971). Eck and Dayhoff (1966) allowed any amino acid to change to
any other, and counted the number of such changes needed to evolve the
protein sequences on each given phylogeny. This has the problem that it
allows replacements which are not consistent with the genetic code, counting
them equally with replacements that are consistent. Fitch, on the other hand,
counted the minimum number of nucleotide substitutions that would be
needed to achieve the given protein sequences. This counts silent
changes equally with those that change the amino acid.
The present method insists that any changes of amino acid be consistent
with the genetic code so that, for example, lysine is allowed to change
to methionine but not to proline. However, changes between two amino acids
via a third are allowed and counted as two changes if each of the two
replacements is individually allowed. This sometimes allows changes that
at first sight you would think should be outlawed. Thus we can change from
phenylalanine to glutamine via leucine in two steps
total. Consulting the genetic code, you will find that there is a leucine
codon one step away from a phenylalanine codon, and a leucine codon one
step away from glutamine. But they are not the same leucine codon. It
actually takes three base substitutions to get from either of the
phenylalanine codons TTT and TTC to either of the glutamine codons
CAA or CAG. Why then does this program count only two? The answer
is that recent DNA sequence comparisons seem to show that synonymous
changes are considerably faster and easier than ones that change the
amino acid. We are assuming that, in effect, synonymous changes occur
so much more readily that they need not be counted. Thus, in the chain
of changes TTT (Phe) --> CTT (Leu) --> CTA (Leu) --> CAA (Glu), the middle
one is not counted because it does not change the amino acid (leucine).
To maintain consistency with the genetic code, it is necessary for the
program internally to treat serine as two separate states (ser1 and ser2)
since the two groups of serine codons are not adjacent in the
code. Changes to the state "deletion" are counted as three steps to prevent the
algorithm from assuming unnecessary deletions. The state "unknown" is
simply taken to mean that the amino acid, which has not been determined,
will in each part of a tree that is evaluated be assumed be whichever one
causes the fewest steps.
The assumptions of this method (which has not been described in the
literature), are thus something like this:
Change in different sites is independent.
Change in different lineages is independent.
The probability of a base substitution that changes the amino
acid sequence is small over the lengths of time involved in
a branch of the phylogeny.
The expected amounts of change in different branches of the phylogeny
do not vary by so much that two changes in a high-rate branch
are more probable than one change in a low-rate branch.
The expected amounts of change do not vary enough among sites that two
changes in one site are more probable than one change in another.
The probability of a base change that is synonymous is much higher
than the probability of a change that is not synonymous.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b, 1988b). For
an opposing view arguing that the parsimony methods make no substantive
assumptions such as these, see the works by Farris (1983) and Sober (1983a,
1983b, 1988), but also read the exchange between Felsenstein and Sober (1986).
The input for the program is fairly standard. The first line contains the
number of species and the number of amino acid positions (counting any
stop codons that you want to include).
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The protein sequences are given by the one-letter code used by
described in the Molecular Sequence Programs documentation file. Note that
if two polypeptide chains are being used that are of different length
owing to one terminating before the other, they should be coded as (say)
HIINMA*????
HIPNMGVWABT
since after the stop codon we do not definitely know that
there has been a deletion, and do not know what amino acid would
have been there. If DNA studies tell us that there is
DNA sequence in that region, then we could use "X" rather than "?". Note
that "X" means an unknown amino acid, but definitely an amino acid,
while "?" could mean either that or a deletion. The distinction is often
significant in regions where there are deletions: one may want to encode
a six-base deletion as "-?????" since that way the program will only count
one deletion, not six deletion events, when the deletion arises. However,
if there are overlapping deletions it may not be so easy to know what
coding is correct.
One will usually want to
use "?" after a stop codon, if one does not know what amino acid is there. If
the DNA sequence has been observed there, one probably ought to resist
putting in the amino acids that this DNA would code for, and one should use
"X" instead, because under the assumptions implicit in this parsimony
method, changes to any noncoding sequence are much easier than
changes in a coding region that change the amino acid, so that they
shouldn't be counted anyway!
The form of this information
is the standard one described in the main documentation file. For the U option
the tree
provided must be a rooted bifurcating tree, with the root placed anywhere
you want, since that root placement does not affect anything.
The options are selected using an interactive menu. The menu looks like this:
Protein parsimony algorithm, version 3.6
Setting for this run:
U Search for best tree? Yes
J Randomize input order of sequences? No. Use input order
O Outgroup root? No, use as outgroup species 1
T Use Threshold parsimony? No, use ordinary parsimony
C Use which genetic code? Universal
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, VT52, ANSI)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each site No
5 Print sequences at all nodes of tree No
6 Write out trees onto tree file? Yes
Are these settings correct? (type Y or the letter for one to change)
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The options U, J, O, T, W, M, and 0 are the usual ones. They are described in
the main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs. Option C allows the user to select among various
nuclear and mitochondrial genetic codes. There is no provision for coping
with data where different genetic codes have been used in different
organisms.
In the U (User tree) option, the trees should
not be preceded by a line with the number of trees on it.
Output is standard: if option 1 is toggled on, the data is printed out,
with the convention that "." means "the same as in the first species".
Then comes a list of equally parsimonious trees, and (if option 2 is
toggled on) a table of the
number of changes of state required in each position. If option 5 is toggled
on, a table is printed
out after each tree, showing for each branch whether there are known to be
changes in the branch, and what the states are inferred to have been at the
top end of the branch. If the inferred state is a "?" there will be multiple
equally-parsimonious assignments of states; the user must work these out for
themselves by hand. If option 6 is left in its default state the trees
found will be written to a tree file, so that they are available to be used
in other programs.
If the U (User Tree) option is used and more than one tree is supplied, the
program also performs a statistical test of each of these trees against the
best tree. This test, which is a version of the test proposed by
Alan Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences
due to Kishino and Hasegawa (1989), and uses the mean
and variance of
step differences between trees, taken across positions. If the mean
is more than 1.96 standard deviations different then the trees are declared
significantly different. The program
prints out a table of the steps for each tree, the differences of
each from the best one, the variance of that quantity as determined by
the step differences at individual positions, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
The program is derived from MIX but has had some rather elaborate
bookkeeping using sets of bits installed. It is not a very fast
program but is speeded up substantially over version 3.2.
CONTENTS OF OUTPUT FILE (with all numerical options on)
Protein parsimony algorithm, version 3.6
3 trees in all found
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
steps in each position:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0! 3 1 5 3 2 0 0 2 0
10! 0
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
1 ANCDEFGHIK
1 2 no ..........
2 Gamma yes ?B..S..*??
2 3 yes ..?.......
3 4 yes ?IK.......
4 Epsilon maybe D.........
4 Delta yes C.........
3 Beta yes .B--......
1 Alpha maybe .B........
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
steps in each position:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0! 3 1 5 3 2 0 0 2 0
10! 0
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
1 ANCDEFGHIK
1 2 no ..........
2 3 maybe ?.........
3 4 yes .IK.......
4 Epsilon maybe D.........
4 Delta yes C.........
3 Gamma yes ?B..S..*??
2 Beta yes .B--......
1 Alpha maybe .B........
+--Epsilon
+-----4
! +--Delta
+--3
! ! +--Gamma
1 +-----2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
steps in each position:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0! 3 1 5 3 2 0 0 2 0
10! 0
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
1 ANCDEFGHIK
1 3 no ..........
3 4 yes ?IK.......
4 Epsilon maybe D.........
4 Delta yes C.........
3 2 no ..........
2 Gamma yes ?B..S..*??
2 Beta yes .B--......
1 Alpha maybe .B........
DOLMOVE is an interactive parsimony program which uses the Dollo and
Polymorphism parsimony criteria. It is inspired on Wayne Maddison and
David Maddison's marvellous program MacClade, which is written for Apple
MacIntosh computers. DOLMOVE reads in a data set which is prepared in almost
the same format as one for the Dollo and polymorhism parsimony program
DOLLOP. It allows the user to choose an initial tree, and displays this tree
on the screen. The user can look at different characters and the way their
states are distributed on that tree, given the most parsimonious reconstruction
of state changes for that particular tree. The user then can specify how the
tree is to be rearraranged, rerooted or written out to a file. By looking at
different rearrangements of the tree the user can manually search for the most
parsimonious tree, and can get a feel for how different characters are affected
by changes in the tree topology.
This program is compatible with fewer computer systems than the other
programs in PHYLIP. It can be adapted to PCDOS systems or to
any system whose screen or terminals emulate DEC VT100
terminals (such as Telnet programs for logging in to remote computers over a
TCP/IP network,
VT100-compatible windows in the X windowing system, and any
terminal compatible with ANSI standard terminals).
For any other screen types, there is a generic option which does
not make use of screen graphics characters to display the character
states. This will be less effective, as the states will be less
easy to see when displayed.
The input data file is set up almost identically to the data files for
DOLLOP.
The user interaction starts with the program presenting a menu. The
menu looks like this:
Interactive Dollo or polymorphism parsimony, version 3.6a3
Settings for this run:
P Parsimony method? Dollo
A Use ancestral states? No
F Use factors information? No
W Sites weighted? No
T Use Threshold parsimony? No, use ordinary parsimony
A Use ancestral states in input file? No
U Initial tree (arbitrary, user, specify)? Arbitrary
0 Graphics type (IBM PC, ANSI, none)? (none)
L Number of lines on screen? 24
S Width of terminal screen? 80
Are these settings correct? (type Y or the letter for one to change)
The P (Parsimony Method) option is the one that toggles between polymorphism
parsimony and Dollo parsimony. The program defaults to Dollo parsimony.
The T (Threshold), F (Factors), A (Ancestors), and 0 (Graphics type) options
are the usual
ones and are described in the main documentation page and in the
Discrete Characters Program documentation page.
(Note: at present DOLMOVE actully
does not use the A (Ancestral states) information). The F (Factors)
option is used to inform the program which
groups of characters are to be counted together in computing the number of
characters compatible with the tree. Thus if three binary characters are all
factors of the same multistate character, the multistate character will
be counted as compatible with the tree only if all three factors are compatible
with it.
The L option allows
the program to take advantage of larger screens if available. The X (Mixed
Methods option is not available in DOLMOVE. The
U (initial tree) option allows the user to choose whether
the initial tree is to be arbitrary, interactively specified by the user, or
read from a tree file. Typing U causes the program to change among the
three possibilities in turn. I
would recommend that for a first run, you allow the tree to be set up
arbitrarily (the default), as the "specify" choice is difficult
to use and the "user tree" choice requires that you have available a tree file
with the tree topology of the initial tree.
Its default name is intree. The program will ask you for its name if
it looks for the input tree file and does not find one of this name.
If you wish to set up some
particular tree you can also do that by the rearrangement commands specified
below. The T (threshold) option allows a continuum of methods between
parsimony and compatibility. Thresholds less than or equal to 0 do not
have any
meaning and should not be used: they will result in a tree dependent only on
the input order of species and not at all on the data!
Note that the usual W (Weights) option is not available in MOVE. We
hope to add it soon.
After the initial menu is displayed and the choices are made,
the program then sets up an initial tree and displays it. Below it will be a
one-line menu of possible commands, which looks like this:
NEXT? (Options: R # + - S . T U W O F C H ? X Q) (H or ? for Help)
If you type H or ? you will get a single screen showing a description of each
of these commands in a few words. Here are slightly more detailed
descriptions:
R
("Rearrange"). This command asks for the number of a node which is to be
removed from the tree. It and everything to the right of it on the tree is to
be removed (by breaking the branch immediately below it). The command also
asks for the number of a node below which that group is to be inserted. If an
impossible number is given, the program refuses to carry out the rearrangement
and asks for a new command. The rearranged tree is displayed: it will often
have a different number of steps than the original. If you wish to undo a
rearrangement, use the Undo command, for which see below.
#
This command, and the +, - and S commands described below, determine
which character has its states displayed on the branches of
the trees. The initial tree displayed by the program does not show
states of sites. When # is typed, the program does not ask the user which
character is to be shown but automatically shows the states of the next
binary character that is not compatible with the tree (the next character that
does not
perfectly fit the current tree). The search for this character "wraps around"
so that if it reaches the last character without finding one that is not
compatible with the tree, the search continues at the first character; if no
incompatible character is found the current character is shown, and if no
current character is shown then the first character is shown. If the last
character has been reached, using + again causes the first
character to be shown. The display takes the form of
different symbols or textures on the branches of the tree. The state of each
branch is actually the state of the node above it. A key of the symbols or
shadings used for states 0, 1 and ? are shown next to the tree. State ? means
that either state 0 or state 1 could exist at that point on the tree, and that
the user may want to consider the different possibilities, which are usually
apparent by inspection.
+
This command is the same as # except that it goes forward one character,
showing the states of the next character. If no character has been shown,
using + will
cause the first character to be shown. Once the last character has been
reached, using + again will show the first character.
-
This command is the same as + except that it goes backwards, showing the
states of the previous character. If no character has been shown, using - will
cause the last character to be shown. Once character number 1 has been
reached, using - again will show the last character.
S
("Show"). This command is the same as + and - except that it causes
the program to ask you for the number of a character. That character is
the one whose states will be displayed. If you give the character number as 0,
the program will go back to not showing the states of the characters.
. (dot)
This command simply causes the current tree to be redisplayed. It is of
use when the tree has partly disappeared off of the top of the screen owing to
too many responses to commands being printed out at the bottom of the screen.
T
("Try rearrangements"). This command asks for the name of a node. The
part of the tree at and above that node is removed from the tree. The program
tries to re-insert it in each possible location on the tree (this may take some
time, and the program reminds you to wait). Then it prints out a summary. For
each possible location the program prints out the number of the node to the
right of the
place of insertion and the number of steps required in each case. These are
divided into those that are better, tied, or worse than the current tree. Once
this summary is printed out, the group that was removed is inserted into its
original position. It is up to you to use the R command to actually carry out
any the arrangements that have been tried.
U
("Undo"). This command reverses the effect of the most recent
rearrangement, outgroup re-rooting, or flipping of branches. It returns to the
previous tree topology. It will be of great use when rearranging the tree and
when a rearrangement proves worse than the preceding one -- it permits you to
abandon the new one and return to the previous one without remembering its
topology in detail.
W
("Write"). This command writes out the current tree onto a tree output
file. If the file already has been written to by this run of DOLMOVE, it will
ask you whether you want to replace the contents of the file, add the tree to
the end of the file, or not write out the tree to the file. The tree
is written in the standard format used by PHYLIP (a subset of the
Newick standard). It is in the proper format to serve as the
User-Defined Tree for setting up the initial tree in a subsequent run of the
program.
O
("Outgroup"). This asks for the number of a node which is to be the
outgroup. The tree will be redisplayed with that node
as the left descendant of the bottom fork. The number of
steps required on the tree may change on re-rooting. Note that it is possible
to use this to make a multi-species group the outgroup (i.e., you can give the
number of an interior node of the tree as the outgroup, and the program will
re-root the tree properly with that on the left of the bottom fork).
F
("Flip"). This asks for a node number and then flips the two branches at
that, so that the left-right order of branches at that node is
changed. This does not actually change the tree topology (or the number of
steps on that tree) but it does change the appearance of the tree.
C
("Clade"). When the data consist of more than 12 species (or more than
half the number of lines on the screen if this is not 24), it may be
difficult to display the tree on one screen. In that case the tree
will be squeezed down to
one line per species. This is too small to see all the interior states of the
tree. The C command instructs the program to print out only that part of the
tree (the "clade") from a certain node on up. The program will prompt you for
the number of this node. Remember that thereafter you are not looking at the
whole tree. To go back to looking at the whole tree give the C command again
and enter "0" for the node number when asked. Most users will not want to use
this option unless forced to.
H
("Help"). Prints a one-screen summary of what the commands do, a few
words for each command.
?
("huh?"). A synonym for H. Same as Help command.
X
("Exit"). Exit from program. If the current tree has not yet been saved
into a file, the program will ask you whether it should be saved.
Q
("Quit"). A synonym for X. Same as the eXit command.
OUTPUT
If the A option is used, then
the program will infer, for any character whose ancestral state is unknown
("?") whether the ancestral state 0 or 1 will give the fewest changes
(according to the criterion in use). If these are tied, then it may not be
possible for the program to infer the state in the internal nodes, and many of
these will be shown as "?". If the A option is not used, then the program will
assume 0 as the ancestral state.
When reconstructing the placement of forward
changes and reversions under the Dollo method, keep in mind that each
polymorphic state in the input data will require one "last minute"
reversion. This is included in the counts. Thus if we have both states 0 and
1 at a tip of the tree the program will assume that the lineage had state 1 up
to the last minute, and then state 0 arose in that population by reversion,
without loss of state 1.
When DOLMOVE calculates the number of characters
compatible with the tree, it will take the F option into
account and count the multistate characters as units, counting a character
as compatible with the tree only when all of the binary characters
corresponding to it are compatible with the tree.
ADAPTING THE PROGRAM TO YOUR COMPUTER AND TO YOUR TERMINAL
As we have seen, the initial menu of the program allows you to choose
among three screen types (PC, ANSI, and none).
If you want to
avoid having to make this choice every time, you can change
some of the
constants in the file phylip.h to have the terminal type initialize
itself in the proper way, and recompile.
The constants that need attention are ANSICRT and IBMCRT.
Currently these are both set to "false" on Macintosh and on Unix/Linux
systems, and IBMCRT is set to "true" on Windows systems. If your system
has an ANSI compatible terminal, you might want to find the
definition of ANSICRT in phylip.h and set it to "true", and
IBMCRT to "false".
MORE ABOUT THE PARSIMONY CRITERION
DOLMOVE uses as its numerical criterion the Dollo and
polymorphism parsimony methods. The program defaults to carrying out Dollo
parsimony.
The Dollo parsimony method was
first suggested in print in verbal form by Le Quesne (1974) and was
first well-specified by Farris (1977). The method is named after Louis
Dollo since he was one of the first to assert that in evolution it is
harder to gain a complex feature than to lose it. The algorithm
explains the presence of the state 1 by allowing up to one forward
change 0-->1 and as many reversions 1-->0 as are necessary to explain
the pattern of states seen. The program attempts to minimize the number
of 1-->0 reversions necessary.
The assumptions of this method are in effect:
We know which state is the ancestral one (state 0).
The characters are evolving independently.
Different lineages evolve independently.
The probability of a forward change (0-->1) is small over the
evolutionary times involved.
The probability of a reversion (1-->0) is also small, but
still far larger than the probability of a forward change, so
that many reversions are easier to envisage than even one
extra forward change.
Retention of polymorphism for both states (0 and 1) is highly
improbable.
The lengths of the segments of the true tree are not so
unequal that two changes in a long segment are as probable as
one in a short segment.
One problem can arise when using additive binary recoding to
represent a multistate character as a series of two-state characters. Unlike
the Camin-Sokal, Wagner, and Polymorphism methods, the Dollo
method can reconstruct ancestral states which do not exist. An example
is given in my 1979 paper. It will be necessary to check the output to
make sure that this has not occurred.
The polymorphism parsimony method was first used by me,
and the results published
(without a clear
specification of the method) by Inger (1967). The method was
published by Farris (1978a) and by me (1979). The method
assumes that we can explain the pattern of states by no more than one
origination (0-->1) of state 1, followed by retention of polymorphism
along as many segments of the tree as are necessary, followed by loss of
state 0 or of state 1 where necessary. The program tries to minimize
the total number of polymorphic characters, where each polymorphism is
counted once for each segment of the tree in which it is retained.
The assumptions of the polymorphism parsimony method are in effect:
The ancestral state (state 0) is known in each character.
The characters are evolving independently of each other.
Different lineages are evolving independently.
Forward change (0-->1) is highly improbable over the length of
time involved in the evolution of the group.
Retention of polymorphism is also improbable, but far more
probable that forward change, so that we can more easily
envisage much polymorhism than even one additional forward
change.
Once state 1 is reached, reoccurrence of state 0 is very
improbable, much less probable than multiple retentions of
polymorphism.
The lengths of segments in the true tree are not so unequal
that we can more easily envisage retention events occurring in
both of two long segments than one retention in a short
segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
Below is a test data set, but we cannot show the
output it generates because of the interactive nature of the program.
The programs FITCH, KITSCH, and NEIGHBOR are for dealing with data which
comes in the form of a matrix of pairwise distances between all pairs of taxa,
such as distances based on molecular sequence data,
gene frequency genetic distances, amounts of DNA hybridization, or
immunological distances. In analyzing these
data, distance matrix programs implicitly assume that:
Each distance is measured independently from the others: no item of
data contributes to more than one distance.
The distance between each pair of taxa is drawn from a distribution
with an expectation which is the sum of values (in effect amounts of evolution)
along the tree from one tip to the other. The variance of the distribution is
proportional to a power p of the expectation.
These assumptions can be traced in the least squares methods of programs
FITCH and KITSCH but it is not quite so easy to see them in operation in the
Neighbor-Joining method of NEIGHBOR, where the independence assumptions is less
obvious.
THESE TWO ASSUMPTIONS ARE DUBIOUS IN MOST CASES: independence will not be
expected to be true in most kinds of data, such as genetic distances from gene
frequency data. For genetic distance data in which pure genetic drift without
mutation can be assumed to be the mechanism of change CONTML may be more
appropriate. However, FITCH, KITSCH, and NEIGHBOR will not give positively
misleading results (they will not make a statistically inconsistent estimate)
provided that additivity holds, which it will if the distance is computed from
the original data by a method which corrects for reversals and parallelisms in
evolution. If additivity is not expected to hold, problems are more severe. A
short discussion of these matters will be found in a review article of mine
(1984a). For detailed, if sometimes irrelevant, controversy see the papers by
Farris (1981, 1985, 1986) and myself (1986, 1988b).
For genetic distances from gene frequencies, FITCH, KITSCH, and NEIGHBOR
may be appropriate if a neutral mutation model can be assumed and Nei's genetic
distance is used, or if pure drift can be assumed and either Cavalli-Sforza's
chord measure or Reynolds, Weir, and Cockerham's (1983) genetic distance is
used. However, in the latter case (pure drift) CONTML should be better.
Restriction site and restriction fragment data can be treated by distance
matrix methods if a distance such as that of Nei and Li (1979) is used.
Distances of this sort can be computed in PHYLIp by the program RESTDIST.
For nucleic acid sequences, the distances computed in DNADIST allow
correction for multiple hits (in different ways) and should allow one to
analyse the data under the presumption of additivity. In all of these cases
independence will not be expected to hold. DNA hybridization and
immunological distances may be additive and independent if transformed properly
and if (and only if) the standards against which each value is measured are
independent. (This is rarely exactly true).
FITCH and the Neighbor-Joining option of NEIGHBOR fit a tree which has the
branch lengths unconstrained. KITSCH and the UPGMA option of NEIGHBOR, by
contrast, assume that an "evolutionary clock" is valid, according to which the
true branch lengths from the root of the tree to each tip are the same: the
expected amount of evolution in any lineage is proportional to elapsed time.
The input format for distance data is straightforward. The first line of
the input file contains the number of species. There follows species data,
starting, as with all other programs, with a species name. The species name is
ten characters long, and must be padded out with blanks if shorter. For each
species there then follows a set of distances to all the other species (options
selected in the programs' menus
allow the distance matrix to be upper or lower triangular or square).
The distances can continue to a new line after any of them. If the matrix
is lower-triangular, the diagonal entries (the distances from a species to
itself) will not be read by the programs. If they are included anyway, they
will be ignored by the programs, except for the case where one of them
starts a new line, in which case the program will mistake it for a species
name and get very confused.
For example, here is a sample input matrix, with a square matrix:
Note that the name "Mouse" in this matrix must be padded out by blanks to the
full length of 10 characters.
In general the distances are assumed to all be present: at the moment
there is only one way we can have missing entries in the distance matrix. If
the S option (which allows the user to specify the degree of replication of
each distance) is invoked, with some of the entries having degree of
replication zero, if the U (User Tree) option is in effect, and if the tree
being examined is such that every branch length can be estimated from the data,
it will be possible to solve for the branch lengths and sum of squares when
there is some missing data. You may not get away with this if the U option is
not in effect, as a tree may be tried on which the program will calculate a
branch length by dividing zero by zero, and get upset.
The present version of NEIGHBOR does allow the Subreplication option to be
used and the number of replicates to be in the input file, but it actally does
nothing with this information except read it in. It makes use of the average
distances in the cells of the input data matrix. This means that you cannot use
the S option to treat zero cells. We hope to modify NEIGHBOR in the future to
allow Subreplication. Of course the U (User tree) option is not available in
NEIGHBOR in any case.
The present versions of FITCH and KITSCH will do much better on missing
values than did previous versions, but you will still have to be careful about
them. Nevertheless you might (just) be able to explore relevant alternative
tree topologies one at a time using the U option when there is missing data.
Alternatively, if the missing values in one cell always correspond to a
cell with non-missing values on the opposite side of the main diagonal (i.e.,
if D(i,j) missing implies that D(j,i) is not missing), then use of the S option
will always be sufficient to cope with missing values. When it is used, the
missing distances should be entered as if present (any number can be
used) and the degree of replication for them should be given as 0.
Note that the algorithm for searching among topologies in FITCH and KITSCH
is the same one used in other programs, so that it is necessary to try
different orders of species in the input data. The J (Jumble) menu option may
be sufficient for most purposes.
The programs FITCH and KITSCH carry out the method of Fitch and Margoliash
(1967) for fitting trees to distance matrices. They also are able to carry out
the least squares method of Cavalli-Sforza and Edwards (1967), plus a variety
of other methods of the same family (see the discussion of the P option below).
They can also be set to use the Minimum Evolution method (Nei and Rzhetsky,
1993; Kidd and Sgaramella-Zonta, 1971).
The objective of these methods is to find that tree which minimizes
__ __
\ \ nij ( Dij - dij)2
Sum of squares = /_ /_ ------------------
i j Dijp
(the symbol made up of \, / and _ characters is of course a summation sign)
where D is the observed distance between species i and
j and d is the expected
distance, computed as the sum of the lengths (amounts of evolution) of the
segments of the tree from species i to species j. The
quantity n is the number
of times each distance has been replicated. In simple cases this is taken to
be one, but the user can, as an option, specify the degree of replication for
each distance. The distance is then assumed to be a mean of those replicates.
The power P is what distinguished the various methods. For the Fitch-
Margoliash method, which is the default method with this program, P
is 2.0. For the Cavalli-Sforza and Edwards least squares method it should be set to 0
(so that the denominator is always 1). An intermediate method is also
available in which P is 1.0, and any other value of P, such as 4.0 or -2.3, can
also be used. This generates a whole family of methods.
The P (Power) option is not available in the Neighbor-Joining program
NEIGHBOR. Implicitly, in this program P is 0.0 (though it is hard to prove
this). The UPGMA option of NEIGHBOR will assign the same branch lengths to the
particular tree topology that it finds as will KITSCH when given the same tree
and Power = 0.0.
All these methods make the assumptions of additivity and independent
errors. The difference between the methods is how they weight departures of
observed from expected. In effect, these methods differ in how they assume
that the variance of measurement of a distance will rise as a function of the
expected value of the distance.
These methods assume that the variance of the measurement error is
proportional to the P-th power of the expectation (hence the standard deviation
will be proportional to the P/2-th power of the expectation). If
you have
reason to think that the measurement error of a distance is the same for small
distances as it is for large, then you should set P=0 and use the
least squares
method, but if you have reason to think that the relative (percentage) error is
more nearly constant than the absolute error, you should use P=2,
the Fitch-Margoliash method. In between, P=1 would be appropriate if the
sizes of the errors were proportional to the square roots of the expected
distance.
One question which arises frequently is what the units of branch length are
in the resulting trees. In general, they are not time but units of
distance. Thus if two species have a distance 0.3 between them, they will
tend to be separated by branches whose total length is about 0.3. In the
case of DNA distances, for example, the unit of branch length will be
subsxtitutions per base. (In the case of protein distances, it will be
amino acid substitutions per amino acid posiiton.
tend to be sd
OPTIONS
Here are the options available in all three programs. They are selected using
the menu of options.
U
the User tree option.
The trees in FITCH are regarded as unrooted, and are
specified with a trifurcation (three-way split) at their base:
e. g.:
((A,B),C,(D,E));
while in KITSCH they are to be regarded as rooted and have a
bifurcation at the base:
((A,B),(C,(D,E)));
Be careful not to move User trees from FITCH to KITSCH without
changing their form appropriately (you can use RETREE to do
this). User trees are not available in NEIGHBOR. In FITCH if
you specify the branch lengths on one or more branches, you can
select the L (use branch Lengths) option to avoid having those
branches iterated, so that the tree is evaluated with their
lengths fixed.
P
indicates that you are going to set the Power (P in the above
formula). The default value is 2 (the Fitch-Margoliash method).
The power, a real number such as 1.0, is prompted for by the
programs. This option is not available in NEIGHBOR.
-
indicates that negative segment lengths are to be allowed in the
tree (default is to require that all branch lengths be
nonnegative). This option is not available in NEIGHBOR.
O
is the usual Outgroup option, available in FITCH and NEIGHBOR but
not in KITSCH, nor when the UPGMA option of NEIGHBOR is used.
L
indicates that the distance matrix is input in Lower-triangular
form (the lower-left half of the distance matrix only, without
the zero diagonal elements).
R
indicates that the distance matrix is input in uppeR-triangular
form (the upper-right half of the distance matrix only, without
the zero diagonal elements).
S
is the Subreplication option. It informs the program that after
each distance will be provided an integer indicating that the
distance is a mean of that many replicates. There is no
auxiliary information, but the presence of the S option indicates
that the data will be in a different form. Each distance must be
followed by an integer indicating the number of replicates, so
that a line of data looks like this:
Delta 3.00 5 3.21 3 1.84 9
the 5, 3, and 9 being the number of times the measurement was
replicated. When the number of replicates is zero, a distance
value must still be provided, although its vale will not afect
the result. This option is not available in NEIGHBOR.
G
is the usual Global branch-swapping option. It is available in
FITCH and KITSCH but is not relevant to NEIGHBOR.
J
indicates the usual J (Jumble) option for entering species in a
random order. In FITCH and KITSCH if you do multiple jumbles in
one run the program will print out the best tree found overall.
M
is the usal Multiple data sets option, available in all of these
programs. It allows us (when the output tree file is analyzed in
CONSENSE) to do a bootstrap (or delete-half-jackknife) analysis
with the distance matrix{ programs.
The numerical options are the usual ones and should be clear from the
menu.
Note that when the options L or R are used one of the species, the first
or last one, will have its name on an otherwise empty line. Even so, the name
should be padded out to full length with blanks. Here is a sample lower-
triangular data set.
<--- note: five blanks should follow the name "Alpha"
Be careful if you are using lower- or upper-triangular trees to make the
corresponding selection from the menu (L or R), as the
program may get horribly confused otherwise, but it still gives a result even
though the result is then meaningless. With the menu option selected all
should be well.
PHYLIPNEW-3.69.650/doc/proml.html 0000664 0001750 0001750 00000102217 07712247475 013074 0000000 0000000
This program implements the maximum likelihood method for protein
amino acid sequences.
It uses the either the Jones-Taylor-Thornton or the Dayhoff
probability model of change between amino acids.
The assumptions of these present models are:
Each position in the sequence evolves independently.
Different lineages evolve independently.
Each position undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of occurrence)
which we specify.
All relevant positions are included in the sequence, not just those that
have changed or those that are "phylogenetically informative".
The probabilities of change between amino acids are given by the
model of Jones, Taylor, and Thornton (1992) or by the PAM model of
Dayhoff (Dayhoff and Eck, 1968; Dayhoff et. al., 1979).
Note the assumption that we are looking at all positions, including those
that have not changed at all. It is important not to restrict attention
to some positions based on whether or not they have changed; doing that
would bias branch lengths by making them too long, and that in turn
would cause the method to misinterpret the meaning of those positions that
had changed.
This program uses a Hidden Markov Model (HMM)
method of inferring different rates of evolution at different amino acid
positions. This
was described in a paper by me and Gary Churchill (1996). It allows us to
specify to the program that there will be
a number of different possible evolutionary rates, what the prior
probabilities of occurrence of each is, and what the average length of a
patch of positions all having the same rate. The rates can also be chosen
by the program to approximate a Gamma distribution of rates, or a
Gamma distribution plus a class of invariant positions. The program computes the
the likelihood by summing it over all possible assignments of rates to positions,
weighting each by its prior probability of occurrence.
For example, if we have used the C and A options (described below) to specify
that there are three possible rates of evolution, 1.0, 2.4, and 0.0,
that the prior probabilities of a position having these rates are 0.4, 0.3, and
0.3, and that the average patch length (number of consecutive positions
with the same rate) is 2.0, the program will sum the likelihood over
all possibilities, but giving less weight to those that (say) assign all
positions to rate 2.4, or that fail to have consecutive positions that have the
same rate.
The Hidden Markov Model framework for rate variation among positions
was independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of
rates; we allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant positions.
This feature effectively removes the artificial assumption that all positions
have the same rate, and also means that we need not know in advance the
identities of the positions that have a particular rate of evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each positions (for example, we might want
amino acid positions in the active site of a protein to change more slowly
than other positions. This is done with the categories input file and the
C option. We then specify (using the menu) the relative rates of evolution of
amino acid positions
in the different categories. For example, we might specify that positions
in the active site
evolve at relative rates of 0.2 compared to 1.0 at other positions. If we
are assuming that a particular position maintains a cysteine bridge to another,
we may want to put it in a category of positions (including perhaps the
initial position of the protein sequence which maintains methionine) which
changes at a rate of 0.0.
If both user-assigned rate categories and Hidden Markov Model rates
are allowed, the program assumes that the
actual rate at a position is the product of the user-assigned category rate
and the Hidden Markov Model regional rate. (This may not always make
perfect biological sense: it would be more natural to assume some upper
bound to the rate, as we have discussed in the Felsenstein and Churchill
paper). Nevertheless you may want to use both types of rate variation.
INPUT FORMAT AND OPTIONS
Subject to these assumptions, the program is a
correct maximum likelihood method. The
input is fairly standard, with one addition. As usual the first line of the
file gives the number of species and the number of amino acid positions.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter amino acid code. The sequences must
either be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The options are selected using an interactive menu. The menu looks like this:
Amino acid sequence Maximum Likelihood method, version 3.6a3
Settings for this run:
U Search for best tree? Yes
P JTT or PAM amino acid change model? Jones-Taylor-Thornton model
C One category of sites? Yes
R Rate variation among sites? constant rate of change
W Sites weighted? No
S Speedier but rougher analysis? Yes
G Global rearrangements? No
J Randomize input order of sequences? No. Use input order
O Outgroup root? No, use as outgroup species 1
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
5 Reconstruct hypothetical sequences? No
Y to accept these or type the letter for one to change
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The options U, W, J, O, M, and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
The P option toggles between two models of amino acid change. One
is the Jones-Taylor-Thornton model, the other the Dayhoff PAM matrix
model. These are both based on Margaret Dayhoff's (Dayhoff and Eck, 1968;
Dayhoff et. al., 1979) method of empirical tabulation of changes of
amino acid sequences, and conversion of these to a probability
model of amino acid change which is used to make a transition probability
matrix which allows prediction of the probability of changing from any
one amino acid to any other, and also predicts equilibrium amino acid
composition.
The default method is that of Jones,
Taylor, and Thornton (1992). This is similar to the Dayhoff
PAM model, except that it is based on a recounting of the number of
observed changes in amino acids, using a much larger sample of protein
sequences than did Dayhoff. Because its sample is so much larger this
model is to be preferred over the original Dayhoff PAM model.
The Dayhoff model uses Dayhoff's PAM 001 matrix from
Dayhoff et. al. (1979), page 348.
The R (Hidden Markov Model rates) option allows the user to
approximate a Gamma distribution of rates among positions, or a
Gamma distribution plus a class of invariant positions, or to specify how
many categories of
substitution rates there will be in a Hidden Markov Model of rate
variation, and what are the rates and probabilities
for each. By repeatedly selecting the R option one toggles among
no rate variation, the Gamma, Gamma+I, and general HMM possibilities.
If you choose Gamma or Gamma+I the program will ask how many rate
categories you want. If you have chosen Gamma+I, keep in mind that
one rate category will be set aside for the invariant class and only
the remaining ones used to approximate the Gamma distribution.
For the approximation we do not use the quantile method of Yang (1995)
but instead use a quadrature method using generalized Laguerre
polynomials. This should give a good approximation to the Gamma
distribution with as few as 5 or 6 categories.
In the Gamma and Gamma+I cases, the user will be
asked to supply the coefficient of variation of the rate of substitution
among positions. This is different from the parameters used by Nei and Jin
(1990) but
related to them: their parameter a is also known as "alpha",
the shape parameter of the Gamma distribution. It is
related to the coefficient of variation by
CV = 1 / a1/2
or
a = 1 / (CV)2
(their parameter b is absorbed here by the requirement that time is scaled so
that the mean rate of evolution is 1 per unit time, which means that a = b).
As we consider cases in which the rates are less variable we should set a
larger and larger, as CV gets smaller and smaller.
If the user instead chooses the general Hidden Markov Model option,
they are first asked how many HMM rate categories there
will be (for the moment there is an upper limit of 9,
which should not be restrictive). Then
the program asks for the rates for each category. These rates are
only meaningful relative to each other, so that rates 1.0, 2.0, and 2.4
have the exact same effect as rates 2.0, 4.0, and 4.8. Note that an
HMM rate category
can have rate of change 0, so that this allows us to take into account that
there may be a category of amino acid positions that are invariant. Note that
the run time
of the program will be proportional to the number of HMM rate categories:
twice as
many categories means twice as long a run. Finally the program will ask for
the probabilities of a random amino acid position falling into each of these
regional rate categories. These probabilities must be nonnegative and sum to
1. Default
for the program is one category, with rate 1.0 and probability 1.0 (actually
the rate does not matter in that case).
If more than one HMM rate category is specified, then another
option, A, becomes
visible in the menu. This allows us to specify that we want to assume that
positions that have the same HMM rate category are expected to be clustered
so that there is autocorrelation of rates. The
program asks for the value of the average patch length. This is an expected
length of patches that have the same rate. If it is 1, the rates of
successive positions will be independent. If it is, say, 10.25, then the
chance of change to a new rate will be 1/10.25 after every position. However
the "new rate" is randomly drawn from the mix of rates, and hence could
even be the same. So the actual observed length of patches with the same
rate will be a bit larger than 10.25. Note below that if you choose
multiple patches, there will be an estimate in the output file as to
which combination of rate categories contributed most to the likelihood.
Note that the autocorrelation scheme we use is somewhat different
from Yang's (1995) autocorrelated Gamma distribution. I am unsure
whether this difference is of any importance -- our scheme is chosen
for the ease with which it can be implemented.
The C option allows user-defined rate categories. The user is prompted
for the number of user-defined rates, and for the rates themselves,
which cannot be negative but can be zero. These numbers, which must be
nonnegative (some could be 0),
are defined relative to each other, so that if rates for three categories
are set to 1 : 3 : 2.5 this would have the same meaning as setting them
to 2 : 6 : 5.
The assignment of rates to amino acid positions
is then made by reading a file whose default name is "categories".
It should contain a string of digits 1 through 9. A new line or a blank
can occur after any character in this string. Thus the categories file
might look like this:
122231111122411155
1155333333444
With the current options R, A, and C the program has a good
ability to infer different rates at different positions and estimate
phylogenies under a more realistic model. Note that Likelihood Ratio
Tests can be used to test whether one combination of rates is
significantly better than another, provided one rate scheme represents
a restriction of another with fewer parameters. The number of parameters
needed for rate variation is the number of regional rate categories, plus
the number of user-defined rate categories less 2, plus one if the
regional rate categories have a nonzero autocorrelation.
The G (global search) option causes, after the last species is added to
the tree, each possible group to be removed and re-added. This improves the
result, since the position of every species is reconsidered. It
approximately triples the run-time of the program.
The User tree (option U) is read from a file whose default name is
intree. The trees can be multifurcating. They must be
preceded in the file by a line giving the number of trees in the file.
If the U (user tree) option is chosen another option appears in
the menu, the L option. If it is selected,
it signals the program that it
should take any branch lengths that are in the user tree and
simply evaluate the likelihood of that tree, without further altering
those branch lengths. This means that if some branches have lengths
and others do not, the program will estimate the lengths of those that
do not have lengths given in the user tree. Note that the program RETREE
can be used to add and remove lengths from a tree.
The U option can read a multifurcating tree. This allows us to
test the hypothesis that a certain branch has zero length (we can also
do this by using RETREE to set the length of that branch to 0.0 when
it is present in the tree). By
doing a series of runs with different specified lengths for a branch we
can plot a likelihood curve for its branch length while allowing all
other branches to adjust their lengths to it. If all branches have
lengths specified, none of them will be iterated. This is useful to allow
a tree produced by another method to have its likelihood
evaluated. The L option has no effect and does not appear in the
menu if the U option is not used.
The W (Weights) option is invoked in the usual way, with only weights 0
and 1 allowed. It selects a set of positions to be analyzed, ignoring the
others. The positions selected are those with weight 1. If the W option is
not invoked, all positions are analyzed.
The Weights (W) option
takes the weights from a file whose default name is "weights". The weights
follow the format described in the main documentation file.
The M (multiple data sets) option will ask you whether you want to
use multiple sets of weights (from the weights file) or multiple data sets
from the input file.
The ability to use a single data set with multiple weights means that
much less disk space will be used for this input data. The bootstrapping
and jackknifing tool Seqboot has the ability to create a weights file with
multiple weights. Note also that when we use multiple weights for
bootstrapping we can also then maintain different rate categories for
different positions in a meaningful way. You should not use the multiple
data sets option without using multiple weights, you should not at the
same time use the user-defined rate categories option (option C).
The algorithm used for searching among trees uses
a technique invented by David Swofford
and J. S. Rogers. This involves not iterating most branch lengths on most
trees when searching among tree topologies, This is of necessity a
"quick-and-dirty" search but it saves much time. There is a menu option
(option S) which can turn off this search and revert to the earlier
search method which iterated branch lengths in all topologies. This will
be substantially slower but will also be a bit more likely to find the
tree topology of highest likelihood. If the Swofford/Rogers search
finds the best tree topology, the branch lengths inferred will
be almost precisely the same as they would be with the more thorough
search, as the maximization of likelihood with respect to branch
lengths for the final tree is not different in the two kinds of search.
OUTPUT FORMAT
The output starts by giving the number of species and the number of amino acid
positions.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of positions is printed, as well
as the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the menu
option to print them, with the sequences printed in
groups of ten amino acids. The
trees found are printed as an unrooted
tree topology (possibly rooted by outgroup if so requested). The
internal nodes are numbered arbitrarily for the sake of
identification. The number of trees evaluated so far and the log
likelihood of the tree are also given. Note that the trees printed out
have a trifurcation at the base. The branch lengths in the diagram are
roughly proportional to the estimated branch lengths, except that very short
branches are printed out at least three characters in length so that the
connections can be seen. The unit of branch length is the expected
fraction of amino acids changed (so that 1.0 is 100 PAMs).
A table is printed
showing the length of each tree segment (in units of expected amino acid
substitutions per position), as well as (very) rough confidence
limits on their lengths. If a confidence limit is
negative, this indicates that rearrangement of the tree in that region
is not excluded, while if both limits are positive, rearrangement is
still not necessarily excluded because the variance calculation on which
the confidence limits are based results in an underestimate, which makes
the confidence limits too narrow.
In addition to the confidence limits,
the program performs a crude Likelihood Ratio Test (LRT) for each
branch of the tree. The program computes the ratio of likelihoods with and
without this branch length forced to zero length. This done by comparing the
likelihoods changing only that branch length. A truly correct LRT would
force that branch length to zero and also allow the other branch lengths to
adjust to that. The result would be a likelihood ratio closer to 1. Therefore
the present LRT will err on the side of being too significant. YOU ARE
WARNED AGAINST TAKING IT TOO SERIOUSLY. If you want to get a better
likelihood curve for a branch length you can do multiple runs with
different prespecified lengths for that branch, as discussed above in the
discussion of the L option.
One should also
realize that if you are looking not at a previously-chosen branch but at all
branches, that you are seeing the results of multiple tests. With 20 tests,
one is expected to reach significance at the P = .05 level purely by
chance. You should therefore use a much more conservative significance level,
such as .05 divided by the number of tests. The significance of these tests
is shown by printing asterisks next to
the confidence interval on each branch length. It is important to keep
in mind that both the confidence limits and the tests
are very rough and approximate, and probably indicate more significance than
they should. Nevertheless, maximum likelihood is one of the few methods that
can give you any indication of its own error; most other methods simply fail to
warn the user that there is any error! (In fact, whole philosophical schools
of taxonomists exist whose main point seems to be that there isn't any
error, that the "most parsimonious" tree is the best tree by definition and
that's that).
The log likelihood printed out with the final tree can be used to perform
various likelihood ratio tests. One can, for example, compare runs with
different values of the relative rate of change in the active site and in
the rest of the protein to determine
which value is the maximum likelihood estimate, and what is the allowable range
of values (using a likelihood ratio test, which you will find described in
mathematical statistics books). One could also estimate the base frequencies
in the same way. Both of these, particularly the latter, require multiple runs
of the program to evaluate different possible values, and this might get
expensive.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the
rates at different amino acid positions, the
program also performs a statistical test of each of these trees against the
one with highest likelihood. If there are two user trees, the test
done is one which is due to Kishino and Hasegawa (1989), a version
of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of
log-likelihood differences between trees, taken across amino acid
positions. If the two
trees' means are more than 1.96 standard deviations different
then the trees are
declared significantly different. This use of the empirical variance of
log-likelihood differences is more robust and nonparametric than the
classical likelihood ratio test, and may to some extent compensate for the
any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods across
amino acid positions are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the highest log-likelihood exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the log-likelihoods of each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the log-likelihood differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one. However
the test is not available if we assume that there
is autocorrelation of rates at neighboring positions (option A) and is not
done in those cases.
The branch lengths printed out are scaled in terms of expected numbers of
amino acid substitutions, scaled so that the average rate of
change, averaged over all the positions analyzed, is set to 1.0.
if there are multiple categories of positions. This means that whether or not
there are multiple categories of positions, the expected fraction of change
for very small branches is equal to the branch length. Of course,
when a branch is twice as
long this does not mean that there will be twice as much net change expected
along it, since some of the changes occur in the same position and overlie or
even reverse each
other. The branch length estimates here are in terms of the expected
underlying numbers of changes. That means that a branch of length 0.26
is 26 times as long as one which would show a 1% difference between
the amino acid sequences at the beginning and end of the branch. But we
would not expect the sequences at the beginning and end of the branch to be
26% different, as there would be some overlaying of changes.
Confidence limits on the branch lengths are
also given. Of course a
negative value of the branch length is meaningless, and a confidence
limit overlapping zero simply means that the branch length is not necessarily
significantly different from zero. Because of limitations of the numerical
algorithm, branch length estimates of zero will often print out as small
numbers such as 0.00001. If you see a branch length that small, it is really
estimated to be of zero length.
Another possible source of confusion is the existence of negative values for
the log likelihood. This is not really a problem; the log likelihood is not a
probability but the logarithm of a probability. When it is
negative it simply means that the corresponding probability is less
than one (since we are seeing its logarithm). The log likelihood is
maximized by being made more positive: -30.23 is worse than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what amino acid position
categories contributed the most to the final likelihood. This combination of
HMM rate categories need not have contributed a majority of the likelihood,
just a plurality. Still, it will be helpful as a view of where the
program infers that the higher and lower rates are. Note that the
use in this calculations of the prior probabilities of different rates,
and the average patch length, gives this inference a "smoothed"
appearance: some other combination of rates might make a greater
contribution to the likelihood, but be discounted because it conflicts
with this prior information. See the example output below to see
what this printout of rate categories looks like.
A second list will also be printed out, showing for each position which
rate accounted for the highest fraction of the likelihood. If the fraction
of the likelihood accounted for is less than 95%, a dot is printed instead.
Option 3 in the menu controls whether the tree is printed out into
the output file. This is on by default, and usually you will want to
leave it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees
which are written onto the output tree file, rather than the trees
printed on the output file. To keep the output file from becoming too
large, it may be wisest to use option 3 to prevent trees being
printed onto the output file.
Option 4 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined
trees are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated
at each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species which
are the input sequences).
The symbol printed out is for the amino acid which accounts for the
largest fraction of the likelihood at that position.
In that table, if a position has an amino acid which
accounts for more than 95% of the likelihood, its symbol printed in capital
letters (W rather than w). One limitation of the current
version of the program is that when there are multiple HMM rates
(option R) the reconstructed amino acids are based on only the single
assignment of rates to positions which accounts for the largest amount of the
likelihood. Thus the assessment of 95% of the likelihood, in tabulating
the ancestral states, refers to 95% of the likelihood that is accounted
for by that particular combination of rates.
PROGRAM CONSTANTS
The constants defined at the beginning of the program include "maxtrees",
the maximum number of user trees that can be processed. It is small (100)
at present to save some further memory but the cost of increasing it
is not very great. Other constants
include "maxcategories", the maximum number of position
categories, "namelength", the length of species names in
characters, and three others, "smoothings", "iterations", and "epsilon", that
help "tune" the algorithm and define the compromise between execution speed and
the quality of the branch lengths found by iteratively maximizing the
likelihood. Reducing iterations and smoothings, and increasing epsilon, will
result in faster execution but a worse result. These values
will not usually have to be changed.
The program spends most of its time doing real arithmetic.
The algorithm, with separate and independent computations
occurring for each pattern, lends itself readily to parallel processing.
PAST AND FUTURE OF THE PROGRAM
This program is derived in version 3.6 by Lucas Mix from DNAML,
with which it shares
many of its data structures and much of its strategy.
TEST DATA SET
(Note that although these may look like DNA sequences, they are being
treated as protein sequences consisting entirely of alanine, cystine,
glycine, and threonine).
CONTENTS OF OUTPUT FILE (with all numerical options on)
(It was run with HMM rates having gamma-distributed rates
approximated by 5 rate categories,
with coefficient of variation of rates 1.0, and with patch length
parameter = 1.5. Two user-defined rate categories were used, one for
the first 6 positions, the other for the last 7, with rates 1.0 : 2.0.
Weights were used, with sites 1 and 13 given weight 0, and all others
weight 1.)
Amino acid sequence Maximum Likelihood method, version 3.6a3
5 species, 13 sites
Site categories are:
1111112222 222
Sites are weighted as follows:
0111111111 111
Jones-Taylor-Thornton model of amino acid change
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta ..G..C.... ..C
Gamma C.TT.C.T.. C.A
Delta GGTA.TT.GG CC.
Epsilon GGGA.CT.GG CCC
Discrete approximation to gamma distributed rates
Coefficient of variation of rates = 1.000000 (alpha = 1.000000)
States in HMM Rate of change Probability
1 0.264 0.522
2 1.413 0.399
3 3.596 0.076
4 7.086 0.0036
5 12.641 0.000023
Site category Rate of change
1 1.000
2 2.000
+Beta
|
| +Epsilon
| +-----------------------------3
1---------2 +-------------------Delta
| |
| +--------------------------Gamma
|
+-----------------Alpha
remember: this is an unrooted tree!
Ln Likelihood = -121.49044
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
1 Alpha 60.18362 ( zero, 135.65380) **
1 Beta 0.00010 ( zero, infinity)
1 2 32.56292 ( zero, 96.08019) *
2 3 141.85557 ( zero, 304.10906) **
3 Epsilon 0.00010 ( zero, infinity)
3 Delta 68.68682 ( zero, 151.95402) **
2 Gamma 89.79037 ( zero, 198.93830) **
* = significantly positive, P < 0.05
** = significantly positive, P < 0.01
Combination of categories that contributes the most to the likelihood:
1122121111 112
Most probable category at each site if > 0.95 probability ("." otherwise)
....1..... ...
Probable sequences at interior nodes:
node Reconstructed sequence (caps if > 0.95)
1 .AGGTCGCCA AAC
Beta AAGGTCGCCA AAC
2 .AggTCGCCA CAC
3 .GGATCTCGG CCC
Epsilon GGGATCTCGG CCC
Delta GGTATTTCGG CCT
Gamma CATTTCGTCA CAA
Alpha AACGTGGCCA AAT
This program carries out Fitch-Margoliash, Least Squares,
and a number of similar methods as described in the documentation
file for distance methods.
The options for FITCH are selected through the menu, which looks like
this:
Fitch-Margoliash method version 3.6a3
Settings for this run:
D Method (F-M, Minimum Evolution)? Fitch-Margoliash
U Search for best tree? Yes
P Power? 2.00000
- Negative branch lengths allowed? No
O Outgroup root? No, use as outgroup species 1
L Lower-triangular data matrix? No
R Upper-triangular data matrix? No
S Subreplicates? No
G Global rearrangements? No
J Randomize input order of species? No. Use input order
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
Most of the input options
(U, P, -, O, L, R, S, J, and M) are as given in
the documentation page for distance matrix programs, and their input format is
the same as given there. The
U (User Tree) option has one additional feature when the N (Lengths)
option is used. This menu option will appear only if the U (User Tree)
option is selected. If N (Lengths) is set to "Yes" then if any branch
in the user tree has a branch length, that branch will not have its
length iterated. Thus you can prevent all branches from having their
lengths changed by giving them all lengths in the user tree, or hold
only one length unchanged by giving only that branch a length (such
as, for example, 0.00). You may find program RETREE useful for
adding and removing branch lengths from a tree. This option can
also be used to compute the Average Percent Standard Deviation for a
tree obtained from NEIGHBOR, for comparison with trees obtained by
FITCH or KITSCH.
The D (methods) option allows choice between the Fitch-Margoliash
criterion and the Minimum Evolution method (Kidd and Sgaramella-Zonta, 1971;
Rzhetsky and Nei, 1993). Minimum Evolution (not to be confused with
parsimony) uses the Fitch-Margoliash criterion to fit branch lengths to each
topology, but then chooses topologies based on their total branch length
(rather than the goodness of fit sum of squares). There is no
constraint on negative branch lengths in the Minimum Evolution method;
it sometimes gives rather strange results, as it can like solutions
that have large negative branch lengths, as these reduce the total
sum of branch lengths!
Another input option available in FITCH that is not available in KITSCH
or NEIGHBOR
is the G (Global) option. G is the
Global search option. This causes, after the last species is added to
the tree, each possible group to be removed and re-added. This improves the
result, since the position of every species is reconsidered. It
approximately triples the run-time of the program. It is not an option in
KITSCH because it is the default and is always in force there. The
O (Outgroup) option is described in the main
documentation file of this package. The O option has no effect if the
tree is a user-defined tree (if the U option is in effect). The
U (User Tree) option requires an unrooted tree; that is, it require
that the tree have a trifurcation at its base:
((A,B),C,(D,E));
The output consists of an unrooted tree and the lengths of the
interior segments. The sum of squares is printed out, and if P = 2.0
Fitch and Margoliash's "average percent standard deviation" is also computed
and printed out. This is the sum of squares, divided by
N-2, and
then square-rooted and then multiplied by 100 (n is the number of
species on the tree):
APSD = ( SSQ / (N-2) )1/2 x 100.
where N is the total number of off-diagonal distance measurements that
are in the (square) distance matrix. If the S (subreplication) option
is in force it is instead the sum of the numbers of replicates in all the
non-diagonal
cells of the distance matrix. But if the L or R option is also in effect, so
that the distance matrix read in is lower- or upper-triangular, then the
sum of replicates is only over those cells actually read in. If S is not in
force, the number of replicates in
each cell is assumed to be 1, so that N is n(n-1),
where n is the number
of species. The APSD gives an indication of the average percentage
error. The number of trees examined is also printed out.
The constants
available for modification at the beginning of the program are:
"smoothings", which gives the number of passes through
the algorithm which adjusts the lengths of the segments of the tree so
as to minimize the sum of squares, "delta", which controls the size of
improvement in sum of squares that is used to control the number of
iterations improving branch lengths,
and "epsilonf",
which defines a small quantity needed in
some of the calculations. There is no feature saving multiply trees
tied for best,
partly because we do not expect exact ties except in cases where the branch
lengths make the nature of the tie obvious, as when a branch is of zero
length.
The algorithm can be slow. As the number of species
rises, so does the number of distances from each species to the others. The
speed of this algorithm will thus rise as the fourth power of the
number of species, rather than as the third power as do most of the
others. Hence it is expected to get very slow as the number of species
is made larger.
These programs are intended for the use of morphological
systematists who are dealing with discrete characters,
or by molecular evolutionists dealing with presence-absence data on
restriction sites. One of the programs (PARS) allows multistate
characters, with up to 8 states, plus the unknown state symbol "?".
For the others, the characters
are assumed to be coded into a series of (0,1) two-state characters. For
most of the programs there are two other states possible, "P", which
stands for the state of Polymorphism for both states (0 and 1), and "?",
which stands for the state of ignorance: it is the state "unknown", or
"does not apply". The state "P" can also be denoted by "B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching sequences
of character states
by Kluge and Farris (1969) for recoding a multistate character
into a series of two-state (0,1) characters. Suppose we had a character
with four states whose character-state tree had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We can
represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above character
state tree. Possession of one of the new states corresponds to whether or not
the old state had that arrow in its ancestry. Thus the first new state
corresponds to the bottommost arrow, which only state 3 has in its ancestry,
the second state to the rightmost of the top arrows, and the third state to
the leftmost top arrow. This coding will guarantee that the number of times
that states arise on the tree (in programs MIX, MOVE, PENNY and BOOT)
or the number of polymorphic states in a tree segment (in the Polymorphism
option of DOLLOP, DOLMOVE, DOLPENNY and DOLBOOT) will correctly
correspond to what would have been the case had our programs been able to take
multistate characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on unrooted
multistate characters as long as the connections between the states are known
and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE, DOLPENNY
and DOLBOOT the multistate recoding does not necessarily work properly, as it
may lead the program to reconstruct nonexistent state combinations such as
010. An example of this problem is given in my paper on alternative
phylogenetic methods (1979).
If you have multistate character data where the states are connected in a
branching "character state tree" you may want to do the binary recoding
yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for unordered
character states.
COMPARISON OF METHODS
The methods used in these programs make different assumptions about
evolutionary rates, probabilities of different kinds of events, and our
knowledge about the characters or about the character state trees.
Basic references on these assumptions are my 1979, 1981b and 1983b
papers, particularly the latter. The
assumptions of each method are briefly described in the documentation
file for the corresponding program. In most cases my assertions about what are
the assumptions of these methods are challenged by others, whose papers I also
cite at that point. Personally, I believe that they are wrong and I am
right. I must emphasize the importance of
understanding the assumptions underlying the methods you are using. No
matter how fancy the algorithms, how maximum the likelihood or how
minimum the number of steps, your results can only be as good as the
correspondence between biological reality and your assumptions!
INPUT FORMAT
The input format is as described in the general documentation file. The
input starts with a line containing the number of
species and the number of characters.
In PARS, each character can have up to 8 states plus a "?" state. In any
character, the first 8 symbols encountered will be taken to represent
these states. Any of the digits 0-9, letters A-Z and a-z, and even symbols
such as + and -, can be used (and in fact which 8 symbols are used can
be different in different characters).
In the other discrete characters programs the allowable states are,
0, 1, P, B, and ?. Blanks
may be included between the states (i. e. you can have a
species whose data is DISCOGLOSS0 1 1 0 1 1 1). It is possible for
extraneous information to follow the end of the character state data on
the same line. For example, if there were 7 characters in the data set,
a line of species data could read "DISCOGLOSS0110111 Hello there").
The discrete character data can continue to a new line whenever needed.
The characters are not in the "aligned" or "interleaved" format used by the
molecular sequence programs: they have the name and entire set of characters
for one species, then the name and entire set of characters for the next
one, and so on. This is known as the sequential format. Be particularly
careful when you use restriction sites
data, which can be in either the aligned or the sequential format for use in
RESTML but must be in the sequential format for these discrete character
programs.
For PARS the discrete character data can be in either Sequential or
Interleaved format; the latter is the default.
Errors in the input data will often be detected by the programs, and this will
cause them to issue an error message such as 'BAD OUTGROUP NUMBER: ' together
with information as to which species, character, or in this case outgroup
number is the incorrect one. The program will them terminate; you will have
to look at the data and figure out what went wrong and fix it. Often an error
in the data causes a lack of synchronization between what is in the data file
and what the program thinks is to be there. Thus a missing character may
cause the program to read part of the next species name as a character and
complain about its value. In this type of case you should look for the error
earlier in the data file than the point about which the program is
complaining.
OPTIONS GENERALLY AVAILABLE
Specific information on options will be given in the documentation
file associated with each program. However, some options occur in many
programs. Options are selected from the menu in each
program, but the Old Style programs CLIQUE and FACTOR require information to be put into
the beginning of the input file (Particularly the Ancestors, Factors, Weights,
and Mixtures options). The options information described here is for
the other programs. See the documentation page for CLIQUE and
FACTOR to find out how they get their options information.
The A (Ancestral states) option. This indicates that we are
specifying the ancestral states for each character. In the menu the
ancestors (A) option must be selected.
An ancestral states input file is read, whose default name is
ancestors. It contains
a line or lines giving the ancestral states for each character.
These may be 0, 1 or ?, the latter
indicating that the ancestral state is unknown.
An example is:
001??11
The ancestor information can be continued to a new line and can have blanks
between any of the characters in the same way that species character data
can.
In the program CLIQUE the ancestor is instead to be included as a
regular species and
no A option is available.
The F (Factors) option. This is used in programs MOVE, DOLMOVE,
and FACTOR. It specifies which binary characters correspond
to which multistate characters. To use the F option you
choose the F option in the program menu. After that the program
will read a factors file (default name factors
Which consists of a line or lines containing a symbol
for each binary character. The
symbol can be anything, provided that it is the same for binary characters
that correspond to the same multistate character, and changes between
multistate characters. A good practice is to make it the lower-order digit
of the number of the multistate character.
For example, if there were 20 binary characters that had been generated by
nine multistate characters having respectively 4, 3, 3, 2, 1, 2, 2, 2, and 1
binary factors you would make the factors file be:
11112223334456677889
although it could equivalently be:
aaaabbbaaabbabbaabba
All that is important is that the symbol
for each binary character change only when adjacent binary characters
correspond to different mutlistate characters. The factors
file contents
can continue to a new line at any time except during the initial characters
filling out the length of a species name.
In programs CLIQUE and FACTOR the factors information is given in
the Old Style system of putting that information into the input
data file. The method for doing so is described in the documentation
files for these programs. We hope to change this in the next
release to use an input factors file.
The J (Jumble) option. This causes the species to be entered into the
tree in a random order rather than in their order in the input file. The
program prompts you for a random number seed. This option is described in
the main documentation file.
The M (Multiple data sets) option. This has also been described in the
main documentation file. It is not to be confused with the M option specified
in the input file, which is the Mixture of methods option (yes, I know
this is confusing).
The O (outgroup) option. This has also already been discussed in the
general documentation file. It specifies the number of the particular species
which will be used as the outgroup in rerooting the final tree when it is
printed out. It will not have any effect if the tree is already rooted or is
a user-defined tree. This option is not available in DOLLOP, DOLMOVE,
or DOLPENNY, which always infer a rooted tree, or CLIQUE, which
requires you to work out the rerooting by hand. The menu selection will
cause you to be prompted for the number of the outgroup.
The T (threshold) option. This sets a threshold such that if the
number of steps counted in a character is higher than the threshold, it
will be taken to be the threshold value rather than the actual number of
steps. This option has already been described in the main documentation
file. The user is prompted for the threshold value. My 1981 paper
(Felsenstein, 1981b)
explains the logic behind the Threshold option, which is an attarctive
alternative to successive weighting of characters.
The U (User tree) option. This has already been described in the
main documentation file. For all of these programs user trees are to be
specified as bifurcating trees, even in the cases where the tree that
is inferred by the programs is to be regarded as unrooted.
The W (Weights) option. This allows us to specify weights on the
characters, including the possibility of omitting characters from the
analysis. It has already been described in the main documentation file. If
the Weights option is used there must be a W on the first line of the
input file.
The X (miXture) option. In the programs MIX, MOVE, and PENNY
the user can specify for each character which parsimony method is
in effect. This is done by selecting menu option X (not M) and having
an input mixture file, whose default name is mixture.
It contains a line or lines with and one letter for
each character. These letters are C or S if the character is to
be reconstructed according to Camin-Sokal parsimony, W or ? if the
character is to be reconstructed according to Wagner parsimony. So if
there are 20 characters the line giving the mixture might look like this:
WWWCC WWCWC
Note that blanks in the seqence of characters (after the first ones that
are as long as the species names) will be ignored, and the information
can go on to a new line at any point. So this could equally well have been
specified by
WW
CCCWWCWC
30! 1 2 1 1 1 2 1 3 1 1
40! 1
The numbers across the top and down the side indicate which character
is being referred to. Thus character 23 is column "3" of row "20"
and has 2 steps in this case.
I cannot emphasize too strongly that just because the tree diagram
which the program prints out contains a particular
branch DOES NOT MEAN
THAT WE HAVE EVIDENCE THAT THE BRANCH IS OF NONZERO LENGTH.
In program PARS the branches have lengths estimated and there
can be trifurcations, but in all other discrete characters programs
the procedure which prints out the tree cannot cope with a trifurcation, nor
can the internal data structures used in my programs. Therefore, even
when we have no resolution and a multifurcation, successive bifurcations
will be printed out, although some of the branches shown will in fact
actually be of zero length. To find out which, you will have to work out
character by character where the placements of the changes on the tree
are, under all possible ways that the changes can be placed on that
tree.
In PARS the trees are truly multifurcating, and the search is over both
bifurcating and multifurcating trees. A branch is retained in a tree only
if there is at least one character, under at least one possible most
parsimonious reconstruction of the placement of changes, that has a change in
that branch. This means that two branches can both be present which are,
however, not both in existence at the same time (in that there is no
most parsimonious reconstruction of changes n the characters that has changes
in both these branches at the same time).
In PARS, MIX, PENNY, DOLLOP, and DOLPENNY the trees will be (if the user selects
the option to see them)
accompanied by tables showing the reconstructed states of the characters in
the hypothetical ancestral nodes in the interior of the tree. This will enable
you to reconstruct where the changes were in each of the characters. In some
cases the state shown in an interior node will be "?", which means that either
0 or 1 would be possible at that point. In such cases you have to work out
the ambiguity by hand. A unique assignment of locations of changes is often
not possible in the case of the Wagner parsimony method. There may be multiple
ways of assigning changes to segments of the tree with that method. Printing
only one would be misleading, as it might imply that certain segments of the
tree had no change, when another equally valid assignment would put changes
there. It must be emphasized that all these multiple assignments have exactly
equal numbers of total changes, so that none is preferred over any other.
I have followed the convention of having
a "." printed out in the table of character states of the hypothetical
ancestral nodes whenever a state is 0 or 1 and its immediate ancestor is the
same. This has the effect of highlighting the places where changes might have
occurred and making it easy for the user to reconstruct all the alternative
patterns of the characters states in the hypothetical ancestral nodes.
In PARS you can, using the menu, turn off this dot-differencing
convention and see all states at all hypothetical ancestral nodes of the tree.
On the line in that table corresponding to each branch of the tree will also
be printed "yes", "no" or "maybe" as an answer to the question of whether this
branch is of nonzero length. If there is no evidence that any character has
changed in that branch, then "no" will be printed. If there is definite
evidence that one has changed, then "yes" will be printed. If the matter is
ambiguous, then "maybe" will be printed. You should keep in mind that all of
these conclusions assume that we are only interested in the assignment of
states that requires the least amount of change. In reality, the confidence
limit on tree topology usually includes many different topologies, and
presumably also then the confidence limits on amounts of change in branches
are also very broad.
In addition to the table showing numbers of events, a table may be printed out
showing which ancestral state causes the fewest events for each
occurred and making it easy for the user to reconstruct all the alternative
patterns of the characters states in the hypothetical ancestral nodes.
In PARS you can, using the menu, turn off this dot-differencing
convention and see all states at all hypothetical ancestral nodes of the tree.
On the line in that table corresponding to each branch of the tree will also
be printed "yes", "no" or "maybe" as an answer to the question of whether this
branch is of nonzero length. If there is no evidence that any character has
changed in that branch, then "no" will be printed. If there is definite
evidence that one has changed, then "yes" will be printed. If the matter is
ambiguous, then "maybe" will be printed. You should keep in mind that all of
these conclusions assume that we are only interested in the assignment of
states that requires the least amount of change. In reality, the confidence
limit on tree topology usually includes many different topologies, and
presumably also then the confidence limits on amounts of change in branches
are also very broad.
In addition to the table showing numbers of events, a table may be printed out
showing which ancestral state causes the fewest events for each
character. This will not always be done, but only when the tree is rooted and
some ancestral states are unknown. This can be used to infer states of
ancestors. For example, if you use the O (Outgroup) and A (Ancestral states)
options together, with at least some of the ancestral states being given as
"?", then inferences will be made for those characters, as the outgroup makes
the tree rooted if it was not already.
In programs MIX and PENNY, if you are using the Camin-Sokal parsimony option
with ancestral state "?" and it turns out that the program cannot decide
between ancestral states 0 and 1, it will fail to even attempt reconstruction
of states of the hypothetical ancestors, printing them all out as "." for
those characters. This is done for internal bookkeeping reasons -- to
reconstruct their changes would require a fair amount of additional code and
additional data structures. It is not too hard to reconstruct the internal
states by hand, trying the two possible ancestral states one after the
other. A similar comment applies to the use of ancestral state "?" in the
Dollo or Polymorphism parsimony methods (programs DOLLOP and DOLPENNY) which
also can result in a similar hesitancy to print the estimate of the states of
the hypothetical ancestors. In all of these cases the program will print "?"
rather than "no" when it describes whether there are any changes in a branch,
since there might or might not be changes in those characters which are not
reconstructed.
For further information see the documentation files for the
individual programs.
PHYLIPNEW-3.69.650/doc/treedist.html 0000664 0001750 0001750 00000027466 07712247476 013603 0000000 0000000
This program computes distances between trees. The distance that is
computed is the Symmetric Distance of Robinson and Foulds (1981). This
does not use branch length information, only the tree topologies. It
must also be borne in mind that the distance does not have any immediate
statistical interpretation -- we cannot say whether a larger distance is
significantly larger than a smaller one.
The Symmetric Distance is computed by considering each of the branches of
the two trees. Each branch divides the set of species into two groups --
the ones connected to one end of the branch and the ones connected to the
other. This makes a partition of the full set of species. (in Newick notation)
((A,C),(D,(B,E)))
has two internal branches. One induces the partition {A, C | B, D, E}
and the other induces the partition {A, C, D | B, E}. A different tree
with the same set of species,
(((A,D),C),(B,E)))
has internal branches that correspond to the two partitions {A, C, D | B, E}
and {A, D | B, C, E}. Note that the other branches, all of which are
external branches, induce partitions that separate one species from all the
others. Thus there are 5 partitions like this: {C | A, B, D, E} on each
of these trees. These are always present on all trees, provided that each
tree has each species at the end of its own branch.
The Symmetric Distance is simply a count of how many partitions there are,
among the two trees, that are on one tree and not on the other. In the
example above there are two partitions, {A, C | B, D, E} and {A, D | B, C, E},
each of which is present on only one of the two trees. The Symmetric
Distance between the two trees is therefore 2. When the two trees are
fully resolved bifurcating trees, their symmetric distance must be an even
number; it can range from 0 to twice the number of internal branches, which
for n species is 4n-6.
We have assumed that nothing is lost if the trees are treated as unrooted trees.
It is easy to define a counterpart to the Symmetric Distance for rooted trees.
each branch then defines a set of species, namely the clade defined by that
branch. Thus if the first of the two trees above were considered as a rooted
tree it would define the three clades {A, C}, {B, D, E}, and {B, E}. The
symmetric distance between two rooted trees is simply the count of the number
of clades that are defined by one but not by the other. For the second tree
the clades would be {A, D}, {B, C, E}, and {B, E}. The Symmetric Distance
between thee two rooted trees would then be 4.
Although the examples we have discussed have involved fully
bifurcating trees, the input trees can have multifurcations.
This can lead to distances that are odd numbers.
INPUT AND OPTIONS
The program reads one or two input tree files. If there is one input tree
file, its default name is intree. If there are two their default
names are intree and intree2. The tree files may either
have the number of trees on their first line, or not. If the number of
trees is given, it is actually ignored and all trees in the tree file
are considered, even if there are more trees than indicated by the number.
(This is a bug and it will be fixed in the future).
The options are selected from a menu, which looks like this:
Tree distance program, version 3.6a3
Settings for this run:
O Outgroup root: No, use as outgroup species 1
R Trees to be treated as Rooted: No
T Terminal type (IBM PC, ANSI, none): (none)
1 Print indications of progress of run: Yes
2 Tree distance submenu: Distance between adjacent pairs
Are these settings correct? (type Y or the letter for one to change)
The O option allows you to root the trees using an outgroup. It is specified
by giving its number, where the species are numbered in the order they
appear in the first tree. Outgroup-rooting all the trees does not
affect the unrooted Symmetric Distance, and if it is done and trees are
treated as rooted, the distances turn out to be the same as the unrooted
ones. Thus it is unlikely that you will find this option of interest.
The R option controls whether the Summetric Distance that is computed is
to treat the trees as unrooted or rooted. Unrooted is the default.
The terminal type (0) and progress (1) options do not need description here.
Option 2 controls how many tree files are read in, which trees are to
be compared, and how the output is to be presented. It causes
another menu to appear:
Tree Pairing Submenu:
A Distances between adjacent pairs in tree file.
P Distances between all possible pairs in tree file.
C Distances between corresponding pairs in one tree file and another.
L Distances between all pairs in one tree file and another.
Option A computes the distances between successive pairs of trees in the
tree input file -- between trees 1 and 2, trees 3 and 4, trees
5 and 6, and so on. If there are an odd number of trees in the input tree
file the last tree will be ignored and a warning message printed to
remind the user that nothing was done with it.
Option P computes distances between all pairs of trees in the input tree
file. Thus with 10 trees 10 x 10 = 100 distances will be computed,
including distances between each tree and itself.
Option C takes input from two tree files and cmputes distances between
corresponding members of the two tree files. Thus distances will be
computed between tree 1 of the first tree file and tree 1 of the second one,
between tree 2 of the first file and tree 2 of the second one, and so on.
If the number of trees in the two files differs, the extra trees in the
file that has more of them are ignored and a warning is printed out.
Option L computes distances between all pairs of trees, where one tree is
taken from one tree file and the other from the other tree file. Thus if
the first tree file has 7 trees and the second has 5 trees, 7 x 5 = 35
different distances will be computed. Note -- this option seems not
to work at the moment. We hope to fix this soon.
If option 2 is not selected, the program defaults to looking at one tree
file and computing distances of adjacent pairs (so that option A is
the default).
OUTPUT
The results of the analysis are written onto an output file whose
default file name is outfile.
If any of the four types of analysis are selected, the program asks the
user how they want the results presented. Here is that menu for options
P or L:
Distances output options:
F Full matrix.
V One pair per line, verbose.
S One pair per line, sparse.
Choose one: (F,V,S)
The Full matrix (choice F) is a table showing all distances. It is
written onto the output file. The table is presented as groups of
10 columns. Here is the Full matrix for the 12 trees in the input
tree file which is given as an example at the end of this page.
The Full matrix is only available for analyses P and L (not for A or C).
Option V (Verbose) writes one distance per line. The Verbose
output is the default. Here it is for the example data set given below:
Tree distance program, version 3.6a3
Symmetric differences between adjacent pairs of trees:
Trees 1 and 2: 4
Trees 3 and 4: 10
Trees 5 and 6: 4
Trees 7 and 8: 4
Trees 9 and 10: 4
Trees 11 and 12: 10
Option S (Sparse or terse) is similar except that all that is
given on each line are the numbers of the two trees and the distance,
separated by blanks. This may be a convenient format if you want to
write a program to read these numbers in, and you want to spare yourself
the effort of having the program wade through the words on each line
in the Verbose output.
The first four lines of the Sparse output are titles that your program would
want to skip past. Here is the Sparse output for the example trees.
Tree distance program, version 3.6
Symmetric differences between adjacent pairs of trees:
1 2 4
3 4 10
5 6 4
7 8 4
9 10 4
11 12 10
CREDITS AND FUTURE
TREEDIST was written by Dan Fineman. In the future we hope to expand it
to consider a distance based on branch lengths as well as tree topologies.
The Branch Score distance defined by Kuhner and Felsenstein (1994) is
the one we have in mind (the Branch Score defined by them is actually
the square of the distance). We also hope to compute a distance based on
quartets shared and not shared by trees (implicit in the work of Estabrook, McMorris, and
Meacham, 1985).
The output from default settings for this test set is given above (it is the
Verbose output example).
PHYLIPNEW-3.69.650/doc/factor.html 0000664 0001750 0001750 00000031124 07712247475 013217 0000000 0000000
Note: Factor is an Old Style program.
This means that it takes some of its options information, notably the
Ancestral states and Factors
options from the input file rather than from separate files of their own
as the New Style programs in this version of PHYLIP do.
Programmed by C. Meacham, Botany, Univ. of Georgia, Athens, Georgia
.ce
(current address: University of California, Berkeley, California 94720)
.ce
additional code and documentation by Joe Felsenstein
This program factors a data set that contains multistate
characters, creating a data set consisting entirely of binary (0,1)
characters that, in turn, can be used as input to any of the other
discrete character programs in this package, except for PARS.
Besides this primary
function, FACTOR also provides an easy way of deleting characters from a
data set. The input format for FACTOR is very similar to the input
format for the other discrete character programs except for the
addition of character-state tree descriptions.
Note that this program has no way of converting an unordered multistate
character into binary characters. This is a weakness of the Old Style
discrete characters programs in this package.
Fortunately, PARS has joined the package, and it enables unordered
multistate characters, in which any state can change to any other in
one step, to be analyzed with parsimony.
FACTOR is really for a different case, that in which there are
multiple states related on a "character state tree", which specifies
for each state which other states it can change to. That graph of
states is assumed to be a tree, with no loops in it.
The first line of the input file should contain the number of
species and the number of multistate characters. This
first line is followed by the lines describing the character-state
trees, one description per line. The species information constitutes
the last part of the file. Any number of lines may be used for a single
species.
FIRST LINE
The first line is free format with the number of species first,
separated by at least one blank (space) from the number of multistate
characters, which in turn is separated by at least one blank from the
options, if present.
OPTIONS
The options are selected from a menu that looks like this:
Factor -- multistate to binary recoding program, version 3.6a3
Settings for this run:
A put ancestral states in output file? No
F put factors information in output file? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print indications of progress of run Yes
Are these settings correct? (type Y or the letter for one to change)
The options particular to this program are:
A
Choosing the A (Ancestors) options toggles on and off the setting
that causes a line to be written in the output that
describes the states of the ancestor as indicated by the
character-state tree descriptions (see below). If the ancestral
state is not specified by a particular character-state tree,
a "?" signifying an unknown character state will be written.
The multistate characters are factored in such a way that the
ancestral state in the factored data set will always be "0".
The ancestor line does not get counted as a species.
F
Choosing the F (Factors) option toggles on and off
a setting that will cause a "FACTORS" line to
be written in the output.
This line will indicate to other programs which factors came
from the same multistate character. Of the programs currently in
the package only SEQBOOT, MOVE, and DOLMOVE use this information.
CHARACTER-STATE TREE DESCRIPTIONS
The character-state trees are described in free format. The
character number of the multistate character is given first followed
by the description of the tree itself. Each description must be
completed on a single line. Each character that is to be factored must
have a description, and the characters must be described in the order
that they occur in the input, that is, in numerical order.
The tree is described by listing the pairs of character states that
are adjacent to each other in the character-state tree. The two
character states in each adjacent pair are separated by a colon (":").
If character fifteen has this character state tree for possible states
"A", "B", "C", and "D":
A ---- B ---- C
|
|
|
D
then the character-state tree description would be
15 A:B B:C D:B
Note that either symbol may appear first. The ancestral state is
identified, if desired, by putting it "adjacent" to a period. If we
wanted to root character fifteen at state C:
A <--- B <--- C
|
|
V
D
we could write
15 B:D A:B C:B .:C
Both the order in which the pairs are listed and the order of the
symbols in each pair are arbitrary. However, each pair may only appear
once in the list. Any symbols may be used for a character state in the
input except the character that signals the connection between two states (in
the distribution copy this is set to ":"), ".", and, of course, a
blank. Blanks are ignored
completely in the tree description so that even B:DA:BC:B.:C or
B : DA : BC : B. : C would be equivalent to the above example.
However, at least one blank must separate the character number from the
tree description.
DELETING CHARACTERS FROM A DATA SET
If no description line appears in the input for a particular
character, then that character will be omitted from the output. If the
character number is given on the line, but no character-state tree is
provided, then the symbol for the character in the input will be copied
directly to the output without change. This is useful for characters
that are already coded "0" and "1". Characters can be deleted from a
data set simply by listing only those that are to appear in the output.
TERMINATING THE LIST OF TREE DESCRIPTIONS
The last character-state tree description should be followed by a
line containing the number "999". This terminates processing of the
trees and indicates the beginning of the species information.
SPECIES INFORMATION
The format for the species information is basically identical to
the other discrete character programs. The first ten character positions
are allotted to the species name (this value may be changed by altering
the value of the constant nmlngth at the beginning of the program). The
character states follow and may be continued to as many lines as
desired. There is no current method for indicating polymorphisms. It is
possible to either put blanks between characters or not.
There is a method for indicating uncertainty about states. There is
one character value that stands for "unknown". If this appears in
the input data then "?" is written out in all the corresponding
positions in the output file. The character value that designates
"unknown" is given in the constant unkchar at the beginning of the
program, and can be changed by changing that constant. It is set to
"?" in the distribution copy.
OUTPUT
The first line of output will contain the number of species and
the number of binary characters in the factored data set followed by
the letter "A" if the A option was specified in the input. If option
F was specified, the next line will begin "FACTORS". If option A was
specified, the line describing the ancestor will follow next. Finally,
the factored characters will be written for each species in the format
required for input by the other discrete programs in the package. The
maximum length of the output lines is 80 characters, but this maximum
length can be changed prior to compilation.
In fact, the format of the output file for the A and F options is not
correct for the current release of PHYLIP. We need to change their
output to write a factors file and an ancestors file instead of
putting the Factors and Ancestors information into the data file.
ERRORS
The output should be checked for error messages. Errors will occur
in the character-state tree descriptions if the format is incorrect
(colons in the wrong place, etc.), if more than one root is specified,
if the tree contains loops (and hence is not a tree), and if the tree is
not connected, e.g.
A:B B:C D:E
describes
A ---- B ---- C D ---- E
This "tree" is in two unconnected pieces. An error will also occur if a symbol
appears in the data set that is not in the tree description for that
character. Blanks at the end of lines when the species information
is continued to a new line will cause this kind of error.
CONSTANTS AVAILABLE TO BE CHANGED
At the beginning of the program a number of
are available to be changed to accomodate larger data sets. These are
"maxstates", "maxoutput", "sizearray", "factchar" and "unkchar". The
constant "maxstates"
gives the maximum number of states per character (set at 20 in the
distribution copy). The constant "maxoutput"
gives the maximum width of a line in the output file (80 in the
distribution copy). The constant "sizearray"
must be less than the sum of squares
of the numbers of states in the characters. It is initially set to
set to 2000, so that although 20 states are allowed (at the initial
setting of maxstates) per character, there cannot be 20 states in all
of 100 characters.
Particularly important constants are "factchar" and "unkchar"
which are not numerical
values but a character. Initially set to the colon ":",
"factchar" is the character that will be used to separate states in the input of character
state trees. It can be changed by changing this
constant. (We could have used a hyphen ("-") but didn't because that would make the
minus-sign ("-") unavailable as a character state in +/- characters).
The constant "unkchar"
is the character value in the input data that
indicates that the state is unknown. It is set to "?" in the
distribution copy. If your computer is one that lacks the colon ":" in its
character set or uses a nonstandard character code such as EBCDIC, you
will want to change the constant "factchar".
INPUT AND OUTPUT FILES
The input file for the program has the default file name "infile"
and the output file, the one that has the binary character state data,
has the name "outfile".
4 species; 6 characters; A option on
A ---- B ---- C
B ---> A
Character 3 deleted; 4 unchanged
0 ---> 1 ---> 2
% <--- # ---> $
Signals end of trees
Species information begins
5 species (incl. anc.); 8 factors
Chars. 1 and 2 come from old number 1
Char. 3 comes from old number 2
Char. 4 is old number 4
Chars. 5 and 6 come from old number 5
Chars. 7 and 8 come from old number 6
This program implements the compatibility method for DNA sequence
data. For a four-state character without a character-state tree, as in
DNA sequences, the usual clique theorems cannot be applied. The
approach taken in this program is to directly evaluate each tree
topology by counting how many substitutions are needed in each site,
comparing this to the minimum number that might be needed (one less than
the number of bases observed at that site), and then evaluating the
number of sites which achieve the minimum number. This is the
evaluation of the tree (the number of compatible sites), and the
topology is chosen so as to maximize that number.
Compatibility methods originated with Le Quesne's (1969) suggestion that
one ought to look for trees supported by the largest number of perfectly
fitting (compatible) characters. Fitch (1975) showed by counterexample that
one could not use the pairwise compatibility methods used in CLIQUE to
discover the largest clique of jointly compatible characters.
The assumptions of this method are similar to those of CLIQUE. In
a paper in the Biological Journal of the Linnean Society (1981b)
I discuss this matter extensively. In effect, the assumptions are that:
Each character evolves independently.
Different lineages evolve independently.
The ancestral base at each site is unknown.
The rates of change in most sites over the time spans involved
in the the divergence of the group are very small.
A few of the sites have very high rates of change.
We do not know in advance which are the high and which the low
rate sites.
That these are the assumptions of compatibility methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing
view arguing that arguments such as mine are invalid
and that parsimony (and perhaps compatibility) methods make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b, 1988), but also read the exchange between Felsenstein and Sober (1986).
There is, however, some reason to believe that the present criterion is not the
proper way to correct for the presence of some sites with high rates of
change in nucleotide sequence data. It can be argued that sites showing more
than two nucleotide states, even if those are compatible with the other sites,
are also candidates for sites with high rates of change. It might then be more
proper to use DNAPARS with the Threshold option with a threshold value of 2.
Change from an occupied site to a gap is counted as one
change. Reversion from a gap to an occupied site is allowed and is also
counted as one change. Note that this in effect assumes that a gap
N bases long is N separate events. This may be an overcorrection. When
we have nonoverlapping gaps, we could instead code a gap as a
single event by changing all but the first "-" in the gap into "?" characters.
In this way only the first base of the gap causes the program to infer a
change.
The input data is standard. The first line of the input file contains the
number of species and the number of sites.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The options are selected using an interactive menu. The menu looks like this:
DNA compatibility algorithm, version 3.6a3
Settings for this run:
U Search for best tree? Yes
J Randomize input order of sequences? No. Use input order
O Outgroup root? No, use as outgroup species 1
W Sites weighted? No
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print steps & compatibility at sites No
5 Print sequences at all nodes of tree No
6 Write out trees onto tree file? Yes
Are these settings correct? (type Y or the letter for one to change)
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The options U, J, O, W, M, and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
The O (outgroup) option has no effect if the U (user-defined tree) option
is in effect. The user-defined trees (option U) fed in must be strictly
bifurcating, with a two-way split at their base.
The interpretation of weights (option W) in the case of a compatibility method
is that they count how many times the character (in this case the site) is
counted in the analysis. Thus a character can be dropped from the
analysis by assigning it zero weight. On the other hand, giving it a
weight of 5 means that in any clique it is in, it is counted as 5
characters when the size of the clique is evaluated. Generally, weights
other than 0 or 1 do not have much meaning when dealing with DNA sequences.
Output is standard: if option 1 is toggled on, the data is printed out,
with the convention that "." means "the same as in the first species".
Then comes a list of equally parsimonious trees, and (if option 2 is
toggled on) a table of the
number of changes of state required in each character. If option 5 is toggled
on, a table is printed
out after each tree, showing for each branch whether there are known to be
changes in the branch, and what the states are inferred to have been at the
top end of the branch. If the inferred state is a "?" or one of the IUB
ambiguity symbols, there will be multiple
equally-parsimonious assignments of states; the user must work these out for
themselves by hand. A "?" in the reconstructed states means that in
addition to one or more bases, a gap may or may not be present. If
option 6 is left in its default state the trees
found will be written to a tree file, so that they are available to be used
in other programs.
If the U (User Tree) option is used and more than one tree is supplied,
the program also performs a statistical test of each of these trees against the
one with highest likelihood. If there are two user trees, the test
done is one which is due to Kishino and Hasegawa (1989), a version
of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of weighted
compatibility differences between trees, taken across sites. If the two
trees compatibilities are more than 1.96 standard deviations different then
the trees are declared significantly different.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of weighted
compatibilities of sites are computed for all pairs of trees. To
test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected compatibility,
compatibilities for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the highest compatibility exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the compatibility of each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the compatibility differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
The algorithm is a straightforward modification of DNAPARS, but with
some extra machinery added to calculate, as each species is added, how
many base changes are the minimum which could be required at that site. The
program runs fairly quickly.
The constants
which can be changed at the beginning of the program are:
the name length "nmlngth",
"maxtrees", the maximum number of trees which the program will store for output,
and "maxuser",
the maximum number of user trees that can be used in the paired sites test.
SEQBOOT is a general bootstrapping and data set translation tool. It is intended to allow you to
generate multiple data sets that are resampled versions of the input data
set. Since almost all programs in the package can analyze these multiple
data sets, this allows almost anything in this package to be bootstrapped,
jackknifed, or permuted. SEQBOOT can handle molecular sequences,
binary characters, restriction sites, or gene frequencies. It
can also convert data sets between Sequential and Interleaved
format, and into NEXUS and a new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some method
in the package, you may need to use three programs. First, you need to run
SEQBOOT to take the original data set and produce a large number of
bootstrapped or jackknifed data
sets (somewhere between 100 and 1000 is usually adequate).
Then you need to find the phylogeny estimate for
each of these, using the particular method of interest. For example, if
you were using DNAPARS you would first run SEQBOOT and make a file with 100
bootstrapped data sets. Then you would give this file the proper name to
have it be the input file for DNAPARS. Running DNAPARS with the M (Multiple
Data Sets) menu choice and informing it to expect 100 data sets, you
would generate a big output file as well as a treefile with the trees from
the 100 data sets. This treefile could be renamed so that it would serve
as the input for CONSENSE. When CONSENSE is run the majority rule consensus
tree will result, showing the outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer than
a run of a single bootstrap program with the same original data and the same
number of replicates. This is not very hard and allows bootstrapping on many of
the methods in
this package. The same steps are necessary with all of them. Doing things
this way some of the intermediate files (the tree file from the DNAPARS
run, for example) can be used to summarize the results of the bootstrap in
other ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add one extra
step to this, calculating distance matrices from each of the replicate data
sets, using DNADIST or GENDIST. So (for example) you would run SEQBOOT, then
run DNADIST using the output of SEQBOOT as its input, then run (say) NEIGHBOR
using the output of DNADIST as its input, and then run CONSENSE using the
tree file from NEIGHBOR as its input.
The resampling methods available are three:
The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me (Felsenstein, 1985b;
see also Penny and Hendy, 1985).
It involves creating a new data set by sampling N characters randomly
with replacement, so that the resulting data set has the same size as the
original, but some characters have been left out and others are duplicated.
The random variation of the results from analyzing these bootstrapped
data sets can be shown statistically to be typical of the variation that
you would get from collecting new data sets. The method assumes that the
characters evolve independently, an assumption that may not be realistic
for many kinds of data.
Block-bootstrapping. One pattern of departure from indeopendence
of character evolution is correlation of evolution in adjacent characters.
When this is thought to have occurred, we can correct for it by samopling,
not individual characters, but blocks of adjacent characters. This is
called a block bootstrap and was introduced by Künsch (1989). If the
correlations are believed to extend over some number of characters, you
choose a block size, B, that is larger than this, and choose
N/B blocks of size B. In its implementation here the
block bootstrap "wraps around" at the end of the characters (so that if a
block starts in the last B-1 characters, it continues by wrapping
around to the first character after it reaches the last character). Note also
that if you have a DNA sequence data set of an exon of a coding region, you
can ensure that equal numbers of first, second, and third coding positions
are sampled by using the block bootstrap with B = 3.
Delete-half-jackknifing. This alternative to the bootstrap involves
sampling a random half of the characters, and including them in the data
but dropping the others. The resulting data sets are half the size of the
original, and no characters are duplicated. The random variation from
doing this should be very similar to that obtained from the bootstrap.
The method is advocated by Wu (1986). It was mentioned by me in my
bootstrapping paper (Felsenstein, 1985b), and has been available for many
years in this program as an option. Jackknifing is advocated by
Farris et. al. (1996) but as deleting a fraction 1/e (1/2.71828). This
retains too many characters and will lead to overconfidence in the
resulting groups.
Permuting species within characters. This method of resampling (well, OK,
it may not be best to call it resampling) was introduced by Archie (1989)
and Faith (1990; see also Faith and Cranston, 1991). It involves permuting the
columns of the data matrix
separately. This produces data matrices that have the same number and kinds
of characters but no taxonomic structure. It is used for different purposes
than the bootstrap, as it tests not the variation around an estimated tree
but the hypothesis that there is no taxonomic structure in the data: if
a statistic such as number of steps is significantly smaller in the actual
data than it is in replicates that are permuted, then we can argue that there
is some taxonomic structure in the data (though perhaps it might be just a
pair of sibling species).
The data input file is of standard form for molecular sequences (either in
interleaved or sequential form), restriction sites, gene frequencies, or
binary morphological characters.
When the program runs it first asks you for a random number seed. This should
be an integer greater than zero (and probably less than 32767) and which is
of the form 4n+1, that is, it leaves a remainder of 1 when divided by 4. This
can be judged by looking at the last two digits of the integer (for instance
7651 is not of form 4n+1 as 51, when divided by 4, leaves the remainder 3).
The random number seed is used to start the random number generator.
If the randum number seed is not odd, the program will request it again.
Any odd number can be used, but may result in a random number sequence that
repeats itself after less than the full one billion numbers. Usually this
is not a problem. As the random numbers appear to be unpredictable,
there is no such thing as a "good" seed -- the numbers produced from one
seed are indistinguishable from those produced by another, and it is
not true that the numbers produced from one seed (say 4533) are similar to
those produced from a nearby seed (say 4537).
Then the program shows you a menu to allow you to choose options. The menu
looks like this:
Bootstrapping algorithm, version 3.6a3
Settings for this run:
D Sequence, Morph, Rest., Gene Freqs? Molecular sequences
J Bootstrap, Jackknife, Permute, Rewrite? Bootstrap
B Block size for block-bootstrapping? 1 (regular bootstrap)
R How many replicates? 100
W Read weights of characters? No
C Read categories of sites? No
F Write out data sets or just weights? Data sets
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
Y to accept these or type the letter for one to change
The user selects options by typing one of the letters in the left column,
and continues to do so until all options are correctly set. Then the
program can be run by typing Y.
It is important to select the correct data type (the D selection). Each
time D is typed the program will change data type, proceeding successively
through Molecular Sequences, Discrete Morphological Characters, Restriction
Sites, and Gene Frequencies. Some of these will cause additional entries
to appear in the menu. If Molecular Sequences or Restriction Sites settings
and chosen the I (Interleaved)
option appears in the menu (and as Molecular Sequences are also the default,
it therefore appears in the first menu). It is the usual
I option discussed in the Molecular Sequences document file and in the main
documentation files for the package, and is on by default.
If the Restriction Sites option is chosen the menu option E appears, which
asks whether the input file contains a third number on the first line of
the file, for the number of restriction enzymes used to detect these sites.
This is necessary because data sets for RESTML need this third number, but
other programs do not, and SEQBOOT needs to know what to expect.
If the Gene Frequencies option is chosen an menu option A appears which allows
the user to specify that all alleles at each locus are in the input file.
The default setting is that one allele is absent at each locus.
The J option allows the user to select Bootstrapping, Delete-Half-Jackknifing,
or the Archie-Faith permutation of species within characters. It changes
successively among these three each time J is typed.
The B option selects the Block Bootstrap. When you select option B the program
will ask you to enter the block length. When the block length is 1,
this means that we are doing regular bootstrapping rather than
block-bootstrapping.
The R option allows the user to set the number of replicate data sets.
This defaults to 100. Most statisticians would be happiest with 1000 to
10,000 replicates in a bootstrap, but 100 gives a rough picture. You
will have to decide this based on how long a running time you are willing to
tolerate.
The W (Weights) option allows weights to be read
from a file whose default name is "weights". The weights
follow the format described in the main documentation file.
Weights can only be 0 or 1, and act to select
the characters (or sites) that will be used in the resampling, the others
being ignored and always omitted from the output data sets.
Note: At present, if you use W together with the F (just weights)
option, you write a file of weights, but with only weights for the
sites that had input weights of 1, the others being omitted. Thus if
you had 100 characters, and gave 60 of them weights of 1, when you
produce the output weights these will only have 60 weights, not 100.
Thus they could only be used together with a data file that had been
edited to remove the sites that you gave 0 weights to. This is
clumsy and we need to correct it.
The C (Categories) option can be used with molecular sequence programs to
allow assignment of sites or amino acid positions to user-defined rate
categories. The assignment of rates to
sites is then made by reading a file whose default name is "categories".
It should contain a string of digits 1 through 9. A new line or a blank
can occur after any character in this string. Thus the categories file
might look like this:
122231111122411155
1155333333444
The only use of the Categories information in SEQBOOT is that they
are sampled along with the sites (or amino acid positions) and are
written out onto a file whose default name is "outcategories",
which has one set of categories information for each bootstrap
or jackknife replicate.
The F option is a particularly important one. It is used whether to
produce multiple output files or multiple weights. If your
data set is large, a file with (say) 1000 such data sets can be very
large and may use up too much space on your system. If you choose
the F option, the program will instead produce a weights file with
multiple sets of weights. The default name of this file is "outweights".
Except for some programs that cannot handle multiple sets of
weights,
the programs have an M (multiple data sets) option that asks the
user whether to use multiple data sets or multiple sets of weights.
If the latter is selected when running those programs, they
read one data set, but analyze it multiple times, each time reading a new
set of weights. As both bootstrapping and jackknifing can be thought of
as reweighting the characters, this accomplishes the same thing (the
multiple weights option is not available for Archie/Faith permutation).
As the file with multiple sets of weights is much smaller than a file with
multiple data sets, this can be an attractive way to save file space.
When multiple sets of weights is chosen, they reflect the sampling as
well as any set of weights that was read in, so that you can use
SEQBOOT's W option as well.
The 0 (Terminal type) option is the usual one.
Input File
The data files read by SEQBOOT are the standard ones for the various kinds of
data. For molecular sequences the sequences may be either interleaved or
sequential, and similarly for restriction sites. Restriction sites data
may either have or not have the third argument, the number of restriction
enzymes used. Discrete morphological
characters are always assumed to be in sequential format. Gene frequencies
data start with the number of species and the number of loci, and then
follow that by a line with the number of alleles at each locus. The data for
each locus may either have one entry for each allele, or omit one allele at
each locus. The details of the formats are given in the main documentation
file, and in the documentation files for the groups of programs.
The only option that can be present in the
input file is F (Factors), the latter only in the case of
binary (0,1) characters. The Factors
option allows us to specify that groups of binary characters represent
one multistate character. When sampling is done they will be sampled or
omitted together, and when permutations of species are done they will all
have the same permutation, as would happen if they really were just one
column in the data matrix. For futher description of the F (Factors) option
see the Discrete Characters Programs documentation file.
Output
The output file will contain the data sets generated by the resampling
process. Note that, when Gene Frequencies data is used or when
Discrete Morphological characters with the Factors option are used,
the number of characters in each data set may vary. It may also vary
if there are an odd number of characters or sites and the Delete-Half-Jackknife
resampling method is used, for then there will be a 50% chance of choosing
(n+1)/2 characters and a 50% chance of choosing (n-1)/2 characters.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these data
avoid any result which is sensitive to
the input order of species from showing up repeatedly
and thus appearing to have evidence in its favor.
The numerical options 1 and 2 in the menu also affect the output file.
If 1 is chosen (it is off by default) the program will print the original
input data set on the output file before the resampled data sets. I cannot
actually see why anyone would want to do this. Option 2 toggles the
feature (on by default) that prints out up to 20 times during the resampling
process a notification that the program has completed a certain number of
data sets. Thus if 100 resampled data sets are being produced, every 5
data sets a line is printed saying which data set has just been completed.
This option should be turned off if the program is running in background and
silence is desirable. At the end of execution the program will always (whatever
the setting of option 2) print
a couple of lines saying that output has been written to the output file.
Size and Speed
The program runs moderately quickly, though more slowly when the Permutation
resampling method is used than with the others.
Future
I hope in the future to include code to pass on the Ancestors
option from the input file (for use in programs MIX and DOLLOP)
to the output file, a serious
omission in the current version.
This program implements the maximum likelihood method for DNA
sequences under the constraint that the trees estimated must be
consistent with a molecular clock. The molecular clock is the
assumption that the tips of the tree are all equidistant, in branch
length, from its root. This program is indirectly related to DNAML.
Details of the algorithm are not yet published, but many aspects
of it are similar to DNAML, and these are published in
the paper by Felsenstein and Churchill (1996).
The model of base substitution allows the expected frequencies
of the four bases to be unequal, allows the expected frequencies of
transitions and transversions to be unequal, and has several
ways of allowing different rates of evolution at
different sites.
The assumptions of the model are:
Each site in the sequence evolves independently.
Different lineages evolve independently.
There is a molecular clock.
Each site undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of occurrence)
which we specify.
All relevant sites are included in the sequence, not just those that
have changed or those that are "phylogenetically informative".
A substitution consists of one of two sorts of events:
(a)
The first kind
of event consists of the replacement of the existing base by a base
drawn from a pool of purines or a pool of pyrimidines (depending on
whether the base being replaced was a purine or a pyrimidine). It can
lead either to no change or to a transition.
(b)
The second kind of
event consists of the replacement of the existing base
by a base drawn at random from a pool of bases at known
frequencies, independently of the identity of the base which
is being replaced. This could lead either to a no change, to a transition
or to a transversion.
The ratio of the two
purines in the purine replacement pool is the same as their ratio in the
overall pool, and similarly for the pyrimidines.
The ratios of transitions to transversions can be set by the
user. The substitution process can be diagrammed as follows:
Suppose that you specified A, C, G, and T base frequencies of
0.24, 0.28, 0.27, and 0.21.
First kind of event:
Determine whether the existing base is a purine or a pyrimidine.
Draw from the proper pool:
Purine pool: Pyrimidine pool:
| | | |
| 0.4706 A | | 0.5714 C |
| 0.5294 G | | 0.4286 T |
| (ratio is | | (ratio is |
| 0.24 : 0.27) | | 0.28 : 0.21) |
|_______________| |_______________|
Second kind of event:
Draw from the overall pool:
| |
| 0.24 A |
| 0.28 C |
| 0.27 G |
| 0.21 T |
|__________________|
Note that if the existing base is, say, an A, the first kind of event has
a 0.4706 probability of "replacing" it by another A. The second kind of
event has a 0.24 chance of replacing it by another A. This rather
disconcerting model is used because it has nice mathematical properties that
make likelihood calculations far easier. A closely similar, but not
precisely identical model having different rates of transitions and
transversions has been used by Hasegawa et. al. (1985b). The transition
probability formulas for the current model were given (with my
permission) by Kishino and Hasegawa (1989). Another explanation is
available in the paper by Felsenstein and Churchill (1996).
Note the assumption that we are looking at all sites, including those
that have not changed at all. It is important not to restrict attention
to some sites based on whether or not they have changed; doing that
would bias branch lengths by making them too long, and that in turn
would cause the method to misinterpret the meaning of those sites that
had changed.
This program uses a Hidden Markov Model (HMM)
method of inferring different rates of evolution at different sites. This
was described in a paper by me and Gary Churchill (1996). It allows us to
specify to the program that there will be
a number of different possible evolutionary rates, what the prior
probabilities of occurrence of each is, and what the average length of a
patch of sites all having the same rate. The rates can also be chosen
by the program to approximate a Gamma distribution of rates, or a
Gamma distribution plus a class of invariant sites. The program computes the
the likelihood by summing it over all possible assignments of rates to sites,
weighting each by its prior probability of occurrence.
For example, if we have used the C and A options (described below) to specify
that there are three possible rates of evolution, 1.0, 2.4, and 0.0,
that the prior probabilities of a site having these rates are 0.4, 0.3, and
0.3, and that the average patch length (number of consecutive sites
with the same rate) is 2.0, the program will sum the likelihood over
all possibilities, but giving less weight to those that (say) assign all
sites to rate 2.4, or that fail to have consecutive sites that have the
same rate.
The Hidden Markov Model framework for rate variation among sites
was independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of
rates; we allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant sites.
This feature effectively removes the artificial assumption that all sites
have the same rate, and also means that we need not know in advance the
identities of the sites that have a particular rate of evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each site (for example, we might want first, second,
and third codon positions in a protein coding sequence to be three different
categories. This is done with the categories input file and the C option.
We then specify (using the menu) the relative rates of evolution of sites
in the different categories. For example, we might specify that first,
second, and third positions evolve at relative rates of 1.0, 0.8, and 2.7.
If both user-assigned rate categories and Hidden Markov Model rates
are allowed, the program assumes that the
actual rate at a site is the product of the user-assigned category rate
and the Hidden Markov Model regional rate. (This may not always make
perfect biological sense: it would be more natural to assume some upper
bound to the rate, as we have discussed in the Felsenstein and Churchill
paper). Nevertheless you may want to use both types of rate variation.
INPUT FORMAT AND OPTIONS
Subject to these assumptions, the program is a
correct maximum likelihood method. The
input is fairly standard, with one addition. As usual the first line of the
file gives the number of species and the number of sites.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The options are selected using an interactive menu. The menu looks like this:
Nucleic acid sequence
Maximum Likelihood method with molecular clock, version 3.6a3
Settings for this run:
U Search for best tree? Yes
T Transition/transversion ratio: 2.0
F Use empirical base frequencies? Yes
C One category of substitution rates? Yes
R Rate variation among sites? constant rate
G Global rearrangements? No
W Sites weighted? No
J Randomize input order of sequences? No. Use input order
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
5 Reconstruct hypothetical sequences? No
Are these settings correct? (type Y or the letter for one to change)
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The options U, W, J, O, M, and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
The T option in this program does not stand for Threshold,
but instead is the Transition/transversion option. The user is prompted for
a real number greater than 0.0, as the expected ratio of transitions to
transversions. Note
that this is not the ratio of the first to the second kinds of events,
but the resulting expected ratio of transitions to transversions. The exact
relationship between these two quantities depends on the frequencies in the
base pools. The default value of the T parameter if you do not use the T
option is 2.0.
The F (Frequencies) option is one which may save users much time. If you
want to use the empirical frequencies of the bases, observed in the input
sequences, as the base frequencies, you simply use the default setting of
the F option. These empirical
frequencies are not really the maximum likelihood estimates of the base
frequencies, but they will often be close to those values (what they are is
maximum likelihood estimates under a "star" or "explosion" phylogeny).
If you change the setting of the F option you will be prompted for the
frequencies of the four bases. These must add to 1 and are to be typed on
one line separated by blanks, not commas.
The R (Hidden Markov Model rates) option allows the user to
approximate a Gamma distribution of rates among sites, or a
Gamma distribution plus a class of invariant sites, or to specify how
many categories of
substitution rates there will be in a Hidden Markov Model of rate
variation, and what are the rates and probabilities
for each. By repeatedly selecting the R option one toggles among
no rate variation, the Gamma, Gamma+I, and general HMM possibilities.
If you choose Gamma or Gamma+I the program will ask how many rate
categories you want. If you have chosen Gamma+I, keep in mind that
one rate category will be set aside for the invariant class and only
the remaining ones used to approximate the Gamma distribution.
For the approximation we do not use the quantile method of Yang (1995)
but instead use a quadrature method using generalized Laguerre
polynomials. This should give a good approximation to the Gamma
distribution with as few as 5 or 6 categories.
In the Gamma and Gamma+I cases, the user will be
asked to supply the coefficient of variation of the rate of substitution
among sites. This is different from the parameters used by Nei and Jin
(1990) but
related to them: their parameter a is also known as "alpha",
the shape parameter of the Gamma distribution. It is
related to the coefficient of variation by
CV = 1 / a1/2
or
a = 1 / (CV)2
(their parameter b is absorbed here by the requirement that time is scaled so
that the mean rate of evolution is 1 per unit time, which means that a = b).
As we consider cases in which the rates are less variable we should set a
larger and larger, as CV gets smaller and smaller.
If the user instead chooses the general Hidden Markov Model option,
they are first asked how many HMM rate categories there
will be (for the moment there is an upper limit of 9,
which should not be restrictive). Then
the program asks for the rates for each category. These rates are
only meaningful relative to each other, so that rates 1.0, 2.0, and 2.4
have the exact same effect as rates 2.0, 4.0, and 4.8. Note that an
HMM rate category
can have rate of change 0, so that this allows us to take into account that
there may be a category of sites that are invariant. Note that the run time
of the program will be proportional to the number of HMM rate categories:
twice as
many categories means twice as long a run. Finally the program will ask for
the probabilities of a random site falling into each of these
regional rate categories. These probabilities must be nonnegative and sum to
1. Default
for the program is one category, with rate 1.0 and probability 1.0 (actually
the rate does not matter in that case).
If more than one HMM rate category is specified, then another
option, A, becomes
If more than one category is specified, then another option, A, becomes
visible in the menu. This allows us to specify that we want to assume that
sites that have the same HMM rate category are expected to be clustered
so that there is autocorrelation of rates. The
program asks for the value of the average patch length. This is an expected
length of patches that have the same rate. If it is 1, the rates of
successive sites will be independent. If it is, say, 10.25, then the
chance of change to a new rate will be 1/10.25 after every site. However
the "new rate" is randomly drawn from the mix of rates, and hence could
even be the same. So the actual observed length of patches with the same
rate will be a bit larger than 10.25. Note below that if you choose
multiple patches, there will be an estimate in the output file as to
which combination of rate categories contributed most to the likelihood.
Note that the autocorrelation scheme we use is somewhat different
from Yang's (1995) autocorrelated Gamma distribution. I am unsure
whether this difference is of any importance -- our scheme is chosen
for the ease with which it can be implemented.
The C option allows user-defined rate categories. The user is prompted
for the number of user-defined rates, and for the rates themselves,
which cannot be negative but can be zero. These numbers, which must be
nonnegative (some could be 0),
are defined relative to each other, so that if rates for three categories
are set to 1 : 3 : 2.5 this would have the same meaning as setting them
to 2 : 6 : 5.
The assignment of rates to
sites is then made by reading a file whose default name is "categories".
It should contain a string of digits 1 through 9. A new line or a blank
can occur after any character in this string. Thus the categories file
might look like this:
122231111122411155
1155333333444
With the current options R, A, and C the program has gained greatly in its
ability to infer different rates at different sites and estimate
phylogenies under a more realistic model. Note that Likelihood Ratio
Tests can be used to test whether one combination of rates is
significantly better than another, provided one rate scheme represents
a restriction of another with fewer parameters. The number of parameters
needed for rate variation is the number of regional rate categories, plus
the number of user-defined rate categories less 2, plus one if the
regional rate categories have a nonzero autocorrelation.
The G (global search) option causes, after the last species is added to
the tree, each possible group to be removed and re-added. This improves the
result, since the position of every species is reconsidered. It
approximately triples the run-time of the program.
The User tree (option U) is read from a file whose default name is
intree.
The trees can be multifurcating. This allows us to test the
hypothesis that a given branch has zero length.
If the U (user tree) option is chosen another option appears in
the menu, the L option. If it is selected,
it signals the program that it
should take any branch lengths that are in the user tree and
simply evaluate the likelihood of that tree, without further altering
those branch lengths. In the case of a clock, if some branches have lengths
and others do not, the program does not estimate the lengths of those that
do not have lengths given in the user tree. If any of the branches
do not have lengths, the program re-estimates the lengths of all of them.
This is done because estimating some and not others is hard in the
case of a clock.
The W (Weights) option is invoked in the usual way, with only weights 0
and 1 allowed. It selects a set of sites to be analyzed, ignoring the
others. The sites selected are those with weight 1. If the W option is
not invoked, all sites are analyzed.
The Weights (W) option
takes the weights from a file whose default name is "weights". The weights
follow the format described in the main documentation file.
The M (multiple data sets) option will ask you whether you want to
use multiple sets of weights (from the weights file) or multiple data sets
from the input file.
The ability to use a single data set with multiple weights means that
much less disk space will be used for this input data. The bootstrapping
and jackknifing tool Seqboot has the ability to create a weights file with
multiple weights. Note also that when we use multiple weights for
bootstrapping we can also then maintain different rate categories for
different sites in a meaningful way. You should not use the multiple
data sets option without using multiple weights, you should not at the
same time use the user-defined rate categories option (option C).
The algorithm used for searching among trees is faster than it was in
version 3.5, thanks to using a technique invented by David Swofford
and J. S. Rogers. This involves not iterating most branch lengths on most
trees when searching among tree topologies, This is of necessity a
"quick-and-dirty" search but it saves much time.
OUTPUT FORMAT
The output starts by giving the number of species, the number of sites,
and the base frequencies for A, C, G, and T that have been specified. It
then prints out the transition/transversion ratio that was specified or
used by default. It also uses the base frequencies to compute the actual
transition/transversion ratio implied by the parameter.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of sites is printed, as well
as the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the menu
option to print them out, with the base sequences printed in
groups of ten bases along the lines of the Genbank and EMBL formats. The
trees found are printed as a rooted
tree topology. The
internal nodes are numbered arbitrarily for the sake of
identification. The number of trees evaluated so far and the log
likelihood of the tree are also given. The branch lengths in the diagram are
roughly proportional to the estimated branch lengths, except that very short
branches are printed out at least three characters in length so that the
connections can be seen.
A table is printed
showing the length of each tree segment, and the time (in units of
expected nucleotide substitutions per site) of each fork in the tree,
measured from the root of the tree. I have not attempted in include
code for approximate confidence limits on branch points, as I have done
for branch lengths in DNAML, both because of the extreme crudeness of
that test, and because the variation of times for different forks would be
highly correlated.
The log likelihood printed out with the final tree can be used to perform
various likelihood ratio tests. One can, for example, compare runs with
different values of the expected transition/transversion ratio to determine
which value is the maximum likelihood estimate, and what is the allowable range
of values (using a likelihood ratio test, which you will find described in
mathematical statistics books). One could also estimate the base frequencies
in the same way. Both of these, particularly the latter, require multiple runs
of the program to evaluate different possible values, and this might get
expensive.
This program makes possible a (reasonably) legitimate
statistical test of the molecular clock. To do such a test, run DNAML
and DNAMLK on the same data. If the trees obtained are of the same
topology (when considered as unrooted), it is legitimate to compare
their likelihoods by the likelihood ratio test. In DNAML the likelihood
has been computed by estimating 2n-3 branch lengths, if their are n tips
on the tree. In DNAMLK it has been computed by estimating n-1 branching
times (in effect, n-1 branch lengths). The difference in the number of
parameters is (2n-3)-(n-1) = n-2. To perform the test take the
difference in log likelihoods between the two runs (DNAML should be the
higher of the two, barring numerical iteration difficulties) and double
it. Look this up on a chi-square distribution with n-2 degrees of
freedom. If the result is significant, the log likelihood has been
significantly increased by allowing all 2n-3 branch lengths to be
estimated instead of just n-1, and molecular clock may be rejected.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the
rates at different sites, the
program also performs a statistical test of each of these trees against the
one with highest likelihood. If there are two user trees, the test
done is one which is due to Kishino and Hasegawa (1989), a version
of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of
log-likelihood differences between trees, taken across sites. If the two
trees' means are more than 1.96 standard deviations different
then the trees are
declared significantly different. This use of the empirical variance of
log-likelihood differences is more robust and nonparametric than the
classical likelihood ratio test, and may to some extent compensate for the
any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods across
sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the highest log-likelihood exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the log-likelihoods of each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the log-likelihood differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one. However
the test is not available if we assume that there
is autocorrelation of rates at neighboring sites (option A) and is not
done in those cases.
The branch lengths printed out are scaled in terms of expected numbers of
substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate of
change, averaged over all sites analyzed, is set to 1.0
if there are multiple categories of sites. This means that whether or not
there are multiple categories of sites, the expected fraction of change
for very small branches is equal to the branch length. Of course,
when a branch is twice as
long this does not mean that there will be twice as much net change expected
along it, since some of the changes occur in the same site and overlie or
even reverse each
other. The branch length estimates here are in terms of the expected
underlying numbers of changes. That means that a branch of length 0.26
is 26 times as long as one which would show a 1% difference between
the nucleotide sequences at the beginning and end of the branch. But we
would not expect the sequences at the beginning and end of the branch to be
26% different, as there would be some overlaying of changes.
Because of limitations of the numerical
algorithm, branch length estimates of zero will often print out as small
numbers such as 0.00001. If you see a branch length that small, it is really
estimated to be of zero length.
Another possible source of confusion is the existence of negative values for
the log likelihood. This is not really a problem; the log likelihood is not a
probability but the logarithm of a probability. When it is
negative it simply means that the corresponding probability is less
than one (since we are seeing its logarithm). The log likelihood is
maximized by being made more positive: -30.23 is worse than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what site categories
contributed the most to the final likelihood. This combination of
HMM rate categories need not have contributed a majority of the likelihood,
just a plurality. Still, it will be helpful as a view of where the
program infers that the higher and lower rates are. Note that the
use in this calculations of the prior probabilities of different rates,
and the average patch length, gives this inference a "smoothed"
appearance: some other combination of rates might make a greater
contribution to the likelihood, but be discounted because it conflicts
with this prior information. See the example output below to see
what this printout of rate categories looks like.
A second list will also be printed out, showing for each site which
rate accounted for the highest fraction of the likelihood. If the fraction
of the likelihood accounted for is less than 95%, a dot is printed instead.
Option 3 in the menu controls whether the tree is printed out into
the output file. This is on by default, and usually you will want to
leave it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees
which are written onto the output tree file, rather than the trees
printed on the output file. To keep the output file from becoming too
large, it may be wisest to use option 3 to prevent trees being
printed onto the output file.
Option 4 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined
trees are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated
at each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species which
are the input sequences). In that table, if a site has a base which
accounts for more than 95% of the likelihood, it is printed in capital
letters (A rather than a). If the best nucleotide accounts for less
than 50% of the likelihood, the program prints out an ambiguity code
(such as M for "A or C") for the set of nucleotides which, taken together,
account for more half of the likelihood. The ambiguity codes are listed
in the sequence programs documentation file. One limitation of the current
version of the program is that when there are multiple HMM rates
(option R) the reconstructed nucleotides are based on only the single
assignment of rates to sites which accounts for the largest amount of the
likelihood. Thus the assessment of 95% of the likelihood, in tabulating
the ancestral states, refers to 95% of the likelihood that is accounted
for by that particular combination of rates.
PROGRAM CONSTANTS
The constants defined at the beginning of the program include "maxtrees",
the maximum number of user trees that can be processed. It is small (100)
at present to save some further memory but the cost of increasing it
is not very great. Other constants
include "maxcategories", the maximum number of site
categories, "namelength", the length of species names in
characters, and three others, "smoothings", "iterations", and "epsilon", that
help "tune" the algorithm and define the compromise between execution speed and
the quality of the branch lengths found by iteratively maximizing the
likelihood. Reducing iterations and smoothings, and increasing epsilon, will
result in faster execution but a worse result. These values
will not usually have to be changed.
The program spends most of its time doing real arithmetic.
The algorithm, with separate and independent computations
occurring for each pattern, lends itself readily to parallel processing.
PAST AND FUTURE OF THE PROGRAM
This program was developed in 1989 by combining code from DNAPARS and from
DNAML. It was speeded up
by two major developments, the use of aliasing of nucleotide sites (version
3.1) and pretabulation of some exponentials (added by Akiko Fuseki in version
3.4). In version 3.5 the Hidden Markov Model code was added and the method
of iterating branch lengths was changed from an EM algorithm to direct
search. The Hidden Markov Model code slows things down, especially if
there is autocorrelation between sites, so this version is slower than
version 3.4. Nevertheless we hope that the sacrifice is worth it.
One change that is needed in the future is to put in some way of
allowing for base composition of nucleotide sequences in different parts
of the phylogeny.
CONTENTS OF OUTPUT FILE (with all numerical options on)
(It was run with HMM rates having gamma-distributed rates
approximated by 5 rate categories,
with coefficient of variation of rates 1.0, and with patch length
parameter = 1.5. Two user-defined rate categories were used, one for
the first 6 sites, the other for the last 7, with rates 1.0 : 2.0.
Weights were used, with sites 1 and 13 given weight 0, and all others
weight 1.)
Nucleic acid sequence
Maximum Likelihood method with molecular clock, version 3.6a3
5 species, 13 sites
Site categories are:
1111112222 222
Sites are weighted as follows:
0111111111 111
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
Empirical Base Frequencies:
A 0.23333
C 0.30000
G 0.23333
T(U) 0.23333
Transition/transversion ratio = 2.000000
Discrete approximation to gamma distributed rates
Coefficient of variation of rates = 1.000000 (alpha = 1.000000)
State in HMM Rate of change Probability
1 0.264 0.522
2 1.413 0.399
3 3.596 0.076
4 7.086 0.0036
5 12.641 0.000023
Expected length of a patch of sites having the same rate = 1.500
Site category Rate of change
1 1.000
2 2.000
+-----Epsilon
+------------------------------------------------4
! +-----Delta
--3
! +----------Gamma
+-------------------------------------------2
! +--Beta
+-------1
+--Alpha
Ln Likelihood = -68.25148
Ancestor Node Node Height Length
-------- ---- ---- ------ ------
root 3
3 4 4.37769 4.37769
4 Epsilon 4.92983 0.55214
4 Delta 4.92983 0.55214
3 2 3.97954 3.97954
2 Gamma 4.92983 0.95029
2 1 4.64910 0.66957
1 Beta 4.92983 0.28073
1 Alpha 4.92983 0.28073
Combination of categories that contributes the most to the likelihood:
1122121111 112
Most probable category at each site if > 0.95 probability ("." otherwise)
.......... ...
Probable sequences at interior nodes:
node Reconstructed sequence (caps if > 0.95)
3 .rymtyscsr ymy
4 .GkaTcTCGG CCy
Epsilon GGGATCTCGG CCC
Delta GGTATTTCGG CCT
2 .AykTcGcCA mAy
Gamma CATTTCGTCA CAA
1 .AcGTcGCCA AAy
Beta AAGGTCGCCA AAC
Alpha AACGTGGCCA AAT
PHYLIPNEW-3.69.650/doc/dnapars.html 0000664 0001750 0001750 00000033201 07712247475 013367 0000000 0000000
main
This program carries out unrooted parsimony (analogous to Wagner
trees) (Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA
sequences. The method of Fitch (1971) is used to count the number of
changes of base needed on a given tree.
The assumptions of this method are analogous to those of MIX:
Each site evolves independently.
Different lineages evolve independently.
The probability of a base substitution at a given site is
small over the lengths of time involved in
a branch of the phylogeny.
The expected amounts of change in different branches of the phylogeny
do not vary by so much that two changes in a high-rate branch
are more probable than one change in a low-rate branch.
The expected amounts of change do not vary enough among sites that two
changes in one site are more probable than one change in another.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b, 1988b). For
an opposing view arguing that the parsimony methods make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b, 1988), but also read the exchange between Felsenstein and Sober (1986).
Change from an occupied site to a deletion is counted as one
change. Reversion from a deletion to an occupied site is allowed and is also
counted as one change. Note that this in effect assumes that a deletion
N bases long is N separate events.
Dnapars can handle both bifurcating and multifurcating trees. In doing its
search for most parsimonious trees, it adds species not only by creating new
forks in the middle of existing branches, but it also tries putting them at
the end of new branches which are added to existing forks. Thus it searches
among both bifurcating and multifurcating trees. If a branch in a tree
does not have any characters which might change in that branch in the most
parsimonious tree, it does not save that tree. Thus in any tree that
results, a branch exists only if some character has a most parsimonious
reconstruction that would involve change in that branch.
It also saves a number of trees tied for best (you can alter the number
it saves using the V option in the menu). When rearranging trees, it
tries rearrangements of all of the saved trees. This makes the algorithm
slower than earlier versions of Dnapars.
The input data is standard. The first line of the input file contains the
number of species and the number of sites.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The options are selected using an interactive menu. The menu looks like this:
DNA parsimony algorithm, version 3.6a3
Setting for this run:
U Search for best tree? Yes
S Search option? More thorough search
V Number of trees to save? 100
J Randomize input order of sequences? No. Use input order
O Outgroup root? No, use as outgroup species 1
T Use Threshold parsimony? No, use ordinary parsimony
N Use Transversion parsimony? No, count all steps
W Sites weighted? No
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each site No
5 Print sequences at all nodes of tree No
6 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The N option allows you to choose transversion parsimony, which counts only
transversions (changes between one of the purines A or G and one of the
pyrimidines C or T). This setting is turned off by default.
The Weights (W) option
takes the weights from a file whose default name is "weights". The weights
follow the format described in the main documentation file, with integer
weights from 0 to 35 allowed by using the characters 0, 1, 2, ..., 9 and
A, B, ... Z.
The User tree (option U) is read from a file whose default name is intree.
The trees can be multifurcating. They must be preceded in the file by a
line giving the number of trees in the file.
The options J, O, T, M, and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
The M (multiple data sets option) will ask you whether you want to
use multiple sets of weights (from the weights file) or multiple data sets.
The ability to use a single data set with multiple weights means that
much less disk space will be used for this input data. The bootstrapping
and jackknifing tool Seqboot has the ability to create a weights file with
multiple weights.
The O (outgroup) option will have no effect if the U (user-defined tree)
option is in effect.
The T (threshold) option allows a continuum of methods
between parsimony and compatibility. Thresholds less than or equal to 1.0 do
not have any meaning and should
not be used: they will result in a tree dependent only on the input
order of species and not at all on the data!
Output is standard: if option 1 is toggled on, the data is printed out,
with the convention that "." means "the same as in the first species".
Then comes a list of equally parsimonious trees.
Each tree has branch lengths. These are computed using an algorithm
published by Hochbaum and Pathria (1997) which I first heard of from
Wayne Maddison who invented it independently of them. This algorithm
averages the number of reconstructed changes of state over all sites a
over all possible most parsimonious placements of the changes of state
among branches. Note that it does not correct in any way for multiple
changes that overlay each other.
If option 2 is
toggled on a table of the
number of changes of state required in each character is also
printed. If option 5 is toggled
on, a table is printed
out after each tree, showing for each branch whether there are known to be
changes in the branch, and what the states are inferred to have been at the
top end of the branch. This is a reconstruction of the ancestral sequences
in the tree. If you choose option 5, a menu item D appears which gives you
the opportunity to turn off dot-differencing so that complete ancestral
sequences are shown. If the inferred state is a "?" or one of the IUB
ambiguity symbols, there will be multiple
equally-parsimonious assignments of states; the user must work these out for
themselves by hand. A "?" in the reconstructed states means that in
addition to one or more bases, a deletion may or may not be present. If
option 6 is left in its default state the trees
found will be written to a tree file, so that they are available to be used
in other programs.
If the U (User Tree) option is used and more than one tree is supplied, the
program also performs a statistical test of each of these trees against the
best tree. This test, which is a version of the test proposed by
Alan Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences
due to Kishino and Hasegawa (1989), and
uses the mean and variance of
step differences between trees, taken across sites. If the mean
is more than 1.96 standard deviations different then the trees are declared
significantly different. The program
prints out a table of the steps for each tree, the differences of
each from the best one, the variance of that quantity as determined by
the step differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the
rates at different sites, the
program also performs a statistical test of each of these trees against the
one with highest likelihood. If there are two user trees, this
is a version of the test proposed by
Alan Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences
due to Kishino and Hasegawa (1989)
It uses the mean and variance of the differences in the number
of steps between trees, taken across sites. If the two
trees' means are more than 1.96 standard deviations different,
then the trees are
declared significantly different.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sums of steps across
sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected number of steps,
numbers of steps for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the lowest number of steps exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the number of steps for each tree, the differences of
each from the lowest one, the variance of that quantity as determined by
the differences of the numbers of steps at individual sites,
and a conclusion as to
whether that tree is or is not significantly worse than the best one.
Option 6 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined
trees are written to the output tree file.
The program is a straightforward relative of MIX
and runs reasonably quickly, especially with many sites and few species.
DRAWGRAM interactively plots a cladogram- or phenogram-like rooted tree
diagram, with many options including orientation of tree and branches,
style of tree, label sizes and angles, tree depth, margin sizes, stem
lengths, and placement of nodes in the tree. Particularly if you can
use your computer to preview the plot, you can very
effectively adjust the details of the plotting to get just the kind of
plot you want.
To understand the working of DRAWGRAM and DRAWTREE, you should first
read the Tree Drawing Programs web page
in this documentation.
As with DRAWTREE, to run DRAWGRAM you need a compiled copy of the
program, a font file, and a tree file. The tree file has a default name
of intree. The font file has a default name of "fontfile". If there is
no file of that name, the program will ask you for the name of a font file
(we provide ones that have the names font1 through font6).
Once you decide on a favorite one of these, you could make a copy of it
and call it fontfile, and it will then be used by default.
Note that the program will get confused if the input tree file has the number
of trees on the first line of the file, so that numbr may have to be removed.
Once these choices have been made you will see the central menu of the
program, which looks like this:
Rooted tree plotting program version 3.6a3
Here are the settings:
0 Screen type (IBM PC, ANSI): (none)
P Final plotting device: Postscript printer
V Previewing device: X Windows display
H Tree grows: Horizontally
S Tree style: Phenogram
B Use branch lengths: Yes
L Angle of labels: 90.0
R Scale of branch length: Automatically rescaled
D Depth/Breadth of tree: 0.53
T Stem-length/tree-depth: 0.05
C Character ht / tip space: 0.3333
A Ancestral nodes: Weighted
F Font: Times-Roman
M Horizontal margins: 1.65 cm
M Vertical margins: 2.16 cm
# Pages per tree: one page per tree
Y to accept these or type the letter for one to change
These are the settings that control the appearance of the tree, which
has already been read in. You can either accept these as is, in which
case you would answer Y to the question and press the Return or Enter
key, or you can answer N if you want to change one, or simply type the
character corresponding to the one you want to change (if you answer N it
will just immediately ask you for that number anyway).
For a first run, particularly if previewing is available, you might accept
these default values and see what the result looks like. The program
will then tell you it is about to preview the tree and ask you to press
Return or Enter when you are ready to see this (you will probably have
to press it twice). If you are on a Windows system (and have its graphics
selected as your previewing option), on a Unix or Linux system and are
using X windows for previewing, or are on a Macintosh system, a new
window will open with the preview in it. If you are using the Tektronix
preview option the preview will appear in the window where the menu was.
On X Windows, Macintosh, and Windows you can resize the preview window,
though for some of these you may have to ask the system to redraw the
preview to see it at the new window size.
Once you are finished looking at the preview, you will want to
specify whether the program should make the final plot or change some of
the settings. This is done differently on the different previews:
In X Windows you should make the menu window the active
window. You may need to move the mouse over it, or click in it, or
click on its top bar. You do not need to try to close the preview
window yourself, and usually if you do this will cause trouble.
In Windows use the File menu in the preview window
and choose either the Change Parameters menu item, or if
you are ready to make the final plot, choose the Plot menu item.
On a Macintosh system, you can simply use the little box in
the corner of the preview window to close it. The text window for the
menu will then be active.
In PC graphics press on the Enter key. The screen with the
preview should disappear and the settings menu reappear.
With a Tektronix preview, you may need to change your screen
from a Tektronix-compatible mode to see the menu again.
Except with the Macintosh preview, the program will
now ask you if the tree is now ready to be plotted. If you answer Y (for
Yes) (or choose this option in the File menu of the preview
window in the case of Windows) the program will usually write a plot file
(with some plot options it will draw the tree on the screen). Then it will
terminate.
But if you do not say that you are ready to plot the tree,
it will go back to the above menu, allow
you to change more options, and go through the whole process again. The
easiest way to learn the meaning of the options is to try them,
particularly if previewing is available. Below I will describe them one
by one; you may prefer to skip reading this unless you are puzzled about
one of them.
THE OPTIONS
O
This is an option that allows you to change the menu window
to be an ANSI terminal or an IBM PC terminal. Generally you will not
want to change this.
P
This allows you to choose the Plotting device or file
format. We have discussed the possible choices in the
draw programs documentation web page.
V
This allows you to change the type of preView window (or
even turn off previewing. We have discussed the different possible
choices in the draw programs documentation web page.
H
Whether the tree grows Horizontally or
vertically. The horizontal growth will be from left to right. This
option is self explanatory. The other options are designed so that when
we switch this direction of growth the tree still looks the same, except
for orientation and overall size. This option is toggled, that is,
when it is chosen the orientation changes, going back and forth between
Vertical and Horizontal. The default orientation is Horizontal.
S
The Style of the tree. There are six
styles possible: Cladogram, Phenogram, Curvogram, Eurogram, Swoopogram,
and Circular Tree. These are chosen by the letters C, P, V, E, S and O.
These take a little explaining.
In spite of the words "cladogram" and "phenogram", there is no
implication of the extent to which you consider these diagrams as being
genealogies or phenetic clustering diagrams. The names refer to pictorial
style, not your own intended final use for the diagram. The six styles
can be described as follows (assuming a vertically growing tree):
Cladogram
nodes are connected to other nodes and to tips by straight
lines going directly from one to the other. This gives a V-shaped
appearance. The default settings if there are no branch lengths are
designed to yield a V-shaped tree with a 90-degree angle at the base.
Phenogram
nodes are connected to other nodes and to other tips by
a horizontal and then a vertical line. This gives a particularly
precise idea of horizontal levels.
Curvogram
nodes are connected to other nodes and to tips by a curve
which is one fourth of an ellipse, starting out horizontally and then
curving upwards to become vertical. This pattern was suggested by
Joan Rudd.
Eurogram
so-called because it is a version of cladogram diagram
popular in Europe. Nodes are
connected to other nodes and to tips by a diagonal line that goes outwards
and goes at most one-third of the way up to the next node, then turns
sharply straight upwards and is vertical. Unfortunately it is nearly
impossible to guarantee, when branch lengths are used, that the angles
of divergence of lines are the same.
Swoopogram
this option connects two nodes
or a node and a tip using two curves that are actually each one-quarter
of an ellipse. The first part starts out vertical and then bends over
to become horizontal. The second part, which is at least two-thirds
of the total, starts out horizontal and then bends up to become
vertical. The effect is that two lineages split apart gradually, then
more rapidly, then both turn upwards.
Circular Tree
This is a style introduced by David Swofford
in PAUP*. The tree grows outward from a central point, being essentially
a Phenogram style tree in polar coordinates. The tips form a 360-degree
circle. The "vertical" lines run outward radially from the center, and the
"horizontal" lines are arcs of circles centered on it.
You should experiment with these and decide which you want -- it depends
very much on the effect you want.
B
Whether the tree has Branch lengths that are
being used in the diagram. If the tree that was read in had a full set
of branch lengths, it will be assumed as a default that you want to use
them in the diagram, but you can specify that they are not to be used. If
the tree does not have a full set of branch lengths then this will
be indicated, and if you try to use branch lengths the program will
refuse to allow you to do so. Note that when you change option B, the node
position option A may change as well.
L
The angle of the Labels. The angle is always
calculated relative to a vertical tree; whether the tree is horizontal
or vertical, if the labels are at an angle of 90 degrees they run
parallel to direction of tree growth. The default value is 90
degrees. The option allows you to choose any angle from 0 to 90 degrees.
R
How the branch lengths will be translated
into distances on the output device. Note that when branch lengths
have not been provided, there are implicit branch lengths specified
by the type of tree being drawn. This
option will toggle back and forth between automatic
adjustment of branch lengths so that the diagram will just fit into the
margins, and you specifying how many centimeters there will be per unit
branch length. This is included so that you can plot different trees
to a common scale, showing which ones have longer or shorter branches than
others. Note that if you choose too large a value for centimeters per
unit branch length, the tree will be so big it will overrun the plotting
area and may cause failure of the diagram to display properly. Too small
a value will cause the tree to be a nearly invisible dot.
D
The ratio between the Depth and the
breadth of the tree. It is initially set near 0.5, to approximate a
V-shaped tree, but you may want to try a larger value to get a longer
and narrower tree. Depth and breadth are described as if the tree grew
vertically, so that depth is always measured from the root to the tips
(not including the length of the labels).
T
The length of the sTem of the tree
as a fraction of the depth of the tree. You may want to either lengthen
the stem or remove it entirely by giving a value of zero.
C
The Character height, measured as a fraction
of the tip spacing. If the labels are rotated to a shallow
angle, the character height will be automatically adjusted in hopes of
avoiding collision of labels at different tips. This option allows you
to change the size of the labels yourself. On output devices where
line thicknesses can be varied, the thickness of the tree lines will
automatically be adjusted to be proportional to the character height,
which is an additional reason you may want to change character height.
A
Controls the
positions of the Ancestral (interior) nodes. This can greatly affect the
appearance of the tree. The vertical positions (these descriptions assume a
a tree growing vertically) are not under your control except insofar as you
specify the use or non-use of branch lengths. If you choose to change
this option you will see the menu:
Should interior node positions:
be Intermediate between their immediate descendants,
Weighted average of tip positions
Centered among their ultimate descendants
iNnermost of immediate descendants
or so that tree is V-shaped
(type I, W, C, N or V):
The five methods (Intermediate, Weighted, Centered, Innermost, and
V-shaped) are different horizontal positionings of the interior nodes.
It will be helpful to you to try these out and see which you like best.
Intermediate places the node halfway between its immediate descendants
(horizontally), Weighted places it closer to that descendant who is
closer vertically as well, and Centered centers the node below the
horizontal positions of the tips that are descended from that node. You
may want to choose that option that prevents lines from crossing each
other.
V-shaped is another option, one designed, if there are no branch lengths
being used, to yield a v-shaped tree of regular appearance. With branch
lengths it will not necessarily do so. "Innermost" is the most unusual
option: it chooses a center for the tree, and always places interior
nodes below the innermost of their immediate descendants. This leads
to a tree that has vertical lines in the center, like a tree with a
trunk.
If the tree you are plotting has a full set of lengths, then when it is
read in the node position option is automatically set to "intermediate",
which is the setting with the least likelihood of lines in the tree
crossing. If it does not have lengths the option is set to "V-shaped".
If you change option B which tells the program whether to try to use
the branch lengths, then the node position option will automatically be
reset to the appropriate one of these defaults. This may be confusing
if you do not realise that it is happening.
F
Allows you to select the
name of the Font that you will use for the species names. This is
allowed for some of the plotter drivers (this menu item does not
appear for the others). You can
select the name of any font that is available for your plotter, for
example "Courier-Bold" or "Helvetica". The label will then be
printed using that font rather than being drawn line-by-line as it
is in the default Hershey font. In the preview of the tree, the
Hershey font is always used (which means that it may look different from
the final font). The size of the characters in the species names is
scaled according to the label heights you have selected in the menu,
whether plotter fonts or the Hershey font are used. Note that for some
plotter drivers (particular Xfig and PICT) fonts can be used only if the
species labels are horizontal or vertical (at angles of 0 degrees or
90 degrees).
M
The horizontal and vertical Margins in
centimeters. You can enter new margins (you must enter new values for
both horizontal and vertical margins, though these need not be different
from the old values). For the moment I do not allow you to specify left
and right margins separately, or top and bottom margins separately. In
a future release I hope to do so.
#
The number of pages per tree. Defaults to one, but if
you need a physically large tree you may want to choose a larger
number. For example, to make a big tree for a poster, choose a larger
number of pages horizontally and vertically (the program will ask you
for these numbers), get out your scissors and paste or tape, and
go to work.
I recommend that you try all of these options (particularly if you can
preview the trees). It is of particular use to try combinations of the
style of tree (option S) with the different methods of placing
interior nodes (option A). You will find that a wide variety of
effects can be achieved.
DOLPENNY is a program that will find all of the most parsimonious trees
implied by your data when the Dollo or polymorphism parsimony criteria are
employed. It does so not by examining all possible trees,
but by using the more sophisticated "branch and bound" algorithm, a
standard computer science search strategy first applied to
phylogenetic inference by Hendy and Penny (1982). (J. S. Farris
[personal communication, 1975] had also suggested that this strategy,
which is well-known in computer science, might
be applied to phylogenies, but he did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem of
finding these has been shown (Graham and Foulds, 1982; Day, 1983) to be
NP-complete, which is equivalent to saying that there is no
fast algorithm that is guaranteed to solve the problem in all cases
(for a discussion of NP-completeness, see the Scientific American
article by Lewis and Papadimitriou, 1978). The result is that
this program, despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs
in the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of someone
who can let a microcomputer grind all night than for someone who
has the "benefit" of paying for time on the campus mainframe
computer). IT IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE
PROGRAM WILL TAKE ON YOUR DATA. This can be done by running it on subsets
of the species, increasing the number of species in the run until you
either are able to treat the full data set or know that the program
will take unacceptably long on it. (Making a plot of the logarithm of run
time against species number may help to project run times).
The Algorithm
The search strategy used by DOLPENNY starts by making a tree consisting of the
first two species (the first three if the tree is to be unrooted). Then
it tries to add the next species in all possible places (there are three
of these). For each of the resulting trees it evaluates the number of
losses. It adds the next species to each of these, again in all
possible spaces. If this process would continue it would simply
generate all possible trees, of which there are a very large number even
when the number of species is moderate (34,459,425 with 10 species). Actually
it does not do this, because the trees are generated in a
particular order and some of them are never generated.
Actually the order in which trees are generated is not quite as
implied above, but is a "depth-first search". This means that first
one adds the third species in the first possible
place, then the fourth species in its first possible place, then
the fifth and so on until the first possible tree has been produced. Its
number of steps is evaluated. Then one "backtracks" by trying the
alternative placements of the last species. When these are exhausted
one tries the next placement of the next-to-last species. The order of
placement in a depth-first search is like this for a
four-species case (parentheses enclose monophyletic groups):
Make tree of first two species (A,B)
Add C in first place ((A,B),C)
Add D in first place (((A,D),B),C)
Add D in second place ((A,(B,D)),C)
Add D in third place (((A,B),D),C)
Add D in fourth place ((A,B),(C,D))
Add D in fifth place (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place (((A,D),C),B)
Add D in second place ((A,(C,D)),B)
Add D in third place (((A,C),D),B)
Add D in fourth place ((A,C),(B,D))
Add D in fifth place (((A,C),B),D)
Add C in third place (A,(B,C))
Add D in first place ((A,D),(B,C))
Add D in second place (A,((B,D),C))
Add D in third place (A,(B,(C,D)))
Add D in fourth place (A,((B,C),D))
Add D in fifth place ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species
rooted bifurcating trees, each exactly once (the parentheses each enclose
a monophyletic group). As displayed above, the backtracking
depth-first search algorithm is just another way of producing all
possible trees one at a time. The branch and bound algorithm
consists of this with one change. As each tree is constructed,
including the partial trees such as (A,(B,C)), its number of losses
(or retentions of polymorphism)
is evaluated.
The point of this is that if a previously-found
tree such as ((A,B),(C,D)) required fewer losses, then we know that
there is no point in even trying to add D to ((A,C),B). We have
computed the bound that enables us to cut off a whole line of inquiry
(in this case five trees) and avoid going down that particular branch
any farther.
The branch-and-bound algorithm thus allows us to find all most parsimonious
trees without generating all possible trees. How much of a saving this
is depends strongly on the data. For very clean (nearly "Hennigian")
data, it saves much time, but on very messy data it will still take
a very long time.
The algorithm in the program differs from the one outlined here
in some essential details: it investigates possibilities in the
order of their apparent promise. This applies to the order of addition
of species, and to the places where they are added to the tree. After
the first two-species tree is constructed, the program tries adding
each of the remaining species in turn, each in the best possible place it
can find. Whichever of those species adds (at a minimum) the most
additional steps is taken to be the one to be added next to the tree. When
it is added, it is added in turn to places which cause the fewest
additional steps to be added. This sounds a bit complex, but it is done
with the intention of eliminating regions of the search of all possible
trees as soon as possible, and lowering the bound on tree length as quickly
as possible.
The program keeps a list of all the most parsimonious
trees found so far. Whenever
it finds one that has fewer losses than
these, it clears out the list and
restarts the list with that tree. In the process the bound tightens and
fewer possibilities need be investigated. At the end the list contains
all the shortest trees. These are then printed out. It should be
mentioned that the program CLIQUE for finding all largest cliques
also works by branch-and-bound. Both problems are NP-complete but for
some reason CLIQUE runs far faster. Although their worst-case behavior
is bad for both programs, those worst cases occur far more frequently
in parsimony problems than in compatibility problems.
Controlling Run Times
Among the quantities available to be set at the
beginning of a run of DOLPENNY, two (howoften and howmany) are of particular
importance. As DOLPENNY goes along it will keep count of how many
trees it has examined. Suppose that howoften is 100 and howmany is 300,
the default settings. Every time 100 trees have been examined, DOLPENNY
will print out a line saying how many multiples of 100 trees have now been
examined, how many steps the most parsimonious tree found so far has,
how many trees of with that number of steps have been found, and a very
rough estimate of what fraction of all trees have been looked at so far.
When the number of these multiples printed out reaches the number howmany
(say 1000), the whole algorithm aborts and prints out that it has not
found all most parsimonious trees, but prints out what is has got so far
anyway. These trees need not be any of the most parsimonious trees: they are
simply the most parsimonious ones found so far. By setting the product
(howoften X howmany) large you can make
the algorithm less likely to abort, but then you risk getting bogged
down in a gigantic computation. You should adjust these constants so that
the program cannot go beyond examining the number of trees you are reasonably
willing to pay for (or wait for). In their initial setting the program will
abort after looking at 100,000 trees. Obviously you may want to adjust
howoften in order to get more or fewer lines of intermediate notice of how
many trees have been looked at so far. Of course, in small cases you may
never even reach the first multiple of howoften and nothing will be printed out
except some headings and then the final trees.
The indication of the approximate percentage of trees searched so far will
be helpful in judging how much farther you would have to go to get the full
search. Actually, since that fraction is the fraction of the set of all
possible trees searched or ruled out so far, and since the search becomes
progressively more efficient, the approximate fraction printed out will
usually be an underestimate of how far along the program is, sometimes a
serious underestimate.
A constant that affects the result is "maxtrees",
which controls the maximum number of trees that can be stored. Thus if
"maxtrees"
is 25, and 32 most parsimonious trees are found, only the first 25 of these are
stored and printed out. If "maxtrees"
is increased, the program does not run any slower but requires a little
more intermediate storage space. I recommend
that "maxtrees"
be kept as large as you can, provided you are willing to
look at an output with that many trees on it! Initially,
"maxtrees" is set to 100 in the distribution copy.
Methods and Options
The counting of the length of trees is done by an algorithm nearly
identical to the corresponding algorithms in DOLLOP, and thus the remainder
of this document will be nearly identical to the DOLLOP document. The
Dollo parsimony method was
first suggested in print in verbal form by Le Quesne (1974) and was
first well-specified by Farris (1977). The method is named after Louis
Dollo since he was one of the first to assert that in evolution it is
harder to gain a complex feature than to lose it. The algorithm
explains the presence of the state 1 by allowing up to one forward
change 0-->1 and as many reversions 1-->0 as are necessary to explain
the pattern of states seen. The program attempts to minimize the number
of 1-->0 reversions necessary.
The assumptions of this method are in effect:
We know which state is the ancestral one (state 0).
The characters are evolving independently.
Different lineages evolve independently.
The probability of a forward change (0-->1) is small over the
evolutionary times involved.
The probability of a reversion (1-->0) is also small, but
still far larger than the probability of a forward change, so
that many reversions are easier to envisage than even one
extra forward change.
Retention of polymorphism for both states (0 and 1) is highly
improbable.
The lengths of the segments of the true tree are not so
unequal that two changes in a long segment are as probable as
one in a short segment.
That these are the assumptions is established in several of my
papers (1973a, 1978b, 1979, 1981b, 1983). For an opposing view arguing
that the parsimony methods make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
One problem can arise when using additive binary recoding to
represent a multistate character as a series of two-state characters. Unlike
the Camin-Sokal, Wagner, and Polymorphism methods, the Dollo
method can reconstruct ancestral states which do not exist. An example
is given in my 1979 paper. It will be necessary to check the output to
make sure that this has not occurred.
The polymorphism parsimony method was first used by me,
and the results published
(without a clear
specification of the method) by Inger (1967). The method was
published by Farris (1978a) and by me (1979). The method
assumes that we can explain the pattern of states by no more than one
origination (0-->1) of state 1, followed by retention of polymorphism
along as many segments of the tree as are necessary, followed by loss of
state 0 or of state 1 where necessary. The program tries to minimize
the total number of polymorphic characters, where each polymorphism is
counted once for each segment of the tree in which it is retained.
The assumptions of the polymorphism parsimony method are in effect:
The ancestral state (state 0) is known in each character.
The characters are evolving independently of each other.
Different lineages are evolving independently.
Forward change (0-->1) is highly improbable over the length of
time involved in the evolution of the group.
Retention of polymorphism is also improbable, but far more
probable that forward change, so that we can more easily
envisage much polymorhism than even one additional forward
change.
Once state 1 is reached, reoccurrence of state 0 is very
improbable, much less probable than multiple retentions of
polymorphism.
The lengths of segments in the true tree are not so unequal
that we can more easily envisage retention events occurring in
both of two long segments than one retention in a short
segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
The input format is the standard one, with "?", "P", "B" states
allowed. Most of the options are selected using a menu:
Penny algorithm for Dollo or polymorphism parsimony, version 3.6a3
branch-and-bound to find all most parsimonious trees
Settings for this run:
P Parsimony method? Dollo
H How many groups of 100 trees: 1000
F How often to report, in trees: 100
S Branch and bound is simple? Yes
T Use Threshold parsimony? No, use ordinary parsimony
A Use ancestral states? No
W Sites weighted? No
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each character No
5 Print states at all nodes of tree No
6 Write out trees onto tree file? Yes
Are these settings correct? (type Y or the letter for one to change)
The P option toggles between the Polymorphism parsimony method and the
default Dollo parsimony method.
The options T, A, and M are the usual Threshold, Ancestral
States, and Multiple Data Sets options. They are described in the Main
documentation file and in the Discrete Characters Programs documentation
file.
Options F and H reset the
variables howoften (F) and howmany (H). The user is prompted for the new
values. By setting these larger the program will report its progress less
often (howoften) and will run longer (howmany times howoften). These values
default to 100 and 1000 which
guarantees a search of 100,000 trees, but these can be changed. Note that
option F in this program is not the Factors option available in some of
the other programs in this section of the package.
The use of the A
option allows implementation of the unordered Dollo parsimony and unordered
polymorphism parsimony methods which I have
described elsewhere (1984b). When the A option is used the ancestor is
not to be counted as one of the species. The O (outgroup) option is not
available since the tree produced is already rooted.
Setting T at or below
1.0 but above 0 causes the criterion to become compatibility rather than
polymorphism parsimony, although there is no advantage to using this
program instead of PENNY to do a compatibility method. Setting
the threshold value higher brings about an intermediate between
the Dollo or polymorphism parsimony methods and the compatibility method,
so that there is some rationale for doing that.
Using a threshold value of 1.0 or lower, but above 0, one can
obtain a rooted (or, if the A option is used with ancestral states of
"?", unrooted) compatibility criterion, but there is no particular
advantage to using this program for that instead of MIX. Higher
threshold values are of course meaningful and provide
intermediates between Dollo and compatibility methods.
The S (Simple) option alters a step in DOLPENNY which reconsiders the
order in which species are added to the tree. Normally the decision as to
what species to add to the tree next is made as the first tree is being
constructucted; that ordering of species is not altered subsequently. The
R option causes it to be continually reconsidered. This will probably
result in a substantial increase in run time, but on some data sets of
intermediate messiness it may help. It is included in case it might prove
of use on some data sets.
The Factors
option is not available in this program, as it would have no effect on
the result even if that information were provided in the input file.
The output format is also standard. It includes a rooted tree and,
if the user selects option 4, a table
of the numbers of reversions or retentions of polymorphism necessary
in each character. If any of the
ancestral states has been specified to be unknown, a table of
reconstructed ancestral states is also provided. When reconstructing
the placement of forward changes and reversions under the Dollo method,
keep in mind that each
polymorphic state in the input data will require one "last minute"
reversion. This is included in the tabulated counts. Thus if we have
both states 0 and 1 at a tip of the tree the program will assume that
the lineage had state 1 up to the last minute, and then state 0 arose in
that population by reversion, without loss of state 1.
A table is available to be printed out after each tree, showing for each
branch whether
there are known to be changes in the branch, and what the states are inferred
to have been at the top end of the branch. If the inferred state is a "?"
there will be multiple equally-parsimonious assignments of states; the user
must work these out for themselves by hand.
If the A option is used, then the program will
infer, for any character whose ancestral state is unknown ("?") whether the
ancestral state 0 or 1 will give the best tree. If these are
tied, then it may not be possible for the program to infer the
state in the internal nodes, and these will all be printed as ".". If this
has happened and you want to know more about the states at the internal
nodes, you will find helpful to use DOLMOVE to display the tree and examine
its interior states, as the algorithm in DOLMOVE shows all that can be known
in this case about the interior states, including where there is and is not
amibiguity. The algorithm in DOLPENNY gives up more easily on displaying these
states.
At the beginning of the program are a series of constants,
which can be changed to help adapt the program to different computer systems.
Two are the initial values of howmany and howoften,
constants "often" and "many". Constant "maxtrees"
is the maximum number of tied trees that will
be stored.
This program implements the maximum likelihood method for DNA
sequences. The
present version is faster than earlier versions of
DNAML. Details of the algorithm are published in
the paper by Felsenstein and Churchill (1996).
The model of base substitution allows the expected frequencies
of the four bases to be unequal, allows the expected frequencies of
transitions and transversions to be unequal, and has several
ways of allowing different rates of evolution at
different sites.
The assumptions of the present model are:
Each site in the sequence evolves independently.
Different lineages evolve independently.
Each site undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of occurrence)
which we specify.
All relevant sites are included in the sequence, not just those that
have changed or those that are "phylogenetically informative".
A substitution consists of one of two sorts of events:
(a)
The first kind
of event consists of the replacement of the existing base by a base
drawn from a pool of purines or a pool of pyrimidines (depending on
whether the base being replaced was a purine or a pyrimidine). It can
lead either to no change or to a transition.
(b)
The second kind of
event consists of the replacement of the existing base
by a base drawn at random from a pool of bases at known
frequencies, independently of the identity of the base which
is being replaced. This could lead either to a no change, to a transition
or to a transversion.
The ratio of the two
purines in the purine replacement pool is the same as their ratio in the
overall pool, and similarly for the pyrimidines.
The ratios of transitions to transversions can be set by the
user. The substitution process can be diagrammed as follows:
Suppose that you specified A, C, G, and T base frequencies of
0.24, 0.28, 0.27, and 0.21.
First kind of event:
Determine whether the existing base is a purine or a pyrimidine.
Draw from the proper pool:
Purine pool: Pyrimidine pool:
| | | |
| 0.4706 A | | 0.5714 C |
| 0.5294 G | | 0.4286 T |
| (ratio is | | (ratio is |
| 0.24 : 0.27) | | 0.28 : 0.21) |
|_______________| |_______________|
Second kind of event:
Draw from the overall pool:
| |
| 0.24 A |
| 0.28 C |
| 0.27 G |
| 0.21 T |
|__________________|
Note that if the existing base is, say, an A, the first kind of event has
a 0.4706 probability of "replacing" it by another A. The second kind of
event has a 0.24 chance of replacing it by another A. This rather
disconcerting model is used because it has nice mathematical properties that
make likelihood calculations far easier. A closely similar, but not
precisely identical model having different rates of transitions and
transversions has been used by Hasegawa et. al. (1985b). The transition
probability formulas for the current model were given (with my
permission) by Kishino and Hasegawa (1989). Another explanation is
available in the paper by Felsenstein and Churchill (1996).
Note the assumption that we are looking at all sites, including those
that have not changed at all. It is important not to restrict attention
to some sites based on whether or not they have changed; doing that
would bias branch lengths by making them too long, and that in turn
would cause the method to misinterpret the meaning of those sites that
had changed.
This program uses a Hidden Markov Model (HMM)
method of inferring different rates of evolution at different sites. This
was described in a paper by me and Gary Churchill (1996). It allows us to
specify to the program that there will be
a number of different possible evolutionary rates, what the prior
probabilities of occurrence of each is, and what the average length of a
patch of sites all having the same rate. The rates can also be chosen
by the program to approximate a Gamma distribution of rates, or a
Gamma distribution plus a class of invariant sites. The program computes the
the likelihood by summing it over all possible assignments of rates to sites,
weighting each by its prior probability of occurrence.
For example, if we have used the C and A options (described below) to specify
that there are three possible rates of evolution, 1.0, 2.4, and 0.0,
that the prior probabilities of a site having these rates are 0.4, 0.3, and
0.3, and that the average patch length (number of consecutive sites
with the same rate) is 2.0, the program will sum the likelihood over
all possibilities, but giving less weight to those that (say) assign all
sites to rate 2.4, or that fail to have consecutive sites that have the
same rate.
The Hidden Markov Model framework for rate variation among sites
was independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of
rates; we allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant sites.
This feature effectively removes the artificial assumption that all sites
have the same rate, and also means that we need not know in advance the
identities of the sites that have a particular rate of evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each site (for example, we might want first, second,
and third codon positions in a protein coding sequence to be three different
categories. This is done with the categories input file and the C option.
We then specify (using the menu) the relative rates of evolution of sites
in the different categories. For example, we might specify that first,
second, and third positions evolve at relative rates of 1.0, 0.8, and 2.7.
If both user-assigned rate categories and Hidden Markov Model rates
are allowed, the program assumes that the
actual rate at a site is the product of the user-assigned category rate
and the Hidden Markov Model regional rate. (This may not always make
perfect biological sense: it would be more natural to assume some upper
bound to the rate, as we have discussed in the Felsenstein and Churchill
paper). Nevertheless you may want to use both types of rate variation.
INPUT FORMAT AND OPTIONS
Subject to these assumptions, the program is a
correct maximum likelihood method. The
input is fairly standard, with one addition. As usual the first line of the
file gives the number of species and the number of sites.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The options are selected using an interactive menu. The menu looks like this:
Nucleic acid sequence Maximum Likelihood method, version 3.6a3
Settings for this run:
U Search for best tree? Yes
T Transition/transversion ratio: 2.0000
F Use empirical base frequencies? Yes
C One category of sites? Yes
R Rate variation among sites? constant rate
W Sites weighted? No
S Speedier but rougher analysis? Yes
G Global rearrangements? No
J Randomize input order of sequences? No. Use input order
O Outgroup root? No, use as outgroup species 1
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
5 Reconstruct hypothetical sequences? No
Y to accept these or type the letter for one to change
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The options U, W, J, O, M, and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
The T option in this program does not stand for Threshold,
but instead is the Transition/transversion option. The user is prompted for
a real number greater than 0.0, as the expected ratio of transitions to
transversions. Note
that this is not the ratio of the first to the second kinds of events,
but the resulting expected ratio of transitions to transversions. The exact
relationship between these two quantities depends on the frequencies in the
base pools. The default value of the T parameter if you do not use the T
option is 2.0.
The F (Frequencies) option is one which may save users much time. If you
want to use the empirical frequencies of the bases, observed in the input
sequences, as the base frequencies, you simply use the default setting of
the F option. These empirical
frequencies are not really the maximum likelihood estimates of the base
frequencies, but they will often be close to those values (what they are is
maximum likelihood estimates under a "star" or "explosion" phylogeny).
If you change the setting of the F option you will be prompted for the
frequencies of the four bases. These must add to 1 and are to be typed on
one line separated by blanks, not commas.
The R (Hidden Markov Model rates) option allows the user to
approximate a Gamma distribution of rates among sites, or a
Gamma distribution plus a class of invariant sites, or to specify how
many categories of
substitution rates there will be in a Hidden Markov Model of rate
variation, and what are the rates and probabilities
for each. By repeatedly selecting the R option one toggles among
no rate variation, the Gamma, Gamma+I, and general HMM possibilities.
If you choose Gamma or Gamma+I the program will ask how many rate
categories you want. If you have chosen Gamma+I, keep in mind that
one rate category will be set aside for the invariant class and only
the remaining ones used to approximate the Gamma distribution.
For the approximation we do not use the quantile method of Yang (1995)
but instead use a quadrature method using generalized Laguerre
polynomials. This should give a good approximation to the Gamma
distribution with as few as 5 or 6 categories.
In the Gamma and Gamma+I cases, the user will be
asked to supply the coefficient of variation of the rate of substitution
among sites. This is different from the parameters used by Nei and Jin
(1990) but
related to them: their parameter a is also known as "alpha",
the shape parameter of the Gamma distribution. It is
related to the coefficient of variation by
CV = 1 / a1/2
or
a = 1 / (CV)2
(their parameter b is absorbed here by the requirement that time is scaled so
that the mean rate of evolution is 1 per unit time, which means that a = b).
As we consider cases in which the rates are less variable we should set a
larger and larger, as CV gets smaller and smaller.
If the user instead chooses the general Hidden Markov Model option,
they are first asked how many HMM rate categories there
will be (for the moment there is an upper limit of 9,
which should not be restrictive). Then
the program asks for the rates for each category. These rates are
only meaningful relative to each other, so that rates 1.0, 2.0, and 2.4
have the exact same effect as rates 2.0, 4.0, and 4.8. Note that an
HMM rate category
can have rate of change 0, so that this allows us to take into account that
there may be a category of sites that are invariant. Note that the run time
of the program will be proportional to the number of HMM rate categories:
twice as
many categories means twice as long a run. Finally the program will ask for
the probabilities of a random site falling into each of these
regional rate categories. These probabilities must be nonnegative and sum to
1. Default
for the program is one category, with rate 1.0 and probability 1.0 (actually
the rate does not matter in that case).
If more than one HMM rate category is specified, then another
option, A, becomes
visible in the menu. This allows us to specify that we want to assume that
sites that have the same HMM rate category are expected to be clustered
so that there is autocorrelation of rates. The
program asks for the value of the average patch length. This is an expected
length of patches that have the same rate. If it is 1, the rates of
successive sites will be independent. If it is, say, 10.25, then the
chance of change to a new rate will be 1/10.25 after every site. However
the "new rate" is randomly drawn from the mix of rates, and hence could
even be the same. So the actual observed length of patches with the same
rate will be a bit larger than 10.25. Note below that if you choose
multiple patches, there will be an estimate in the output file as to
which combination of rate categories contributed most to the likelihood.
Note that the autocorrelation scheme we use is somewhat different
from Yang's (1995) autocorrelated Gamma distribution. I am unsure
whether this difference is of any importance -- our scheme is chosen
for the ease with which it can be implemented.
The C option allows user-defined rate categories. The user is prompted
for the number of user-defined rates, and for the rates themselves,
which cannot be negative but can be zero. These numbers, which must be
nonnegative (some could be 0),
are defined relative to each other, so that if rates for three categories
are set to 1 : 3 : 2.5 this would have the same meaning as setting them
to 2 : 6 : 5.
The assignment of rates to
sites is then made by reading a file whose default name is "categories".
It should contain a string of digits 1 through 9. A new line or a blank
can occur after any character in this string. Thus the categories file
might look like this:
122231111122411155
1155333333444
With the current options R, A, and C the program has gained greatly in its
ability to infer different rates at different sites and estimate
phylogenies under a more realistic model. Note that Likelihood Ratio
Tests can be used to test whether one combination of rates is
significantly better than another, provided one rate scheme represents
a restriction of another with fewer parameters. The number of parameters
needed for rate variation is the number of regional rate categories, plus
the number of user-defined rate categories less 2, plus one if the
regional rate categories have a nonzero autocorrelation.
The G (global search) option causes, after the last species is added to
the tree, each possible group to be removed and re-added. This improves the
result, since the position of every species is reconsidered. It
approximately triples the run-time of the program.
The User tree (option U) is read from a file whose default name is
intree.
The trees can be multifurcating.
If the U (user tree) option is chosen another option appears in
the menu, the L option. If it is selected,
it signals the program that it
should take any branch lengths that are in the user tree and
simply evaluate the likelihood of that tree, without further altering
those branch lengths. This means that if some branches have lengths
and others do not, the program will estimate the lengths of those that
do not have lengths given in the user tree. Note that the program RETREE
can be used to add and remove lengths from a tree.
The U option can read a multifurcating tree. This allows us to
test the hypothesis that a certain branch has zero length (we can also
do this by using RETREE to set the length of that branch to 0.0 when
it is present in the tree). By
doing a series of runs with different specified lengths for a branch we
can plot a likelihood curve for its branch length while allowing all
other branches to adjust their lengths to it. If all branches have
lengths specified, none of them will be iterated. This is useful to allow
a tree produced by another method to have its likelihood
evaluated. The L option has no effect and does not appear in the
menu if the U option is not used.
The W (Weights) option is invoked in the usual way, with only weights 0
and 1 allowed. It selects a set of sites to be analyzed, ignoring the
others. The sites selected are those with weight 1. If the W option is
not invoked, all sites are analyzed.
The Weights (W) option
takes the weights from a file whose default name is "weights". The weights
follow the format described in the main documentation file.
The M (multiple data sets) option will ask you whether you want to
use multiple sets of weights (from the weights file) or multiple data sets
from the input file.
The ability to use a single data set with multiple weights means that
much less disk space will be used for this input data. The bootstrapping
and jackknifing tool Seqboot has the ability to create a weights file with
multiple weights. Note also that when we use multiple weights for
bootstrapping we can also then maintain different rate categories for
different sites in a meaningful way. You should not use the multiple
data sets option without using multiple weights, you should not at the
same time use the user-defined rate categories option (option C).
The algorithm used for searching among trees is faster than it was in
version 3.5, thanks to using a technique invented by David Swofford
and J. S. Rogers. This involves not iterating most branch lengths on most
trees when searching among tree topologies, This is of necessity a
"quick-and-dirty" search but it saves much time. There is a menu option
(option S) which can turn off this search and revert to the earlier
search method which iterated branch lengths in all topologies. This will
be substantially slower but will also be a bit more likely to find the
tree topology of highest likelihood.
OUTPUT FORMAT
The output starts by giving the number of species, the number of sites,
and the base frequencies for A, C, G, and T that have been specified. It
then prints out the transition/transversion ratio that was specified or
used by default. It also uses the base frequencies to compute the actual
transition/transversion ratio implied by the parameter.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of sites is printed, as well
as the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the menu
option to print them out, with the base sequences printed in
groups of ten bases along the lines of the Genbank and EMBL formats. The
trees found are printed as an unrooted
tree topology (possibly rooted by outgroup if so requested). The
internal nodes are numbered arbitrarily for the sake of
identification. The number of trees evaluated so far and the log
likelihood of the tree are also given. Note that the trees printed out
have a trifurcation at the base. The branch lengths in the diagram are
roughly proportional to the estimated branch lengths, except that very short
branches are printed out at least three characters in length so that the
connections can be seen.
A table is printed
showing the length of each tree segment (in units of expected nucleotide
substitutions per site), as well as (very) rough confidence
limits on their lengths. If a confidence limit is
negative, this indicates that rearrangement of the tree in that region
is not excluded, while if both limits are positive, rearrangement is
still not necessarily excluded because the variance calculation on which
the confidence limits are based results in an underestimate, which makes
the confidence limits too narrow.
In addition to the confidence limits,
the program performs a crude Likelihood Ratio Test (LRT) for each
branch of the tree. The program computes the ratio of likelihoods with and
without this branch length forced to zero length. This done by comparing the
likelihoods changing only that branch length. A truly correct LRT would
force that branch length to zero and also allow the other branch lengths to
adjust to that. The result would be a likelihood ratio closer to 1. Therefore
the present LRT will err on the side of being too significant. YOU ARE
WARNED AGAINST TAKING IT TOO SERIOUSLY. If you want to get a better
likelihood curve for a branch length you can do multiple runs with
different prespecified lengths for that branch, as discussed above in the
discussion of the L option.
One should also
realize that if you are looking not at a previously-chosen branch but at all
branches, that you are seeing the results of multiple tests. With 20 tests,
one is expected to reach significance at the P = .05 level purely by
chance. You should therefore use a much more conservative significance level,
such as .05 divided by the number of tests. The significance of these tests
is shown by printing asterisks next to
the confidence interval on each branch length. It is important to keep
in mind that both the confidence limits and the tests
are very rough and approximate, and probably indicate more significance than
they should. Nevertheless, maximum likelihood is one of the few methods that
can give you any indication of its own error; most other methods simply fail to
warn the user that there is any error! (In fact, whole philosophical schools
of taxonomists exist whose main point seems to be that there isn't any
error, that the "most parsimonious" tree is the best tree by definition and
that's that).
The log likelihood printed out with the final tree can be used to perform
various likelihood ratio tests. One can, for example, compare runs with
different values of the expected transition/transversion ratio to determine
which value is the maximum likelihood estimate, and what is the allowable range
of values (using a likelihood ratio test, which you will find described in
mathematical statistics books). One could also estimate the base frequencies
in the same way. Both of these, particularly the latter, require multiple runs
of the program to evaluate different possible values, and this might get
expensive.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the
rates at different sites, the
program also performs a statistical test of each of these trees against the
one with highest likelihood. If there are two user trees, the test
done is one which is due to Kishino and Hasegawa (1989), a version
of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of
log-likelihood differences between trees, taken across sites. If the two
trees' means are more than 1.96 standard deviations different
then the trees are
declared significantly different. This use of the empirical variance of
log-likelihood differences is more robust and nonparametric than the
classical likelihood ratio test, and may to some extent compensate for the
any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods across
sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the highest log-likelihood exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the log-likelihoods of each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the log-likelihood differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one. However
the test is not available if we assume that there
is autocorrelation of rates at neighboring sites (option A) and is not
done in those cases.
The branch lengths printed out are scaled in terms of expected numbers of
substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate of
change, averaged over all sites analyzed, is set to 1.0
if there are multiple categories of sites. This means that whether or not
there are multiple categories of sites, the expected fraction of change
for very small branches is equal to the branch length. Of course,
when a branch is twice as
long this does not mean that there will be twice as much net change expected
along it, since some of the changes occur in the same site and overlie or
even reverse each
other. The branch length estimates here are in terms of the expected
underlying numbers of changes. That means that a branch of length 0.26
is 26 times as long as one which would show a 1% difference between
the nucleotide sequences at the beginning and end of the branch. But we
would not expect the sequences at the beginning and end of the branch to be
26% different, as there would be some overlaying of changes.
Confidence limits on the branch lengths are
also given. Of course a
negative value of the branch length is meaningless, and a confidence
limit overlapping zero simply means that the branch length is not necessarily
significantly different from zero. Because of limitations of the numerical
algorithm, branch length estimates of zero will often print out as small
numbers such as 0.00001. If you see a branch length that small, it is really
estimated to be of zero length. Note that versions 2.7 and earlier of this
program printed out the branch lengths in terms of expected probability of
change, so that they were scaled differently.
Another possible source of confusion is the existence of negative values for
the log likelihood. This is not really a problem; the log likelihood is not a
probability but the logarithm of a probability. When it is
negative it simply means that the corresponding probability is less
than one (since we are seeing its logarithm). The log likelihood is
maximized by being made more positive: -30.23 is worse than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what site categories
contributed the most to the final likelihood. This combination of
HMM rate categories need not have contributed a majority of the likelihood,
just a plurality. Still, it will be helpful as a view of where the
program infers that the higher and lower rates are. Note that the
use in this calculations of the prior probabilities of different rates,
and the average patch length, gives this inference a "smoothed"
appearance: some other combination of rates might make a greater
contribution to the likelihood, but be discounted because it conflicts
with this prior information. See the example output below to see
what this printout of rate categories looks like.
A second list will also be printed out, showing for each site which
rate accounted for the highest fraction of the likelihood. If the fraction
of the likelihood accounted for is less than 95%, a dot is printed instead.
Option 3 in the menu controls whether the tree is printed out into
the output file. This is on by default, and usually you will want to
leave it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees
which are written onto the output tree file, rather than the trees
printed on the output file. To keep the output file from becoming too
large, it may be wisest to use option 3 to prevent trees being
printed onto the output file.
Option 4 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined
trees are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated
at each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species which
are the input sequences). In that table, if a site has a base which
accounts for more than 95% of the likelihood, it is printed in capital
letters (A rather than a). If the best nucleotide accounts for less
than 50% of the likelihood, the program prints out an ambiguity code
(such as M for "A or C") for the set of nucleotides which, taken together,
account for more half of the likelihood. The ambiguity codes are listed
in the sequence programs documentation file. One limitation of the current
version of the program is that when there are multiple HMM rates
(option R) the reconstructed nucleotides are based on only the single
assignment of rates to sites which accounts for the largest amount of the
likelihood. Thus the assessment of 95% of the likelihood, in tabulating
the ancestral states, refers to 95% of the likelihood that is accounted
for by that particular combination of rates.
PROGRAM CONSTANTS
The constants defined at the beginning of the program include "maxtrees",
the maximum number of user trees that can be processed. It is small (100)
at present to save some further memory but the cost of increasing it
is not very great. Other constants
include "maxcategories", the maximum number of site
categories, "namelength", the length of species names in
characters, and three others, "smoothings", "iterations", and "epsilon", that
help "tune" the algorithm and define the compromise between execution speed and
the quality of the branch lengths found by iteratively maximizing the
likelihood. Reducing iterations and smoothings, and increasing epsilon, will
result in faster execution but a worse result. These values
will not usually have to be changed.
The program spends most of its time doing real arithmetic.
The algorithm, with separate and independent computations
occurring for each pattern, lends itself readily to parallel processing.
PAST AND FUTURE OF THE PROGRAM
This program, which in version 2.6 replaced the old version of DNAML,
is not derived directly
from it but instead was developed by modifying CONTML, with which it shares
many of its data structures and much of its strategy. It was speeded up
by two major developments, the use of aliasing of nucleotide sites (version
3.1) and pretabulation of some exponentials (added by Akiko Fuseki in version
3.4). In version 3.5 the Hidden Markov Model code was added and the method
of iterating branch lengths was changed from an EM algorithm to direct
search. The Hidden Markov Model code slows things down, especially if
there is autocorrelation between sites, so this version is slower than
version 3.4. Nevertheless we hope that the sacrifice is worth it.
One change that is needed in the future is to put in some way of
allowing for base composition of nucleotide sequences in different parts
of the phylogeny.
CONTENTS OF OUTPUT FILE (with all numerical options on)
(It was run with HMM rates having gamma-distributed rates
approximated by 5 rate categories,
with coefficient of variation of rates 1.0, and with patch length
parameter = 1.5. Two user-defined rate categories were used, one for
the first 6 sites, the other for the last 7, with rates 1.0 : 2.0.
Weights were used, with sites 1 and 13 given weight 0, and all others
weight 1.)
Nucleic acid sequence Maximum Likelihood method, version 3.6a3
5 species, 13 sites
Site categories are:
1111112222 222
Sites are weighted as follows:
0111111111 111
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
Empirical Base Frequencies:
A 0.23333
C 0.30000
G 0.23333
T(U) 0.23333
Transition/transversion ratio = 2.000000
Discrete approximation to gamma distributed rates
Coefficient of variation of rates = 1.000000 (alpha = 1.000000)
State in HMM Rate of change Probability
1 0.264 0.522
2 1.413 0.399
3 3.596 0.076
4 7.086 0.0036
5 12.641 0.000023
Expected length of a patch of sites having the same rate = 1.500
Site category Rate of change
1 1.000
2 2.000
+Beta
|
| +Epsilon
| +------------------------------------------------------3
1--2 +--Delta
| |
| +--------Gamma
|
+--Alpha
remember: this is an unrooted tree!
Ln Likelihood = -66.19167
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
1 Alpha 0.49468 ( zero, 1.23032) **
1 Beta 0.00006 ( zero, 0.62569)
1 2 0.22531 ( zero, 2.28474)
2 3 8.20666 ( zero, 23.52785) **
3 Epsilon 0.00006 ( zero, 0.65419)
3 Delta 0.44668 ( zero, 1.10233) **
2 Gamma 1.34187 ( zero, 3.46288) **
* = significantly positive, P < 0.05
** = significantly positive, P < 0.01
Combination of categories that contributes the most to the likelihood:
1122121111 112
Most probable category at each site if > 0.95 probability ("." otherwise)
.......... ...
Probable sequences at interior nodes:
node Reconstructed sequence (caps if > 0.95)
1 .AGGTCGCCA AAC
Beta AAGGTCGCCA AAC
2 .AggTcGcCA aAc
3 .GGATCTCGG CCC
Epsilon GGGATCTCGG CCC
Delta GGTATTTCGG CCT
Gamma CATTTCGTCA CAA
Alpha AACGTGGCCA AAT
DNAPENNY is a program that will find all of the most parsimonious trees
implied by your data when the nucleic acid sequence parsimony criterion is
employed. It does so not by examining all possible trees,
but by using the more sophisticated "branch and bound" algorithm, a
standard computer science search strategy first applied to
phylogenetic inference by Hendy and Penny (1982). (J. S. Farris
[personal communication, 1975] had also suggested that this strategy,
which is well-known in computer science, might
be applied to phylogenies, but he did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem of
finding these has been shown (Graham and Foulds, 1982; Day, 1983) to be
NP-complete, which is equivalent to saying that there is no
fast algorithm that is guaranteed to solve the problem in all cases
(for a discussion of NP-completeness, see the Scientific American
article by Lewis and Papadimitriou, 1978). The result is that this program,
despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs
in the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of someone
who can let a microcomputer grind all night than for someone who
has the "benefit" of paying for time on the campus mainframe computer). IT
IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE PROGRAM
WILL TAKE ON YOUR DATA. This can be done by running it on subsets
of the species, increasing the number of species in the run until you
either are able to treat the full data set or know that the program
will take unacceptably long on it. (Making a plot of the logarithm of
run time against species number may help to project run times).
The Algorithm
The search strategy used by DNAPENNY starts by making a tree consisting of the
first two species (the first three if the tree is to be unrooted). Then
it tries to add the next species in all possible places (there are three
of these). For each of the resulting trees it evaluates the number of
base substitutions. It adds the next species to each of these, again in all
possible spaces. If this process would continue it would simply
generate all possible trees, of which there are a very large number even
when the number of species is moderate (34,459,425 with 10 species). Actually
it does not do this, because the trees are generated in a
particular order and some of them are never generated.
This is because the order in which trees are generated is not quite as implied
above, but is a "depth-first search". This means that first one adds the third
species in the first possible place, then the fourth species in its first
possible place, then the fifth and so on until the first possible tree has
been produced. For each tree the number of steps is evaluated. Then one
"backtracks" by trying the alternative placements of the last species. When
these are exhausted one tries the next placement of the next-to-last
species. The order of placement in a depth-first search is like this for a
four-species case (parentheses enclose monophyletic groups):
Make tree of first two species: (A,B)
Add C in first place: ((A,B),C)
Add D in first place: (((A,D),B),C)
Add D in second place: ((A,(B,D)),C)
Add D in third place: (((A,B),D),C)
Add D in fourth place: ((A,B),(C,D))
Add D in fifth place: (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place: (((A,D),C),B)
Add D in second place: ((A,(C,D)),B)
Add D in third place: (((A,C),D),B)
Add D in fourth place: ((A,C),(B,D))
Add D in fifth place: (((A,C),B),D)
Add C in third place: (A,(B,C))
Add D in first place: ((A,D),(B,C))
Add D in second place: (A,((B,D),C))
Add D in third place: (A,(B,(C,D)))
Add D in fourth place: (A,((B,C),D))
Add D in fifth place: ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species
rooted trees, each exactly once (the parentheses each enclose
a monophyletic group). As displayed above, the backtracking
depth-first search algorithm is just another way of producing all
possible trees one at a time. The branch and bound algorithm
consists of this with one change. As each tree is constructed,
including the partial trees such as (A,(B,C)), its number of steps
is evaluated. In addition a prediction is made as to how many
steps will be added, at a minimum, as further species are added.
This is done by counting how many sites which are invariant in the data up the
most recent species added will ultimately show variation when further species
are added. Thus if 20 sites vary among species A, B, and C and their root,
and if tree ((A,C),B) requires 24 steps, then if there are 8 more sites which
will be seen to vary when species D is added, we can immediately say that no
matter how we add D, the resulting tree can have no less than 24 + 8 = 32
steps. The point of all this is that if a previously-found tree such as
((A,B),(C,D)) required only 30 steps, then we know that there is no point in
even trying to add D to ((A,C),B). We have computed the bound that enables us
to cut off a whole line of inquiry (in this case five trees) and avoid going
down that particular branch any farther.
The branch-and-bound algorithm thus allows us to find all most parsimonious
trees without generating all possible trees. How much of a saving this
is depends strongly on the data. For very clean (nearly "Hennigian")
data, it saves much time, but on very messy data it will still take
a very long time.
The algorithm in the program differs from the one outlined here
in some essential details: it investigates possibilities in the
order of their apparent promise. This applies to the order of addition
of species, and to the places where they are added to the tree. After
the first two-species tree is constructed, the program tries adding
each of the remaining species in turn, each in the best possible place it
can find. Whichever of those species adds (at a minimum) the most
additional steps is taken to be the one to be added next to the tree. When
it is added, it is added in turn to places which cause the fewest
additional steps to be added. This sounds a bit complex, but it is done
with the intention of eliminating regions of the search of all possible
trees as soon as possible, and lowering the bound on tree length as quickly
as possible. This process of evaluating which species to add in which
order goes on the first time the search makes a tree; thereafter it uses that
order.
The program keeps a list of all the most parsimonious
trees found so far. Whenever it finds one that has fewer losses than
these, it clears out the list and
restarts it with that tree. In the process the bound tightens and
fewer possibilities need be investigated. At the end the list contains
all the shortest trees. These are then printed out. It should be
mentioned that the program CLIQUE for finding all largest cliques
also works by branch-and-bound. Both problems are NP-complete but for
some reason CLIQUE runs far faster. Although their worst-case behavior
is bad for both programs, those worst cases occur far more frequently
in parsimony problems than in compatibility problems.
Controlling Run Times
Among the quantities available to be set from the menu of
DNAPENNY, two (howoften and howmany) are of particular
importance. As DNAPENNY goes along it will keep count of how many
trees it has examined. Suppose that howoften is 100 and howmany is 1000,
the default settings. Every time 100 trees have been examined, DNAPENNY
will print out a line saying how many multiples of 100 trees have now been
examined, how many steps the most parsimonious tree found so far has,
how many trees of with that number of steps have been found, and a very
rough estimate of what fraction of all trees have been looked at so far.
When the number of these multiples printed out reaches the number howmany
(say 1000), the whole algorithm aborts and prints out that it has not
found all most parsimonious trees, but prints out what is has got so far
anyway. These trees need not be any of the most parsimonious trees: they are
simply the most parsimonious ones found so far. By setting the product
(howoften times howmany) large you can make
the algorithm less likely to abort, but then you risk getting bogged
down in a gigantic computation. You should adjust these constants so that
the program cannot go beyond examining the number of trees you are reasonably
willing to pay for (or wait for). In their initial setting the program will
abort after looking at 100,000 trees. Obviously you may want to adjust
howoften in order to get more or fewer lines of intermediate notice of how
many trees have been looked at so far. Of course, in small cases you may
never even reach the first multiple of howoften, and nothing will be printed
out except some headings and then the final trees.
The indication of the approximate percentage of trees searched so far will
be helpful in judging how much farther you would have to go to get the full
search. Actually, since that fraction is the fraction of the set of all
possible trees searched or ruled out so far, and since the search becomes
progressively more efficient, the approximate fraction printed out will
usually be an underestimate of how far along the program is, sometimes a
serious underestimate.
A constant
at the beginning of the program that affects the result is
"maxtrees",
which controls the
maximum number of trees that can be stored. Thus if maxtrees is 25,
and 32 most parsimonious trees are found, only the first 25 of these are
stored and printed out. If maxtrees is increased, the program does not
run any slower but requires a little
more intermediate storage space. I recommend
that maxtrees be kept as large as you can, provided you are willing to
look at an output with that many trees on it! Initially, maxtrees is set
to 100 in the distribution copy.
Method and Options
The counting of the length of trees is done by an algorithm nearly
identical to the corresponding algorithms in DNAPARS, and thus the remainder
of this document will be nearly identical to the DNAPARS document.
This program carries out unrooted parsimony (analogous to Wagner
trees) (Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA
sequences. The method of Fitch (1971) is used to count the number of
changes of base needed on a given tree. The assumptions of this
method are exactly analogous to those of DNAPARS:
Each site evolves independently.
Different lineages evolve independently.
The probability of a base substitution at a given site is
small over the lengths of time involved in
a branch of the phylogeny.
The expected amounts of change in different branches of the phylogeny
do not vary by so much that two changes in a high-rate branch
are more probable than one change in a low-rate branch.
The expected amounts of change do not vary enough among sites that two
changes in one site are more probable than one change in another.
Change from an occupied site to a deletion is counted as one
change. Reversion from a deletion to an occupied site is allowed and is also
counted as one change.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an
opposing view arguing that the parsimony methods make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
Change from an occupied site to a deletion is counted as one
change. Reversion from a deletion to an occupied site is allowed and is also
counted as one change. Note that this in effect assumes that a deletion
N bases long is N separate events.
The input data is standard. The first line of the input file contains the
number of species and the number of sites. If the Weights option is being
used, there must also be a W in this first line to signal its presence.
There are only two options requiring information to be present in the input
file, W (Weights) and U (User tree). All options other than W (including U) are
invoked using the menu.
Next come the species data. Each
sequence starts on a new line, has a ten-character species name
that must be blank-filled to be of that length, followed immediately
by the species data in the one-letter code. The sequences must either
be in the "interleaved" or "sequential" formats
described in the Molecular Sequence Programs document. The I option
selects between them. The sequences can have internal
blanks in the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a deletion.
The options are selected using an interactive menu. The menu looks like this:
Penny algorithm for DNA, version 3.6a3
branch-and-bound to find all most parsimonious trees
Settings for this run:
H How many groups of 100 trees: 1000
F How often to report, in trees: 100
S Branch and bound is simple? Yes
O Outgroup root? No, use as outgroup species 1
T Use Threshold parsimony? No, use ordinary parsimony
W Sites weighted? No
M Analyze multiple data sets? No
I Input sequences interleaved? Yes
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each site No
5 Print sequences at all nodes of tree No
6 Write out trees onto tree file? Yes
Are these settings correct? (type Y or the letter for one to change)
The user either types "Y" (followed, of course, by a carriage-return)
if the settings shown are to be accepted, or the letter or digit corresponding
to an option that is to be changed.
The options O, T, W, M, and 0 are the usual ones. They are described in the
main documentation file of this package. Option I is the same as in
other molecular sequence programs and is described in the documentation file
for the sequence programs.
The T (threshold) option allows a continuum of methods
between parsimony and compatibility. Thresholds less than or equal to 1.0 do
not have any meaning and should
not be used: they will result in a tree dependent only on the input
order of species and not at all on the data!
The W (Weights) option allows only weights of 0 or 1.
The M (Multiple data sets) option for this program does not allow multiple
sets of weights. We hope to change this soon.
The options H, F, and S are not found in the other molecular sequence programs.
H (How many) allows the user to set the quantity howmany, which we have
already seen controls number of times that the program
will report on its progress. F allows the user to set the quantity howoften,
which sets how often it will report -- after scanning how many trees.
The S (Simple) option alters a step in DNAPENNY which reconsiders the
order in which species are added to the tree. Normally the decision as to
what species to add to the tree next is made as the first tree is being
constructed; that ordering of species is not altered subsequently. The S
option causes it to be continually reconsidered. This will probably
result in a substantial increase in run time, but on some data sets of
intermediate messiness it may help. It is included in case it might prove
of use on some data sets.
Output is standard: if option 1 is toggled on, the data is printed out,
with the convention that "." means "the same as in the first species".
Then comes a list of equally parsimonious trees, and (if option 2 is
toggled on) a table of the
number of changes of state required in each character. If option 5 is toggled
on, a table is printed
out after each tree, showing for each branch whether there are known to be
changes in the branch, and what the states are inferred to have been at the
top end of the branch. If the inferred state is a "?" or one of the IUB
ambiguity symbols, there will be multiple
equally-parsimonious assignments of states; the user must work these out for
themselves by hand. A "?" in the reconstructed states means that in
addition to one or more bases, a deletion may or may not be present. If
option 6 is left in its default state the trees
found will be written to a tree file, so that they are available to be used
in other programs.
This program implements the Neighbor-Joining method of Nei and Saitou (1987)
and the UPGMA method of clustering. The program was written by Mary Kuhner
and Jon Yamato, using some code from program FITCH. An important part of the
code was translated
from FORTRAN code from the neighbor-joining program written by Naruya Saitou
and by Li Jin, and is used with the kind permission of Drs. Saitou and Jin.
NEIGHBOR constructs a tree by successive clustering of lineages, setting
branch lengths as the lineages join. The tree is not rearranged
thereafter. The tree does not assume an evolutionary clock, so that it
is in effect an unrooted tree. It should be somewhat similar to the tree
obtained by FITCH. The program cannot evaluate a User tree, nor can it prevent
branch lengths from becoming negative. However the algorithm is far faster
than FITCH or KITSCH. This will make it particularly effective in their place
for large studies or for bootstrap or jackknife resampling studies which
require runs on multiple data sets.
The UPGMA option constructs a tree by successive (agglomerative) clustering
using an average-linkage method of clustering. It has some relationship
to KITSCH, in that when the tree topology turns out the same, the
branch lengths with UPGMA will turn out to be the same as with the P = 0
option of KITSCH.
The options for NEIGHBOR are selected through the menu, which looks like
this:
Neighbor-Joining/UPGMA method version 3.6a3
Settings for this run:
N Neighbor-joining or UPGMA tree? Neighbor-joining
O Outgroup root? No, use as outgroup species 1
L Lower-triangular data matrix? No
R Upper-triangular data matrix? No
S Subreplicates? No
J Randomize input order of species? No. Use input order
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
Most of the input options
(L, R, S, J, and M) are as given in the Distance Matrix Programs
documentation file,
that file, and their input format is the same as given there.
The O (Outgroup) option
is described in the main
documentation file of this package. It is not available when the
UPGMA option is selected. The Jumble option (J) does not allow
multiple jumbles (as most of the other programs that have it do),
as there is no objective way of choosing which of the multiple
results is best, there being no explicit criterion for optimality of the tree.
Option N chooses between the Neighbor-Joining and UPGMA methods. Option
S is the usual Subreplication option. Here, however, it is present only
to allow NEIGHBOR to read the input data: the number of replicates is
actually ignored, even though it is read in. Note that this means that
one cannot use it to have missing data in the input file, if NEIGHBOR is
to be used.
The output consists of an tree (rooted if UPGMA, unrooted if Neighbor-Joining)
and the lengths of the
interior segments. The Average Percent Standard Deviation is not
computed or printed out. If the tree found by Neighbor is fed into FITCH
as a User Tree, it will compute this quantity if one also selects the
N option of FITCH to ensure that none of the branch lengths is re-estimated.
As NEIGHBOR runs it prints out an account of the successive clustering
levels, if you allow it to. This is mostly for reassurance and can be
suppressed using menu option 2. In this printout of cluster levels
the word "OTU" refers to a tip species, and the word "NODE" to an
interior node of the resulting tree.
The constants available for modification at the beginning of the
program are "namelength" which gives the length of a
species name, and the usual boolean
constants that initiliaze the terminal type. There is no feature saving
multiply trees tied for best,
partly because we do not expect exact ties except in cases where the branch
lengths make the nature of the tie obvious, as when a branch is of zero
length.
The major advantage of NEIGHBOR is its speed: it requires a time only
proportional to the square of the number of species. It is significantly
faster than version 3.5 of this program. By contrast FITCH
and KITSCH require a time that rises as the fourth power of the number
of species. Thus NEIGHBOR is well-suited to bootstrapping studies and
to analysis of very large trees. Our simulation studies (Kuhner
and Felsenstein, 1994) show that, contrary to statements in the
literature by others, NEIGHBOR does not get as accurate an estimate of
the phylogeny as does FITCH. However it does nearly as well, and in
view of its speed this will make it a quite useful program.
RETREE is a tree editor. It reads in a tree,
or allows the user to construct one, and
displays this tree on the screen. The
user then can specify how the tree is to
be rearraranged, rerooted or written out to a file.
The input trees are in one file (with default file name
intree), the
output trees are written into another (outtree). The user
can reroot, flip branches, change names of species, change or remove
branch lengths, and move around to look at various parts of the tree if it is
too large to fit on the screen. The trees can be multifurcating at any
level, although the user is warned that many PHYLIP programs still cannot
handle multifurcations above the root, or even at the root.
A major use for this program will be to change rootedness of trees so that
a rooted tree derived from one program can be fed in as an unrooted tree to
another (you are asked about this when you give the command to write out
the tree onto the tree output file). It will also be useful for specifying
the length of a branch in
a tree where you want a program like DNAML, DNAMLK, FITCH, or CONTML to
hold that branch length constant (see the L suboption of the User Tree
option in those programs. It will also be useful for changing the order
of species for purely cosmetic reasons for DRAWGRAM and DRAWTREE, including
using the Midpoint method of rooting the tree. It can also be used to write out
a tree file in the Nexus format used by Paup and MacClade or in our XML tree
file format.
This program uses graphic characters that show the tree to best
advantage on some computer systems.
Its graphic characters will work best on MSDOS systems or MSDOS windows in
Windows, and to
any system whose screen or terminals emulate ANSI standard terminals
such as old Digitial VT100 terminals,
Telnet programs,
or VT100-compatible windows in the X windowing system.
For any other screen types, (such as Macintosh windows) there is a generic
option which does
not make use of screen graphics characters. The program will work well
in those cases, but the tree it displays will look a bit uglier.
The user interaction starts with the program presenting a menu. The
menu looks like this:
Tree Rearrangement, version 3.6a3
Settings for this run:
U Initial tree (arbitrary, user, specify)? User tree from tree file
N Format to write out trees (PHYLIP, Nexus, XML)? PHYLIP
0 Graphics type (IBM PC, ANSI)? (none)
W Width of terminal screen, of plotting area? 80, 80
L Number of lines on screen? 24
Are these settings correct? (type Y or the letter for one to change)
The 0 (Graphics type) option is the usual
one and is described in the main documentation file. The U (initial tree)
option allows the user to choose whether
the initial tree is to be arbitrary, interactively specified by the user, or
read from a tree file. Typing U causes the program to change among the
three possibilities in turn. Usually we will want to use a User Tree from
a file. It requires that you have available a tree file
with the tree topology of the initial tree. If you wish to set up some other
particular tree you can either use the "specify" choice in the initial tree
option (which is somewhat clumsy to use) or rearrange a User Tree of an
arbitrary tree into the shape you want by using
the rearrangement commands given below.
The L (screen Lines) option allows the user to change the height of the
screen (in lines of characters) that is assumed to be available on the
display. This may be particularly helpful when displaying large trees
on displays that have more than 24 lines per screen, or on workstation
or X-terminal screens that can emulate the ANSI terminals with more than
24 lines.
The N (output file format) option allows the user to specify that the tree files that
are written by the program will be in one of three formats:
The PHYLIP default file format (the Newick standard) used by the
programs in this package.
The Nexus format defined by
David Swofford and by Wayne Maddison and David Maddison for their programs
PAUP and MacClade. A tree file written in Nexus format should be directly
readable by those programs (They also have options to read a regular
PHYLIP tree file as well).
An XML tree file format which we have defined.
The XML tree file format is fairly simple. Each tree is included in tags
<PHYLOGENY> ... </PHYLOGENY>. Each branch of the tree is enclosed in a pair of tags
<BRANCH> ... </BRANCH>, which enclose the branch and all its descendants.
If the branch has a length, this is given by the LENGTH attribute of the
BRANCH tag, so that the pair of tags looks like this:
<BRANCH LENGTH=0.09362> ... </BRANCH>
A tip of the tree is at the end of a branch (and hence enclosed in a pair of
<BRANCH> ... </BRANCH> tags. Its name is enclosed by <NAME> ... </NAME>
tags. Here is an XML tree:
The indentation is for readability but is not part of the XML tree
standard, which ignores that kind of white space.
What programs can read an XML tree? None right now, not even PHYLIP programs.
But soon our lab's LAMARC package will have programs that can read an XML tree.
XML is rapidly becoming the standard for representing and interchanging
complex data -- it is time to have an XML tree standard. Certain extensions
are obvious (to represent the bootstrap proportion for a branch, use
BOOTP=0.83 in the BRANCH tag, for example).
The W (screen and window Width) option specifies the width in characters
of the area which the trees will be plotted to fit into. This is by
default 80 characters so that they will fit on a normal width terminal. The
actual width of the display on the terminal (normally 80 characters) will
be regarded as a window displaying part of the tree. Thus you could
set the "plotting area" to 132 characters, and inform the program that
the screen width is 80 characters. Then the program will display only part
of the tree at any one time. Below we will show how to move the "window"
and see other parts of the tree.
After the initial menu is displayed and the choices are made,
the program then sets up an initial tree and displays it. Below it will be a
one-line menu of possible commands. Here is what the tree and the menu
look like (this is the tree specified by the example input tree given at
the bottom of this page, as it displays when the terminal type is "none"):
,>>1:Human
,>22
,>21 `>>2:Chimp
! !
,>20 `>>>>>3:Gorilla
! !
,>>>>>>>>>>19 `>>>>>>>>4:Orang
! !
,>18 `>>>>>>>>>>>5:Gibbon
! !
! ! ,>>>>>>>>6:Barbary Ma
! `>>>>>>>>>>>>>23
! ! ,>>>>>7:Crab-e. Ma
,>>>>>>>17 `>24
! ! ! ,>>8:Rhesus Mac
! ! `>25
! ! `>>9:Jpn Macaq
,>16 !
! ! `>>>>>>>>>>>>>>>>>>>>>>>>>10:Squir. Mon
! !
! ! ,>11:Tarsier
** 7 lines below screen **
NEXT? (Options: R . U W O T F D B N H J K L C + ? X Q) (? for Help)
The tree that was read in had no branch lengths on its branches. The
absence of a branch length is indicated by drawing the branch with ">"
characters (>>>>>>>). When branches have branch lengths, they are
drawn with "-" characters (-------) and their
lengths on the screen are approximately proportional to the branch length.
If you type "?" you will get a single screen showing a description of each
of these commands in a few words. Here are slightly more detailed
descriptions of the commands:
R
("Rearrange"). This command asks for the number of a node which is to be
removed from the tree. It and everything to the right of it on the tree is to
be removed (by breaking the branch immediately below it). (This is also
everything "above" it on the tree when the tree grows upwards, but as the
tree grows from left to right on the screen we use "right" rather than
"above"). The command also
asks whether that branch is to be inserted At a node or Before a node.
The first will insert it as an additional branch coming out of an
existing node (creating a more multifurcating tree), and the second will insert
it so that a new internal node is created in the tree, located in the
branch that precedes the node (to the left of it), with the branch that is
inserted coming off from that new node. In both cases the program asks you
for the number of a node at (or before) which that group is to be inserted.
If an
impossible number is given, the program refuses to carry out the rearrangement
and asks for a new command. The rearranged tree is displayed: it will often
have a different number of steps than the original. If you wish to undo a
rearrangement, use the Undo command, for which see below.
.
(dot) This command simply causes the current tree to be redisplayed. It is of
use when the tree has partly disappeared off of the top of the screen owing to
too many responses to commands being printed out at the bottom of the screen.
=
(toggle display of branch lengths). This option is available whenever
the tree has a full set of branch lengths. It toggles on and off whether
the tree displayed on the screen is shown with the relative branch lengths
roughly correct. (It cannot be better than roughly correct because the
display is in units of length of whole character widths on the screen). It
does not actually remove any branch lengths from the tree: if the tree
showing on the screen seems to have no branch lengths after use of the "="
option, if it were written out at that point, it would still have a full]
set of branch lengths.
U
("Undo"). This command reverses the effect of the most recent
rearrangement, outgroup re-rooting, or flipping of branches. It returns to the
previous tree topology. It will be of great use when rearranging the tree and
when one -- it permits you to
abandon the new one and return to the previous one without remembering its
topology in detail. Some operations, such as the simultaneous removal of
lengths from all branches, cannot be reversed.
W
("Write"). This command writes out the current tree onto a tree output
file. If the file already has been written to by this run of RETREE, it will
ask you whether you want to replace the contents of the file, add the tree to
the end of the file, or not write out the tree to the file. It will also
ask you whether you want the tree to written out as Rooted or Unrooted. If
you choose Unrooted, it will write the outermost split of the tree as a
three-way split with the three branches being those that issue from one of
the nodes. This node will be the left (upper) interior node which is next
to the root, or the other one if there is no interior node to the left (above)
the root. The tree
is written in the standard format used by PHYLIP (a subset of the
Newick standard), in the Nexus format, or in an XML tree file format.
A normal PHYLIP tree
is in the proper format to serve as the
User-Defined Tree for setting up the initial tree in a subsequent run of the
program. However, some programs also require a line in the tree input
file that gives the number of trees in the file. You may have to add this
line using an editor such as vi, Emacs, Windows
Notepad, or MacOS's Simpletext.
O
("Outgroup"). This asks for the number of a node which is to be the
outgroup. The tree will be redisplayed with that node
as the left descendant of the bottom fork. Note that it is possible to
use this to make a multi-species group the outgroup (i.e., you can give the
number of an interior node of the tree as the outgroup, and the program will
re-root the tree properly with that on the left of the bottom fork.
M
("Midpoint root"). This reroots a tree that has a complete set of
branches using the Midpoint rooting method. That rooting method finds the
centroid of the tree -- the point that is equidistant from the two
farthest points of the tree, and roots the tree there. This is the point
in the middle of the longest path from one tip to another in the tree.
This has the effect
of making the two farthest tips stick out an equal distance to the
right. Note that as the tree is rerooted, the scale may change on the screen
so that it looks like it ahas suddenly gotted a bit longer. It will not
have actually changed in total length. This option is not in the menu
if the tree does not have a full set of branch lengths.
T
("Transpose"). This asks for a node number and then flips the two
branches at that node, so that the left-right order of branches at that node is
changed. This also does not actually change the tree topology
but it does change the appearance of the tree. However, unlike the F
option discussed below, the individual subtrees defined by those branches do
not have the order of any branches reversed in them.
F
("Flip"). This asks for a node number and then flips the entire
subtree at that node, so that the left-right order of branches in the whole
subtree is changed. This does not actually change the tree topology
but it does change the appearance of the tree. Note that it works differently
than the F option in the programs MOVE, DNAMOVE, and DOLMOVE, which
is actually like the T option mentioned above.
B
("Branch length"). This asks you for the number of a node
which is at the end of a branch length, then asks you whether you want to
enter a branch length for that branch, change the branch length for that
branch (if there is one already) or remove the branch length from the
branch.
N
("Name"). This asks you which species you want to change the
name for (referring to it by the number for that branch), then gives you the
option of either removing the name, typing a new name, or leaving the
name as is. Be sure not to try to enter a parentheses ("(" or ")"), a
colon (":"), a comma (",") or a semicolon (";") in a name, as those may
be mistaken for structural information about the tree when the tree file
is read by another program.
H, J, K, or L.
These are the movement commands for scrolling the
"window" across a tree. H moves the "window" leftwards (though not beyond
column 1, J moves it down, K up, and L right. The "window" will
move 20 columns or rows at a time, and the tree will be redrawn in
the new "window". Note that this amount of movement is not a full screen.
C
("Clade"). The C command instructs the program to print out
only that part of the
tree (the "clade") from a certain node on up. The program will prompt you for
the number of this node. Remember that thereafter you are not looking at the
whole tree. To go back to looking at the whole tree give the C command again
and enter "0" for the node number when asked. Most users will not want to use
this option unless forced to, as much can be accomplished with the window
movement commands H, J, K, and L.
+
("next tree"). This causes the program to read in the next tree in
the input file, if there is one. Currently the program does not detect
gracefully that it has come to the end of the input tree file, and may
crash with a "segmentation fault" if it does. However usually it will not
lose any tree file that it has written. On Unix or Linux systems the
crash may produce a useless "core dump" (a big file named "core") which
you will want to delete.
?
("Help"). Prints a one-screen summary of what the commands do, a few
words for each command.
X
("Exit"). Exit from program. If the current tree has not yet been saved
into a file, the program will first ask you whether it should be saved.
Q
("Quit"). A synonym for X. Same as the eXit command.
The program was written by Andrew Keeffe, using some code from DNAMOVE, which
he also wrote.
Below is a test tree file. We have already showed (above), what the
resulting tree display looks like when the terminal type is "none".
For ANSI or IBM PC screens it will look better, using the graphics characters
of those screens, which we do not attempt to show here.
This program carries out the Dollo and polymorphism parsimony methods. The
Dollo parsimony method was
first suggested in print in verbal form by Le Quesne (1974) and was
first well-specified by Farris (1977). The method is named after Louis
Dollo since he was one of the first to assert that in evolution it is
harder to gain a complex feature than to lose it. The algorithm
explains the presence of the state 1 by allowing up to one forward
change 0-->1 and as many reversions 1-->0 as are necessary to explain
the pattern of states seen. The program attempts to minimize the number
of 1-->0 reversions necessary.
The assumptions of this method are in effect:
We know which state is the ancestral one (state 0).
The characters are evolving independently.
Different lineages evolve independently.
The probability of a forward change (0-->1) is small over the
evolutionary times involved.
The probability of a reversion (1-->0) is also small, but
still far larger than the probability of a forward change, so
that many reversions are easier to envisage than even one
extra forward change.
Retention of polymorphism for both states (0 and 1) is highly
improbable.
The lengths of the segments of the true tree are not so
unequal that two changes in a long segment are as probable as
one in a short segment.
One problem can arise when using additive binary recoding to
represent a multistate character as a series of two-state characters. Unlike
the Camin-Sokal, Wagner, and Polymorphism methods, the Dollo
method can reconstruct ancestral states which do not exist. An example
is given in my 1979 paper. It will be necessary to check the output to
make sure that this has not occurred.
The polymorphism parsimony method was first used by me, and the results
published (without a clear
specification of the method) by Inger (1967). The method was
independently published by Farris (1978a) and by me (1979). The method
assumes that we can explain the pattern of states by no more than one
origination (0-->1) of state 1, followed by retention of polymorphism
along as many segments of the tree as are necessary, followed by loss of
state 0 or of state 1 where necessary. The program tries to minimize
the total number of polymorphic characters, where each polymorphism is
counted once for each segment of the tree in which it is retained.
The assumptions of the polymorphism parsimony method are in effect:
The ancestral state (state 0) is known in each character.
The characters are evolving independently of each other.
Different lineages are evolving independently.
Forward change (0-->1) is highly improbable over the length of
time involved in the evolution of the group.
Retention of polymorphism is also improbable, but far more
probable that forward change, so that we can more easily
envisage much polymorhism than even one additional forward
change.
Once state 1 is reached, reoccurrence of state 0 is very
improbable, much less probable than multiple retentions of
polymorphism.
The lengths of segments in the true tree are not so unequal
that we can more easily envisage retention events occurring in
both of two long segments than one retention in a short
segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
The input format is the standard one, with "?", "P", "B" states
allowed. The options are selected using a menu:
Dollo and polymorphism parsimony algorithm, version 3.6a3
Settings for this run:
U Search for best tree? Yes
P Parsimony method? Dollo
J Randomize input order of species? No. Use input order
T Use Threshold parsimony? No, use ordinary parsimony
A Use ancestral states in input file? No
W Sites weighted? No
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Print out steps in each character No
5 Print states at all nodes of tree No
6 Write out trees onto tree file? Yes
Are these settings correct? (type Y or the letter for one to change)
The options U, J, T, A, and M are the usual User Tree, Jumble,
Ancestral States, and Multiple Data Sets options, described either
in the main documentation file or in the Discrete Characters Programs
documentation file. The A (Ancestral States)
option allows implementation of the unordered Dollo parsimony and unordered
polymorphism parsimony methods which I have
described elsewhere (1984b). When the A option is used the ancestor is
not to be counted as one of the species. The O (outgroup) option is not
available since the tree produced is already rooted. Since the Dollo and
polymorphism methods produce a rooted
tree, the user-defined trees required by the U option have two-way forks
at each level.
The P (Parsimony Method) option is the one that toggles between polymorphism
parsimony and Dollo parsimony. The program defaults to Dollo parsimony.
The T (Threshold) option has already been described in
the Discrete Characters programs documentation file. Setting T at or below
1.0 but above 0 causes the criterion to become compatibility rather than
polymorphism parsimony, although there is no advantage to using this
program instead of MIX to do a compatibility method. Setting the
threshold value higher brings about an intermediate between
the Dollo or polymorphism parsimony methods and the compatibility method,
so that there is some rationale for doing that. Since the Dollo and
polymorphism methods produces a rooted
tree, the user-defined trees required by the U option have two-way forks
at each level.
Using a threshold value of 1.0 or lower, but above 0, one can
obtain a rooted (or, if the A option is used with ancestral states of
"?", unrooted) compatibility criterion, but there is no particular
advantage to using this program for that instead of MIX. Higher
threshold values are of course meaningful and provide
intermediates between Dollo and compatibility methods.
The X
(Mixed parsimony methods) option is not available in this program. The
Factors option is also not available in this program, as it would have no
effect on the result even if that information were provided in the input file.
Output is standard: a list of equally parsimonious trees, and, if the
user selects menu option 4, a table
of the numbers of reversions or retentions of polymorphism necessary
in each character. If any of the
ancestral states has been specified to be unknown, a table of
reconstructed ancestral states is also provided. When reconstructing
the placement of forward changes and reversions under the Dollo method,
keep in mind that each
polymorphic state in the input data will require one "last minute"
reversion. This is included in the tabulated counts. Thus if we have
both states 0 and 1 at a tip of the tree the program will assume that
the lineage had state 1 up to the last minute, and then state 0 arose in
that population by reversion, without loss of state 1.
If the user selects menu option 5, a table is printed out after each
tree, showing for each branch whether
there are known to be changes in the branch, and what the states are inferred
to have been at the top end of the branch. If the inferred state is a "?"
there may be multiple equally-parsimonious assignments of states; the user
must work these out for themselves by hand.
If the A option is used, then the program will
infer, for any character whose ancestral state is unknown ("?") whether the
ancestral state 0 or 1 will give the best tree. If these are
tied, then it may not be possible for the program to infer the
state in the internal nodes, and these will all be printed as ".". If this
has happened and you want to know more about the states at the internal
nodes, you will find helpful to use DOLMOVE to display the tree and examine
its interior states, as the algorithm in DOLMOVE shows all that can be known
in this case about the interior states, including where there is and is not
amibiguity. The algorithm in DOLLOP gives up more easily on displaying these
states.
If the U (User Tree) option is used and more than one tree is supplied, the
program also performs a statistical test of each of these trees against the
best tree. This test, which is a version of the test proposed by
Alan Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences
invented by Kishino and Hasegawa (1989), and uses the mean and variance of
step differences between trees, taken across characters. If the mean
is more than 1.96 standard deviations different then the trees are declared
significantly different. The program
prints out a table of the steps for each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the step differences at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one. It
is important to understand that the test assumes that all the binary
characters are evolving independently, which is unlikely to be true for
many suites of morphological characters.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sums of steps across
characters are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected number of steps,
numbers of steps for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the lowest number of steps exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the number of steps for each tree, the differences of
each from the lowest one, the variance of that quantity as determined by
the differences of the numbers of steps at individual characters,
and a conclusion as to
whether that tree is or is not significantly worse than the best one.
At the beginning of the program is the constant
"maxtrees", the maximum number of trees which the program will store for
output.
The algorithm is a fairly simple adaptation of the one used in
the program SOKAL, which was formerly in this package and has been
superseded by MIX. It requires two passes through each tree to count the
numbers of reversions.
DNAMOVE is an interactive DNA parsimony program, inspired by Wayne Maddison and
David and Wayne Maddison's marvellous program MacClade, which is written for
Macintosh computers. DNAMOVE reads in a data set which is prepared in almost
the same format as one for the DNA parsimony program DNAPARS. It allows
the user to choose an initial tree, and displays this tree on the screen. The
user can look at different sites and the way the nucleotide states are
distributed on that tree, given the most parsimonious reconstruction of state
changes for that particular tree. The user then can specify how the tree is to
be rearraranged, rerooted or written out to a file. By looking at different
rearrangements of the tree the user can manually search for the most
parsimonious tree, and can get a feel for how different sites are affected
by changes in the tree topology.
This program uses graphic characters that show the tree to best
advantage on some computer systems.
Its graphic characters will work best on MSDOS systems or MSDOS windows in
Windows, and to
any system whose screen or terminals emulate ANSI standard terminals
such as old Digital VT100 terminals,
Telnet programs,
or VT100-compatible windows in the X windowing system.
For any other screen types, (such as Macintosh windows) there is a generic
option which does
not make use of screen graphics characters. The program will work well
in those cases, but the tree it displays will look a bit uglier.
The input data file is set up almost identically to the data files for
DNAPARS. The code for nucleotide sequences is the standard one, as
described in the molecular sequence programs document.
The user trees are contained in the input tree file
which is used for input of the starting tree (if desired). The
output tree file is used for the final tree.
The user interaction starts with the program presenting a menu. The
menu looks like this:
Interactive DNA parsimony, version 3.6a3
Settings for this run:
O Outgroup root? No, use as outgroup species 1
W Sites weighted? No
T Use Threshold parsimony? No, use ordinary parsimony
I Input sequences interleaved? Yes
U Initial tree (arbitrary, user, specify)? Arbitrary
0 Graphics type (IBM PC, ANSI, none)? (none)
S Width of terminal screen? 80
L Number of lines on screen? 24
Are these settings correct? (type Y or the letter for one to change)
The O (Outgroup), W (Weights), T (Threshold), and 0 (Graphics type) options
are the usual
ones and are described in the main documentation file. The I
(Interleaved) option is the usual one and is described in the main
documentation file and the molecular sequences programs documentation file.
The U (initial tree) option allows the user to choose whether
the initial tree is to be arbitrary, interactively specified by the user, or
read from a tree file. Typing U causes the program to change among the
three possibilities in turn. I
would recommend that for a first run, you allow the tree to be set up
arbitrarily (the default), as the "specify" choice is difficult
to use and the "user tree" choice requires that you have available a tree file
with the tree topology of the initial tree, which must be a rooted tree.
Its default name is intree. The program will ask you for its name if
it looks for the input tree file and does not find one of this name.
If you wish to set up some
particular tree you can also do that by the rearrangement commands specified
below.
The W (Weights) option allows only weights of 0 or 1.
The T (threshold) option allows a continuum of methods between parsimony and
compatibility. Thresholds less than or equal to 1.0 do not have any
meaning and should not be used: they will result in a tree dependent only on
the input order of species and not at all on the data!
The L (screen Lines) option allows the user to change the height of the
screen (in lines of characters) that is assumed to be available on the
display. This may be particularly helpful when displaying large trees
on terminals that have more than 24 lines per screen, or on workstation
or X-terminal screens that can emulate the ANSI terminals with more than
24 lines.
After the initial menu is displayed and the choices are made,
the program then sets up an initial tree and displays it. Below it will be a
one-line menu of possible commands, which looks like this:
NEXT? (Options: R # + - S . T U W O F C H ? X Q) (H or ? for Help)
If you type H or ? you will get a single screen showing a description of each
of these commands in a few words. Here are slightly more detailed
descriptions:
R ("Rearrange")
This command asks for the number of a node which is to be
removed from the tree. It and everything to the right of it on the tree is to
be removed (by breaking the branch immediately below it). The command also
asks for the number of a node below which that group is to be inserted. If an
impossible number is given, the program refuses to carry out the rearrangement
and asks for a new command. The rearranged tree is displayed: it will often
have a different number of steps than the original. If you wish to undo a
rearrangement, use the Undo command, for which see below.
#
This command, and the +, - and S commands described below, determine
which site has its states displayed on the branches of
the trees. The initial tree displayed by the program does not show
states of sites. When # is typed, the program does not ask the user which
site is to be shown but automatically shows the states of the next
site that is not compatible with the tree (the next site that does not
perfectly fit the current tree). The search for this site "wraps around"
so that if it reaches the last site without finding one that is not
compatible with the tree, the search continues at the first site; if no
incompatible site is found the current site is shown again, and if no current
site is being shown then the first site is shown. The display takes the form of
different symbols or textures on the branches of the tree. The state of each
branch is actually the state of the node above it. A key of the symbols or
shadings used for states A, C, G, T (U) and ? are shown next to the
tree. State ? means that more than one possible nucleotide could exist at
that point
on the tree, and that the user may want to consider the different
possibilities, which are usually apparent by inspection.
+
This command is the same as \# except that it goes forward one site,
showing the states of the next site. If no site has been shown, using + will
cause the first site to be shown. Once the last site has been
reached, using + again will show the first site.
-
This command is the same as + except that it goes backwards, showing the
states of the previous site. If no site has been shown, using - will
cause the last site to be shown. Once site number 1 has been
reached, using - again will show the last site.
S ("Show").
This command is the same as + and - except that it causes
the program to ask you for the number of a site. That site is
the one whose states will be displayed. If you give the site number as 0,
the program will go back to not showing the states of the sites.
. (dot)
This command simply causes the current tree to be redisplayed. It is of
use when the tree has partly disappeared off of the top of the screen owing to
too many responses to commands being printed out at the bottom of the screen.
T ("Try rearrangements").
This command asks for the name of a node. The
part of the tree at and above that node is removed from the tree. The program
tries to re-insert it in each possible location on the tree (this may take some
time, and the program reminds you to wait). Then it prints out a summary. For
each possible location the program prints out the number of the node to the
right of the
place of insertion and the number of steps required in each case. These are
divided into those that are better then or tied with the current tree. Once
this summary is printed out, the group that was removed is reinserted into its
original position. It is up to you to use the R command to actually carry out
any of the arrangements that have been tried.
U ("Undo").
This command reverses the effect of the most recent
rearrangement, outgroup re-rooting, or flipping of branches. It returns to the
previous tree topology. It will be of great use when rearranging the tree and
when a rearrangement proves worse than the preceding one -- it permits you to
abandon the new one and return to the previous one without remembering its
topology in detail.
W ("Write").
This command writes out the current tree onto a tree output
file. If the file already has been written to by this run of DNAMOVE, it will
ask you whether you want to replace the contents of the file, add the tree to
the end of the file, or not write out the tree to the file. The tree
is written in the standard format used by PHYLIP (a subset of the
Newick standard). It is in the proper format to serve as the
User-Defined Tree for setting up the initial tree in a subsequent run of the
program. Note that if you provided the initial tree topology in a tree file
and replace its contents, that initial tree will be lost.
O ("Outgroup").
This asks for the number of a node which is to be the
outgroup. The tree will be redisplayed with that node
as the left descendant of the bottom fork. Note that it is possible to
use this to make a multi-species group the outgroup (i.e., you can give the
number of an interior node of the tree as the outgroup, and the program will
re-root the tree properly with that on the left of the bottom fork.
F ("Flip").
This asks for a node number and then flips the two branches at
that node, so that the left-right order of branches at that node is
changed. This does not actually change the tree topology (or the number of
steps on that tree) but it does change the appearance of the tree.
C ("Clade").
When the data consist of more than 12 species (or more than
half the number of lines on the screen if this is not 24), it may be
difficult to display the tree on one screen. In that case the tree
will be squeezed down to
one line per species. This is too small to see all the interior states of the
tree. The C command instructs the program to print out only that part of the
tree (the "clade") from a certain node on up. The program will prompt you for
the number of this node. Remember that thereafter you are not looking at the
whole tree. To go back to looking at the whole tree give the C command again
and enter "0" for the node number when asked. Most users will not want to use
this option unless forced to.
H ("Help").
Prints a one-screen summary of what the commands do, a few
words for each command.
? ("huh?").
A synonym for H. Same as Help command.
X ("Exit").
Exit from program. If the current tree has not yet been saved
into a file, the program will first ask you whether it should be saved.
Q ("Quit").
A synonym for X. Same as the eXit command.
ADAPTING THE PROGRAM TO YOUR COMPUTER AND TO YOUR TERMINAL
As we have seen, the initial menu of the program allows you to choose
among three screen types (PCDOS, Ansi, and none). We have tried to
have the default values be correct for PC, Macintosh, and Unix
screens. If the setting is "none" (which is necessary on
Macintosh screens), the special graphics
characters will not be used to indicate nucleotide states, but only letters
will be used for the four nucleotides. This is less easy to look at.
MORE ABOUT THE PARSIMONY CRITERION
This program carries out unrooted parsimony (analogous to Wagner
trees) (Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA
sequences. The method of Fitch (1971) is used to count the number of
changes of base needed on a given tree. The assumptions of this
method are exactly analogous to those of MIX:
Each site evolves independently.
Different lineages evolve independently.
The probability of a base substitution at a given site is
small over the lengths of time involved in
a branch of the phylogeny.
The expected amounts of change in different branches of the phylogeny
do not vary by so much that two changes in a high-rate branch
are more probable than one change in a low-rate branch.
The expected amounts of change do not vary enough among sites that two
changes in one site are more probable than one change in another.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive
assumptions such as these, see the papers by Farris (1983) and Sober (1983a,
1983b), but also read the exchange between Felsenstein and Sober (1986).
Change from an occupied site to a deletion is counted as one
change. Reversion from a deletion to an occupied site is allowed and is also
counted as one change.
Below is a test data set, but we cannot show the
output it generates because of the interactive nature of the program.
This program estimates phylogenies by the restricted maximum likelihood method
based on the Brownian motion model. It is based on the model of Edwards and
Cavalli-Sforza (1964; Cavalli-Sforza and Edwards, 1967). Gomberg (1966),
Felsenstein (1973b, 1981c) and Thompson (1975) have done extensive further work
leading to efficient algorithms. CONTML uses restricted maximum
likelihood estimation (REML), which is the criterion used by Felsenstein
(1973b). The actual algorithm is an iterative EM Algorithm (Dempster,
Laird, and Rubin, 1977) which is guaranteed to always give increasing
likelihoods. The algorithm is described in detail in a paper of mine
(Felsenstein, 1981c), which you should definitely consult if you are
going to use this program. Some simulation tests of it are given
by Rohlf and Wooten (1988) and Kim and Burgman (1988).
The default (gene frequency) mode treats the input as gene frequencies at a
series of loci, and
square-root-transforms the allele frequencies (constructing the frequency of
the missing allele at each locus first). This enables us to use the
Brownian motion model on the resulting coordinates, in an approximation
equivalent to using Cavalli-Sforza and Edwards's (1967) chord measure
of genetic distance and taking that to give distance between particles
undergoing pure Brownian motion. It assumes that each locus evolves
independently by pure genetic drift.
The alternative continuous characters mode (menu option C) treats the input
as a series of coordinates of each species in N dimensions. It assumes
that we have transformed the characters to remove correlations and to
standardize their variances.
The input file is as described in the continuous characters
documentation file above. Options are selected using a menu:
Continuous character Maximum Likelihood method version 3.6a3
Settings for this run:
U Search for best tree? Yes
C Gene frequencies or continuous characters? Gene frequencies
A Input file has all alleles at each locus? No, one allele missing at each
O Outgroup root? No, use as outgroup species 1
G Global rearrangements? No
J Randomize input order of species? No. Use input order
M Analyze multiple data sets? No
0 Terminal type (IBM PC, ANSI, none)? (none)
1 Print out the data at start of run No
2 Print indications of progress of run Yes
3 Print out tree Yes
4 Write out trees onto tree file? Yes
Y to accept these or type the letter for one to change
Option U is the usual User Tree option. Options C (Continuous Characters)
and A (All alleles present) have been described
in the Gene Frequencies and Continuous Characters Programs documentation
file. The options G, J, O and M are the usual Global Rearrangements, Jumble
order of species, Outgroup root, and Multiple Data Sets options.
The M (Multiple data sets) option does not allow multiple sets of weights
instead of multiple data sets, as there are no weights in this program.
The G and J options have no effect if the User Tree option is selected. User
trees are given with a trifurcation (three-way split) at the base. They
can start from any interior node. Thus the tree:
(there are of course 69 other representations as well obtained from these
by swapping the order of branches at an interior node).
The output has a standard appearance. The topology of the tree
is given by an unrooted tree diagram. The lengths (in time or in
expected amounts of variance) are given in a table below the topology,
and a rough confidence interval given for each length. Negative lower
bounds on length indicate that rearrangements may be acceptable.
The units of length are amounts of expected accumulated variance (not
time). The
log likelihood (natural log) of each tree is also given, and it is
indicated how many topologies have been tried. The tree does not
necessarily have all tips contemporary, and the log likelihood may be
either positive or negative (this simply corresponds to whether the
density function does or does not exceed 1) and a negative log
likelihood does not indicate any error. The log likelihood allows
various formal likelihood ratio hypothesis tests. The description of
the tree includes approximate standard errors on the lengths of segments
of the tree. These are calculated by considering only the curvature of
the likelihood surface as the length of the segment is varied, holding
all other lengths constant. As such they are most probably underestimates of
the variance, and hence may give too much confidence in the given tree.
One should use caution in interpreting the likelihoods that are printed
out. If the model is wrong, it will not be possible to use the
likelihoods to make formal statistical statements. Thus, if gene
frequencies are being analyzed, but the gene frequencies change not only
by genetic drift, but also by mutation, the model is not correct. It
would be as well-justified in this case to use GENDIST to compute the
Nei (1972) genetic distance and then use FITCH, KITSCH or NEIGHBOR to make a
tree. If continuous characters are being analyzed, but if the
characters have not been transformed to new coordinates that evolve
independently and at equal rates, then the model is also violated and no
statistical analysis is possible.
If the U (User Tree) option is used and more than one tree is supplied,
the program also performs a statistical test of each of these trees against the
one with highest likelihood. If there are two user trees, the test
done is one which is due to Kishino and Hasegawa (1989), a version
of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of
log-likelihood differences between trees, taken across loci. If the two
trees means are more than 1.96 standard deviations different then the trees are
declared significantly different. This use of the empirical variance of
log-likelihood differences is more robust and nonparametric than the
classical likelihood ratio test, and may to some extent compensate for the
any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of
the KHT test, due to Shimodaira and Hasegawa (1999). They pointed out
that a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. The version
used here is a multivariate normal approximation to their test; it is
due to Shimodaira (1998). The variances and covariances of the sum of
log likelihoods across loci are computed for all pairs of trees. To test
whether the difference between each tree and the best one is larger than
could have been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and equal
means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference between
the tree's value and the highest log-likelihood exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program
prints out a table of the log-likelihoods of each tree, the differences of
each from the highest one, the variance of that quantity as determined by
the log-likelihood differences at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
One problem which sometimes arises is that the program is fed two species
(or populations) with identical transformed gene frequencies: this can
happen if sample sizes are small and/or many loci are monomorphic. In
this case the program "gets its knickers in a twist" and can divide by
zero, usually causing a crash. If you suspect that this has happened,
check for two species with identical coordinates. If you find them,
eliminate one from the problem: the two must always show up as being at the
same point on the tree anyway.
The constants
available for modification at the beginning of the
program include "epsilon1",
a small quantity used in the iterations of branch lengths,
"epsilon2", another not quite so small quantity used to check
whether gene frequencies that were fed in for all alleles do not add up to 1,
"smoothings", the number of passes through a
given tree in the iterative likelihood maximization for a given topology,
"maxtrees", the maximum number of user trees that will be used for the
Kishino-Hasegawa-Templeton test, and
"namelength", the length of species names.
There is no provision in this program for saving multiple trees that are
tied for having the highest likelihood, mostly because an exact tie is
unlikely anyway.
The algorithm does not run as quickly as the discrete character
methods but is not enormously slower. Like them, its execution time
should rise as the cube of the number of species.
TEST DATA SET
This data set was compiled by me from the compilation of human gene
frequencies by Mourant (1976). It appeared in a paper of mine
(Felsenstein, 1981c) on maximum likelihood phylogenies from gene
frequencies. The names of the loci and alleles are given in that
paper.
TEST SET OUTPUT (WITH ALL NUMERICAL OPTIONS TURNED ON)
Continuous character Maximum Likelihood method version 3.6a3
5 Populations, 10 Loci
Numbers of alleles at the loci:
------- -- ------- -- --- -----
2 2 2 2 2 2 2 2 2 2
Name Gene Frequencies
---- ---- -----------
locus: 1 2 3 4 5 6
7 8 9 10
European 0.28680 0.56840 0.44220 0.42860 0.38280 0.72850
0.63860 0.02050 0.80550 0.50430
African 0.13560 0.48400 0.06020 0.03970 0.59770 0.96750
0.95110 0.06000 0.75820 0.62070
Chinese 0.16280 0.59580 0.72980 1.00000 0.38110 0.79860
0.77820 0.07260 0.74820 0.73340
American 0.01440 0.69900 0.32800 0.74210 0.66060 0.86030
0.79240 0.00000 0.80860 0.86360
Australian 0.12110 0.22740 0.58210 1.00000 0.20180 0.90000
0.98370 0.03960 0.90970 0.29760
+----------------------------------African
!
! +--------American
1--------------2
! ! +-----------------------Australian
! +--------------------3
! +Chinese
!
+--European
remember: this is an unrooted tree!
Ln Likelihood = 33.29060
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
1 African 0.08464 ( 0.02351, 0.17917)
1 2 0.03569 ( -0.00262, 0.09493)
2 American 0.02094 ( -0.00904, 0.06731)
2 3 0.05098 ( 0.00555, 0.12124)
3 Australian 0.05959 ( 0.01775, 0.12430)
3 Chinese 0.00221 ( -0.02034, 0.03710)
1 European 0.00624 ( -0.01948, 0.04601)
PHYLIPNEW-3.69.650/config.guess 0000755 0001750 0001750 00000127432 12171071677 012626 0000000 0000000 #! /bin/sh
# Attempt to guess a canonical system name.
# Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999,
# 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,
# 2011, 2012 Free Software Foundation, Inc.
timestamp='2012-06-10'
# This file is free software; you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
# General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, see .
#
# As a special exception to the GNU General Public License, if you
# distribute this file as part of a program that contains a
# configuration script generated by Autoconf, you may include it under
# the same distribution terms that you use for the rest of that program.
# Originally written by Per Bothner. Please send patches (context
# diff format) to and include a ChangeLog
# entry.
#
# This script attempts to guess a canonical system name similar to
# config.sub. If it succeeds, it prints the system name on stdout, and
# exits with 0. Otherwise, it exits with 1.
#
# You can get the latest version of this script from:
# http://git.savannah.gnu.org/gitweb/?p=config.git;a=blob_plain;f=config.guess;hb=HEAD
me=`echo "$0" | sed -e 's,.*/,,'`
usage="\
Usage: $0 [OPTION]
Output the configuration name of the system \`$me' is run on.
Operation modes:
-h, --help print this help, then exit
-t, --time-stamp print date of last modification, then exit
-v, --version print version number, then exit
Report bugs and patches to ."
version="\
GNU config.guess ($timestamp)
Originally written by Per Bothner.
Copyright (C) 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000,
2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012
Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE."
help="
Try \`$me --help' for more information."
# Parse command line
while test $# -gt 0 ; do
case $1 in
--time-stamp | --time* | -t )
echo "$timestamp" ; exit ;;
--version | -v )
echo "$version" ; exit ;;
--help | --h* | -h )
echo "$usage"; exit ;;
-- ) # Stop option processing
shift; break ;;
- ) # Use stdin as input.
break ;;
-* )
echo "$me: invalid option $1$help" >&2
exit 1 ;;
* )
break ;;
esac
done
if test $# != 0; then
echo "$me: too many arguments$help" >&2
exit 1
fi
trap 'exit 1' 1 2 15
# CC_FOR_BUILD -- compiler used by this script. Note that the use of a
# compiler to aid in system detection is discouraged as it requires
# temporary files to be created and, as you can see below, it is a
# headache to deal with in a portable fashion.
# Historically, `CC_FOR_BUILD' used to be named `HOST_CC'. We still
# use `HOST_CC' if defined, but it is deprecated.
# Portable tmp directory creation inspired by the Autoconf team.
set_cc_for_build='
trap "exitcode=\$?; (rm -f \$tmpfiles 2>/dev/null; rmdir \$tmp 2>/dev/null) && exit \$exitcode" 0 ;
trap "rm -f \$tmpfiles 2>/dev/null; rmdir \$tmp 2>/dev/null; exit 1" 1 2 13 15 ;
: ${TMPDIR=/tmp} ;
{ tmp=`(umask 077 && mktemp -d "$TMPDIR/cgXXXXXX") 2>/dev/null` && test -n "$tmp" && test -d "$tmp" ; } ||
{ test -n "$RANDOM" && tmp=$TMPDIR/cg$$-$RANDOM && (umask 077 && mkdir $tmp) ; } ||
{ tmp=$TMPDIR/cg-$$ && (umask 077 && mkdir $tmp) && echo "Warning: creating insecure temp directory" >&2 ; } ||
{ echo "$me: cannot create a temporary directory in $TMPDIR" >&2 ; exit 1 ; } ;
dummy=$tmp/dummy ;
tmpfiles="$dummy.c $dummy.o $dummy.rel $dummy" ;
case $CC_FOR_BUILD,$HOST_CC,$CC in
,,) echo "int x;" > $dummy.c ;
for c in cc gcc c89 c99 ; do
if ($c -c -o $dummy.o $dummy.c) >/dev/null 2>&1 ; then
CC_FOR_BUILD="$c"; break ;
fi ;
done ;
if test x"$CC_FOR_BUILD" = x ; then
CC_FOR_BUILD=no_compiler_found ;
fi
;;
,,*) CC_FOR_BUILD=$CC ;;
,*,*) CC_FOR_BUILD=$HOST_CC ;;
esac ; set_cc_for_build= ;'
# This is needed to find uname on a Pyramid OSx when run in the BSD universe.
# (ghazi@noc.rutgers.edu 1994-08-24)
if (test -f /.attbin/uname) >/dev/null 2>&1 ; then
PATH=$PATH:/.attbin ; export PATH
fi
UNAME_MACHINE=`(uname -m) 2>/dev/null` || UNAME_MACHINE=unknown
UNAME_RELEASE=`(uname -r) 2>/dev/null` || UNAME_RELEASE=unknown
UNAME_SYSTEM=`(uname -s) 2>/dev/null` || UNAME_SYSTEM=unknown
UNAME_VERSION=`(uname -v) 2>/dev/null` || UNAME_VERSION=unknown
# Note: order is significant - the case branches are not exclusive.
case "${UNAME_MACHINE}:${UNAME_SYSTEM}:${UNAME_RELEASE}:${UNAME_VERSION}" in
*:NetBSD:*:*)
# NetBSD (nbsd) targets should (where applicable) match one or
# more of the tuples: *-*-netbsdelf*, *-*-netbsdaout*,
# *-*-netbsdecoff* and *-*-netbsd*. For targets that recently
# switched to ELF, *-*-netbsd* would select the old
# object file format. This provides both forward
# compatibility and a consistent mechanism for selecting the
# object file format.
#
# Note: NetBSD doesn't particularly care about the vendor
# portion of the name. We always set it to "unknown".
sysctl="sysctl -n hw.machine_arch"
UNAME_MACHINE_ARCH=`(/sbin/$sysctl 2>/dev/null || \
/usr/sbin/$sysctl 2>/dev/null || echo unknown)`
case "${UNAME_MACHINE_ARCH}" in
armeb) machine=armeb-unknown ;;
arm*) machine=arm-unknown ;;
sh3el) machine=shl-unknown ;;
sh3eb) machine=sh-unknown ;;
sh5el) machine=sh5le-unknown ;;
*) machine=${UNAME_MACHINE_ARCH}-unknown ;;
esac
# The Operating System including object format, if it has switched
# to ELF recently, or will in the future.
case "${UNAME_MACHINE_ARCH}" in
arm*|i386|m68k|ns32k|sh3*|sparc|vax)
eval $set_cc_for_build
if echo __ELF__ | $CC_FOR_BUILD -E - 2>/dev/null \
| grep -q __ELF__
then
# Once all utilities can be ECOFF (netbsdecoff) or a.out (netbsdaout).
# Return netbsd for either. FIX?
os=netbsd
else
os=netbsdelf
fi
;;
*)
os=netbsd
;;
esac
# The OS release
# Debian GNU/NetBSD machines have a different userland, and
# thus, need a distinct triplet. However, they do not need
# kernel version information, so it can be replaced with a
# suitable tag, in the style of linux-gnu.
case "${UNAME_VERSION}" in
Debian*)
release='-gnu'
;;
*)
release=`echo ${UNAME_RELEASE}|sed -e 's/[-_].*/\./'`
;;
esac
# Since CPU_TYPE-MANUFACTURER-KERNEL-OPERATING_SYSTEM:
# contains redundant information, the shorter form:
# CPU_TYPE-MANUFACTURER-OPERATING_SYSTEM is used.
echo "${machine}-${os}${release}"
exit ;;
*:OpenBSD:*:*)
UNAME_MACHINE_ARCH=`arch | sed 's/OpenBSD.//'`
echo ${UNAME_MACHINE_ARCH}-unknown-openbsd${UNAME_RELEASE}
exit ;;
*:ekkoBSD:*:*)
echo ${UNAME_MACHINE}-unknown-ekkobsd${UNAME_RELEASE}
exit ;;
*:SolidBSD:*:*)
echo ${UNAME_MACHINE}-unknown-solidbsd${UNAME_RELEASE}
exit ;;
macppc:MirBSD:*:*)
echo powerpc-unknown-mirbsd${UNAME_RELEASE}
exit ;;
*:MirBSD:*:*)
echo ${UNAME_MACHINE}-unknown-mirbsd${UNAME_RELEASE}
exit ;;
alpha:OSF1:*:*)
case $UNAME_RELEASE in
*4.0)
UNAME_RELEASE=`/usr/sbin/sizer -v | awk '{print $3}'`
;;
*5.*)
UNAME_RELEASE=`/usr/sbin/sizer -v | awk '{print $4}'`
;;
esac
# According to Compaq, /usr/sbin/psrinfo has been available on
# OSF/1 and Tru64 systems produced since 1995. I hope that
# covers most systems running today. This code pipes the CPU
# types through head -n 1, so we only detect the type of CPU 0.
ALPHA_CPU_TYPE=`/usr/sbin/psrinfo -v | sed -n -e 's/^ The alpha \(.*\) processor.*$/\1/p' | head -n 1`
case "$ALPHA_CPU_TYPE" in
"EV4 (21064)")
UNAME_MACHINE="alpha" ;;
"EV4.5 (21064)")
UNAME_MACHINE="alpha" ;;
"LCA4 (21066/21068)")
UNAME_MACHINE="alpha" ;;
"EV5 (21164)")
UNAME_MACHINE="alphaev5" ;;
"EV5.6 (21164A)")
UNAME_MACHINE="alphaev56" ;;
"EV5.6 (21164PC)")
UNAME_MACHINE="alphapca56" ;;
"EV5.7 (21164PC)")
UNAME_MACHINE="alphapca57" ;;
"EV6 (21264)")
UNAME_MACHINE="alphaev6" ;;
"EV6.7 (21264A)")
UNAME_MACHINE="alphaev67" ;;
"EV6.8CB (21264C)")
UNAME_MACHINE="alphaev68" ;;
"EV6.8AL (21264B)")
UNAME_MACHINE="alphaev68" ;;
"EV6.8CX (21264D)")
UNAME_MACHINE="alphaev68" ;;
"EV6.9A (21264/EV69A)")
UNAME_MACHINE="alphaev69" ;;
"EV7 (21364)")
UNAME_MACHINE="alphaev7" ;;
"EV7.9 (21364A)")
UNAME_MACHINE="alphaev79" ;;
esac
# A Pn.n version is a patched version.
# A Vn.n version is a released version.
# A Tn.n version is a released field test version.
# A Xn.n version is an unreleased experimental baselevel.
# 1.2 uses "1.2" for uname -r.
echo ${UNAME_MACHINE}-dec-osf`echo ${UNAME_RELEASE} | sed -e 's/^[PVTX]//' | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz'`
# Reset EXIT trap before exiting to avoid spurious non-zero exit code.
exitcode=$?
trap '' 0
exit $exitcode ;;
Alpha\ *:Windows_NT*:*)
# How do we know it's Interix rather than the generic POSIX subsystem?
# Should we change UNAME_MACHINE based on the output of uname instead
# of the specific Alpha model?
echo alpha-pc-interix
exit ;;
21064:Windows_NT:50:3)
echo alpha-dec-winnt3.5
exit ;;
Amiga*:UNIX_System_V:4.0:*)
echo m68k-unknown-sysv4
exit ;;
*:[Aa]miga[Oo][Ss]:*:*)
echo ${UNAME_MACHINE}-unknown-amigaos
exit ;;
*:[Mm]orph[Oo][Ss]:*:*)
echo ${UNAME_MACHINE}-unknown-morphos
exit ;;
*:OS/390:*:*)
echo i370-ibm-openedition
exit ;;
*:z/VM:*:*)
echo s390-ibm-zvmoe
exit ;;
*:OS400:*:*)
echo powerpc-ibm-os400
exit ;;
arm:RISC*:1.[012]*:*|arm:riscix:1.[012]*:*)
echo arm-acorn-riscix${UNAME_RELEASE}
exit ;;
arm:riscos:*:*|arm:RISCOS:*:*)
echo arm-unknown-riscos
exit ;;
SR2?01:HI-UX/MPP:*:* | SR8000:HI-UX/MPP:*:*)
echo hppa1.1-hitachi-hiuxmpp
exit ;;
Pyramid*:OSx*:*:* | MIS*:OSx*:*:* | MIS*:SMP_DC-OSx*:*:*)
# akee@wpdis03.wpafb.af.mil (Earle F. Ake) contributed MIS and NILE.
if test "`(/bin/universe) 2>/dev/null`" = att ; then
echo pyramid-pyramid-sysv3
else
echo pyramid-pyramid-bsd
fi
exit ;;
NILE*:*:*:dcosx)
echo pyramid-pyramid-svr4
exit ;;
DRS?6000:unix:4.0:6*)
echo sparc-icl-nx6
exit ;;
DRS?6000:UNIX_SV:4.2*:7* | DRS?6000:isis:4.2*:7*)
case `/usr/bin/uname -p` in
sparc) echo sparc-icl-nx7; exit ;;
esac ;;
s390x:SunOS:*:*)
echo ${UNAME_MACHINE}-ibm-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
sun4H:SunOS:5.*:*)
echo sparc-hal-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
sun4*:SunOS:5.*:* | tadpole*:SunOS:5.*:*)
echo sparc-sun-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
i86pc:AuroraUX:5.*:* | i86xen:AuroraUX:5.*:*)
echo i386-pc-auroraux${UNAME_RELEASE}
exit ;;
i86pc:SunOS:5.*:* | i86xen:SunOS:5.*:*)
eval $set_cc_for_build
SUN_ARCH="i386"
# If there is a compiler, see if it is configured for 64-bit objects.
# Note that the Sun cc does not turn __LP64__ into 1 like gcc does.
# This test works for both compilers.
if [ "$CC_FOR_BUILD" != 'no_compiler_found' ]; then
if (echo '#ifdef __amd64'; echo IS_64BIT_ARCH; echo '#endif') | \
(CCOPTS= $CC_FOR_BUILD -E - 2>/dev/null) | \
grep IS_64BIT_ARCH >/dev/null
then
SUN_ARCH="x86_64"
fi
fi
echo ${SUN_ARCH}-pc-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
sun4*:SunOS:6*:*)
# According to config.sub, this is the proper way to canonicalize
# SunOS6. Hard to guess exactly what SunOS6 will be like, but
# it's likely to be more like Solaris than SunOS4.
echo sparc-sun-solaris3`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
sun4*:SunOS:*:*)
case "`/usr/bin/arch -k`" in
Series*|S4*)
UNAME_RELEASE=`uname -v`
;;
esac
# Japanese Language versions have a version number like `4.1.3-JL'.
echo sparc-sun-sunos`echo ${UNAME_RELEASE}|sed -e 's/-/_/'`
exit ;;
sun3*:SunOS:*:*)
echo m68k-sun-sunos${UNAME_RELEASE}
exit ;;
sun*:*:4.2BSD:*)
UNAME_RELEASE=`(sed 1q /etc/motd | awk '{print substr($5,1,3)}') 2>/dev/null`
test "x${UNAME_RELEASE}" = "x" && UNAME_RELEASE=3
case "`/bin/arch`" in
sun3)
echo m68k-sun-sunos${UNAME_RELEASE}
;;
sun4)
echo sparc-sun-sunos${UNAME_RELEASE}
;;
esac
exit ;;
aushp:SunOS:*:*)
echo sparc-auspex-sunos${UNAME_RELEASE}
exit ;;
# The situation for MiNT is a little confusing. The machine name
# can be virtually everything (everything which is not
# "atarist" or "atariste" at least should have a processor
# > m68000). The system name ranges from "MiNT" over "FreeMiNT"
# to the lowercase version "mint" (or "freemint"). Finally
# the system name "TOS" denotes a system which is actually not
# MiNT. But MiNT is downward compatible to TOS, so this should
# be no problem.
atarist[e]:*MiNT:*:* | atarist[e]:*mint:*:* | atarist[e]:*TOS:*:*)
echo m68k-atari-mint${UNAME_RELEASE}
exit ;;
atari*:*MiNT:*:* | atari*:*mint:*:* | atarist[e]:*TOS:*:*)
echo m68k-atari-mint${UNAME_RELEASE}
exit ;;
*falcon*:*MiNT:*:* | *falcon*:*mint:*:* | *falcon*:*TOS:*:*)
echo m68k-atari-mint${UNAME_RELEASE}
exit ;;
milan*:*MiNT:*:* | milan*:*mint:*:* | *milan*:*TOS:*:*)
echo m68k-milan-mint${UNAME_RELEASE}
exit ;;
hades*:*MiNT:*:* | hades*:*mint:*:* | *hades*:*TOS:*:*)
echo m68k-hades-mint${UNAME_RELEASE}
exit ;;
*:*MiNT:*:* | *:*mint:*:* | *:*TOS:*:*)
echo m68k-unknown-mint${UNAME_RELEASE}
exit ;;
m68k:machten:*:*)
echo m68k-apple-machten${UNAME_RELEASE}
exit ;;
powerpc:machten:*:*)
echo powerpc-apple-machten${UNAME_RELEASE}
exit ;;
RISC*:Mach:*:*)
echo mips-dec-mach_bsd4.3
exit ;;
RISC*:ULTRIX:*:*)
echo mips-dec-ultrix${UNAME_RELEASE}
exit ;;
VAX*:ULTRIX*:*:*)
echo vax-dec-ultrix${UNAME_RELEASE}
exit ;;
2020:CLIX:*:* | 2430:CLIX:*:*)
echo clipper-intergraph-clix${UNAME_RELEASE}
exit ;;
mips:*:*:UMIPS | mips:*:*:RISCos)
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#ifdef __cplusplus
#include /* for printf() prototype */
int main (int argc, char *argv[]) {
#else
int main (argc, argv) int argc; char *argv[]; {
#endif
#if defined (host_mips) && defined (MIPSEB)
#if defined (SYSTYPE_SYSV)
printf ("mips-mips-riscos%ssysv\n", argv[1]); exit (0);
#endif
#if defined (SYSTYPE_SVR4)
printf ("mips-mips-riscos%ssvr4\n", argv[1]); exit (0);
#endif
#if defined (SYSTYPE_BSD43) || defined(SYSTYPE_BSD)
printf ("mips-mips-riscos%sbsd\n", argv[1]); exit (0);
#endif
#endif
exit (-1);
}
EOF
$CC_FOR_BUILD -o $dummy $dummy.c &&
dummyarg=`echo "${UNAME_RELEASE}" | sed -n 's/\([0-9]*\).*/\1/p'` &&
SYSTEM_NAME=`$dummy $dummyarg` &&
{ echo "$SYSTEM_NAME"; exit; }
echo mips-mips-riscos${UNAME_RELEASE}
exit ;;
Motorola:PowerMAX_OS:*:*)
echo powerpc-motorola-powermax
exit ;;
Motorola:*:4.3:PL8-*)
echo powerpc-harris-powermax
exit ;;
Night_Hawk:*:*:PowerMAX_OS | Synergy:PowerMAX_OS:*:*)
echo powerpc-harris-powermax
exit ;;
Night_Hawk:Power_UNIX:*:*)
echo powerpc-harris-powerunix
exit ;;
m88k:CX/UX:7*:*)
echo m88k-harris-cxux7
exit ;;
m88k:*:4*:R4*)
echo m88k-motorola-sysv4
exit ;;
m88k:*:3*:R3*)
echo m88k-motorola-sysv3
exit ;;
AViiON:dgux:*:*)
# DG/UX returns AViiON for all architectures
UNAME_PROCESSOR=`/usr/bin/uname -p`
if [ $UNAME_PROCESSOR = mc88100 ] || [ $UNAME_PROCESSOR = mc88110 ]
then
if [ ${TARGET_BINARY_INTERFACE}x = m88kdguxelfx ] || \
[ ${TARGET_BINARY_INTERFACE}x = x ]
then
echo m88k-dg-dgux${UNAME_RELEASE}
else
echo m88k-dg-dguxbcs${UNAME_RELEASE}
fi
else
echo i586-dg-dgux${UNAME_RELEASE}
fi
exit ;;
M88*:DolphinOS:*:*) # DolphinOS (SVR3)
echo m88k-dolphin-sysv3
exit ;;
M88*:*:R3*:*)
# Delta 88k system running SVR3
echo m88k-motorola-sysv3
exit ;;
XD88*:*:*:*) # Tektronix XD88 system running UTekV (SVR3)
echo m88k-tektronix-sysv3
exit ;;
Tek43[0-9][0-9]:UTek:*:*) # Tektronix 4300 system running UTek (BSD)
echo m68k-tektronix-bsd
exit ;;
*:IRIX*:*:*)
echo mips-sgi-irix`echo ${UNAME_RELEASE}|sed -e 's/-/_/g'`
exit ;;
????????:AIX?:[12].1:2) # AIX 2.2.1 or AIX 2.1.1 is RT/PC AIX.
echo romp-ibm-aix # uname -m gives an 8 hex-code CPU id
exit ;; # Note that: echo "'`uname -s`'" gives 'AIX '
i*86:AIX:*:*)
echo i386-ibm-aix
exit ;;
ia64:AIX:*:*)
if [ -x /usr/bin/oslevel ] ; then
IBM_REV=`/usr/bin/oslevel`
else
IBM_REV=${UNAME_VERSION}.${UNAME_RELEASE}
fi
echo ${UNAME_MACHINE}-ibm-aix${IBM_REV}
exit ;;
*:AIX:2:3)
if grep bos325 /usr/include/stdio.h >/dev/null 2>&1; then
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#include
main()
{
if (!__power_pc())
exit(1);
puts("powerpc-ibm-aix3.2.5");
exit(0);
}
EOF
if $CC_FOR_BUILD -o $dummy $dummy.c && SYSTEM_NAME=`$dummy`
then
echo "$SYSTEM_NAME"
else
echo rs6000-ibm-aix3.2.5
fi
elif grep bos324 /usr/include/stdio.h >/dev/null 2>&1; then
echo rs6000-ibm-aix3.2.4
else
echo rs6000-ibm-aix3.2
fi
exit ;;
*:AIX:*:[4567])
IBM_CPU_ID=`/usr/sbin/lsdev -C -c processor -S available | sed 1q | awk '{ print $1 }'`
if /usr/sbin/lsattr -El ${IBM_CPU_ID} | grep ' POWER' >/dev/null 2>&1; then
IBM_ARCH=rs6000
else
IBM_ARCH=powerpc
fi
if [ -x /usr/bin/oslevel ] ; then
IBM_REV=`/usr/bin/oslevel`
else
IBM_REV=${UNAME_VERSION}.${UNAME_RELEASE}
fi
echo ${IBM_ARCH}-ibm-aix${IBM_REV}
exit ;;
*:AIX:*:*)
echo rs6000-ibm-aix
exit ;;
ibmrt:4.4BSD:*|romp-ibm:BSD:*)
echo romp-ibm-bsd4.4
exit ;;
ibmrt:*BSD:*|romp-ibm:BSD:*) # covers RT/PC BSD and
echo romp-ibm-bsd${UNAME_RELEASE} # 4.3 with uname added to
exit ;; # report: romp-ibm BSD 4.3
*:BOSX:*:*)
echo rs6000-bull-bosx
exit ;;
DPX/2?00:B.O.S.:*:*)
echo m68k-bull-sysv3
exit ;;
9000/[34]??:4.3bsd:1.*:*)
echo m68k-hp-bsd
exit ;;
hp300:4.4BSD:*:* | 9000/[34]??:4.3bsd:2.*:*)
echo m68k-hp-bsd4.4
exit ;;
9000/[34678]??:HP-UX:*:*)
HPUX_REV=`echo ${UNAME_RELEASE}|sed -e 's/[^.]*.[0B]*//'`
case "${UNAME_MACHINE}" in
9000/31? ) HP_ARCH=m68000 ;;
9000/[34]?? ) HP_ARCH=m68k ;;
9000/[678][0-9][0-9])
if [ -x /usr/bin/getconf ]; then
sc_cpu_version=`/usr/bin/getconf SC_CPU_VERSION 2>/dev/null`
sc_kernel_bits=`/usr/bin/getconf SC_KERNEL_BITS 2>/dev/null`
case "${sc_cpu_version}" in
523) HP_ARCH="hppa1.0" ;; # CPU_PA_RISC1_0
528) HP_ARCH="hppa1.1" ;; # CPU_PA_RISC1_1
532) # CPU_PA_RISC2_0
case "${sc_kernel_bits}" in
32) HP_ARCH="hppa2.0n" ;;
64) HP_ARCH="hppa2.0w" ;;
'') HP_ARCH="hppa2.0" ;; # HP-UX 10.20
esac ;;
esac
fi
if [ "${HP_ARCH}" = "" ]; then
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#define _HPUX_SOURCE
#include
#include
int main ()
{
#if defined(_SC_KERNEL_BITS)
long bits = sysconf(_SC_KERNEL_BITS);
#endif
long cpu = sysconf (_SC_CPU_VERSION);
switch (cpu)
{
case CPU_PA_RISC1_0: puts ("hppa1.0"); break;
case CPU_PA_RISC1_1: puts ("hppa1.1"); break;
case CPU_PA_RISC2_0:
#if defined(_SC_KERNEL_BITS)
switch (bits)
{
case 64: puts ("hppa2.0w"); break;
case 32: puts ("hppa2.0n"); break;
default: puts ("hppa2.0"); break;
} break;
#else /* !defined(_SC_KERNEL_BITS) */
puts ("hppa2.0"); break;
#endif
default: puts ("hppa1.0"); break;
}
exit (0);
}
EOF
(CCOPTS= $CC_FOR_BUILD -o $dummy $dummy.c 2>/dev/null) && HP_ARCH=`$dummy`
test -z "$HP_ARCH" && HP_ARCH=hppa
fi ;;
esac
if [ ${HP_ARCH} = "hppa2.0w" ]
then
eval $set_cc_for_build
# hppa2.0w-hp-hpux* has a 64-bit kernel and a compiler generating
# 32-bit code. hppa64-hp-hpux* has the same kernel and a compiler
# generating 64-bit code. GNU and HP use different nomenclature:
#
# $ CC_FOR_BUILD=cc ./config.guess
# => hppa2.0w-hp-hpux11.23
# $ CC_FOR_BUILD="cc +DA2.0w" ./config.guess
# => hppa64-hp-hpux11.23
if echo __LP64__ | (CCOPTS= $CC_FOR_BUILD -E - 2>/dev/null) |
grep -q __LP64__
then
HP_ARCH="hppa2.0w"
else
HP_ARCH="hppa64"
fi
fi
echo ${HP_ARCH}-hp-hpux${HPUX_REV}
exit ;;
ia64:HP-UX:*:*)
HPUX_REV=`echo ${UNAME_RELEASE}|sed -e 's/[^.]*.[0B]*//'`
echo ia64-hp-hpux${HPUX_REV}
exit ;;
3050*:HI-UX:*:*)
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#include
int
main ()
{
long cpu = sysconf (_SC_CPU_VERSION);
/* The order matters, because CPU_IS_HP_MC68K erroneously returns
true for CPU_PA_RISC1_0. CPU_IS_PA_RISC returns correct
results, however. */
if (CPU_IS_PA_RISC (cpu))
{
switch (cpu)
{
case CPU_PA_RISC1_0: puts ("hppa1.0-hitachi-hiuxwe2"); break;
case CPU_PA_RISC1_1: puts ("hppa1.1-hitachi-hiuxwe2"); break;
case CPU_PA_RISC2_0: puts ("hppa2.0-hitachi-hiuxwe2"); break;
default: puts ("hppa-hitachi-hiuxwe2"); break;
}
}
else if (CPU_IS_HP_MC68K (cpu))
puts ("m68k-hitachi-hiuxwe2");
else puts ("unknown-hitachi-hiuxwe2");
exit (0);
}
EOF
$CC_FOR_BUILD -o $dummy $dummy.c && SYSTEM_NAME=`$dummy` &&
{ echo "$SYSTEM_NAME"; exit; }
echo unknown-hitachi-hiuxwe2
exit ;;
9000/7??:4.3bsd:*:* | 9000/8?[79]:4.3bsd:*:* )
echo hppa1.1-hp-bsd
exit ;;
9000/8??:4.3bsd:*:*)
echo hppa1.0-hp-bsd
exit ;;
*9??*:MPE/iX:*:* | *3000*:MPE/iX:*:*)
echo hppa1.0-hp-mpeix
exit ;;
hp7??:OSF1:*:* | hp8?[79]:OSF1:*:* )
echo hppa1.1-hp-osf
exit ;;
hp8??:OSF1:*:*)
echo hppa1.0-hp-osf
exit ;;
i*86:OSF1:*:*)
if [ -x /usr/sbin/sysversion ] ; then
echo ${UNAME_MACHINE}-unknown-osf1mk
else
echo ${UNAME_MACHINE}-unknown-osf1
fi
exit ;;
parisc*:Lites*:*:*)
echo hppa1.1-hp-lites
exit ;;
C1*:ConvexOS:*:* | convex:ConvexOS:C1*:*)
echo c1-convex-bsd
exit ;;
C2*:ConvexOS:*:* | convex:ConvexOS:C2*:*)
if getsysinfo -f scalar_acc
then echo c32-convex-bsd
else echo c2-convex-bsd
fi
exit ;;
C34*:ConvexOS:*:* | convex:ConvexOS:C34*:*)
echo c34-convex-bsd
exit ;;
C38*:ConvexOS:*:* | convex:ConvexOS:C38*:*)
echo c38-convex-bsd
exit ;;
C4*:ConvexOS:*:* | convex:ConvexOS:C4*:*)
echo c4-convex-bsd
exit ;;
CRAY*Y-MP:*:*:*)
echo ymp-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
CRAY*[A-Z]90:*:*:*)
echo ${UNAME_MACHINE}-cray-unicos${UNAME_RELEASE} \
| sed -e 's/CRAY.*\([A-Z]90\)/\1/' \
-e y/ABCDEFGHIJKLMNOPQRSTUVWXYZ/abcdefghijklmnopqrstuvwxyz/ \
-e 's/\.[^.]*$/.X/'
exit ;;
CRAY*TS:*:*:*)
echo t90-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
CRAY*T3E:*:*:*)
echo alphaev5-cray-unicosmk${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
CRAY*SV1:*:*:*)
echo sv1-cray-unicos${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
*:UNICOS/mp:*:*)
echo craynv-cray-unicosmp${UNAME_RELEASE} | sed -e 's/\.[^.]*$/.X/'
exit ;;
F30[01]:UNIX_System_V:*:* | F700:UNIX_System_V:*:*)
FUJITSU_PROC=`uname -m | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz'`
FUJITSU_SYS=`uname -p | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/\///'`
FUJITSU_REL=`echo ${UNAME_RELEASE} | sed -e 's/ /_/'`
echo "${FUJITSU_PROC}-fujitsu-${FUJITSU_SYS}${FUJITSU_REL}"
exit ;;
5000:UNIX_System_V:4.*:*)
FUJITSU_SYS=`uname -p | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/\///'`
FUJITSU_REL=`echo ${UNAME_RELEASE} | tr 'ABCDEFGHIJKLMNOPQRSTUVWXYZ' 'abcdefghijklmnopqrstuvwxyz' | sed -e 's/ /_/'`
echo "sparc-fujitsu-${FUJITSU_SYS}${FUJITSU_REL}"
exit ;;
i*86:BSD/386:*:* | i*86:BSD/OS:*:* | *:Ascend\ Embedded/OS:*:*)
echo ${UNAME_MACHINE}-pc-bsdi${UNAME_RELEASE}
exit ;;
sparc*:BSD/OS:*:*)
echo sparc-unknown-bsdi${UNAME_RELEASE}
exit ;;
*:BSD/OS:*:*)
echo ${UNAME_MACHINE}-unknown-bsdi${UNAME_RELEASE}
exit ;;
*:FreeBSD:*:*)
UNAME_PROCESSOR=`/usr/bin/uname -p`
case ${UNAME_PROCESSOR} in
amd64)
echo x86_64-unknown-freebsd`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` ;;
*)
echo ${UNAME_PROCESSOR}-unknown-freebsd`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'` ;;
esac
exit ;;
i*:CYGWIN*:*)
echo ${UNAME_MACHINE}-pc-cygwin
exit ;;
*:MINGW*:*)
echo ${UNAME_MACHINE}-pc-mingw32
exit ;;
i*:MSYS*:*)
echo ${UNAME_MACHINE}-pc-msys
exit ;;
i*:windows32*:*)
# uname -m includes "-pc" on this system.
echo ${UNAME_MACHINE}-mingw32
exit ;;
i*:PW*:*)
echo ${UNAME_MACHINE}-pc-pw32
exit ;;
*:Interix*:*)
case ${UNAME_MACHINE} in
x86)
echo i586-pc-interix${UNAME_RELEASE}
exit ;;
authenticamd | genuineintel | EM64T)
echo x86_64-unknown-interix${UNAME_RELEASE}
exit ;;
IA64)
echo ia64-unknown-interix${UNAME_RELEASE}
exit ;;
esac ;;
[345]86:Windows_95:* | [345]86:Windows_98:* | [345]86:Windows_NT:*)
echo i${UNAME_MACHINE}-pc-mks
exit ;;
8664:Windows_NT:*)
echo x86_64-pc-mks
exit ;;
i*:Windows_NT*:* | Pentium*:Windows_NT*:*)
# How do we know it's Interix rather than the generic POSIX subsystem?
# It also conflicts with pre-2.0 versions of AT&T UWIN. Should we
# UNAME_MACHINE based on the output of uname instead of i386?
echo i586-pc-interix
exit ;;
i*:UWIN*:*)
echo ${UNAME_MACHINE}-pc-uwin
exit ;;
amd64:CYGWIN*:*:* | x86_64:CYGWIN*:*:*)
echo x86_64-unknown-cygwin
exit ;;
p*:CYGWIN*:*)
echo powerpcle-unknown-cygwin
exit ;;
prep*:SunOS:5.*:*)
echo powerpcle-unknown-solaris2`echo ${UNAME_RELEASE}|sed -e 's/[^.]*//'`
exit ;;
*:GNU:*:*)
# the GNU system
echo `echo ${UNAME_MACHINE}|sed -e 's,[-/].*$,,'`-unknown-gnu`echo ${UNAME_RELEASE}|sed -e 's,/.*$,,'`
exit ;;
*:GNU/*:*:*)
# other systems with GNU libc and userland
echo ${UNAME_MACHINE}-unknown-`echo ${UNAME_SYSTEM} | sed 's,^[^/]*/,,' | tr '[A-Z]' '[a-z]'``echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'`-gnu
exit ;;
i*86:Minix:*:*)
echo ${UNAME_MACHINE}-pc-minix
exit ;;
aarch64:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
aarch64_be:Linux:*:*)
UNAME_MACHINE=aarch64_be
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
alpha:Linux:*:*)
case `sed -n '/^cpu model/s/^.*: \(.*\)/\1/p' < /proc/cpuinfo` in
EV5) UNAME_MACHINE=alphaev5 ;;
EV56) UNAME_MACHINE=alphaev56 ;;
PCA56) UNAME_MACHINE=alphapca56 ;;
PCA57) UNAME_MACHINE=alphapca56 ;;
EV6) UNAME_MACHINE=alphaev6 ;;
EV67) UNAME_MACHINE=alphaev67 ;;
EV68*) UNAME_MACHINE=alphaev68 ;;
esac
objdump --private-headers /bin/sh | grep -q ld.so.1
if test "$?" = 0 ; then LIBC="libc1" ; else LIBC="" ; fi
echo ${UNAME_MACHINE}-unknown-linux-gnu${LIBC}
exit ;;
arm*:Linux:*:*)
eval $set_cc_for_build
if echo __ARM_EABI__ | $CC_FOR_BUILD -E - 2>/dev/null \
| grep -q __ARM_EABI__
then
echo ${UNAME_MACHINE}-unknown-linux-gnu
else
if echo __ARM_PCS_VFP | $CC_FOR_BUILD -E - 2>/dev/null \
| grep -q __ARM_PCS_VFP
then
echo ${UNAME_MACHINE}-unknown-linux-gnueabi
else
echo ${UNAME_MACHINE}-unknown-linux-gnueabihf
fi
fi
exit ;;
avr32*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
cris:Linux:*:*)
echo ${UNAME_MACHINE}-axis-linux-gnu
exit ;;
crisv32:Linux:*:*)
echo ${UNAME_MACHINE}-axis-linux-gnu
exit ;;
frv:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
hexagon:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
i*86:Linux:*:*)
LIBC=gnu
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#ifdef __dietlibc__
LIBC=dietlibc
#endif
EOF
eval `$CC_FOR_BUILD -E $dummy.c 2>/dev/null | grep '^LIBC'`
echo "${UNAME_MACHINE}-pc-linux-${LIBC}"
exit ;;
ia64:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
m32r*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
m68*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
mips:Linux:*:* | mips64:Linux:*:*)
eval $set_cc_for_build
sed 's/^ //' << EOF >$dummy.c
#undef CPU
#undef ${UNAME_MACHINE}
#undef ${UNAME_MACHINE}el
#if defined(__MIPSEL__) || defined(__MIPSEL) || defined(_MIPSEL) || defined(MIPSEL)
CPU=${UNAME_MACHINE}el
#else
#if defined(__MIPSEB__) || defined(__MIPSEB) || defined(_MIPSEB) || defined(MIPSEB)
CPU=${UNAME_MACHINE}
#else
CPU=
#endif
#endif
EOF
eval `$CC_FOR_BUILD -E $dummy.c 2>/dev/null | grep '^CPU'`
test x"${CPU}" != x && { echo "${CPU}-unknown-linux-gnu"; exit; }
;;
or32:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
padre:Linux:*:*)
echo sparc-unknown-linux-gnu
exit ;;
parisc64:Linux:*:* | hppa64:Linux:*:*)
echo hppa64-unknown-linux-gnu
exit ;;
parisc:Linux:*:* | hppa:Linux:*:*)
# Look for CPU level
case `grep '^cpu[^a-z]*:' /proc/cpuinfo 2>/dev/null | cut -d' ' -f2` in
PA7*) echo hppa1.1-unknown-linux-gnu ;;
PA8*) echo hppa2.0-unknown-linux-gnu ;;
*) echo hppa-unknown-linux-gnu ;;
esac
exit ;;
ppc64:Linux:*:*)
echo powerpc64-unknown-linux-gnu
exit ;;
ppc:Linux:*:*)
echo powerpc-unknown-linux-gnu
exit ;;
s390:Linux:*:* | s390x:Linux:*:*)
echo ${UNAME_MACHINE}-ibm-linux
exit ;;
sh64*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
sh*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
sparc:Linux:*:* | sparc64:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
tile*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
vax:Linux:*:*)
echo ${UNAME_MACHINE}-dec-linux-gnu
exit ;;
x86_64:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
xtensa*:Linux:*:*)
echo ${UNAME_MACHINE}-unknown-linux-gnu
exit ;;
i*86:DYNIX/ptx:4*:*)
# ptx 4.0 does uname -s correctly, with DYNIX/ptx in there.
# earlier versions are messed up and put the nodename in both
# sysname and nodename.
echo i386-sequent-sysv4
exit ;;
i*86:UNIX_SV:4.2MP:2.*)
# Unixware is an offshoot of SVR4, but it has its own version
# number series starting with 2...
# I am not positive that other SVR4 systems won't match this,
# I just have to hope. -- rms.
# Use sysv4.2uw... so that sysv4* matches it.
echo ${UNAME_MACHINE}-pc-sysv4.2uw${UNAME_VERSION}
exit ;;
i*86:OS/2:*:*)
# If we were able to find `uname', then EMX Unix compatibility
# is probably installed.
echo ${UNAME_MACHINE}-pc-os2-emx
exit ;;
i*86:XTS-300:*:STOP)
echo ${UNAME_MACHINE}-unknown-stop
exit ;;
i*86:atheos:*:*)
echo ${UNAME_MACHINE}-unknown-atheos
exit ;;
i*86:syllable:*:*)
echo ${UNAME_MACHINE}-pc-syllable
exit ;;
i*86:LynxOS:2.*:* | i*86:LynxOS:3.[01]*:* | i*86:LynxOS:4.[02]*:*)
echo i386-unknown-lynxos${UNAME_RELEASE}
exit ;;
i*86:*DOS:*:*)
echo ${UNAME_MACHINE}-pc-msdosdjgpp
exit ;;
i*86:*:4.*:* | i*86:SYSTEM_V:4.*:*)
UNAME_REL=`echo ${UNAME_RELEASE} | sed 's/\/MP$//'`
if grep Novell /usr/include/link.h >/dev/null 2>/dev/null; then
echo ${UNAME_MACHINE}-univel-sysv${UNAME_REL}
else
echo ${UNAME_MACHINE}-pc-sysv${UNAME_REL}
fi
exit ;;
i*86:*:5:[678]*)
# UnixWare 7.x, OpenUNIX and OpenServer 6.
case `/bin/uname -X | grep "^Machine"` in
*486*) UNAME_MACHINE=i486 ;;
*Pentium) UNAME_MACHINE=i586 ;;
*Pent*|*Celeron) UNAME_MACHINE=i686 ;;
esac
echo ${UNAME_MACHINE}-unknown-sysv${UNAME_RELEASE}${UNAME_SYSTEM}${UNAME_VERSION}
exit ;;
i*86:*:3.2:*)
if test -f /usr/options/cb.name; then
UNAME_REL=`sed -n 's/.*Version //p' /dev/null >/dev/null ; then
UNAME_REL=`(/bin/uname -X|grep Release|sed -e 's/.*= //')`
(/bin/uname -X|grep i80486 >/dev/null) && UNAME_MACHINE=i486
(/bin/uname -X|grep '^Machine.*Pentium' >/dev/null) \
&& UNAME_MACHINE=i586
(/bin/uname -X|grep '^Machine.*Pent *II' >/dev/null) \
&& UNAME_MACHINE=i686
(/bin/uname -X|grep '^Machine.*Pentium Pro' >/dev/null) \
&& UNAME_MACHINE=i686
echo ${UNAME_MACHINE}-pc-sco$UNAME_REL
else
echo ${UNAME_MACHINE}-pc-sysv32
fi
exit ;;
pc:*:*:*)
# Left here for compatibility:
# uname -m prints for DJGPP always 'pc', but it prints nothing about
# the processor, so we play safe by assuming i586.
# Note: whatever this is, it MUST be the same as what config.sub
# prints for the "djgpp" host, or else GDB configury will decide that
# this is a cross-build.
echo i586-pc-msdosdjgpp
exit ;;
Intel:Mach:3*:*)
echo i386-pc-mach3
exit ;;
paragon:*:*:*)
echo i860-intel-osf1
exit ;;
i860:*:4.*:*) # i860-SVR4
if grep Stardent /usr/include/sys/uadmin.h >/dev/null 2>&1 ; then
echo i860-stardent-sysv${UNAME_RELEASE} # Stardent Vistra i860-SVR4
else # Add other i860-SVR4 vendors below as they are discovered.
echo i860-unknown-sysv${UNAME_RELEASE} # Unknown i860-SVR4
fi
exit ;;
mini*:CTIX:SYS*5:*)
# "miniframe"
echo m68010-convergent-sysv
exit ;;
mc68k:UNIX:SYSTEM5:3.51m)
echo m68k-convergent-sysv
exit ;;
M680?0:D-NIX:5.3:*)
echo m68k-diab-dnix
exit ;;
M68*:*:R3V[5678]*:*)
test -r /sysV68 && { echo 'm68k-motorola-sysv'; exit; } ;;
3[345]??:*:4.0:3.0 | 3[34]??A:*:4.0:3.0 | 3[34]??,*:*:4.0:3.0 | 3[34]??/*:*:4.0:3.0 | 4400:*:4.0:3.0 | 4850:*:4.0:3.0 | SKA40:*:4.0:3.0 | SDS2:*:4.0:3.0 | SHG2:*:4.0:3.0 | S7501*:*:4.0:3.0)
OS_REL=''
test -r /etc/.relid \
&& OS_REL=.`sed -n 's/[^ ]* [^ ]* \([0-9][0-9]\).*/\1/p' < /etc/.relid`
/bin/uname -p 2>/dev/null | grep 86 >/dev/null \
&& { echo i486-ncr-sysv4.3${OS_REL}; exit; }
/bin/uname -p 2>/dev/null | /bin/grep entium >/dev/null \
&& { echo i586-ncr-sysv4.3${OS_REL}; exit; } ;;
3[34]??:*:4.0:* | 3[34]??,*:*:4.0:*)
/bin/uname -p 2>/dev/null | grep 86 >/dev/null \
&& { echo i486-ncr-sysv4; exit; } ;;
NCR*:*:4.2:* | MPRAS*:*:4.2:*)
OS_REL='.3'
test -r /etc/.relid \
&& OS_REL=.`sed -n 's/[^ ]* [^ ]* \([0-9][0-9]\).*/\1/p' < /etc/.relid`
/bin/uname -p 2>/dev/null | grep 86 >/dev/null \
&& { echo i486-ncr-sysv4.3${OS_REL}; exit; }
/bin/uname -p 2>/dev/null | /bin/grep entium >/dev/null \
&& { echo i586-ncr-sysv4.3${OS_REL}; exit; }
/bin/uname -p 2>/dev/null | /bin/grep pteron >/dev/null \
&& { echo i586-ncr-sysv4.3${OS_REL}; exit; } ;;
m68*:LynxOS:2.*:* | m68*:LynxOS:3.0*:*)
echo m68k-unknown-lynxos${UNAME_RELEASE}
exit ;;
mc68030:UNIX_System_V:4.*:*)
echo m68k-atari-sysv4
exit ;;
TSUNAMI:LynxOS:2.*:*)
echo sparc-unknown-lynxos${UNAME_RELEASE}
exit ;;
rs6000:LynxOS:2.*:*)
echo rs6000-unknown-lynxos${UNAME_RELEASE}
exit ;;
PowerPC:LynxOS:2.*:* | PowerPC:LynxOS:3.[01]*:* | PowerPC:LynxOS:4.[02]*:*)
echo powerpc-unknown-lynxos${UNAME_RELEASE}
exit ;;
SM[BE]S:UNIX_SV:*:*)
echo mips-dde-sysv${UNAME_RELEASE}
exit ;;
RM*:ReliantUNIX-*:*:*)
echo mips-sni-sysv4
exit ;;
RM*:SINIX-*:*:*)
echo mips-sni-sysv4
exit ;;
*:SINIX-*:*:*)
if uname -p 2>/dev/null >/dev/null ; then
UNAME_MACHINE=`(uname -p) 2>/dev/null`
echo ${UNAME_MACHINE}-sni-sysv4
else
echo ns32k-sni-sysv
fi
exit ;;
PENTIUM:*:4.0*:*) # Unisys `ClearPath HMP IX 4000' SVR4/MP effort
# says
echo i586-unisys-sysv4
exit ;;
*:UNIX_System_V:4*:FTX*)
# From Gerald Hewes .
# How about differentiating between stratus architectures? -djm
echo hppa1.1-stratus-sysv4
exit ;;
*:*:*:FTX*)
# From seanf@swdc.stratus.com.
echo i860-stratus-sysv4
exit ;;
i*86:VOS:*:*)
# From Paul.Green@stratus.com.
echo ${UNAME_MACHINE}-stratus-vos
exit ;;
*:VOS:*:*)
# From Paul.Green@stratus.com.
echo hppa1.1-stratus-vos
exit ;;
mc68*:A/UX:*:*)
echo m68k-apple-aux${UNAME_RELEASE}
exit ;;
news*:NEWS-OS:6*:*)
echo mips-sony-newsos6
exit ;;
R[34]000:*System_V*:*:* | R4000:UNIX_SYSV:*:* | R*000:UNIX_SV:*:*)
if [ -d /usr/nec ]; then
echo mips-nec-sysv${UNAME_RELEASE}
else
echo mips-unknown-sysv${UNAME_RELEASE}
fi
exit ;;
BeBox:BeOS:*:*) # BeOS running on hardware made by Be, PPC only.
echo powerpc-be-beos
exit ;;
BeMac:BeOS:*:*) # BeOS running on Mac or Mac clone, PPC only.
echo powerpc-apple-beos
exit ;;
BePC:BeOS:*:*) # BeOS running on Intel PC compatible.
echo i586-pc-beos
exit ;;
BePC:Haiku:*:*) # Haiku running on Intel PC compatible.
echo i586-pc-haiku
exit ;;
SX-4:SUPER-UX:*:*)
echo sx4-nec-superux${UNAME_RELEASE}
exit ;;
SX-5:SUPER-UX:*:*)
echo sx5-nec-superux${UNAME_RELEASE}
exit ;;
SX-6:SUPER-UX:*:*)
echo sx6-nec-superux${UNAME_RELEASE}
exit ;;
SX-7:SUPER-UX:*:*)
echo sx7-nec-superux${UNAME_RELEASE}
exit ;;
SX-8:SUPER-UX:*:*)
echo sx8-nec-superux${UNAME_RELEASE}
exit ;;
SX-8R:SUPER-UX:*:*)
echo sx8r-nec-superux${UNAME_RELEASE}
exit ;;
Power*:Rhapsody:*:*)
echo powerpc-apple-rhapsody${UNAME_RELEASE}
exit ;;
*:Rhapsody:*:*)
echo ${UNAME_MACHINE}-apple-rhapsody${UNAME_RELEASE}
exit ;;
*:Darwin:*:*)
UNAME_PROCESSOR=`uname -p` || UNAME_PROCESSOR=unknown
case $UNAME_PROCESSOR in
i386)
eval $set_cc_for_build
if [ "$CC_FOR_BUILD" != 'no_compiler_found' ]; then
if (echo '#ifdef __LP64__'; echo IS_64BIT_ARCH; echo '#endif') | \
(CCOPTS= $CC_FOR_BUILD -E - 2>/dev/null) | \
grep IS_64BIT_ARCH >/dev/null
then
UNAME_PROCESSOR="x86_64"
fi
fi ;;
unknown) UNAME_PROCESSOR=powerpc ;;
esac
echo ${UNAME_PROCESSOR}-apple-darwin${UNAME_RELEASE}
exit ;;
*:procnto*:*:* | *:QNX:[0123456789]*:*)
UNAME_PROCESSOR=`uname -p`
if test "$UNAME_PROCESSOR" = "x86"; then
UNAME_PROCESSOR=i386
UNAME_MACHINE=pc
fi
echo ${UNAME_PROCESSOR}-${UNAME_MACHINE}-nto-qnx${UNAME_RELEASE}
exit ;;
*:QNX:*:4*)
echo i386-pc-qnx
exit ;;
NEO-?:NONSTOP_KERNEL:*:*)
echo neo-tandem-nsk${UNAME_RELEASE}
exit ;;
NSE-*:NONSTOP_KERNEL:*:*)
echo nse-tandem-nsk${UNAME_RELEASE}
exit ;;
NSR-?:NONSTOP_KERNEL:*:*)
echo nsr-tandem-nsk${UNAME_RELEASE}
exit ;;
*:NonStop-UX:*:*)
echo mips-compaq-nonstopux
exit ;;
BS2000:POSIX*:*:*)
echo bs2000-siemens-sysv
exit ;;
DS/*:UNIX_System_V:*:*)
echo ${UNAME_MACHINE}-${UNAME_SYSTEM}-${UNAME_RELEASE}
exit ;;
*:Plan9:*:*)
# "uname -m" is not consistent, so use $cputype instead. 386
# is converted to i386 for consistency with other x86
# operating systems.
if test "$cputype" = "386"; then
UNAME_MACHINE=i386
else
UNAME_MACHINE="$cputype"
fi
echo ${UNAME_MACHINE}-unknown-plan9
exit ;;
*:TOPS-10:*:*)
echo pdp10-unknown-tops10
exit ;;
*:TENEX:*:*)
echo pdp10-unknown-tenex
exit ;;
KS10:TOPS-20:*:* | KL10:TOPS-20:*:* | TYPE4:TOPS-20:*:*)
echo pdp10-dec-tops20
exit ;;
XKL-1:TOPS-20:*:* | TYPE5:TOPS-20:*:*)
echo pdp10-xkl-tops20
exit ;;
*:TOPS-20:*:*)
echo pdp10-unknown-tops20
exit ;;
*:ITS:*:*)
echo pdp10-unknown-its
exit ;;
SEI:*:*:SEIUX)
echo mips-sei-seiux${UNAME_RELEASE}
exit ;;
*:DragonFly:*:*)
echo ${UNAME_MACHINE}-unknown-dragonfly`echo ${UNAME_RELEASE}|sed -e 's/[-(].*//'`
exit ;;
*:*VMS:*:*)
UNAME_MACHINE=`(uname -p) 2>/dev/null`
case "${UNAME_MACHINE}" in
A*) echo alpha-dec-vms ; exit ;;
I*) echo ia64-dec-vms ; exit ;;
V*) echo vax-dec-vms ; exit ;;
esac ;;
*:XENIX:*:SysV)
echo i386-pc-xenix
exit ;;
i*86:skyos:*:*)
echo ${UNAME_MACHINE}-pc-skyos`echo ${UNAME_RELEASE}` | sed -e 's/ .*$//'
exit ;;
i*86:rdos:*:*)
echo ${UNAME_MACHINE}-pc-rdos
exit ;;
i*86:AROS:*:*)
echo ${UNAME_MACHINE}-pc-aros
exit ;;
x86_64:VMkernel:*:*)
echo ${UNAME_MACHINE}-unknown-esx
exit ;;
esac
#echo '(No uname command or uname output not recognized.)' 1>&2
#echo "${UNAME_MACHINE}:${UNAME_SYSTEM}:${UNAME_RELEASE}:${UNAME_VERSION}" 1>&2
eval $set_cc_for_build
cat >$dummy.c <
# include
#endif
main ()
{
#if defined (sony)
#if defined (MIPSEB)
/* BFD wants "bsd" instead of "newsos". Perhaps BFD should be changed,
I don't know.... */
printf ("mips-sony-bsd\n"); exit (0);
#else
#include
printf ("m68k-sony-newsos%s\n",
#ifdef NEWSOS4
"4"
#else
""
#endif
); exit (0);
#endif
#endif
#if defined (__arm) && defined (__acorn) && defined (__unix)
printf ("arm-acorn-riscix\n"); exit (0);
#endif
#if defined (hp300) && !defined (hpux)
printf ("m68k-hp-bsd\n"); exit (0);
#endif
#if defined (NeXT)
#if !defined (__ARCHITECTURE__)
#define __ARCHITECTURE__ "m68k"
#endif
int version;
version=`(hostinfo | sed -n 's/.*NeXT Mach \([0-9]*\).*/\1/p') 2>/dev/null`;
if (version < 4)
printf ("%s-next-nextstep%d\n", __ARCHITECTURE__, version);
else
printf ("%s-next-openstep%d\n", __ARCHITECTURE__, version);
exit (0);
#endif
#if defined (MULTIMAX) || defined (n16)
#if defined (UMAXV)
printf ("ns32k-encore-sysv\n"); exit (0);
#else
#if defined (CMU)
printf ("ns32k-encore-mach\n"); exit (0);
#else
printf ("ns32k-encore-bsd\n"); exit (0);
#endif
#endif
#endif
#if defined (__386BSD__)
printf ("i386-pc-bsd\n"); exit (0);
#endif
#if defined (sequent)
#if defined (i386)
printf ("i386-sequent-dynix\n"); exit (0);
#endif
#if defined (ns32000)
printf ("ns32k-sequent-dynix\n"); exit (0);
#endif
#endif
#if defined (_SEQUENT_)
struct utsname un;
uname(&un);
if (strncmp(un.version, "V2", 2) == 0) {
printf ("i386-sequent-ptx2\n"); exit (0);
}
if (strncmp(un.version, "V1", 2) == 0) { /* XXX is V1 correct? */
printf ("i386-sequent-ptx1\n"); exit (0);
}
printf ("i386-sequent-ptx\n"); exit (0);
#endif
#if defined (vax)
# if !defined (ultrix)
# include
# if defined (BSD)
# if BSD == 43
printf ("vax-dec-bsd4.3\n"); exit (0);
# else
# if BSD == 199006
printf ("vax-dec-bsd4.3reno\n"); exit (0);
# else
printf ("vax-dec-bsd\n"); exit (0);
# endif
# endif
# else
printf ("vax-dec-bsd\n"); exit (0);
# endif
# else
printf ("vax-dec-ultrix\n"); exit (0);
# endif
#endif
#if defined (alliant) && defined (i860)
printf ("i860-alliant-bsd\n"); exit (0);
#endif
exit (1);
}
EOF
$CC_FOR_BUILD -o $dummy $dummy.c 2>/dev/null && SYSTEM_NAME=`$dummy` &&
{ echo "$SYSTEM_NAME"; exit; }
# Apollos put the system type in the environment.
test -d /usr/apollo && { echo ${ISP}-apollo-${SYSTYPE}; exit; }
# Convex versions that predate uname can use getsysinfo(1)
if [ -x /usr/convex/getsysinfo ]
then
case `getsysinfo -f cpu_type` in
c1*)
echo c1-convex-bsd
exit ;;
c2*)
if getsysinfo -f scalar_acc
then echo c32-convex-bsd
else echo c2-convex-bsd
fi
exit ;;
c34*)
echo c34-convex-bsd
exit ;;
c38*)
echo c38-convex-bsd
exit ;;
c4*)
echo c4-convex-bsd
exit ;;
esac
fi
cat >&2 < in order to provide the needed
information to handle your system.
config.guess timestamp = $timestamp
uname -m = `(uname -m) 2>/dev/null || echo unknown`
uname -r = `(uname -r) 2>/dev/null || echo unknown`
uname -s = `(uname -s) 2>/dev/null || echo unknown`
uname -v = `(uname -v) 2>/dev/null || echo unknown`
/usr/bin/uname -p = `(/usr/bin/uname -p) 2>/dev/null`
/bin/uname -X = `(/bin/uname -X) 2>/dev/null`
hostinfo = `(hostinfo) 2>/dev/null`
/bin/universe = `(/bin/universe) 2>/dev/null`
/usr/bin/arch -k = `(/usr/bin/arch -k) 2>/dev/null`
/bin/arch = `(/bin/arch) 2>/dev/null`
/usr/bin/oslevel = `(/usr/bin/oslevel) 2>/dev/null`
/usr/convex/getsysinfo = `(/usr/convex/getsysinfo) 2>/dev/null`
UNAME_MACHINE = ${UNAME_MACHINE}
UNAME_RELEASE = ${UNAME_RELEASE}
UNAME_SYSTEM = ${UNAME_SYSTEM}
UNAME_VERSION = ${UNAME_VERSION}
EOF
exit 1
# Local variables:
# eval: (add-hook 'write-file-hooks 'time-stamp)
# time-stamp-start: "timestamp='"
# time-stamp-format: "%:y-%02m-%02d"
# time-stamp-end: "'"
# End:
PHYLIPNEW-3.69.650/README 0000664 0001750 0001750 00000007321 11253743723 011160 0000000 0000000 This is the EMBOSS integrated version of PHYLIP 3.69
If you require the original PHYLIP 3.69 distribution, you should
obtain it from the author, Joe Felsenstein, at
http://evolution.gs.washington.edu/phylip/software.html
This file records the steps involved in making PHYLIP 3.69 compatible
with EMBOSS as an EMBASSY package. The procedure is relatively simple,
compared to other packages, as PHYLIP has a nicely isolated user
interface and our main task is to write the ACD interface.
1. Make a new directory, and copy in the phylip source (src/
directory) and documentation (doc/ directory) files.
2. Move the include files (*.h) from src/ to include/
3. Create a configure.in file in the ./ directory
4. Create a Makefile.am file in the ./ src/ and emboss_acd/ directories
5. In src/Makefile.am use a prefix 'f' for every program. In this way
the original PHYLIP package can co-exist with the EMBASSY version,
and so can the EMBASSY PHYLIP 3.5 package, which used an 'e'
prefix. We can claim that the 'f' stands for 'PHYLIP' although
being the letter after 'e' is also a significant factor.
6. Add files in the emboss_acd directory (initially from the phylip
embassy package) with the 'f' prefix.
7. In include/phylip.h rename VERSION to ORIGINALVERSION as our new
./configure will define it. Put the same version (3.69) into
./configure
8. Looks like PHYLIP 3.69 has new library source code - these functions
were generally in the main program *.c files before. We add these as extra
sources in Makefile.am
9. PHYLIP 3.69 has programs we did not build in PHYLIP 3.5. This time,
we build them all (for now).
10. Put the ACD interface into each program:
(a) comment out with the existing getoptions function
put /* */ around it
put // on every line so we know it is changed
change /* */ to /# #/
(b) add an emboss_getoptions function in main (after "init()")
to initialise the same variables ad the original getoptions
and to use ajAcdGet calls
(c) use the modified openfile calls in the remaining code
11. Options are also defined in a set of functions in phylip.c
Replace these with calls to standard ACD options. EMBOSS
validation will catch any that are not defined in the ACD file.
12. Make sure we add ajExit() at the end of main to test for unused
ACD options and final debug output.
13. Use perl scriptsd to check for options in the source (prompts in
getoptions and calls to the phylip.c "init" functions. Compare
these to the ACD files from PHYLIP 3.5 and update accordingly.
14. Make test cases using the test data from the phylip doc/*.html
examples. Use these to test both phylip 3.69 and phylip 3.5 and
note any differences.
15. Some programs allow multiple input datasets. This means a
seqsetall ACD type which we don't have yet. Set the maximum to 1
for these, but allow unlimited datasets where the same option
-datasets refers to a weight file which is a simple infile that we
let PHYLIP read.
16. Convert printf and exxit(-1) to use ajErr for the message and make
exxit(-1) call ajExitBad()
17. Programs end with printf("Done") - and other progress reports.
Comment them out.
18. Made new ACD data types for Dist, Freq, Properties, Tree
and tried to read all their many file formats.
19. Made fcontrast work with the new style for frequency and tree
data. This meant parsing trees from strings instead of files (lots
of changes to phylip.c treeread onwards), although the frequency
part was (so far) pretty simple.
20. So remove the old functions that read files (all of them!)
Pass trees as char*
Carefully put Freq->Data into new arrays (in input order :-)
Keep ACD minimal for now.
PHYLIPNEW-3.69.650/data/ 0002775 0001750 0001750 00000000000 12171071713 011261 5 0000000 0000000 PHYLIPNEW-3.69.650/data/font5 0000664 0001750 0001750 00000040766 10227217747 012203 0000000 0000000 CA 3051 21 20 28
-2356 1136 -2152 2235 -2254 2336 -2356 2354 2437 2435
-1441 2241 -835 1435 -1935 2635 -1136 935 -1136 1335
-2236 2035 -2237 2135 -2437 2535 -13035
CB 3052 21 24 28
-1956 1335 -2056 1435 -2156 1535 -1656 2756 3055 3153
3151 3048 2947 2646 -2955 3053 3051 2948 2847 -2756
2855 2953 2951 2848 2646 -1846 2646 2845 2943 2941
2838 2636 2235 1035 -2745 2843 2841 2738 2536 -2646
2744 2741 2638 2436 2235 -1756 2055 -1856 1954 -2256
2054 -2356 2055 -1436 1135 -1437 1235 -1537 1635 -1436
1735 -13435
CC 3053 21 21 28
-2854 2954 3056 2950 2952 2854 2755 2556 2256 1955
1753 1550 1447 1343 1340 1437 1536 1835 2135 2336
2538 2640 -1954 1752 1650 1547 1443 1439 1537 -2256
2055 1852 1750 1647 1543 1538 1636 1835 -13135
CD 3054 21 23 28
-1956 1335 -2056 1435 -2156 1535 -1656 2556 2855 2954
3051 3047 2943 2739 2537 2336 1935 1035 -2755 2854
2951 2947 2843 2639 2437 -2556 2754 2851 2847 2743
2539 2236 1935 -1756 2055 -1856 1954 -2256 2054 -2356
2055 -1436 1135 -1437 1235 -1537 1635 -1436 1735 -13335
CE 3055 21 23 28
-1956 1335 -2056 1435 -2156 1535 -2550 2342 -1656 3156
3050 -1846 2446 -1035 2535 2740 -1756 2055 -1856 1954
-2256 2054 -2356 2055 -2756 3055 -2856 3054 -2956 3053
-3056 3050 -2550 2346 2342 -2448 2246 2344 -2447 2146
2345 -1436 1135 -1437 1235 -1537 1635 -1436 1735 -2035
2536 -2235 2537 -2537 2740 -13335
CF 3056 21 22 28
-1956 1335 -2056 1435 -2156 1535 -2550 2342 -1656 3156
3050 -1846 2446 -1035 1835 -1756 2055 -1856 1954 -2256
2054 -2356 2055 -2756 3055 -2856 3054 -2956 3053 -3056
3050 -2550 2346 2342 -2448 2246 2344 -2447 2146 2345
-1436 1135 -1437 1235 -1537 1635 -1436 1735 -13235
CG 3057 21 22 28
-2854 2954 3056 2950 2952 2854 2755 2556 2256 1955
1753 1550 1447 1343 1340 1437 1536 1835 2035 2336
2538 2742 -1954 1752 1650 1547 1443 1439 1537 -2438
2539 2642 -2256 2055 1852 1750 1647 1543 1538 1636
1835 -2035 2236 2439 2542 -2242 3042 -2342 2541 -2442
2539 -2842 2640 -2942 2641 -13235
CH 3058 21 26 28
-1956 1335 -2056 1435 -2156 1535 -3156 2535 -3256 2635
-3356 2735 -1656 2456 -2856 3656 -1746 2946 -1035 1835
-2235 3035 -1756 2055 -1856 1954 -2256 2054 -2356 2055
-2956 3255 -3056 3154 -3456 3254 -3556 3255 -1436 1135
-1437 1235 -1537 1635 -1436 1735 -2636 2335 -2637 2435
-2737 2835 -2636 2935 -13635
CI 3059 21 14 28
-1956 1335 -2056 1435 -2156 1535 -1656 2456 -1035 1835
-1756 2055 -1856 1954 -2256 2054 -2356 2055 -1436 1135
-1437 1235 -1537 1635 -1436 1735 -12435
CJ 3060 21 19 28
-2456 1939 1837 1635 -2556 2143 2040 1938 -2656 2243
2038 1836 1635 1435 1236 1138 1140 1241 1341 1440
1439 1338 1238 -1240 1239 1339 1340 1240 -2156 2956
-2256 2555 -2356 2454 -2756 2554 -2856 2555 -12935
CK 3061 21 23 28
-1956 1335 -2056 1435 -2156 1535 -3255 1744 -2147 2535
-2247 2635 -2348 2736 -1656 2456 -2956 3556 -1035 1835
-2235 2935 -1756 2055 -1856 1954 -2256 2054 -2356 2055
-3056 3255 -3456 3255 -1436 1135 -1437 1235 -1537 1635
-1436 1735 -2536 2335 -2537 2435 -2637 2835 -13335
CL 3062 21 20 28
-1956 1335 -2056 1435 -2156 1535 -1656 2456 -1035 2535
2741 -1756 2055 -1856 1954 -2256 2054 -2356 2055 -1436
1135 -1437 1235 -1537 1635 -1436 1735 -2035 2536 -2235
2638 -2435 2741 -13035
CM 3063 21 28 28
-1956 1336 -1955 2037 2035 -2056 2137 -2156 2238 -3356
2238 2035 -3356 2735 -3456 2835 -3556 2935 -1656 2156
-3356 3856 -1035 1635 -2435 3235 -1756 1955 -1856 1954
-3656 3454 -3756 3455 -1336 1135 -1336 1535 -2836 2535
-2837 2635 -2937 3035 -2836 3135 -13835
CN 3064 21 25 28
-1956 1336 -1956 2635 -2056 2638 -2156 2738 -3255 2738
2635 -1656 2156 -2956 3556 -1035 1635 -1756 2055 -1856
2054 -3056 3255 -3456 3255 -1336 1135 -1336 1535 -13535
CO 3065 21 22 28
-2256 1955 1753 1550 1447 1343 1340 1437 1536 1735
2035 2336 2538 2741 2844 2948 2951 2854 2755 2556
2256 -1853 1650 1547 1443 1439 1537 -2438 2641 2744
2848 2852 2754 -2256 2055 1852 1750 1647 1543 1538
1636 1735 -2035 2236 2439 2541 2644 2748 2753 2655
2556 -13235
CP 3066 21 23 28
-1956 1335 -2056 1435 -2156 1535 -1656 2856 3155 3253
3251 3148 2946 2545 1745 -3055 3153 3151 3048 2846
-2856 2955 3053 3051 2948 2746 2545 -1035 1835 -1756
2055 -1856 1954 -2256 2054 -2356 2055 -1436 1135 -1437
1235 -1537 1635 -1436 1735 -13335
CQ 3067 21 22 28
-2256 1955 1753 1550 1447 1343 1340 1437 1536 1735
2035 2336 2538 2741 2844 2948 2951 2854 2755 2556
2256 -1853 1650 1547 1443 1439 1537 -2438 2641 2744
2848 2852 2754 -2256 2055 1852 1750 1647 1543 1538
1636 1735 -2035 2236 2439 2541 2644 2748 2753 2655
2556 -1538 1640 1841 1941 2140 2238 2333 2432 2532
2633 -2332 2431 2531 -2238 2231 2330 2530 2633 2634
-13235
CR 3068 21 24 28
-1956 1335 -2056 1435 -2156 1535 -1656 2756 3055 3153
3151 3048 2947 2646 1846 -2955 3053 3051 2948 2847
-2756 2855 2953 2951 2848 2646 -2246 2445 2544 2738
2837 2937 3038 -2737 2836 2936 -2544 2636 2735 2935
3038 3039 -1035 1835 -1756 2055 -1856 1954 -2256 2054
-2356 2055 -1436 1135 -1437 1235 -1537 1635 -1436 1735
-13435
CS 3069 21 23 28
-2954 3054 3156 3050 3052 2954 2855 2556 2156 1855
1653 1650 1748 1946 2543 2641 2638 2536 -1750 1848
2544 2642 -1855 1753 1751 1849 2446 2644 2742 2739
2637 2536 2235 1835 1536 1437 1339 1341 1235 1337
1437 -13335
CT 3070 21 22 28
-2356 1735 -2456 1835 -2556 1935 -1656 1450 -3256 3150
-1656 3256 -1435 2235 -1756 1450 -1956 1553 -2156 1655
-2856 3155 -2956 3154 -3056 3153 -3156 3150 -1836 1535
-1837 1635 -1937 2035 -1836 2135 -13235
CU 3071 21 25 28
-1856 1545 1441 1438 1536 1835 2235 2536 2738 2841
3255 -1956 1645 1541 1537 1636 -2056 1745 1641 1637
1835 -1556 2356 -2956 3556 -1656 1955 -1756 1854 -2156
1954 -2256 1955 -3056 3255 -3456 3255 -13535
CV 3072 21 20 28
-1656 1654 1737 1735 -1755 1838 -1856 1939 -2955 1735
-1456 2156 -2656 3256 -1556 1654 -1956 1854 -2056 1755
-2756 2955 -3156 2955 -13035
CW 3073 21 26 28
-1856 1854 1637 1635 -1955 1738 -2056 1839 -2656 1839
1635 -2656 2654 2437 2435 -2755 2538 -2856 2639 -3455
2639 2435 -1556 2356 -2656 2856 -3156 3756 -1656 1955
-1756 1854 -2156 1953 -2256 1955 -3256 3455 -3656 3455
-13635
CX 3074 21 22 28
-1756 2335 -1856 2435 -1956 2535 -3055 1236 -1556 2256
-2756 3356 -935 1535 -2035 2735 -1656 1854 -2056 1954
-2156 1955 -2856 3055 -3256 3055 -1236 1035 -1236 1435
-2336 2135 -2337 2235 -2437 2635 -13235
CY 3075 21 22 28
-1656 2046 1735 -1756 2146 1835 -1856 2246 1935 -3155
2246 -1456 2156 -2856 3456 -1435 2235 -1556 1755 -1956
1854 -2056 1755 -2956 3155 -3356 3155 -1836 1535 -1837
1635 -1937 2035 -1836 2135 -13235
CZ 3076 21 22 28
-2956 1135 -3056 1235 -3156 1335 -3156 1756 1550 -1135
2535 2741 -1856 1550 -1956 1653 -2156 1755 -2135 2536
-2335 2638 -2435 2741 -13235
Ca 3151 21 22 28
-2649 2442 2438 2536 2635 2835 3037 3139 -2749 2542
2536 -2649 2849 2642 2538 -2442 2445 2348 2149 1949
1648 1445 1342 1340 1437 1536 1735 1935 2136 2237
2339 2442 -1748 1545 1442 1439 1537 -1949 1747 1645
1542 1539 1636 1735 -13235
Cb 3152 21 19 28
-1756 1549 1443 1439 1537 1636 1835 2035 2336 2539
2642 2644 2547 2448 2249 2049 1848 1747 1645 1542
-1856 1649 1545 1539 1636 -2337 2439 2542 2545 2447
-1456 1956 1749 1542 -2035 2237 2339 2442 2445 2348
2249 -1556 1855 -1656 1754 -12935
Cc 3153 21 18 28
-2445 2446 2346 2344 2544 2546 2448 2249 1949 1648
1445 1342 1340 1437 1536 1735 1935 2236 2439 -1647
1545 1442 1439 1537 -1949 1747 1645 1542 1539 1636
1735 -12835
Cd 3154 21 22 28
-2856 2545 2441 2438 2536 2635 2835 3037 3139 -2956
2645 2541 2536 -2556 3056 2642 2538 -2442 2445 2348
2149 1949 1648 1445 1342 1340 1437 1536 1735 1935
2136 2237 2339 2442 -1647 1545 1442 1439 1537 -1949
1747 1645 1542 1539 1636 1735 -2656 2955 -2756 2854
-13235
Ce 3155 21 18 28
-1440 1841 2142 2444 2546 2448 2249 1949 1648 1445
1342 1340 1437 1536 1735 1935 2236 2438 -1647 1545
1442 1439 1537 -1949 1747 1645 1542 1539 1636 1735
-12835
Cf 3156 21 16 28
-2654 2655 2555 2553 2753 2755 2656 2456 2255 2053
1951 1848 1744 1535 1432 1330 1128 -2052 1949 1844
1635 1532 -2456 2254 2152 2049 1944 1736 1633 1531
1329 1128 928 829 831 1031 1029 929 930 -1449
2549 -12635
Cg 3157 21 21 28
-2649 2235 2132 1929 1728 -2749 2335 2131 -2649 2849
2435 2231 2029 1728 1428 1229 1130 1132 1332 1330
1230 1231 -2442 2445 2348 2149 1949 1648 1445 1342
1340 1437 1536 1735 1935 2136 2237 2339 2442 -1647
1545 1442 1439 1537 -1949 1747 1645 1542 1539 1636
1735 -13135
Ch 3158 21 22 28
-1856 1235 1435 -1956 1335 -1556 2056 1435 -1642 1846
2048 2249 2449 2648 2746 2743 2538 -2648 2644 2540
2536 -2646 2441 2438 2536 2635 2835 3037 3139 -1656
1955 -1756 1854 -13235
Ci 3159 21 13 28
-1956 1954 2154 2156 1956 -2056 2054 -1955 2155 -1145
1247 1449 1649 1748 1846 1843 1638 -1748 1744 1640
1636 -1746 1541 1538 1636 1735 1935 2137 2239 -12335
Cj 3160 21 13 28
-2056 2054 2254 2256 2056 -2156 2154 -2055 2255 -1245
1347 1549 1749 1848 1946 1943 1736 1633 1531 1329
1128 928 829 831 1031 1029 929 930 -1848 1843
1636 1533 1431 -1846 1742 1535 1432 1330 1128 -12335
Ck 3161 21 22 28
-1856 1235 1435 -1956 1335 -1556 2056 1435 -2847 2848
2748 2746 2946 2948 2849 2649 2448 2044 1843 -1643
1843 2042 2141 2337 2436 2636 -2041 2237 2336 -1843
1942 2136 2235 2435 2636 2839 -1656 1955 -1756 1854
-13235
Cl 3162 21 12 28
-1856 1545 1441 1438 1536 1635 1835 2037 2139 -1956
1645 1541 1536 -1556 2056 1642 1538 -1656 1955 -1756
1854 -12235
Cm 3163 21 35 28
-1145 1247 1449 1649 1748 1846 1843 1635 -1748 1743
1535 -1746 1642 1435 1635 -1843 2046 2248 2449 2649
2848 2946 2943 2735 -2848 2843 2635 -2846 2742 2535
2735 -2943 3146 3348 3549 3749 3948 4046 4043 3838
-3948 3944 3840 3836 -3946 3741 3738 3836 3935 4135
4337 4439 -14535
Cn 3164 21 24 28
-1145 1247 1449 1649 1748 1846 1843 1635 -1748 1743
1535 -1746 1642 1435 1635 -1843 2046 2248 2449 2649
2848 2946 2943 2738 -2848 2844 2740 2736 -2846 2641
2638 2736 2835 3035 3237 3339 -13435
Co 3165 21 20 28
-1949 1648 1445 1342 1340 1437 1536 1835 2135 2436
2639 2742 2744 2647 2548 2249 1949 -1647 1545 1442
1439 1537 -2437 2539 2642 2645 2547 -1949 1747 1645
1542 1539 1636 1835 -2135 2337 2439 2542 2545 2448
2249 -13035
Cp 3166 21 22 28
-1145 1247 1449 1649 1748 1846 1843 1739 1428 -1748
1743 1639 1328 -1746 1642 1228 -1842 1945 2047 2148
2349 2549 2748 2847 2944 2942 2839 2636 2335 2135
1936 1839 1842 -2747 2845 2842 2739 2637 -2549 2648
2745 2742 2639 2537 2335 -928 1728 -1329 1028 -1330
1128 -1430 1528 -1329 1628 -13235
Cq 3167 21 21 28
-2649 2028 -2749 2128 -2649 2849 2228 -2442 2445 2348
2149 1949 1648 1445 1342 1340 1437 1536 1735 1935
2136 2237 2339 2442 -1647 1545 1442 1439 1537 -1949
1747 1645 1542 1539 1636 1735 -1728 2528 -2129 1828
-2130 1928 -2230 2328 -2129 2428 -13135
Cr 3168 21 18 28
-1145 1247 1449 1649 1748 1846 1842 1635 -1748 1742
1535 -1746 1642 1435 1635 -2647 2648 2548 2546 2746
2748 2649 2449 2248 2046 1842 -12835
Cs 3169 21 17 28
-2446 2447 2347 2345 2545 2547 2448 2149 1849 1548
1447 1445 1543 1742 2041 2240 2338 -1548 1445 -1544
1743 2042 2241 -2340 2236 -1447 1545 1744 2043 2242
2340 2338 2236 1935 1635 1336 1237 1239 1439 1437
1337 1338 -12735
Ct 3170 21 14 28
-1956 1645 1541 1538 1636 1735 1935 2137 2239 -2056
1745 1641 1636 -1956 2156 1742 1638 -1349 2349 -12435
Cu 3171 21 24 28
-1145 1247 1449 1649 1748 1846 1843 1638 -1748 1744
1640 1636 -1746 1541 1538 1636 1835 2035 2236 2438
2641 -2849 2641 2638 2736 2835 3035 3237 3339 -2949
2741 2736 -2849 3049 2842 2738 -13435
Cv 3172 21 20 28
-1145 1247 1449 1649 1748 1846 1843 1638 -1748 1744
1640 1636 -1746 1541 1538 1636 1835 2035 2236 2438
2641 2745 2749 2649 2648 2746 -13035
Cw 3173 21 30 28
-1145 1247 1449 1649 1748 1846 1843 1638 -1748 1744
1640 1636 -1746 1541 1538 1636 1835 2035 2236 2438
2541 -2749 2541 2538 2636 2835 3035 3236 3438 3641
3745 3749 3649 3648 3746 -2849 2641 2636 -2749 2949
2742 2638 -14035
Cx 3174 21 22 28
-1345 1548 1749 1949 2148 2246 2244 -1949 2048 2044
1940 1838 1636 1435 1235 1136 1138 1338 1336 1236
1237 -2147 2144 2040 2037 -2947 2948 2848 2846 3046
3048 2949 2749 2548 2346 2244 2140 2136 2235 -1940
1938 2036 2235 2435 2636 2839 -13235
Cy 3175 21 22 28
-1145 1247 1449 1649 1748 1846 1843 1638 -1748 1744
1640 1636 -1746 1541 1538 1636 1835 2035 2236 2438
2642 -2849 2435 2332 2129 1928 -2949 2535 2331 -2849
3049 2635 2431 2229 1928 1628 1429 1330 1332 1532
1530 1430 1431 -13235
Cz 3176 21 20 28
-2749 2647 2445 1639 1437 1335 -2647 1747 1546 1444
-2447 2048 1748 1647 -2447 2049 1749 1547 1444 -1437
2337 2538 2640 -1637 2036 2336 2437 -1637 2035 2335
2537 2640 -13035
C0 3250 21 21 28
-2256 1955 1753 1550 1447 1343 1340 1437 1536 1735
1935 2236 2438 2641 2744 2848 2851 2754 2655 2456
2256 -1954 1752 1650 1547 1443 1439 1537 -2237 2439
2541 2644 2748 2752 2654 -2256 2055 1852 1750 1647
1543 1538 1636 1735 -1935 2136 2339 2441 2544 2648
2653 2555 2456 -13135
C1 3251 21 21 28
-2252 1735 1935 -2556 2352 1835 -2556 1935 -2556 2253
1951 1750 -2252 2051 1750 -13135
C2 3252 21 21 28
-1751 1752 1852 1850 1650 1652 1754 1855 2156 2456
2755 2853 2851 2749 2547 1541 1339 1135 -2655 2753
2751 2649 2447 2145 -2456 2555 2653 2651 2549 2347
1541 -1237 1338 1538 2037 2537 2638 -1538 2036 2536
-1538 2035 2335 2536 2638 2639 -13135
C3 3253 21 21 28
-1751 1752 1852 1850 1650 1652 1754 1855 2156 2456
2755 2853 2851 2749 2648 2447 2146 -2655 2753 2751
2649 2548 -2456 2555 2653 2651 2549 2347 2146 -1946
2146 2445 2544 2642 2639 2537 2336 2035 1735 1436
1337 1239 1241 1441 1439 1339 1340 -2444 2542 2539
2437 -2146 2345 2443 2439 2337 2236 2035 -13135
C4 3254 21 21 28
-2552 2035 2235 -2856 2652 2135 -2856 2235 -2856 1241
2841 -13135
C5 3255 21 21 28
-1956 1446 -1956 2956 -1955 2755 -1854 2354 2755 2956
-1446 1547 1848 2148 2447 2546 2644 2641 2538 2336
1935 1635 1436 1337 1239 1241 1441 1439 1339 1340
-2446 2544 2541 2438 2236 -2148 2347 2445 2441 2338
2136 1935 -13135
C6 3256 21 21 28
-2752 2753 2653 2651 2851 2853 2755 2556 2256 1955
1753 1550 1447 1343 1340 1437 1536 1735 2035 2336
2538 2640 2643 2545 2446 2247 1947 1746 1645 1543
-1853 1650 1547 1443 1439 1537 -2438 2540 2543 2445
-2256 2055 1852 1750 1647 1543 1538 1636 1735 -2035
2236 2337 2440 2444 2346 2247 -13135
C7 3257 21 21 28
-1656 1450 -2956 2853 2650 2245 2042 1939 1835 -2043
1839 1735 -2650 2044 1841 1739 1635 1835 -1553 1856
2056 2553 -1755 2055 2553 -1553 1754 2054 2553 2753
2854 2956 -13135
C8 3258 21 21 28
-2156 1855 1754 1652 1649 1747 1946 2246 2547 2748
2850 2853 2755 2556 2156 -2356 1855 -1854 1752 1748
1847 -1747 2046 -2146 2547 -2648 2750 2753 2655 -2755
2356 -2156 1954 1852 1848 1946 -2246 2447 2548 2650
2654 2556 -1946 1545 1343 1241 1238 1336 1635 2035
2436 2537 2639 2642 2544 2445 2246 -2046 1545 -1645
1443 1341 1338 1436 -1336 1835 2436 -2437 2539 2542
2444 -2445 2146 -1946 1745 1543 1441 1438 1536 1635
-2035 2236 2337 2439 2443 2345 2246 -13135
C9 3259 21 21 28
-2648 2546 2445 2244 1944 1745 1646 1548 1551 1653
1855 2156 2456 2655 2754 2851 2848 2744 2641 2438
2236 1935 1635 1436 1338 1340 1540 1538 1438 1439
-1746 1648 1651 1753 -2654 2752 2748 2644 2541 2338
-1944 1845 1747 1751 1854 1955 2156 -2456 2555 2653
2648 2544 2441 2339 2136 1935 -13135
C. 3260 21 11 28
-1338 1237 1236 1335 1435 1536 1537 1438 1338 -1337
1336 1436 1437 1337 -12135
C, 3261 21 11 28
-1435 1335 1236 1237 1338 1438 1537 1535 1433 1332
1131 -1337 1336 1436 1437 1337 -1435 1434 1332 -12135
C: 3262 21 11 28
-1649 1548 1547 1646 1746 1847 1848 1749 1649 -1648
1647 1747 1748 1648 -1338 1237 1236 1335 1435 1536
1537 1438 1338 -1337 1336 1436 1437 1337 -12135
C; 3263 21 11 28
-1649 1548 1547 1646 1746 1847 1848 1749 1649 -1648
1647 1747 1748 1648 -1435 1335 1236 1237 1338 1438
1537 1535 1433 1332 1131 -1337 1336 1436 1437 1337
-1435 1434 1332 -12135
C! 3264 21 11 28
-1956 1856 1755 1542 -1955 1855 1542 -1955 1954 1542
-1956 2055 2054 1542 -1338 1237 1236 1335 1435 1536
1537 1438 1338 -1337 1336 1436 1437 1337 -12135
C? 3265 21 21 28
-1751 1752 1852 1850 1650 1652 1754 1855 2156 2556
2855 2953 2951 2849 2748 2547 2146 1945 1943 2142
2242 -2356 2855 -2755 2853 2851 2749 2648 2447 -2556
2655 2753 2751 2649 2548 2146 2045 2043 2142 -1838
1737 1736 1835 1935 2036 2037 1938 1838 -1837 1836
1936 1937 1837 -13135
C/ 3270 21 23 28
-3460 828 928 -3460 3560 928 -13335
C( 3271 21 16 28
-2660 2459 2157 1854 1651 1447 1343 1338 1434 1531
1728 -1954 1751 1547 1442 1434 -2660 2358 2055 1852
1750 1647 1543 1434 -1442 1533 1630 1728 -12635
C) 3272 21 16 28
-1960 2157 2254 2350 2345 2241 2037 1834 1531 1229
1028 -2254 2246 2141 1937 1734 -1960 2058 2155 2246
-2254 2145 2041 1938 1836 1633 1330 1028 -12635
C* 3273 21 17 28
-2056 1955 2145 2044 -2056 2044 -2056 2155 1945 2044
-1553 1653 2447 2547 -1553 2547 -1553 1552 2548 2547
-2553 2453 1647 1547 -2553 1547 -2553 2552 1548 1547
-12735
C- 3274 21 25 28
-1445 3145 3144 -1445 1444 3144 -13535
C 3249 21 16 28
-12635
PHYLIPNEW-3.69.650/data/font4 0000664 0001750 0001750 00000026041 10227217747 012170 0000000 0000000 CA 2051 21 20 28
-2356 1035 -2356 2435 -2254 2335 -1441 2341 -835 1435
-2035 2635 -13035
CB 2052 21 24 28
-1956 1335 -2056 1435 -1656 2756 3055 3153 3151 3048
2947 2646 -2756 2955 3053 3051 2948 2847 2646 -1746
2646 2845 2943 2941 2838 2636 2235 1035 -2646 2745
2843 2841 2738 2536 2235 -13435
CC 2053 21 21 28
-2854 2954 3056 2950 2952 2854 2755 2556 2256 1955
1753 1550 1447 1343 1340 1437 1536 1835 2135 2336
2538 2640 -2256 2055 1853 1650 1547 1443 1440 1537
1636 1835 -13135
CD 2054 21 23 28
-1956 1335 -2056 1435 -1656 2556 2855 2954 3051 3047
2943 2739 2537 2336 1935 1035 -2556 2755 2854 2951
2947 2843 2639 2437 2236 1935 -13335
CE 2055 21 23 28
-1956 1335 -2056 1435 -2450 2242 -1656 3156 3050 3056
-1746 2346 -1035 2535 2740 2435 -13335
CF 2056 21 22 28
-1956 1335 -2056 1435 -2450 2242 -1656 3156 3050 3056
-1746 2346 -1035 1735 -13235
CG 2057 21 22 28
-2854 2954 3056 2950 2952 2854 2755 2556 2256 1955
1753 1550 1447 1343 1340 1437 1536 1835 2035 2336
2538 2742 -2256 2055 1853 1650 1547 1443 1440 1537
1636 1835 -2035 2236 2438 2642 -2342 3042 -13235
CH 2058 21 26 28
-1956 1335 -2056 1435 -3256 2635 -3356 2735 -1656 2356
-2956 3656 -1746 2946 -1035 1735 -2335 3035 -13635
CI 2059 21 13 28
-1956 1335 -2056 1435 -1656 2356 -1035 1735 -12335
CJ 2060 21 18 28
-2556 2039 1937 1836 1635 1435 1236 1138 1140 1241
1340 1239 -2456 1939 1837 1635 -2156 2856 -12835
CK 2061 21 23 28
-1956 1335 -2056 1435 -3356 1643 -2347 2735 -2247 2635
-1656 2356 -2956 3556 -1035 1735 -2335 2935 -13335
CL 2062 21 20 28
-1956 1335 -2056 1435 -1656 2356 -1035 2535 2741 2435
-13035
CM 2063 21 27 28
-1956 1335 -1956 2035 -2056 2137 -3356 2035 -3356 2735
-3456 2835 -1656 2056 -3356 3756 -1035 1635 -2435 3135
-13735
CN 2064 21 25 28
-1956 1335 -1956 2638 -1953 2635 -3256 2635 -1656 1956
-2956 3556 -1035 1635 -13535
CO 2065 21 22 28
-2256 1955 1753 1550 1447 1343 1340 1437 1536 1735
2035 2336 2538 2741 2844 2948 2951 2854 2755 2556
2256 -2256 2055 1853 1650 1547 1443 1440 1537 1735
-2035 2236 2438 2641 2744 2848 2851 2754 2556 -13235
CP 2066 21 23 28
-1956 1335 -2056 1435 -1656 2856 3155 3253 3251 3148
2946 2545 1745 -2856 3055 3153 3151 3048 2846 2545
-1035 1735 -13335
CQ 2067 21 22 28
-2256 1955 1753 1550 1447 1343 1340 1437 1536 1735
2035 2336 2538 2741 2844 2948 2951 2854 2755 2556
2256 -2256 2055 1853 1650 1547 1443 1440 1537 1735
-2035 2236 2438 2641 2744 2848 2851 2754 2556 -1537
1538 1640 1841 1941 2140 2238 2231 2330 2530 2632
2633 -2238 2332 2431 2531 2632 -13235
CR 2068 21 24 28
-1956 1335 -2056 1435 -1656 2756 3055 3153 3151 3048
2947 2646 1746 -2756 2955 3053 3051 2948 2847 2646
-2246 2445 2544 2636 2735 2935 3037 3038 -2544 2737
2836 2936 3037 -1035 1735 -13435
CS 2069 21 23 28
-2954 3054 3156 3050 3052 2954 2855 2556 2156 1855
1653 1651 1749 1848 2544 2742 -1651 1849 2545 2644
2742 2739 2637 2536 2235 1835 1536 1437 1339 1341
1235 1337 1437 -13335
CT 2070 21 21 28
-2356 1735 -2456 1835 -1756 1450 1656 3156 3050 3056
-1435 2135 -13135
CU 2071 21 25 28
-1856 1545 1441 1438 1536 1835 2235 2536 2738 2841
3256 -1956 1645 1541 1538 1636 1835 -1556 2256 -2956
3556 -13535
CV 2072 21 20 28
-1656 1735 -1756 1837 -3056 1735 -1456 2056 -2656 3256
-13035
CW 2073 21 26 28
-1856 1635 -1956 1737 -2656 1635 -2656 2435 -2756 2537
-3456 2435 -1556 2256 -3156 3756 -13635
CX 2074 21 22 28
-1756 2435 -1856 2535 -3156 1135 -1556 2156 -2756 3356
-935 1535 -2135 2735 -13235
CY 2075 21 21 28
-1656 2046 1735 -1756 2146 1835 -3156 2146 -1456 2056
-2756 3356 -1435 2135 -13135
CZ 2076 21 22 28
-3056 1135 -3156 1235 -1856 1550 1756 3156 -1135 2535
2741 2435 -13235
Ca 2151 21 21 28
-2649 2442 2338 2336 2435 2735 2937 3039 -2749 2542
2438 2436 2535 -2442 2445 2348 2149 1949 1648 1445
1342 1339 1437 1536 1735 1935 2136 2339 2442 -1949
1748 1545 1442 1438 1536 -13135
Cb 2152 21 19 28
-1856 1443 1440 1537 1636 -1956 1543 -1543 1646 1848
2049 2249 2448 2547 2645 2642 2539 2336 2035 1835
1636 1539 1543 -2448 2546 2542 2439 2236 2035 -1556
1956 -12935
Cc 2153 21 18 28
-2446 2445 2545 2546 2448 2249 1949 1648 1445 1342
1339 1437 1536 1735 1935 2236 2439 -1949 1748 1545
1442 1438 1536 -12835
Cd 2154 21 21 28
-2856 2442 2338 2336 2435 2735 2937 3039 -2956 2542
2438 2436 2535 -2442 2445 2348 2149 1949 1648 1445
1342 1339 1437 1536 1735 1935 2136 2339 2442 -1949
1748 1545 1442 1438 1536 -2556 2956 -13135
Ce 2155 21 18 28
-1440 1841 2142 2444 2546 2448 2249 1949 1648 1445
1342 1339 1437 1536 1735 1935 2236 2438 -1949 1748
1545 1442 1438 1536 -12835
Cf 2156 21 15 28
-2555 2454 2553 2654 2655 2556 2356 2155 2054 1952
1849 1535 1431 1329 -2356 2154 2052 1948 1739 1635
1532 1430 1329 1128 928 829 830 931 1030 929
-1449 2449 -12535
Cg 2157 21 20 28
-2749 2335 2232 2029 1728 1428 1229 1130 1131 1232
1331 1230 -2649 2235 2132 1929 1728 -2442 2445 2348
2149 1949 1648 1445 1342 1339 1437 1536 1735 1935
2136 2339 2442 -1949 1748 1545 1442 1438 1536 -13035
Ch 2158 21 21 28
-1856 1235 -1956 1335 -1542 1746 1948 2149 2349 2548
2647 2645 2439 2436 2535 -2349 2547 2545 2339 2336
2435 2735 2937 3039 -1556 1956 -13135
Ci 2159 21 13 28
-1956 1855 1954 2055 1956 -1145 1247 1449 1749 1848
1845 1639 1636 1735 -1649 1748 1745 1539 1536 1635
1935 2137 2239 -12335
Cj 2160 21 13 28
-2056 1955 2054 2155 2056 -1245 1347 1549 1849 1948
1945 1635 1532 1430 1329 1128 928 829 830 931
1030 929 -1749 1848 1845 1535 1432 1330 1128 -12335
Ck 2161 21 20 28
-1856 1235 -1956 1335 -2648 2547 2646 2747 2748 2649
2549 2348 1944 1743 1543 -1743 1942 2136 2235 -1743
1842 2036 2135 2335 2536 2739 -1556 1956 -13035
Cl 2162 21 12 28
-1856 1442 1338 1336 1435 1735 1937 2039 -1956 1542
1438 1436 1535 -1556 1956 -12235
Cm 2163 21 33 28
-1145 1247 1449 1749 1848 1846 1742 1535 -1649 1748
1746 1642 1435 -1742 1946 2148 2349 2549 2748 2847
2845 2535 -2549 2747 2745 2435 -2742 2946 3148 3349
3549 3748 3847 3845 3639 3636 3735 -3549 3747 3745
3539 3536 3635 3935 4137 4239 -14335
Cn 2164 21 23 28
-1145 1247 1449 1749 1848 1846 1742 1535 -1649 1748
1746 1642 1435 -1742 1946 2148 2349 2549 2748 2847
2845 2639 2636 2735 -2549 2747 2745 2539 2536 2635
2935 3137 3239 -13335
Co 2165 21 18 28
-1949 1648 1445 1342 1339 1437 1536 1735 1935 2236
2439 2542 2545 2447 2348 2149 1949 -1949 1748 1545
1442 1438 1536 -1935 2136 2339 2442 2446 2348 -12835
Cp 2166 21 21 28
-1145 1247 1449 1749 1848 1846 1742 1328 -1649 1748
1746 1642 1228 -1742 1845 2048 2249 2449 2648 2747
2845 2842 2739 2536 2235 2035 1836 1739 1742 -2648
2746 2742 2639 2436 2235 -928 1628 -13135
Cq 2167 21 20 28
-2649 2028 -2749 2128 -2442 2445 2348 2149 1949 1648
1445 1342 1339 1437 1536 1735 1935 2136 2339 2442
-1949 1748 1545 1442 1438 1536 -1728 2428 -13035
Cr 2168 21 17 28
-1145 1247 1449 1749 1848 1846 1742 1535 -1649 1748
1746 1642 1435 -1742 1946 2148 2349 2549 2648 2647
2546 2447 2548 -12735
Cs 2169 21 17 28
-2447 2446 2546 2547 2448 2149 1849 1548 1447 1445
1544 2240 2339 -1446 1545 2241 2340 2337 2236 1935
1635 1336 1237 1238 1338 1337 -12735
Ct 2170 21 14 28
-1956 1542 1438 1436 1535 1835 2037 2139 -2056 1642
1538 1536 1635 -1349 2249 -12435
Cu 2171 21 23 28
-1145 1247 1449 1749 1848 1845 1639 1637 1835 -1649
1748 1745 1539 1537 1636 1835 2035 2236 2438 2642
-2849 2642 2538 2536 2635 2935 3137 3239 -2949 2742
2638 2636 2735 -13335
Cv 2172 21 20 28
-1145 1247 1449 1749 1848 1845 1639 1637 1835 -1649
1748 1745 1539 1537 1636 1835 1935 2236 2438 2641
2745 2749 2649 2747 -13035
Cw 2173 21 29 28
-1145 1247 1449 1749 1848 1845 1639 1637 1835 -1649
1748 1745 1539 1537 1636 1835 2035 2236 2438 2540
-2749 2540 2537 2636 2835 3035 3236 3438 3540 3644
3649 3549 3647 -2849 2640 2637 2835 -13935
Cx 2174 21 20 28
-1345 1548 1749 2049 2147 2144 -1949 2047 2044 1940
1838 1636 1435 1335 1236 1237 1338 1437 1336 -1940
1937 2035 2335 2536 2739 -2748 2647 2746 2847 2848
2749 2649 2448 2246 2144 2040 2037 2135 -13035
Cy 2175 21 21 28
-1145 1247 1449 1749 1848 1845 1639 1637 1835 -1649
1748 1745 1539 1537 1636 1835 2035 2236 2438 2642
-2949 2535 2432 2229 1928 1628 1429 1330 1331 1432
1531 1430 -2849 2435 2332 2129 1928 -13135
Cz 2176 21 20 28
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CP 3016 21 22 28
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CR 3018 21 22 28
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Co 3115 21 20 28
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Cp 3116 21 21 28
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1328 -1530 1428 -1730 1828 -1729 1928 -13135
Cq 3117 21 20 28
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Cr 3118 21 17 28
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Cs 3119 21 17 28
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Ct 3120 21 15 28
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1737 -1554 1756 1739 1836 1935 -1249 2149 -12535
Cu 3121 21 23 28
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Cv 3122 21 18 28
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1849 -2149 2749 -1249 1547 -1749 1548 -2349 2548 -2649
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Cw 3123 21 24 28
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2635 -2349 2638 -2249 2449 2738 -3048 2738 2635 -1149
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Cy 3125 21 19 28
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Cz 3126 21 18 28
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C0 3200 21 20 28
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1755 1653 1548 1543 1638 1736 1935 -2135 2336 2438
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1547 1647 1648 1548 -1736 1635 1535 1436 1437 1538
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2833 -2238 2338 2833 -13235
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CW 2523 21 26 28
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Ci 2609 21 9 28
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Cp 2616 21 20 28
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1648 1446 1343 1341 1438 1636 1835 2135 2336 2538
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Cr 2618 21 14 28
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Cs 2619 21 17 28
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1338 -2446 2346 2248 -2347 2048 1748 1447 -1548 1446
1544 -1445 1644 2142 2341 2439 2438 2336 2035 1735
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Ct 2620 21 11 28
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1248 1948 -12135
Cu 2621 21 20 28
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Cw 2623 21 24 28
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Cx 2624 21 18 28
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Cy 2625 21 16 28
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2639 2744 2747 2652 2455 2156 1956 -1755 1552 1447
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2647 2552 2355 -2454 2155 1955 1654 -13035
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C3 2703 21 20 28
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1536 1437 1339 1439 -1447 1547 1748 2148 2447 2644
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C6 2706 21 20 28
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1538 1736 2035 2135 2436 2638 2741 2742 2645 2447
2148 2048 1747 1545 -2554 2255 2055 1754 -1855 1652
1547 1542 1638 1936 -1540 1737 2036 2136 2437 2640
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C7 2707 21 20 28
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C8 2708 21 20 28
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2642 2639 2537 2236 1836 1537 1439 1442 1544 1645
1846 2247 2448 2549 2651 2653 2555 2256 1856 -1655
1553 1551 1649 1848 2247 2446 2644 2742 2739 2637
2536 2235 1835 1536 1437 1339 1342 1444 1646 1847
2248 2449 2551 2553 2455 -2554 2255 1855 1554 -1438
1736 -2336 2638 -13035
C9 2709 21 20 28
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1956 2056 2355 2553 2649 2644 2539 2336 2035 1835
1536 1438 1538 1636 -2549 2446 2144 -2548 2345 2044
1944 1645 1448 -1844 1546 1449 1450 1553 1855 -1451
1654 1955 2055 2354 2551 -2155 2453 2549 2544 2439
2236 -2337 2036 1836 1537 -13035
C. 2710 21 11 28
-1538 1437 1436 1535 1635 1736 1737 1638 1538 -1537
1536 1636 1637 1537 -12135
C, 2711 21 11 28
-1736 1635 1535 1436 1437 1538 1638 1737 1734 1632
1431 -1537 1536 1636 1637 1537 -1635 1734 -1736 1632
-12135
C: 2712 21 11 28
-1549 1448 1447 1546 1646 1747 1748 1649 1549 -1548
1547 1647 1648 1548 -1538 1437 1436 1535 1635 1736
1737 1638 1538 -1537 1536 1636 1637 1537 -12135
C; 2713 21 11 28
-1549 1448 1447 1546 1646 1747 1748 1649 1549 -1548
1547 1647 1648 1548 -1736 1635 1535 1436 1437 1538
1638 1737 1734 1632 1431 -1537 1536 1636 1637 1537
-1635 1734 -1736 1632 -12135
C! 2714 21 11 28
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1635 1736 1737 1638 1538 -1537 1536 1636 1637 1537
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C? 2715 21 19 28
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C/ 2720 21 23 28
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C( 2721 21 14 28
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C 2699 21 16 28
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PHYLIPNEW-3.69.650/data/Makefile.am 0000664 0001750 0001750 00000000162 10775447511 013245 0000000 0000000 pkgdata_DATA = font1 font2 font3 font4 font5 \
font6
pkgdatadir=$(prefix)/share/$(PACKAGE)/data/
PHYLIPNEW-3.69.650/data/Makefile.in 0000664 0001750 0001750 00000033034 12171071677 013260 0000000 0000000 # Makefile.in generated by automake 1.12.2 from Makefile.am.
# @configure_input@
# Copyright (C) 1994-2012 Free Software Foundation, Inc.
# This Makefile.in is free software; the Free Software Foundation
# gives unlimited permission to copy and/or distribute it,
# with or without modifications, as long as this notice is preserved.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY, to the extent permitted by law; without
# even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE.
@SET_MAKE@
VPATH = @srcdir@
am__make_dryrun = \
{ \
am__dry=no; \
case $$MAKEFLAGS in \
*\\[\ \ ]*) \
echo 'am--echo: ; @echo "AM" OK' | $(MAKE) -f - 2>/dev/null \
| grep '^AM OK$$' >/dev/null || am__dry=yes;; \
*) \
for am__flg in $$MAKEFLAGS; do \
case $$am__flg in \
*=*|--*) ;; \
*n*) am__dry=yes; break;; \
esac; \
done;; \
esac; \
test $$am__dry = yes; \
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pkgincludedir = $(includedir)/@PACKAGE@
pkglibdir = $(libdir)/@PACKAGE@
pkglibexecdir = $(libexecdir)/@PACKAGE@
am__cd = CDPATH="$${ZSH_VERSION+.}$(PATH_SEPARATOR)" && cd
install_sh_DATA = $(install_sh) -c -m 644
install_sh_PROGRAM = $(install_sh) -c
install_sh_SCRIPT = $(install_sh) -c
INSTALL_HEADER = $(INSTALL_DATA)
transform = $(program_transform_name)
NORMAL_INSTALL = :
PRE_INSTALL = :
POST_INSTALL = :
NORMAL_UNINSTALL = :
PRE_UNINSTALL = :
POST_UNINSTALL = :
build_triplet = @build@
host_triplet = @host@
subdir = data
DIST_COMMON = $(srcdir)/Makefile.am $(srcdir)/Makefile.in
ACLOCAL_M4 = $(top_srcdir)/aclocal.m4
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$(top_srcdir)/m4/hpdf.m4 $(top_srcdir)/m4/java.m4 \
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$(ACLOCAL_M4)
mkinstalldirs = $(install_sh) -d
CONFIG_HEADER = $(top_builddir)/src/config.h
CONFIG_CLEAN_FILES =
CONFIG_CLEAN_VPATH_FILES =
SOURCES =
DIST_SOURCES =
am__can_run_installinfo = \
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2441 2539 2538 2436 2135 1735 1436 1338 1339 1440
1539 1438 -2142 2341 2439 2438 2336 2135 -12835
Ch 2909 21 22 28
-1549 1535 -1649 1635 -2649 2635 -2749 2735 -1249 1949
-2349 3049 -1235 1935 -2335 3035 -2648 1636 -13235
Ci 2910 21 22 28
-1549 1535 -1649 1635 -2649 2635 -2749 2735 -1249 1949
-2349 3049 -1235 1935 -2335 3035 -2648 1636 -1855 1856
1756 1755 1853 2052 2252 2453 2555 -13235
Cj 2911 21 20 28
-1549 1535 -1649 1635 -1249 1949 -1642 1842 2143 2244
2448 2549 2649 2748 2647 2548 -1842 2141 2240 2436
2535 -1842 2041 2140 2336 2435 2635 2736 2838 -1235
1935 -13035
Ck 2912 21 22 28
-1749 1745 1639 1536 1435 1335 1236 1337 1436 -2649
2635 -2749 2735 -1449 3049 -2335 3035 -13235
Cl 2913 21 23 28
-1549 1535 -1549 2135 -1649 2137 -2749 2135 -2749 2735
-2849 2835 -1249 1649 -2749 3149 -1235 1835 -2435 3135
-13335
Cm 2914 21 22 28
-1549 1535 -1649 1635 -2649 2635 -2749 2735 -1249 1949
-2349 3049 -1642 2642 -1235 1935 -2335 3035 -13235
Cn 2915 21 20 28
-1949 1648 1446 1343 1341 1438 1636 1935 2135 2436
2638 2741 2743 2646 2448 2149 1949 -1949 1748 1546
1443 1441 1538 1736 1935 -2135 2336 2538 2641 2643
2546 2348 2149 -13035
Co 2916 21 22 28
-1549 1535 -1649 1635 -2649 2635 -2749 2735 -1249 3049
-1235 1935 -2335 3035 -13235
Cp 2917 21 21 28
-1549 1528 -1649 1628 -1646 1848 2049 2249 2548 2746
2843 2841 2738 2536 2235 2035 1836 1638 -2249 2448
2646 2743 2741 2638 2436 2235 -1249 1649 -1228 1928
-13135
Cq 2918 21 19 28
-2546 2445 2544 2645 2646 2448 2249 1949 1648 1446
1343 1341 1438 1636 1935 2135 2436 2638 -1949 1748
1546 1443 1441 1538 1736 1935 -12935
Cr 2919 21 19 28
-1949 1935 -2049 2035 -1449 1344 1349 2649 2644 2549
-1635 2335 -12935
Cs 2920 21 18 28
-1349 1935 -1449 1937 -2549 1935 1731 1529 1328 1228
1129 1230 1329 -1149 1749 -2149 2749 -12835
Ct 2921 21 21 28
-2056 2028 -2156 2128 -1756 2156 -2046 1948 1849 1649
1448 1345 1339 1436 1635 1835 1936 2038 -1649 1548
1445 1439 1536 1635 -2549 2648 2745 2739 2636 2535
-2146 2248 2349 2549 2748 2845 2839 2736 2535 2335
2236 2138 -1728 2428 -13135
Cu 2922 21 20 28
-1449 2535 -1549 2635 -2649 1435 -1249 1849 -2249 2849
-1235 1835 -2235 2835 -13035
Cv 2923 21 22 28
-1549 1535 -1649 1635 -2649 2635 -2749 2735 -1249 1949
-2349 3049 -1235 3035 3030 2935 -13235
Cw 2924 21 22 28
-1549 1542 1640 1939 2139 2440 2642 -1649 1642 1740
1939 -2649 2635 -2749 2735 -1249 1949 -2349 3049 -2335
3035 -13235
Cx 2925 21 31 28
-1549 1535 -1649 1635 -2549 2535 -2649 2635 -3549 3535
-3649 3635 -1249 1949 -2249 2949 -3249 3949 -1235 3935
-14135
Cy 2926 21 31 28
-1549 1535 -1649 1635 -2549 2535 -2649 2635 -3549 3535
-3649 3635 -1249 1949 -2249 2949 -3249 3949 -1235 3935
3930 3835 -14135
Cz 2927 21 21 28
-1949 1935 -2049 2035 -1449 1344 1349 2349 -2042 2442
2741 2839 2838 2736 2435 1635 -2442 2641 2739 2738
2636 2435 -13135
C{ 2928 21 26 28
-1549 1535 -1649 1635 -1249 1949 -1642 2042 2341 2439
2438 2336 2035 1235 -2042 2241 2339 2338 2236 2035
-3049 3035 -3149 3135 -2749 3449 -2735 3435 -13635
C| 2929 21 17 28
-1549 1535 -1649 1635 -1249 1949 -1642 2042 2341 2439
2438 2336 2035 1235 -2042 2241 2339 2338 2236 2035
-12735
C} 2930 21 19 28
-1447 1349 1345 1447 1548 1749 2049 2348 2546 2643
2641 2538 2336 2035 1735 1536 1338 1339 1440 1539
1438 -2049 2248 2446 2543 2541 2438 2236 2035 -1942
2542 -12935
C~ 2931 21 29 28
-1549 1535 -1649 1635 -1249 1949 -1235 1935 -2849 2548
2346 2243 2241 2338 2536 2835 3035 3336 3538 3641
3643 3546 3348 3049 2849 -2849 2648 2446 2343 2341
2438 2636 2835 -3035 3236 3438 3541 3543 3446 3248
3049 -1642 2242 -13935
C; 2932 21 21 28
-2549 2535 -2649 2635 -2949 1849 1548 1446 1445 1543
1842 2542 -1849 1648 1546 1545 1643 1842 -2342 2041
1940 1736 1635 -2342 2141 2040 1836 1735 1535 1436
1338 -2235 2935 -13135
C0 2700 21 20 28
-1956 1655 1452 1347 1344 1439 1636 1935 2135 2436
2639 2744 2747 2652 2455 2156 1956 -1755 1552 1447
1444 1539 1736 -1637 1936 2136 2437 -2336 2539 2644
2647 2552 2355 -2454 2155 1955 1654 -13035
C1 2701 21 20 28
-1652 1853 2156 2135 -1652 1651 1852 2054 2035 2135
-13035
C2 2702 21 20 28
-1451 1452 1554 1655 1856 2256 2455 2554 2652 2650
2548 2345 1435 -1451 1551 1552 1654 1855 2255 2454
2552 2550 2448 2245 1335 -1436 2736 2735 -1335 2735
-13035
C3 2703 21 20 28
-1556 2656 1947 -1556 1555 2555 -2556 1847 -1948 2148
2447 2645 2742 2741 2638 2436 2135 1835 1536 1437
1339 1439 -1847 2147 2446 2643 -2247 2545 2642 2641
2538 2236 -2640 2437 2136 1836 1537 1439 -1736 1438
-13035
C4 2704 21 20 28
-2353 2335 2435 -2456 2435 -2456 1340 2840 -2353 1440
-1441 2841 2840 -13035
C5 2705 21 20 28
-1556 1447 -1655 1548 -1556 2556 2555 -1655 2555 -1548
1849 2149 2448 2646 2743 2741 2638 2436 2135 1835
1536 1437 1339 1439 -1447 1547 1748 2148 2447 2644
-2248 2546 2643 2641 2538 2236 -2640 2437 2136 1836
1537 1439 -1736 1438 -13035
C6 2706 21 20 28
-2455 2553 2653 2555 2256 2056 1755 1552 1447 1442
1538 1736 2035 2135 2436 2638 2741 2742 2645 2447
2148 2048 1747 1545 -2554 2255 2055 1754 -1855 1652
1547 1542 1638 1936 -1540 1737 2036 2136 2437 2640
-2236 2538 2641 2642 2545 2247 -2643 2446 2147 2047
1746 1543 -1947 1645 1542 -13035
C7 2707 21 20 28
-1356 2756 1735 -1356 1355 2655 -2656 1635 1735 -13035
C8 2708 21 20 28
-1856 1555 1453 1451 1549 1648 1847 2246 2445 2544
2642 2639 2537 2236 1836 1537 1439 1442 1544 1645
1846 2247 2448 2549 2651 2653 2555 2256 1856 -1655
1553 1551 1649 1848 2247 2446 2644 2742 2739 2637
2536 2235 1835 1536 1437 1339 1342 1444 1646 1847
2248 2449 2551 2553 2455 -2554 2255 1855 1554 -1438
1736 -2336 2638 -13035
C9 2709 21 20 28
-2546 2344 2043 1943 1644 1446 1349 1350 1453 1655
1956 2056 2355 2553 2649 2644 2539 2336 2035 1835
1536 1438 1538 1636 -2549 2446 2144 -2548 2345 2044
1944 1645 1448 -1844 1546 1449 1450 1553 1855 -1451
1654 1955 2055 2354 2551 -2155 2453 2549 2544 2439
2236 -2337 2036 1836 1537 -13035
C. 2710 21 11 28
-1538 1437 1436 1535 1635 1736 1737 1638 1538 -1537
1536 1636 1637 1537 -12135
C, 2711 21 11 28
-1736 1635 1535 1436 1437 1538 1638 1737 1734 1632
1431 -1537 1536 1636 1637 1537 -1635 1734 -1736 1632
-12135
C: 2712 21 11 28
-1549 1448 1447 1546 1646 1747 1748 1649 1549 -1548
1547 1647 1648 1548 -1538 1437 1436 1535 1635 1736
1737 1638 1538 -1537 1536 1636 1637 1537 -12135
C; 2713 21 11 28
-1549 1448 1447 1546 1646 1747 1748 1649 1549 -1548
1547 1647 1648 1548 -1736 1635 1535 1436 1437 1538
1638 1737 1734 1632 1431 -1537 1536 1636 1637 1537
-1635 1734 -1736 1632 -12135
C! 2714 21 11 28
-1556 1542 1642 -1556 1656 1642 -1538 1437 1436 1535
1635 1736 1737 1638 1538 -1537 1536 1636 1637 1537
-12135
C' 2715 21 19 28
-1351 1352 1454 1555 1856 2156 2455 2554 2652 2650
2548 2447 2246 1945 -1351 1451 1452 1554 1855 2155
2454 2552 2550 2448 2247 1946 -1453 1755 -2255 2553
-2549 2146 -1946 1942 2042 2046 -1938 1837 1836 1935
2035 2136 2137 2038 1938 -1937 1936 2036 2037 1937
-12935
C/ 2720 21 23 28
-3060 1228 1328 -3060 3160 1328 -13335
C( 2721 21 14 28
-2060 1858 1655 1451 1346 1342 1437 1633 1830 2028
2128 -2060 2160 1958 1755 1551 1446 1442 1537 1733
1930 2128 -12435
C) 2722 21 14 28
-1360 1558 1755 1951 2046 2042 1937 1733 1530 1328
1428 -1360 1460 1658 1855 2051 2146 2142 2037 1833
1630 1428 -12435
C* 2723 21 16 28
-1856 1755 1945 1844 -1856 1844 -1856 1955 1745 1844
-1353 1453 2247 2347 -1353 2347 -1353 1352 2348 2347
-2353 2253 1447 1347 -2353 1347 -2353 2352 1348 1347
-12635
C- 2724 21 25 28
-1445 3145 3144 -1445 1444 3144 -13535
C 2699 21 16 28
-12635
PHYLIPNEW-3.69.650/data/.cvsignore 0000664 0001750 0001750 00000000025 11326104717 013176 0000000 0000000 Makefile.in
Makefile
PHYLIPNEW-3.69.650/ChangeLog 0000664 0001750 0001750 00000004245 11616234655 012056 0000000 0000000 Release 3.69 update July 2011
Changed -thresh to -dothreshold and -gamma to -gammatype to avoid
qualifier name clashes with stricter ACD validation.
The *boot applications reported the status of some boolean options
and printed "Done" at the end. Removed the boolean reports and now
only print "Done" unless -noprogress is set to allow piping.
Release 3.69
Updated all code to include the changes in phylip 3.69.
Release 3.68
Updated all code to include the changes in phylip 3.68.
fdnadist no longer writes a blank line at the end of the output.
fconsense writes trees with 2 decimal places.
A bug in fprotdist for scores of 100.0 is fixed.
Rearrangement messages are no longer printed by fpromlk.
fprotdist and fprotpars now write "Done" when completed.
Renamed fdrawgram qualifiers to make unambiguous names shorter:
xmarginray => xrayshade ymarginray => yrayshade for RayShade
output image size in pixels.
Removed unused fdrawtree qualifiers plotterpcl and plotterpcx.
Added 4 new plotter options for the additional resolutions
previously defined by plotterpcl and plotterpcx.
Renamed fdrawtree qualifiers to make unambiguous names shorter:
xmarginray => xrayshade; ymarginray => yrayshade for RayShade
output image size in pixels.
Release 3.67
Updated all code to phylip 3.67. The output of several programs has
changed - see the phylip release notes for details. Programs with
changed output are all the molecular clock algorithms : fcontml,
fdnaml, fdnamlk, proml, promlk, restml. ftreedist and ftreedistpair
branch score distance output has also changed in phylip 3.67
fontfile now works correctly in fdrawgram and fdrawtree. The
fontfile value must be a known phylip font in the data directory.
previewing with X11 was broken. Setting "none" for previewer no
longer prompts before plotting.
frestdist had a memory access error reported by valgrind. The same
error was found in the original phylip source, and fixed by
copying in code changes in phylip 3.66
fclique had an error reading the ancestors file. Results now agree
with those from the original phylip 3.6 code.
fdnamove had an internal overflow. Array chh[11] needed at least
one extra space.
PHYLIPNEW-3.69.650/COPYING 0000664 0001750 0001750 00000002025 11614250727 011325 0000000 0000000 Copyright Notice for PHYLIP 3.69
The following copyright notice is intended to cover all source code, all
documentation, and all executable programs of the PHYLIP package.
(c) Copyright 1980-2008. University of Washington. All rights
reserved. Permission is granted to reproduce, perform, and modify
these programs and documentation files. Permission is granted to
distribute or provide access to these programs provided that this
copyright notice is not removed, the programs are not integrated with
or called by any product or service that generates revenue, and that
your distribution of these documentation files and programs are free.
Any modified versions of these materials that are distributed or
accessible shall indicate that they are based on these programs.
Institutions of higher education are granted permission to distribute
this material to their students and staff for a fee to recover
distribution costs. Permission requests for any other distribution of
these program should be directed to license(at)u.washington.edu
PHYLIPNEW-3.69.650/include/ 0002775 0001750 0001750 00000000000 12171071713 011773 5 0000000 0000000 PHYLIPNEW-3.69.650/include/discrete.h 0000664 0001750 0001750 00000013234 10075203710 013662 0000000 0000000
/* version 3.6. (c) Copyright 1993-2000 by the University of Washington.
Written by Joseph Felsenstein, Akiko Fuseki, Sean Lamont, and Andrew Keeffe.
Permission is granted to copy and use this program provided no fee is
charged for it and provided that this copyright notice is not removed. */
/*
discrete.h: included in pars
*/
typedef struct gbases {
discbaseptr discbase;
struct gbases *next;
} gbases;
struct LOC_hyptrav {
boolean bottom;
node *r;
discbaseptr hypset;
boolean maybe, nonzero;
unsigned char tempset, anc;
} ;
extern long nonodes, endsite, outgrno, nextree, which;
extern boolean interleaved, printdata, outgropt, treeprint, dotdiff;
extern steptr weight, category, alias, location, ally;
extern sequence y, convtab;
#ifndef OLDC
/*function prototypes*/
void discrete_inputdata(AjPPhyloState, long);
void alloctree(pointarray *, long, boolean);
void setuptree(pointarray, long, boolean);
void alloctip(node *, long *, unsigned char *);
void sitesort(long, steptr);
void sitecombine(long);
void sitescrunch(long);
void makevalues(pointarray, long *, unsigned char *, boolean);
void fillin(node *, node *, node *);
long getlargest(long *);
void multifillin(node *, node *, long);
void sumnsteps(node *, node *, node *, long, long);
void sumnsteps2(node *, node *, node *, long, long, long *);
void multisumnsteps(node *, node *, long, long, long *);
void multisumnsteps2(node *);
void findoutgroup(node *, boolean *);
boolean alltips(node *, node *);
void gdispose(node *, node **, pointarray);
void preorder(node *, node *, node *, node *, node *, node *, long );
void updatenumdesc(node *, node *, long);
void add(node *, node *, node *, node **, boolean, pointarray,
node **, long *, unsigned char *);
void findbelow(node **, node *, node *);
void re_move(node *, node **, node **, boolean, pointarray,
node **, long *, unsigned char *);
void postorder(node *);
void getnufork(node **, node **, pointarray, long *, unsigned char *);
void reroot(node *, node *);
void reroot2(node *, node *);
void reroot3(node *, node *, node *, node *, node **);
void savetraverse(node *);
void newindex(long, node *);
void flipindexes(long, pointarray);
boolean parentinmulti(node *);
long sibsvisited(node *, long *);
long smallest(node *, long *);
void bintomulti(node **, node **, node **, long *, unsigned char *);
void backtobinary(node **, node *, node **);
boolean outgrin(node *, node *);
void flipnodes(node *, node *);
void moveleft(node *, node *, node **);
void savetree(node *, long *, pointarray, node **, long *,
unsigned char *);
void addnsave(node *, node *, node *, node **, node **, boolean multf,
pointarray , long *, long *, unsigned char *);
void addbestever(long *, long *, long, boolean, long *, bestelm *);
void addtiedtree(long, long *, long, boolean, long *, bestelm *);
void clearcollapse(pointarray);
void clearbottom(pointarray);
void collabranch(node *,node *,node *);
boolean allcommonbases(node *, node *, boolean *);
void findbottom(node *, node **);
boolean moresteps(node *, node *);
boolean passdown(node *, node *, node *, node *, node *, node *, node *,
node *, node *, boolean);
boolean trycollapdesc(node *, node *, node *, node *, node *, node *,
node *, node *, node *, boolean ,long *, unsigned char *);
void setbottom(node *);
boolean zeroinsubtree(node *, node *, node *, node *, node *, node *,
node *, node *, boolean , node *, long *, unsigned char *);
boolean collapsible(node *, node *, node *, node *, node *, node *, node *,
node *, boolean , node *, long *, unsigned char *, pointarray);
void replaceback(node **,node *,node *,node **,long *,unsigned char *);
void putback(node *, node *, node *, node **);
void savelocrearr(node *, node *, node *, node *, node *, node *,
node *, node *, node *, node **, long, long *, boolean, boolean,
boolean *, long *, bestelm *, pointarray, node **, long *,
unsigned char *);
void clearvisited(pointarray);
void hyprint(long,long,struct LOC_hyptrav *, pointarray);
void gnubase(gbases **, gbases **, long);
void chuckbase(gbases *, gbases **);
void hyptrav(node *, discbaseptr, long, long, boolean, pointarray,
gbases **);
void hypstates(long, node *, pointarray, gbases **);
void initbranchlen(node *);
void initmin(node *, long, boolean);
void initbase(node *, long);
void inittreetrav(node *, long);
void compmin(node *, node *);
void minpostorder(node *, pointarray);
void branchlength(node *, node *, double *, pointarray);
void printbranchlengths(node *);
void branchlentrav(node *, node *, long, long, double *, pointarray);
void treelength(node *, long, pointarray);
void coordinates(node *, long *, double , long *);
void drawline(long, double, node *);
void printree(node *, double);
void writesteps(long, boolean, steptr, node *);
void treeout(node *, long, long *, node *);
void drawline3(long, double, node *);
void standev(long, long, long, double, double *, long **, longer);
void freetip(node *);
void freenontip(node *);
void freenodes(long, pointarray);
void freenode(node **);
void freetree(long, pointarray);
void freegarbage(gbases **);
void freegrbg(node **);
void treeout3(node *p, long nextree, long *col, node *root);
void collapsetree(node *, node *, node **, pointarray, long *, unsigned char *);
void collapsebestrees(node **, node **, pointarray, bestelm *, long *,
long *, unsigned char *, long, boolean, boolean);
/*function prototypes*/
#endif
PHYLIPNEW-3.69.650/include/dollo.h 0000664 0001750 0001750 00000001772 07712247476 013222 0000000 0000000
/* version 3.6. (c) Copyright 1993-2000 by the University of Washington.
Written by Joseph Felsenstein, Akiko Fuseki, Sean Lamont, and Andrew Keeffe.
Permission is granted to copy and use this program provided no fee is
charged for it and provided that this copyright notice is not removed. */
/*
dollo.h: included in dollop, dolmove & dolpenny
*/
#ifndef OLDC
/* function prototypes */
void correct(node *, long, boolean, bitptr, pointptr);
void fillin(node *);
void postorder(node *);
void count(long *, bitptr, steptr, steptr);
void filltrav(node *);
void hyprint(struct htrav_vars *, boolean *, bitptr, Char *);
void hyptrav(node *, boolean *, bitptr, long, boolean, Char *, pointptr,
gbit *, bitptr, bitptr);
void hypstates(long, boolean, Char *, pointptr, node *, gbit *,
bitptr, bitptr);
void drawline(long, double, node *);
void printree(double, boolean, node *);
void writesteps(boolean, boolean, steptr);
/* function prototypes */
#endif
PHYLIPNEW-3.69.650/include/cons.h 0000664 0001750 0001750 00000003133 11727433657 013043 0000000 0000000
#define OVER 8
#define ADJACENT_PAIRS 1
#define CORR_IN_1_AND_2 2
#define ALL_IN_1_AND_2 3
#define NO_PAIRING 4
#define ALL_IN_FIRST 5
#define TREE1 8
#define TREE2 9
#define FULL_MATRIX 11
#define VERBOSE 22
#define SPARSE 33
/* Number of columns per block in a matrix output */
#define COLUMNS_PER_BLOCK 10
typedef struct pattern_elm {
group_type *apattern;
long *patternsize;
double *length;
} pattern_elm;
#ifndef OLDC
/* function prototypes */
void initconsnode(node **, node **, node *, long, long, long *, long *,
initops, pointarray, pointarray, Char *, Char *, char **);
void phylipcompress(long *);
void sort(long);
void eliminate(long *, long *);
void printset(long);
void bigsubset(group_type *, long);
void recontraverse(node **, group_type *, long, long *);
void reconstruct(long);
void coordinates(node *, long *);
void drawline(long i);
void printree(void);
void consensus(pattern_elm ***, long);
void rehash(void);
void enternodeset(node *r);
void accumulate(node *);
void dupname2(Char *, node *, node *);
void dupname(node *);
void missingname(node *);
void gdispose(node *);
void initreenode(node *);
void reroot(node *, long *);
void store_pattern (pattern_elm ***, int);
boolean samename(naym, plotstring);
void reordertips(void);
void read_groups (pattern_elm ****, long , long, AjPPhyloTree *);
void clean_up_final(void);
void clean_up_final_consense(void);
void freegrbg(node **);
/* function prototypes */
#endif
extern long setsz;
PHYLIPNEW-3.69.650/include/seq.h 0000664 0001750 0001750 00000017450 11253743724 012671 0000000 0000000 /* version 3.6. (c) Copyright 1993-2000 by the University of Washington.
Written by Joseph Felsenstein, Akiko Fuseki, Sean Lamont, and Andrew Keeffe.
Permission is granted to copy and use this program provided no fee is
charged for it and provided that this copyright notice is not removed. */
/*
seq.h: included in dnacomp, dnadist, dnainvar, dnaml, dnamlk, dnamove,
dnapars, dnapenny, protdist, protpars, restdist & restml
*/
#ifndef SEQ_H
#define SEQ_H
#define ebcdic EBCDIC
#define MAXNCH 20
/* All of this came over from cons.h -plc*/
#define OVER 7
#define ADJACENT_PAIRS 1
#define CORR_IN_1_AND_2 2
#define ALL_IN_1_AND_2 3
#define NO_PAIRING 4
#define ALL_IN_FIRST 5
#define TREE1 8
#define TREE2 9
#define FULL_MATRIX 11
#define VERBOSE 22
#define SPARSE 33
/* Number of columns per block in a matrix output */
#define COLUMNS_PER_BLOCK 10
/*end move*/
typedef struct gbases {
baseptr base;
struct gbases *next;
} gbases;
typedef struct nuview_data {
/* A big 'ol collection of pointers used in nuview */
double *yy, *wwzz, *vvzz, *vzsumr, *vzsumy, *sum, *sumr, *sumy;
sitelike *xx;
} nuview_data;
struct LOC_hyptrav {
boolean bottom;
node *r;
long *hypset;
boolean maybe, nonzero;
long tempset, anc;
} ;
extern long nonodes, endsite, outgrno, nextree, which;
extern boolean interleaved, printdata, outgropt, treeprint, dotdiff, transvp;
extern steptr weight, category, alias, location, ally;
extern sequence y;
#ifndef OLDC
/* function prototypes */
void free_all_x_in_array (long, pointarray);
void free_all_x2_in_array (long, pointarray);
void alloctemp(node **, long *, long);
void freetemp(node **);
void freetree2 (pointarray, long);
void alloctree(pointarray *, long, boolean);
void allocx(long, long, pointarray, boolean);
void prot_allocx(long, long, pointarray, boolean);
void setuptree(pointarray, long, boolean);
void setuptree2(tree *);
void alloctip(node *, long *);
void getbasefreqs(double, double, double, double, double *, double *,
double *, double *, double *, double *, double *,
double *xi, double *, double *, boolean, boolean);
void empiricalfreqs(double *,double *,double *,double *,steptr,pointarray);
void sitesort(long, steptr);
void sitecombine(long);
void sitescrunch(long);
void sitesort2(long, steptr);
void sitecombine2(long, steptr);
void sitescrunch2(long, long, long, steptr);
void makevalues(pointarray, long *, boolean);
void makevalues2(long, pointarray, long, long, sequence, steptr);
void fillin(node *, node *, node *);
long getlargest(long *);
void multifillin(node *, node *, long);
void sumnsteps(node *, node *, node *, long, long);
void sumnsteps2(node *, node *, node *, long, long, long *);
void multisumnsteps(node *, node *, long, long, long *);
void multisumnsteps2(node *);
boolean alltips(node *, node *);
void gdispose(node *, node **, pointarray);
void preorder(node *, node *, node *, node *, node *, node *, long);
void updatenumdesc(node *, node *, long);
void add(node *,node *,node *,node **,boolean,pointarray,node **,long *);
void findbelow(node **below, node *item, node *fork);
void re_move(node *item, node **fork, node **root, boolean recompute,
pointarray, node **, long *);
void postorder(node *p);
void getnufork(node **, node **, pointarray, long *);
void reroot(node *, node *);
void reroot2(node *, node *);
void reroot3(node *, node *, node *, node *, node **);
void savetraverse(node *);
void newindex(long, node *);
void flipindexes(long, pointarray);
boolean parentinmulti(node *);
long sibsvisited(node *, long *);
long smallest(node *, long *);
void bintomulti(node **, node **, node **, long *);
void backtobinary(node **, node *, node **);
boolean outgrin(node *, node *);
void flipnodes(node *, node *);
void moveleft(node *, node *, node **);
void savetree(node *, long *, pointarray, node **, long *);
void addnsave(node *, node *, node *, node **, node **,boolean,
pointarray, long *, long *);
void addbestever(long *, long *, long, boolean, long *, bestelm *);
void addtiedtree(long, long *, long, boolean,long *, bestelm *);
void clearcollapse(pointarray);
void clearbottom(pointarray);
void collabranch(node *, node *, node *);
boolean allcommonbases(node *, node *, boolean *);
void findbottom(node *, node **);
boolean moresteps(node *, node *);
boolean passdown(node *, node *, node *, node *, node *, node *,
node *, node *, node *, boolean);
boolean trycollapdesc(node *, node *, node *, node *, node *,
node *, node *, node *, node *, boolean , long *);
void setbottom(node *);
boolean zeroinsubtree(node *, node *, node *, node *, node *,
node *, node *, node *, boolean, node *, long *);
boolean collapsible(node *, node *, node *, node *, node *,
node *, node *, node *, boolean, node *, long *, pointarray);
void replaceback(node **, node *, node *, node **, long *);
void putback(node *, node *, node *, node **);
void savelocrearr(node *, node *, node *, node *, node *, node *,
node *, node *, node *, node **, long, long *, boolean,
boolean , boolean *, long *, bestelm *, pointarray ,
node **, long *);
void clearvisited(pointarray);
void hyprint(long, long, struct LOC_hyptrav *,pointarray, Char *);
void gnubase(gbases **, gbases **, long);
void chuckbase(gbases *, gbases **);
void hyptrav(node *, long *, long, long, boolean,pointarray,
gbases **, Char *);
void hypstates(long , node *, pointarray, gbases **, Char *);
void initbranchlen(node *p);
void initmin(node *, long, boolean);
void initbase(node *, long);
void inittreetrav(node *, long);
void compmin(node *, node *);
void minpostorder(node *, pointarray);
void branchlength(node *,node *,double *,pointarray);
void printbranchlengths(node *);
void branchlentrav(node *,node *,long,long,double *,pointarray);
void treelength(node *, long, pointarray);
void coordinates(node *, long *, double, long *);
void drawline(long, double, node *);
void printree(node *, double);
void writesteps(long, boolean, steptr, node *);
void treeout(node *, long, long *, node *);
void treeout3(node *, long, long *, node *);
void fdrawline2(FILE *fp, long i, double scale, tree *curtree);
void drawline2(long, double, tree);
void drawline3(long, double, node *);
void copynode(node *, node *, long);
void prot_copynode(node *, node *, long);
void copy_(tree *, tree *, long, long);
void prot_copy_(tree *, tree *, long, long);
void standev(long, long, long, double, double *, long **, longer);
void standev2(long, long, long, long, double, double *, double **,
steptr, longer);
void freetip(node *);
void freenontip(node *);
void freenodes(long, pointarray);
void freenode(node **);
void freetree(long, pointarray);
void freex(long, pointarray);
void freex_notip(long, pointarray);
void prot_freex_notip(long nonodes, pointarray treenode);
void prot_freex(long nonodes, pointarray treenode);
void freegarbage(gbases **);
void freegrbg(node **);
/* new functions for EMBOSS */
void seq_inputdata(AjPSeqset, long);
void inputdata(long);
void emboss_treeout(node *, AjPOutfile, long);
void emboss_treeout3(node *, AjPOutfile, long, long *, node *);
void collapsetree(node *, node *, node **, pointarray, long *);
void collapsebestrees(node **, node **, pointarray, bestelm *, long *,
long *, long, boolean, boolean);
void fix_x(node* p,long site, double maxx, long rcategs);
void fix_protx(node* p,long site,double maxx, long rcategs);
/*function prototypes*/
#endif
#endif /* SEQ_H */
PHYLIPNEW-3.69.650/include/disc.h 0000664 0001750 0001750 00000005406 10775447511 013024 0000000 0000000
/* version 3.6. (c) Copyright 1993-2000 by the University of Washington.
Written by Joseph Felsenstein, Akiko Fuseki, Sean Lamont, and Andrew Keeffe.
Permission is granted to copy and use this program provided no fee is
charged for it and provided that this copyright notice is not removed. */
/*
disc.h: included in mix, move, penny, dollop, dolmove, dolpenny,
& clique
*/
/* node and pointptr used in Dollop, Dolmove, Dolpenny, Move, & Clique */
typedef node **pointptr;
/* node and pointptr used in Mix & Penny */
typedef struct node2 { /* describes a tip species or an ancestor */
struct node2 *next, *back;
long index;
boolean tip, bottom,visited;/* present species are tips of tree */
bitptr fulstte1, fulstte0; /* see in PROCEDURE fillin */
bitptr empstte1, empstte0; /* see in PROCEDURE fillin */
bitptr fulsteps,empsteps;
long xcoord, ycoord, ymin; /* used by printree */
long ymax;
} node2;
typedef node2 **pointptr2;
typedef struct gbit {
bitptr bits_;
struct gbit *next;
} gbit;
typedef struct htrav_vars {
node *r;
boolean bottom, nonzero;
gbit *zerobelow, *onebelow;
} htrav_vars;
typedef struct htrav_vars2 {
node2 *r;
boolean bottom, maybe, nonzero;
gbit *zerobelow, *onebelow;
} htrav_vars2;
extern long chars, nonodes, nextree, which;
/* nonodes = number of nodes in tree *
* chars = number of binary characters */
extern steptr weight, extras;
extern boolean printdata;
#ifndef OLDC
/*function prototypes*/
void disc_inputdata(AjPPhyloState, pointptr, boolean, boolean, FILE *);
void disc_inputdata2(AjPPhyloState, pointptr2);
void alloctree(pointptr *);
void alloctree2(pointptr2 *);
void setuptree(pointptr);
void setuptree2(pointptr2);
void inputancestors(boolean *, boolean *);
void inputancestorsstr(AjPStr, boolean *, boolean *);
void inputancestorsnew(boolean *, boolean *);
void printancestors(FILE *, boolean *, boolean *);
void add(node *, node *, node *, node **, pointptr);
void add2(node *, node *, node *, node **, boolean, boolean, pointptr);
void add3(node2 *, node2 *, node2 *, node2 **, pointptr2);
void re_move(node **, node **, node **, pointptr);
void re_move2(node **, node **, node **, boolean *, pointptr);
void re_move3(node2 **, node2 **, node2 **, pointptr2);
void coordinates(node *, long *, double , long *);
void coordinates2(node2 *, long *);
void treeout(node *, long, long *, node *);
void treeout2(node2 *, long *, node2 *);
void standev(long, long, double, double *, double **, longer);
void guesstates(Char *);
void freegarbage(gbit **);
void disc_gnu(gbit **, gbit **);
void disc_chuck(gbit *, gbit **);
/*function prototypes*/
#endif
PHYLIPNEW-3.69.650/include/cont.h 0000664 0001750 0001750 00000001230 10052145534 013020 0000000 0000000
/* version 3.6. (c) Copyright 1993-2000 by the University of Washington.
Written by Joseph Felsenstein, Akiko Fuseki, Sean Lamont, and Andrew Keeffe.
Permission is granted to copy and use this program provided no fee is
charged for it and provided that this copyright notice is not removed. */
/*
cont.h: included in contml & contrast
*/
#ifndef OLDC
/*function prototypes*/
void alloctree(pointarray *, long);
void freetree(pointarray *, long);
void setuptree(tree *, long);
void allocview(tree *, long, long);
void freeview(tree *, long);
void standev2(long, long, long, long, double, double *, double **, longer);
/*function prototypes*/
#endif
PHYLIPNEW-3.69.650/include/wagner.h 0000664 0001750 0001750 00000002374 07712247476 013373 0000000 0000000
/* version 3.6. (c) Copyright 1993-2000 by the University of Washington.
Written by Joseph Felsenstein, Akiko Fuseki, Sean Lamont, and Andrew Keeffe.
Permission is granted to copy and use this program provided no fee is
charged for it and provided that this copyright notice is not removed. */
/*
wagner.h: included in move, mix & penny
*/
#ifndef OLDC
/* function prototypes */
void inputmixture(bitptr);
void inputmixturestr(AjPStr, bitptr);
void printmixture(FILE *, bitptr);
void fillin(node2 *,long, boolean, bitptr, bitptr);
void count(long *, bitptr, steptr, steptr);
void postorder(node2 *, long, boolean, bitptr, bitptr);
void cpostorder(node2 *, boolean, bitptr, steptr, steptr);
void filltrav(node2 *, long, boolean, bitptr, bitptr);
void hyprint(struct htrav_vars2 *,boolean,boolean,boolean,bitptr,Char *);
void hyptrav(node2 *, boolean, bitptr, long, boolean, boolean, bitptr,
bitptr, bitptr, pointptr2, Char *, gbit *);
void hypstates(long, boolean, boolean, boolean, node2 *, bitptr, bitptr,
bitptr, pointptr2, Char *, gbit *);
void drawline(long, double, node2 *);
void printree(boolean, boolean, boolean, node2 *);
void writesteps(boolean, steptr);
/* function prototypes */
#endif
PHYLIPNEW-3.69.650/include/dist.h 0000664 0001750 0001750 00000002106 10052145534 013023 0000000 0000000
/* version 3.6. (c) Copyright 1993-2000 by the University of Washington.
Written by Joseph Felsenstein, Akiko Fuseki, Sean Lamont, and Andrew Keeffe.
Permission is granted to copy and use this program provided no fee is
charged for it and provided that this copyright notice is not removed. */
/*
dist.h: included in fitch, kitsch, & neighbor
*/
#define over 60
typedef long *intvector;
typedef node **pointptr;
#ifndef OLDC
/*function prototypes*/
void alloctree(pointptr *, long);
void freetree(pointptr *, long);
void allocd(long, pointptr);
void freed(long, pointptr);
void allocw(long, pointptr);
void freew(long, pointptr);
void setuptree(tree *, long);
void dist_inputdata(AjPPhyloDist,
boolean, boolean, boolean, boolean, vector *, intvector *);
void coordinates(node *, double, long *, double *, node *, boolean);
void drawline(long, double, node *, boolean);
void printree(node *, boolean, boolean, boolean);
void treeoutr(node *, long *, tree *);
void treeout(node *, long *, double, boolean, node *);
/*function prototypes*/
#endif
PHYLIPNEW-3.69.650/include/moves.h 0000664 0001750 0001750 00000001671 10061567662 013231 0000000 0000000
/*
moves.h: included in dnamove, move, dolmove, & retree
*/
typedef enum {
left, downn, upp, right
} adjwindow;
#ifndef OLDC
/* function prototypes */
void inpnum(long *, boolean *);
void prereverse(boolean);
void postreverse(boolean);
void chwrite(Char, long, long *, long, long);
void nnwrite(long, long, long *, long, long);
void stwrite(const char *,long,long *,long,long);
void help(const char *);
void window(adjwindow, long *, long *, long, long, long, long, long,
long, boolean);
void pregraph(boolean);
void pregraph2(boolean);
void postgraph(boolean);
void postgraph2(boolean);
void nextinc(long *, long *, long *, long, long, boolean *, steptr,
steptr);
void nextchar(long *, long *, long *, long, long, boolean *);
void prevchar(long *, long *, long *, long, long, boolean *);
void show(long *, long *, long *, long, long, boolean *);
/* function prototypes */
#endif
PHYLIPNEW-3.69.650/include/macface.h 0000664 0001750 0001750 00000001222 07712247476 013456 0000000 0000000
#ifndef LAMARC_MAC_INTERFACE
#define LAMARC_MAC_INTERFACE
/* version 3.6. (c) Copyright 1997-2000 by the University of Washington.
* mac interfacing
* this is only inlcuded and used for macs/powermacs
* and needs to be used in conjunction with the customized LAMARC-library
* which is a modification of the Metrowerks custom library v10.
* This file defines a function to fix the outputfiles which was written by
* Sean Lamont 1994.
*
* Peter Beerli 1997
* beerli@genetics.washington.edu
*/
#endif /*LAMARC_MAC_INTERFACE*/
#ifndef OLDC
/* function prototypes */
void fixmacfile(char *);
void eventloop(void);
/* function prototypes */
#endif
PHYLIPNEW-3.69.650/include/io.h 0000664 0001750 0001750 00000000142 07712247476 012506 0000000 0000000 #define MAC_OFFSET 60
#include
#include
#include
#define DRAW
PHYLIPNEW-3.69.650/include/interface.h 0000664 0001750 0001750 00000001671 10052145534 014026 0000000 0000000
#ifndef _INTERFACE_H_
#define _INTERFACE_H_
/* interface.h: access to interface.c, a 2 window text/graphics
environment, with a scrolling text window and c-like I/O functions.
This also sets up some defines for the standard c stuff. */
#ifdef OSX_CARBON
#define MAC_OFFSET 60
#endif
/* function prototypes */
void macsetup(char *,char *);
void queryevent();
void eventloop();
void process_window_closure();
int handleevent();
void textmode();
void gfxmode();
void scroll();
int process_char();
void paint_gfx_window();
#ifndef OSX_CARBON
void resize_gfx_window(EventRecord ev);
#endif
void menu_select(long what);
/*debug void fixmacfile(char *);*/
typedef struct {
char* fn;
double* xo;
double* yo;
double* scale;
long nt;
void* root;
} mpreviewparams;
extern mpreviewparams macpreviewparms;
/* function prototypes */
#ifdef __MWERKS__
#define MAC
#endif
#endif
PHYLIPNEW-3.69.650/include/mlclock.h 0000664 0001750 0001750 00000002477 10775447511 013533 0000000 0000000 #include "phylip.h"
/* Uncomment this line to dump details to dnamlk.log */
/* #define DEBUG */
#ifdef DEBUG
extern double dump_likelihood_graph(FILE *fp, node *p, double min, double max, double step);
extern double dump_likelihood_graph_twonode(FILE *fp, node *p1, double npoints);
double dump_likelihood_graph_2d(FILE *fp, node *p1, double npoints);
extern void get_limits(node **nodea, double *min, double *max);
extern double set_tyme_evaluate(node *, double);
#endif /* DEBUG */
typedef double (*evaluator_t)(node *);
extern const double MIN_BRANCH_LENGTH;
extern const double MIN_ROOT_TYME;
/* module initialization */
extern void mlclock_init(tree *t, evaluator_t f);
/* check or fix node tymes and branch lengths */
extern boolean all_tymes_valid(node *, double, boolean);
/* change node tymes */
extern void setnodetymes(node* p, double newtyme);
/* limits of node movement */
extern double min_child_tyme(node *p);
extern double parent_tyme(node *p);
extern boolean valid_tyme(node *p, double tyme);
/* save/restore tymes */
extern void save_tymes(tree* save_tree, double tymes[]);
extern void restore_tymes(tree *load_tree, double tymes[]);
/* optimize a node tyme */
double maximize(double min_tyme, double cur, double max_tyme, double(*f)(double), double eps, boolean *success);
extern boolean makenewv(node *p);
PHYLIPNEW-3.69.650/include/draw.h 0000664 0001750 0001750 00000012166 10775447511 013040 0000000 0000000
#include "phylip.h"
#ifndef X_DISPLAY_MISSING
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#include
#endif
#ifdef MAC
#include "interface.h"
#endif
#include "math.h"
#define DEFAULT_STRIPE_HEIGHT 20
#define minus '-'
#define stripewidth 3000L
#define maxstripedepth 3500
#define fontsize 3800
#define pi 3.1415926535897932384626433
#define ebcdic EBCDIC
#define segments 40
#define xstart 10
#define ystart 35
#define LF 10
#define CR 13
#define escape (ebcdic ? '\'' : '\033')
#define null '\000'
#define AFMDIR "/usr/lib/transcript/" /* note trailing slash */
typedef unsigned char byte;
/*typedef char byte; */
typedef enum {treepen, labelpen} pentype;
typedef enum {lw,hp,tek,ibm,mac,houston,decregis,epson,oki,fig,
citoh,toshiba,pcx,pcl,pict,ray,pov,xpreview,xbm,bmp,
gif,idraw,vrml,winpreview,other} plottertype;
typedef enum {vertical, horizontal} growth;
typedef enum {cladogram,phenogram,curvogram,
eurogram,swoopogram,circular} treestyle;
typedef enum {penup,pendown} pensttstype;
typedef enum {plotnow, changeparms, quitnow} winactiontype;
typedef short fonttype[fontsize];
typedef Char *striparray;
typedef striparray striptype[maxstripedepth];
struct LOC_plottext { /* Local variables for plottext: */
double height, compress;
short *font;
short coord;
double heightfont, xfactor, yfactor, xfont, yfont, xplot, yplot, sinslope,
cosslope, xx, yy;
pensttstype penstatus;
} ;
typedef struct colortype {
const char *name;
double red, green, blue;
} colortype;
typedef struct vrmllighttype {
double intensity, x, y, z;
} vrmllighttype;
double lengthtext(char *, long, char *, fonttype);
double heighttext(fonttype, char *);
void plotrparms(long ntips);
void clearit(void);
void getplotter(char);
void getpreview(void);
const char *figfontname(int id);
boolean isfigfont(char *);
void plot(pensttstype, double, double);
void curvespline(double, double, double, double, boolean, long);
void swoopspline(double x1, double y1, double x2, double y2, double x3,
double y3, boolean sense, long segs);
void changepen(pentype pen);
void plottext(Char *pstring,long nchars,double height_,double cmpress2,
double x,double y,double slope,short *font_,char *fontname);
void loadfont(short *font, char *application);
long allocstripe(striptype stripe, long x, long y);
boolean plotpreview(char *, double *, double *, double *, long , node *);
void initplotter(long ntips, char *fontname);
void drawit(char *fontname, double *xoffset, double *yoffset,
long numlines, node *root);
void finishplotter(void);
void write_bmp_header(FILE *, int, int);
void turn_rows(byte *, int, int);
void write_full_pic(byte *, int);
void translate_stripe_to_bmp(striptype *stripe, byte *full_pic,
int increment, int width, int div, int *total_bytes);
void plottree(node *, node *);
void plotlabels(char *fontname);
void pout(long);
double computeAngle(double oldx, double oldy, double newx, double newy);
boolean plot_without_preview(char *, double *, double *, double *, long,
node *);
/* For povray, added by Dan F. */
#define TREE_TEXTURE "T_Tree\0"
#define NAME_TEXTURE "T_Name\0"
#ifndef X_DISPLAY_MISSING
Display *display; /* the X display */
extern Window mainwin; /* the main display window */
int x, y; /* the corner of the window */
unsigned int width, height; /* the width and height of the window */
#define FONT "-*-new century schoolbook-medium-r-*-*-14-*"
char *fontrsc; /* the font resource */
XFontStruct *fontst; /* the font strcture for the font */
XGCValues gcv; /* graphics context values */
GC gc1; /* a graphics context */
XtAppContext appcontext;
Widget toplevel;
int nargc;
char** nargv;
extern String res[16];
#define DEFGEOMETRY "600x400+20+50"
#endif
#define LARGE_BUF_LENGTH 500
extern char fontname[LARGE_BUF_LENGTH]; /* the font name to use */
#ifdef WIN32
#define DEFPLOTTER lw
#define DEFPREV winpreview
#endif
#ifdef DOS
#define DEFPLOTTER lw
#define DEFPREV ibm
#endif
#ifdef MAC
#ifdef OSX_CARBON
#define DEFPLOTTER lw
#define DEFPREV mac
#else
#define DEFPLOTTER pict
#define DEFPREV mac
#endif
#endif
#ifdef VMS
#define DEFPLOTTER lw
#define DEFPREV decregis
#endif
#ifndef DOS
#ifndef MAC
#ifndef VMS
#ifndef WIN32
#define DEFPLOTTER lw
#ifndef X_DISPLAY_MISSING
#define DEFPREV xpreview
#endif
#ifdef X_DISPLAY_MISSING
#define DEFPREV tek
#endif
#endif
#endif
#endif
#endif
/* Define SEEK_SET (needed for fseek()) for machines that haven't
got it already, */
#ifndef SEEK_SET
#define SEEK_SET 0
#endif
PHYLIPNEW-3.69.650/include/phylip.h 0000664 0001750 0001750 00000062443 11774775165 013424 0000000 0000000 #ifndef _PHYLIP_H_
#define _PHYLIP_H_
/* version 3.6b. (c) Copyright 1993-2004 by the University of Washington.
Written by Joseph Felsenstein, Akiko Fuseki, Sean Lamont, Andrew Keeffe,
Mike Palczewski, Doug Buxton and Dan Fineman.
Permission is granted to copy and use this program provided no fee is
charged for it and provided that this copyright notice is not removed. */
/* now done via config.h */
/*#define VERSION "3.69"*/
/* Debugging options */
/* Define this to disable assertions ...
but this leads to 'unused variable' warnings */
/*#define NDEBUG*/
/* Define this to enable debugging code */
/* #define DEBUG */
/* machine-specific stuff:
based on a number of factors in the library stdlib.h, we will try
to determine what kind of machine/compiler this program is being
built on. However, it doesn't always succeed. However, if you have
ANSI conforming C, it will probably work.
We will try to figure out machine type
based on defines in stdio, and compiler-defined things as well.: */
#include
#include
#include "emboss.h"
typedef struct EmbossSTreeNode {
AjPStr Name;
} EmbossOTreeNode;
#define EmbossPTreeNode EmbossOTreeNode*
#ifndef X_DISPLAY_MISSING /* X11 is available */
#define X
#endif
#ifdef WIN32
#include
void phyClearScreen(void);
void phySaveConsoleAttributes(void);
void phySetConsoleAttributes(void);
void phyRestoreConsoleAttributes(void);
void phyFillScreenColor(void);
#endif
#ifdef GNUDOS
#define DJGPP
#define DOS
#endif
#ifdef THINK_C
#define MAC
#endif
#ifdef __MWERKS__
#ifndef WIN32
#define MAC
#endif
#endif
/*
** To keep ACD clean let's exclude the CMS (VMS code management system?)
** definitions here
*/
#define EBCDIC false
/*
** these definitions are used in openfile calls
** and match the expected ACD qualifiers for each in/out file type
** They are changed to match ACD standards by appending "file"
** but the shorter phylip names will also work
*/
#define INFILE "infile"
#define OUTFILE "outfile"
#define FONTFILE "fontfile" /* on unix this might be /usr/local/lib/fontfile */
#define PLOTFILE "plotfile"
#define INTREE "intreefile"
#define INTREE2 "bintreefile" /* treedist only */
#define OUTTREE "outtreefile"
#define CATFILE "categoriesfile"
#define WEIGHTFILE "weightsfile"
#define ANCFILE "ancestorsfile"
#define MIXFILE "mixturefile"
#define FACTFILE "factorsfile"
#ifdef L_ctermid /* try and detect for sysV or V7. */
#define SYSTEM_FIVE
#endif
#ifdef sequent
#define SYSTEM_FIVE
#endif
#ifndef SYSTEM_FIVE
#include
# if defined(_STDLIB_H_) || defined(_H_STDLIB) || defined(H_SCCSID) || defined(unix)
# define UNIX
# define MACHINE_TYPE "BSD Unix C"
# endif
#endif
#ifdef __STDIO_LOADED
#define VMS
#define MACHINE_TYPE "VAX/VMS C"
#endif
#ifdef __WATCOMC__
#define QUICKC
#define WATCOM
#define DOS
#include "graph.h"
#endif
/* watcom-c has graphics library calls that are almost identical to *
* quick-c, so the "QUICKC" symbol name stays. */
#ifdef _QC
#define MACHINE_TYPE "MS-DOS / Quick C"
#define QUICKC
#include "graph.h"
#define DOS
#endif
#ifdef _DOS_MODE
#define MACHINE_TYPE "MS-DOS /Microsoft C "
#define DOS /* DOS is always defined if on a DOS machine */
#define MSC /* MSC is defined for microsoft C */
#endif
#ifdef __MSDOS__ /* TURBO c compiler, ONLY (no other DOS C compilers) */
#define DOS
#define TURBOC
#include
#include
#endif
#ifdef DJGPP /* DJ Delorie's original gnu C/C++ port */
#include
#endif
#ifndef MACHINE_TYPE
#define MACHINE_TYPE "ANSI C"
#endif
#ifdef DOS
#define MALLOCRETURN void
#else
#define MALLOCRETURN void
#endif
#ifdef VMS
#define signed /* signed doesn't exist in VMS */
#endif
/* default screen types */
/* if on a DOS but not a Windows system can use IBM PC screen controls */
#ifdef DOS
#ifndef WIN32
#define IBMCRT true
#define ANSICRT false
#endif
#endif
/* if on a Mac cannot use screen controls */
#ifdef MAC
#define IBMCRT false
#define ANSICRT false
#endif
/* if on a Windows system cannot use screen controls */
#ifdef WIN32
#define IBMCRT true
#define ANSICRT false
#endif
/* otherwise, let's assume we are on a Linux or Unix system
with no ANSI terminal controls */
#ifndef MAC
#ifndef DOS
#ifndef WIN32
#define IBMCRT false
#define ANSICRT false
#endif
#endif
#endif
#ifdef DJGPP
#undef MALLOCRETURN
#define MALLOCRETURN void
#endif
/* includes: */
#ifdef UNIX
#include
#else
#include
#endif
#include
#include
#include
#ifdef MAC
#ifdef DRAW
#include "interface.h"
#else
#include "macface.h"
#endif
#define getch gettch
#endif
/* directory delimiters */
#ifdef MAC
#define DELIMITER ':'
#else
#ifdef WIN32
#define DELIMITER '\\'
#else
#define DELIMITER '/'
#endif
#endif
#define FClose(file) if (file) fclose(file) ; file=NULL
#define Malloc(x) mymalloc((long)x)
typedef void *Anyptr;
#define Signed signed
#define Const const
#define Volatile volatile
#define Char char /* Characters (not bytes) */
#define Static static /* Private global funcs and vars */
#define Local static /* Nested functions */
typedef unsigned char boolean;
#define true 1
#define false 0
/* Number of items per machine word in set.
* Used in consensus programs and clique */
#define SETBITS 31
MALLOCRETURN *mymalloc(long);
/*** UI behavior ***/
/* Set to 1 to not ask before overwriting files */
#define OVERWRITE_FILES 0
/*** Static memory parameters ***/
#define FNMLNGTH 200 /* length of array to store a file name */
#define MAXNCH 20 /* must be greater than or equal to nmlngth */
#define nmlngth 10 /* number of characters in species name */
#define maxcategs 9 /* maximum number of site types */
#define maxcategs2 11 /* maximum number of site types + 2 */
#define point "."
#define pointe '.'
#define down 2
#define MAXSHIMOTREES 100
/*** Maximum likelihood parameters ***/
/* Used in proml, promlk, dnaml, dnamlk, etc. */
#define UNDEFINED 1.0 /* undefined or invalid likelihood */
#define smoothings 4 /* number of passes through smoothing algorithm */
#define iterations 8 /* number of iterates for each branch */
#define epsilon 0.0001 /* small number used in makenewv */
#define EPSILON 0.00001 /* small number used in hermite root-finding */
#define initialv 0.1 /* starting branch length unless otherwise */
#define INSERT_MIN_TYME 0.0001 /* Minimum tyme between nodes during inserts */
#define over 60 /* maximum width all branches of tree on screen */
#define LIKE_EPSILON 1e-10 /* Estimate of round-off error in likelihood
* calculations. */
/*** Math constants ***/
#define SQRTPI 1.7724538509055160273
#define SQRT2 1.4142135623730950488
/*** Rearrangement parameters ***/
#define NLRSAVES 5 /* number of views that need to be saved during local *
* rearrangement */
/*** Output options ***/
/* Number of significant figures to display in numeric output */
#define PRECISION 6
/* Maximum line length of matrix output - 0 for unlimited */
#define OUTPUT_TEXTWIDTH 78
/** output_matrix() flags **/
/* Block output: Matrices are vertically split into blocks that
* fit within OUTPUT_TEXTWIDTH columns */
#define MAT_BLOCK 0x1
/* Lower triangle: Values on or above the diagonal are not printed */
#define MAT_LOWER 0x2
/* Print a border between headings and data */
#define MAT_BORDER 0x4
/* Do not print the column header */
#define MAT_NOHEAD 0x8
/* Output the number of columns before the matrix */
#define MAT_PCOLS 0x10
/* Do not enforce maximum line width */
#define MAT_NOBREAK 0x20
/* Pad row header with spaces to 10 char */
#define MAT_PADHEAD 0x40
/* Human-readable format. */
#define MAT_HUMAN MAT_BLOCK
/* Machine-readable format. */
#define MAT_MACHINE (MAT_PCOLS | MAT_NOHEAD | MAT_PADHEAD)
/* Lower-triangular format. */
#define MAT_LOWERTRI (MAT_LOWER | MAT_MACHINE)
typedef long *steptr;
typedef long longer[6];
typedef char naym[MAXNCH];
typedef long *bitptr;
typedef double raterootarray[maxcategs2][maxcategs2];
typedef struct bestelm {
long *btree;
boolean gloreange;
boolean locreange;
boolean collapse;
} bestelm;
extern FILE *infile, *outfile, *intree, *intree2, *outtree,
*weightfile, *catfile, *ancfile, *mixfile, *factfile;
extern AjPFile embossinfile;
extern AjPFile embossoutfile;
extern AjPFile embossintre;
extern AjPFile embossintree2;
extern AjPFile embossouttree;
extern AjPFile embossweightfile;
extern AjPFile embosscatfile;
extern AjPFile embossancfile;
extern AjPFile embossmixfile;
extern AjPFile embossfactfile;
extern long spp, words, bits;
extern boolean ibmpc, ansi, tranvsp;
extern naym *nayme; /* names of species */
#define ebcdic EBCDIC
typedef Char plotstring[MAXNCH];
/* Approx. 1GB, used to test for memory request errors */
#define TOO_MUCH_MEMORY 1000000000
/* The below pre-processor commands define the type used to store
group arrays. We can't use #elif for metrowerks, so we use
cascaded if statements */
#include
/* minimum double we feel safe with, anything less will be considered
underflow */
#define MIN_DOUBLE 10e-100
/* K&R says that there should be a plus in front of the number, but no
machine we've seen actually uses one; we'll include it just in
case. */
#define MAX_32BITS 2147483647
#define MAX_32BITS_PLUS +2147483647
/* If ints are 4 bytes, use them */
#if INT_MAX == MAX_32BITS
typedef int group_type;
#else
#if INT_MAX == MAX_32BITS_PLUS
typedef int group_type;
#else
/* Else, if longs are 4 bytes, use them */
#if LONG_MAX == MAX_32BITS
typedef long group_type;
#else
#if LONG_MAX == MAX_32BITS_PLUS
typedef long group_type;
/* Default to longs */
#else
typedef long group_type;
#endif
#endif
#endif
#endif
#define maxuser 1000 /* maximum number of user-defined trees */
typedef Char **sequence;
typedef enum {
A, C, G, T, O
} bases;
typedef enum {
alanine, arginine, asparagine, aspartic, cysteine,
glutamine, glutamic, glycine, histidine, isoleucine,
leucine, lysine, methionine, phenylalanine, proline,
serine, threonine, tryptophan, tyrosine, valine
} acids;
/* for Pars */
typedef enum {
zero = 0, one, two, three, four, five, six, seven
} discbases;
/* for Protpars */
typedef enum {
ala, arg, asn, asp, cys, gln, glu, gly, his, ileu, leu, lys, met, phe, pro,
ser1, ser2, thr, trp, tyr, val, del, stop, asx, glx, ser, unk, quest
} aas;
typedef double sitelike[(long)T - (long)A + 1]; /* used in dnaml, dnadist */
typedef double psitelike[(long)valine - (long)alanine + 1];
/* used in proml */
typedef long *baseptr; /* baseptr used in dnapars, dnacomp & dnapenny */
typedef long *baseptr2; /* baseptr used in dnamove */
typedef unsigned char *discbaseptr; /* discbaseptr used in pars */
typedef sitelike *ratelike; /* used in dnaml ... */
typedef psitelike *pratelike; /* used in proml */
typedef ratelike *phenotype; /* phenotype used in dnaml, dnamlk, dnadist */
typedef pratelike *pphenotype; /* phenotype used in proml */
typedef double *sitelike2;
typedef sitelike2 *phenotype2; /* phenotype2 used in restml */
typedef double *phenotype3; /* for continuous char programs */
typedef double *vector; /* used in distance programs */
typedef long nucarray[(long)O - (long)A + 1];
typedef long discnucarray[(long)seven - (long)zero + 1];
typedef enum { nocollap, tocollap, undefined } collapstates;
typedef enum { bottom, nonbottom, hslength, tip, iter, length,
hsnolength, treewt, unittrwt } initops;
typedef double **transmatrix;
typedef transmatrix *transptr; /* transptr used in restml */
typedef long sitearray[3];
typedef sitearray *seqptr; /* seqptr used in protpars */
typedef struct node {
struct node *next, *back;
plotstring nayme;
long naymlength, tipsabove, index;
double times_in_tree; /* Previously known as cons_index */
double xcoord, ycoord;
long long_xcoord, long_ycoord; /* for use in cons. */
double oldlen, length, r, theta, oldtheta, width, depth,
tipdist, lefttheta, righttheta;
group_type *nodeset; /* used by accumulate -plc */
long ymin, ymax; /* used by printree -plc */
boolean haslength; /* haslength used in dnamlk */
boolean iter; /* iter used in dnaml, fitch & restml */
boolean initialized; /* initialized used in dnamlk & restml */
long branchnum; /* branchnum used in restml */
phenotype x; /* x used in dnaml, dnamlk, dnadist */
phenotype2 x2; /* x2 used in restml */
phenotype3 view; /* contml etc */
pphenotype protx; /* protx used in proml */
aas *seq; /* the sequence used in protpars */
seqptr siteset; /* temporary storage for aa's used in protpars*/
double v, deltav, ssq; /* ssq used only in contrast */
double bigv; /* bigv used in contml */
double tyme, oldtyme; /* used in dnamlk */
double t; /* time in kitsch */
boolean sametime; /* bookkeeps scrunched nodes in kitsch */
double weight; /* weight of node used by scrunch in kitsch */
boolean processed; /* used by evaluate in kitsch */
boolean deleted; /* true if node is deleted (retree) */
boolean hasname; /* true if tip has a name (retree) */
double beyond; /* distance beyond this node to most distant tip */
/* (retree) */
boolean deadend; /* true if no undeleted nodes beyond this node */
/* (retree) */
boolean onebranch; /* true if there is one undeleted node beyond */
/* this node (retree) */
struct node *onebranchnode;
/* if there is, a pointer to that node (retree)*/
double onebranchlength; /* if there is, the distance from here to there*/
/* (retree) */
boolean onebranchhaslength; /* true if there is a valid combined length*/
/* from here to there (retree) */
collapstates collapse; /* used in dnapars & dnacomp */
boolean tip;
boolean bottom; /* used in dnapars & dnacomp, disc char */
boolean visited; /* used in dnapars & dnacomp disc char */
baseptr base; /* the sequence in dnapars/comp/penny */
discbaseptr discbase; /* the sequence in pars */
baseptr2 base2; /* the sequence in dnamove */
baseptr oldbase; /* record previous sequence */
discbaseptr olddiscbase; /* record previous sequence */
long numdesc; /* number of immediate descendants */
nucarray *numnuc; /* bookkeeps number of nucleotides */
discnucarray *discnumnuc; /* bookkeeps number of nucleotides */
steptr numsteps; /* bookkeeps steps */
steptr oldnumsteps; /* record previous steps */
double sumsteps; /* bookkeeps sum of steps */
nucarray cumlengths; /* bookkeeps cummulative minimum lengths */
discnucarray disccumlengths; /* bookkeeps cummulative minimum lengths */
nucarray numreconst; /* bookkeeps number of reconstructions */
discnucarray discnumreconst; /* bookkeeps number of reconstructions */
vector d, w; /* for distance matrix programs */
double dist; /* dist used in fitch */
bitptr stateone, statezero; /* discrete char programs */
long maxpos; /* maxpos used in Clique */
Char state; /* state used in Dnamove, Dolmove & Move */
double* underflows; /* used to record underflow */
} node;
typedef node **pointarray;
/*** tree structure ***/
typedef struct tree {
/* An array of pointers to nodes. Each tip node and ring of nodes has a
* unique index starting from one. The nodep array contains pointers to each
* one, starting from 0. In the case of internal nodes, the entries in nodep
* point to the rootward node in the group. Since the trees are otherwise
* entirely symmetrical, except at the root, this is the only way to resolve
* parent, child, and sibling relationships.
*
* Indices in range [0, spp) point to tips, while indices [spp, nonodes)
* point to fork nodes
*/
pointarray nodep;
/* A pointer to the first node. Typically, root is used when the tree is rooted,
* and points to an internal node with no back link. */
node *root;
/* start is used when trees are unrooted. It points to an internal node whose
* back link typically points to the outgroup leaf. */
node *start;
/* In maximum likelihood programs, the most recent evaluation is stored here */
double likelihood;
/* Branch transition matrices for restml */
transptr trans; /* all transition matrices */
long *freetrans; /* an array of indexes of free matrices */
long transindex; /* index of last valid entry in freetrans[] */
} tree;
typedef void (*initptr)(node **, node **, node *, long, long,
long *, long *, initops, pointarray,
pointarray, Char *, Char *, char **);
#ifndef OLDC
/* function prototypes */
int filexists(char *);
const char* get_command_name (const char *);
void EOF_error(void);
void getstryng(char *);
/*void openfile(FILE **,const char *,const char *,const char *,const char *,
const char **);*/
void cleerhome(void);
void loopcount(long *, long);
double randum(longer);
void randumize(longer, long *);
double normrand(longer);
void uppercase(Char *);
/*void initseed(long *, long *, longer);*/
/*void initjumble(long *, long *, longer, long *);*/
/*void initoutgroup(long *, long);*/
/*void initthreshold(double *);*/
/*void initcatn(long *);*/
/*void initcategs(long, double *);*/
/*void initprobcat(long, double *, double *);*/
double logfac (long);
double halfroot(double (*func)(long , double), long, double, double);
double hermite(long, double);
void initlaguerrecat(long, double, double *, double *);
void root_hermite(long, double *);
void hermite_weight(long, double *, double *);
void inithermitcat(long, double, double *, double *);
void lgr(long, double, raterootarray);
double glaguerre(long, double, double);
void initgammacat(long, double, double *, double *);
void inithowmany(long *, long);
void inithowoften(long *);
void initlambda(double *);
void initfreqs(double *, double *, double *, double *);
void initratio(double *);
void initpower(double *);
void initdatasets(long *);
void justweights(long *);
void initterminal(boolean *, boolean *);
void initnumlines(long *);
void initbestrees(bestelm *, long, boolean);
void newline(FILE *, long, long, long);
void inputnumbers(long *, long *, long *, long);
void inputnumbersold(long *, long *, long *, long);
void inputnumbers2(long *, long *, long n);
void inputnumbers3(long *, long *);
void samenumsp(long *, long);
void samenumsp2(long);
void readoptions(long *, const char *);
void matchoptions(Char *, const char *);
void inputweightsstr(AjPStr, long, steptr, boolean *);
void inputweightsstrold(AjPStr, long, steptr, boolean *);
void inputweightsstr2(AjPStr, long, long,
long *, steptr, boolean *, const char *);
void printweights(FILE *, long, long, steptr, const char *);
void inputcategsstr(AjPStr, long, long, steptr, long, const char *);
void printcategs(FILE *, long, steptr, const char *);
void inputfactors(long, Char *, boolean *);
void inputfactorsstr(AjPStr, long, Char *, boolean *);
void printfactors(FILE *, long, Char *, const char *);
void headings(long, const char *, const char *);
void initname(long);
void findtree(boolean *,long *,long,long *,bestelm *);
void addtree(long,long *,boolean,long *,bestelm *);
long findunrearranged(bestelm *, long, boolean);
boolean torearrange(bestelm *, long);
void reducebestrees(bestelm *, long *);
void shellsort(double *, long *, long);
void findch(Char, Char *, long);
void findch2(Char, long *, long *, Char *);
void findch3(Char, Char *, long, long);
void processlength(double *,double *,Char *,boolean *,char **,long *);
void writename(long, long, long *);
void memerror(void);
void odd_malloc(long);
void gnu(node **, node **);
void chuck(node **, node *);
void zeronumnuc(node *, long);
void zerodiscnumnuc(node *, long);
void allocnontip(node *, long *, long);
void allocdiscnontip(node *, long *, unsigned char *, long );
void allocnode(node **, long *, long);
void allocdiscnode(node **, long *, unsigned char *, long );
void gnutreenode(node **, node **, long, long, long *);
void gnudisctreenode(node **, node **, long , long, long *,
unsigned char *);
void setupnode(node *, long);
node * pnode(tree *t, node *p);
long count_sibs (node *);
void inittrav (node *);
void commentskipper(char **, long *);
long countcomma(char *, long *);
void hookup(node *, node *);
void unhookup(node *, node *);
void link_trees(long, long , long, pointarray);
void allocate_nodep(pointarray *, char *, long *);
void malloc_pheno(node *, long, long);
void malloc_ppheno(node *, long, long);
long take_name_from_tree (Char *, Char *, char **);
void match_names_to_data (Char *, pointarray, node **, long);
void addelement(node **, node *, Char *, long *, char **, pointarray,
boolean *, boolean *, pointarray, long *, long *, boolean *,
node **, initptr,boolean,long);
void treeread (char **, node **, pointarray, boolean *, boolean *,
pointarray, long *, boolean *, node **, initptr,boolean,long);
void addelement2(node *, Char *, long *, char **, pointarray, boolean,
double *, boolean *, long *, long *, long, boolean *,boolean,
long);
void treeread2 (char **, node **, pointarray, boolean, double *,
boolean *, boolean *, long *,boolean,long);
void exxit (int);
void countup(long *loopcount, long maxcount);
char gettc(FILE* file);
void unroot_r(node* p,node ** nodep, long nonodes);
void unroot(tree* t,long nonodes);
void unroot_here(node* root, node** nodep, long nonodes);
void clear_connections(tree *t, long nonodes);
void init(int argc, char** argv);
char **stringnames_new(void);
void stringnames_delete(char **names);
int fieldwidth_double(double val, unsigned int precision);
void output_matrix_d(FILE *fp, double **matrix,
unsigned long rows, unsigned long cols,
char **row_head, char **col_head, int flags);
void debugtree (tree *, FILE *);
void debugtree2 (pointarray, long, FILE *);
/* new functions for EMBOSS */
void inputnumbersseq(AjPSeqset seqset,
long *spp, long *chars, long *nonodes, long n);
void inputnumbersseq2(AjPSeqset seqset,
long *, long *, long n);
void inputnumbersfreq(AjPPhyloFreq, long *, long *, long *, long);
void inputnumbersstate(AjPPhyloState, long *, long *, long *, long);
void inputnumbers2seq(AjPPhyloDist, long *, long *, long n);
void samenumspfreq(AjPPhyloFreq, long *, long);
void samenumspstate(AjPPhyloState, long *, long);
void samenumspseq(AjPSeqset, long *, long);
void samenumspseq2(AjPPhyloDist, long);
void initnameseq(AjPSeqset, long);
void initnamedist(AjPPhyloDist, long);
void initnamestate(AjPPhyloState, long);
void initnamefreq(AjPPhyloFreq, long);
void emboss_initcatn(long *categs);
void emboss_initcategs(AjPFloat arrayvals, long categs, double *rate);
void sgetch(Char *, long *, char **);
void getch(Char *, long *, FILE *);
void getch2(Char *, long *);
void emboss_openfile(AjPFile outfile, FILE **fp, const char **perm);
void emboss_initseed(long inseed, long *inseed0, longer seed);
void emboss_initoutgroup(long *outgrno, long spp);
void emboss_initcatn(long *categs);
void emboss_initcategs(AjPFloat arrayvals, long categs, double *rate);
double emboss_initprobcat(AjPFloat arrayvals, long categs, double *probcat);
void emboss_printtree(node *p, char* title);
#endif /* OLDC */
#endif /* _PHYLIP_H_ */
PHYLIPNEW-3.69.650/include/printree.h 0000664 0001750 0001750 00000000226 10775447511 013725 0000000 0000000 #include
#include "phylip.h"
extern void mlk_printree(FILE *fp, tree *t);
extern void mlk_describe(FILE *fp, tree *t, double fracchange);
PHYLIPNEW-3.69.650/depcomp 0000755 0001750 0001750 00000050552 12171071677 011661 0000000 0000000 #! /bin/sh
# depcomp - compile a program generating dependencies as side-effects
scriptversion=2012-03-27.16; # UTC
# Copyright (C) 1999-2012 Free Software Foundation, Inc.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2, or (at your option)
# any later version.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
# As a special exception to the GNU General Public License, if you
# distribute this file as part of a program that contains a
# configuration script generated by Autoconf, you may include it under
# the same distribution terms that you use for the rest of that program.
# Originally written by Alexandre Oliva .
case $1 in
'')
echo "$0: No command. Try '$0 --help' for more information." 1>&2
exit 1;
;;
-h | --h*)
cat <<\EOF
Usage: depcomp [--help] [--version] PROGRAM [ARGS]
Run PROGRAMS ARGS to compile a file, generating dependencies
as side-effects.
Environment variables:
depmode Dependency tracking mode.
source Source file read by 'PROGRAMS ARGS'.
object Object file output by 'PROGRAMS ARGS'.
DEPDIR directory where to store dependencies.
depfile Dependency file to output.
tmpdepfile Temporary file to use when outputting dependencies.
libtool Whether libtool is used (yes/no).
Report bugs to .
EOF
exit $?
;;
-v | --v*)
echo "depcomp $scriptversion"
exit $?
;;
esac
# A tabulation character.
tab=' '
# A newline character.
nl='
'
if test -z "$depmode" || test -z "$source" || test -z "$object"; then
echo "depcomp: Variables source, object and depmode must be set" 1>&2
exit 1
fi
# Dependencies for sub/bar.o or sub/bar.obj go into sub/.deps/bar.Po.
depfile=${depfile-`echo "$object" |
sed 's|[^\\/]*$|'${DEPDIR-.deps}'/&|;s|\.\([^.]*\)$|.P\1|;s|Pobj$|Po|'`}
tmpdepfile=${tmpdepfile-`echo "$depfile" | sed 's/\.\([^.]*\)$/.T\1/'`}
rm -f "$tmpdepfile"
# Some modes work just like other modes, but use different flags. We
# parameterize here, but still list the modes in the big case below,
# to make depend.m4 easier to write. Note that we *cannot* use a case
# here, because this file can only contain one case statement.
if test "$depmode" = hp; then
# HP compiler uses -M and no extra arg.
gccflag=-M
depmode=gcc
fi
if test "$depmode" = dashXmstdout; then
# This is just like dashmstdout with a different argument.
dashmflag=-xM
depmode=dashmstdout
fi
cygpath_u="cygpath -u -f -"
if test "$depmode" = msvcmsys; then
# This is just like msvisualcpp but w/o cygpath translation.
# Just convert the backslash-escaped backslashes to single forward
# slashes to satisfy depend.m4
cygpath_u='sed s,\\\\,/,g'
depmode=msvisualcpp
fi
if test "$depmode" = msvc7msys; then
# This is just like msvc7 but w/o cygpath translation.
# Just convert the backslash-escaped backslashes to single forward
# slashes to satisfy depend.m4
cygpath_u='sed s,\\\\,/,g'
depmode=msvc7
fi
if test "$depmode" = xlc; then
# IBM C/C++ Compilers xlc/xlC can output gcc-like dependency informations.
gccflag=-qmakedep=gcc,-MF
depmode=gcc
fi
case "$depmode" in
gcc3)
## gcc 3 implements dependency tracking that does exactly what
## we want. Yay! Note: for some reason libtool 1.4 doesn't like
## it if -MD -MP comes after the -MF stuff. Hmm.
## Unfortunately, FreeBSD c89 acceptance of flags depends upon
## the command line argument order; so add the flags where they
## appear in depend2.am. Note that the slowdown incurred here
## affects only configure: in makefiles, %FASTDEP% shortcuts this.
for arg
do
case $arg in
-c) set fnord "$@" -MT "$object" -MD -MP -MF "$tmpdepfile" "$arg" ;;
*) set fnord "$@" "$arg" ;;
esac
shift # fnord
shift # $arg
done
"$@"
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
mv "$tmpdepfile" "$depfile"
;;
gcc)
## There are various ways to get dependency output from gcc. Here's
## why we pick this rather obscure method:
## - Don't want to use -MD because we'd like the dependencies to end
## up in a subdir. Having to rename by hand is ugly.
## (We might end up doing this anyway to support other compilers.)
## - The DEPENDENCIES_OUTPUT environment variable makes gcc act like
## -MM, not -M (despite what the docs say).
## - Using -M directly means running the compiler twice (even worse
## than renaming).
if test -z "$gccflag"; then
gccflag=-MD,
fi
"$@" -Wp,"$gccflag$tmpdepfile"
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
rm -f "$depfile"
echo "$object : \\" > "$depfile"
alpha=ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz
## The second -e expression handles DOS-style file names with drive letters.
sed -e 's/^[^:]*: / /' \
-e 's/^['$alpha']:\/[^:]*: / /' < "$tmpdepfile" >> "$depfile"
## This next piece of magic avoids the "deleted header file" problem.
## The problem is that when a header file which appears in a .P file
## is deleted, the dependency causes make to die (because there is
## typically no way to rebuild the header). We avoid this by adding
## dummy dependencies for each header file. Too bad gcc doesn't do
## this for us directly.
tr ' ' "$nl" < "$tmpdepfile" |
## Some versions of gcc put a space before the ':'. On the theory
## that the space means something, we add a space to the output as
## well. hp depmode also adds that space, but also prefixes the VPATH
## to the object. Take care to not repeat it in the output.
## Some versions of the HPUX 10.20 sed can't process this invocation
## correctly. Breaking it into two sed invocations is a workaround.
sed -e 's/^\\$//' -e '/^$/d' -e "s|.*$object$||" -e '/:$/d' \
| sed -e 's/$/ :/' >> "$depfile"
rm -f "$tmpdepfile"
;;
hp)
# This case exists only to let depend.m4 do its work. It works by
# looking at the text of this script. This case will never be run,
# since it is checked for above.
exit 1
;;
sgi)
if test "$libtool" = yes; then
"$@" "-Wp,-MDupdate,$tmpdepfile"
else
"$@" -MDupdate "$tmpdepfile"
fi
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
rm -f "$depfile"
if test -f "$tmpdepfile"; then # yes, the sourcefile depend on other files
echo "$object : \\" > "$depfile"
# Clip off the initial element (the dependent). Don't try to be
# clever and replace this with sed code, as IRIX sed won't handle
# lines with more than a fixed number of characters (4096 in
# IRIX 6.2 sed, 8192 in IRIX 6.5). We also remove comment lines;
# the IRIX cc adds comments like '#:fec' to the end of the
# dependency line.
tr ' ' "$nl" < "$tmpdepfile" \
| sed -e 's/^.*\.o://' -e 's/#.*$//' -e '/^$/ d' | \
tr "$nl" ' ' >> "$depfile"
echo >> "$depfile"
# The second pass generates a dummy entry for each header file.
tr ' ' "$nl" < "$tmpdepfile" \
| sed -e 's/^.*\.o://' -e 's/#.*$//' -e '/^$/ d' -e 's/$/:/' \
>> "$depfile"
else
# The sourcefile does not contain any dependencies, so just
# store a dummy comment line, to avoid errors with the Makefile
# "include basename.Plo" scheme.
echo "#dummy" > "$depfile"
fi
rm -f "$tmpdepfile"
;;
xlc)
# This case exists only to let depend.m4 do its work. It works by
# looking at the text of this script. This case will never be run,
# since it is checked for above.
exit 1
;;
aix)
# The C for AIX Compiler uses -M and outputs the dependencies
# in a .u file. In older versions, this file always lives in the
# current directory. Also, the AIX compiler puts '$object:' at the
# start of each line; $object doesn't have directory information.
# Version 6 uses the directory in both cases.
dir=`echo "$object" | sed -e 's|/[^/]*$|/|'`
test "x$dir" = "x$object" && dir=
base=`echo "$object" | sed -e 's|^.*/||' -e 's/\.o$//' -e 's/\.lo$//'`
if test "$libtool" = yes; then
tmpdepfile1=$dir$base.u
tmpdepfile2=$base.u
tmpdepfile3=$dir.libs/$base.u
"$@" -Wc,-M
else
tmpdepfile1=$dir$base.u
tmpdepfile2=$dir$base.u
tmpdepfile3=$dir$base.u
"$@" -M
fi
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile1" "$tmpdepfile2" "$tmpdepfile3"
exit $stat
fi
for tmpdepfile in "$tmpdepfile1" "$tmpdepfile2" "$tmpdepfile3"
do
test -f "$tmpdepfile" && break
done
if test -f "$tmpdepfile"; then
# Each line is of the form 'foo.o: dependent.h'.
# Do two passes, one to just change these to
# '$object: dependent.h' and one to simply 'dependent.h:'.
sed -e "s,^.*\.[a-z]*:,$object:," < "$tmpdepfile" > "$depfile"
sed -e 's,^.*\.[a-z]*:['"$tab"' ]*,,' -e 's,$,:,' < "$tmpdepfile" >> "$depfile"
else
# The sourcefile does not contain any dependencies, so just
# store a dummy comment line, to avoid errors with the Makefile
# "include basename.Plo" scheme.
echo "#dummy" > "$depfile"
fi
rm -f "$tmpdepfile"
;;
icc)
# Intel's C compiler anf tcc (Tiny C Compiler) understand '-MD -MF file'.
# However on
# $CC -MD -MF foo.d -c -o sub/foo.o sub/foo.c
# ICC 7.0 will fill foo.d with something like
# foo.o: sub/foo.c
# foo.o: sub/foo.h
# which is wrong. We want
# sub/foo.o: sub/foo.c
# sub/foo.o: sub/foo.h
# sub/foo.c:
# sub/foo.h:
# ICC 7.1 will output
# foo.o: sub/foo.c sub/foo.h
# and will wrap long lines using '\':
# foo.o: sub/foo.c ... \
# sub/foo.h ... \
# ...
# tcc 0.9.26 (FIXME still under development at the moment of writing)
# will emit a similar output, but also prepend the continuation lines
# with horizontal tabulation characters.
"$@" -MD -MF "$tmpdepfile"
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
rm -f "$depfile"
# Each line is of the form 'foo.o: dependent.h',
# or 'foo.o: dep1.h dep2.h \', or ' dep3.h dep4.h \'.
# Do two passes, one to just change these to
# '$object: dependent.h' and one to simply 'dependent.h:'.
sed -e "s/^[ $tab][ $tab]*/ /" -e "s,^[^:]*:,$object :," \
< "$tmpdepfile" > "$depfile"
sed '
s/[ '"$tab"'][ '"$tab"']*/ /g
s/^ *//
s/ *\\*$//
s/^[^:]*: *//
/^$/d
/:$/d
s/$/ :/
' < "$tmpdepfile" >> "$depfile"
rm -f "$tmpdepfile"
;;
hp2)
# The "hp" stanza above does not work with aCC (C++) and HP's ia64
# compilers, which have integrated preprocessors. The correct option
# to use with these is +Maked; it writes dependencies to a file named
# 'foo.d', which lands next to the object file, wherever that
# happens to be.
# Much of this is similar to the tru64 case; see comments there.
dir=`echo "$object" | sed -e 's|/[^/]*$|/|'`
test "x$dir" = "x$object" && dir=
base=`echo "$object" | sed -e 's|^.*/||' -e 's/\.o$//' -e 's/\.lo$//'`
if test "$libtool" = yes; then
tmpdepfile1=$dir$base.d
tmpdepfile2=$dir.libs/$base.d
"$@" -Wc,+Maked
else
tmpdepfile1=$dir$base.d
tmpdepfile2=$dir$base.d
"$@" +Maked
fi
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile1" "$tmpdepfile2"
exit $stat
fi
for tmpdepfile in "$tmpdepfile1" "$tmpdepfile2"
do
test -f "$tmpdepfile" && break
done
if test -f "$tmpdepfile"; then
sed -e "s,^.*\.[a-z]*:,$object:," "$tmpdepfile" > "$depfile"
# Add 'dependent.h:' lines.
sed -ne '2,${
s/^ *//
s/ \\*$//
s/$/:/
p
}' "$tmpdepfile" >> "$depfile"
else
echo "#dummy" > "$depfile"
fi
rm -f "$tmpdepfile" "$tmpdepfile2"
;;
tru64)
# The Tru64 compiler uses -MD to generate dependencies as a side
# effect. 'cc -MD -o foo.o ...' puts the dependencies into 'foo.o.d'.
# At least on Alpha/Redhat 6.1, Compaq CCC V6.2-504 seems to put
# dependencies in 'foo.d' instead, so we check for that too.
# Subdirectories are respected.
dir=`echo "$object" | sed -e 's|/[^/]*$|/|'`
test "x$dir" = "x$object" && dir=
base=`echo "$object" | sed -e 's|^.*/||' -e 's/\.o$//' -e 's/\.lo$//'`
if test "$libtool" = yes; then
# With Tru64 cc, shared objects can also be used to make a
# static library. This mechanism is used in libtool 1.4 series to
# handle both shared and static libraries in a single compilation.
# With libtool 1.4, dependencies were output in $dir.libs/$base.lo.d.
#
# With libtool 1.5 this exception was removed, and libtool now
# generates 2 separate objects for the 2 libraries. These two
# compilations output dependencies in $dir.libs/$base.o.d and
# in $dir$base.o.d. We have to check for both files, because
# one of the two compilations can be disabled. We should prefer
# $dir$base.o.d over $dir.libs/$base.o.d because the latter is
# automatically cleaned when .libs/ is deleted, while ignoring
# the former would cause a distcleancheck panic.
tmpdepfile1=$dir.libs/$base.lo.d # libtool 1.4
tmpdepfile2=$dir$base.o.d # libtool 1.5
tmpdepfile3=$dir.libs/$base.o.d # libtool 1.5
tmpdepfile4=$dir.libs/$base.d # Compaq CCC V6.2-504
"$@" -Wc,-MD
else
tmpdepfile1=$dir$base.o.d
tmpdepfile2=$dir$base.d
tmpdepfile3=$dir$base.d
tmpdepfile4=$dir$base.d
"$@" -MD
fi
stat=$?
if test $stat -eq 0; then :
else
rm -f "$tmpdepfile1" "$tmpdepfile2" "$tmpdepfile3" "$tmpdepfile4"
exit $stat
fi
for tmpdepfile in "$tmpdepfile1" "$tmpdepfile2" "$tmpdepfile3" "$tmpdepfile4"
do
test -f "$tmpdepfile" && break
done
if test -f "$tmpdepfile"; then
sed -e "s,^.*\.[a-z]*:,$object:," < "$tmpdepfile" > "$depfile"
sed -e 's,^.*\.[a-z]*:['"$tab"' ]*,,' -e 's,$,:,' < "$tmpdepfile" >> "$depfile"
else
echo "#dummy" > "$depfile"
fi
rm -f "$tmpdepfile"
;;
msvc7)
if test "$libtool" = yes; then
showIncludes=-Wc,-showIncludes
else
showIncludes=-showIncludes
fi
"$@" $showIncludes > "$tmpdepfile"
stat=$?
grep -v '^Note: including file: ' "$tmpdepfile"
if test "$stat" = 0; then :
else
rm -f "$tmpdepfile"
exit $stat
fi
rm -f "$depfile"
echo "$object : \\" > "$depfile"
# The first sed program below extracts the file names and escapes
# backslashes for cygpath. The second sed program outputs the file
# name when reading, but also accumulates all include files in the
# hold buffer in order to output them again at the end. This only
# works with sed implementations that can handle large buffers.
sed < "$tmpdepfile" -n '
/^Note: including file: *\(.*\)/ {
s//\1/
s/\\/\\\\/g
p
}' | $cygpath_u | sort -u | sed -n '
s/ /\\ /g
s/\(.*\)/'"$tab"'\1 \\/p
s/.\(.*\) \\/\1:/
H
$ {
s/.*/'"$tab"'/
G
p
}' >> "$depfile"
rm -f "$tmpdepfile"
;;
msvc7msys)
# This case exists only to let depend.m4 do its work. It works by
# looking at the text of this script. This case will never be run,
# since it is checked for above.
exit 1
;;
#nosideeffect)
# This comment above is used by automake to tell side-effect
# dependency tracking mechanisms from slower ones.
dashmstdout)
# Important note: in order to support this mode, a compiler *must*
# always write the preprocessed file to stdout, regardless of -o.
"$@" || exit $?
# Remove the call to Libtool.
if test "$libtool" = yes; then
while test "X$1" != 'X--mode=compile'; do
shift
done
shift
fi
# Remove '-o $object'.
IFS=" "
for arg
do
case $arg in
-o)
shift
;;
$object)
shift
;;
*)
set fnord "$@" "$arg"
shift # fnord
shift # $arg
;;
esac
done
test -z "$dashmflag" && dashmflag=-M
# Require at least two characters before searching for ':'
# in the target name. This is to cope with DOS-style filenames:
# a dependency such as 'c:/foo/bar' could be seen as target 'c' otherwise.
"$@" $dashmflag |
sed 's:^['"$tab"' ]*[^:'"$tab"' ][^:][^:]*\:['"$tab"' ]*:'"$object"'\: :' > "$tmpdepfile"
rm -f "$depfile"
cat < "$tmpdepfile" > "$depfile"
tr ' ' "$nl" < "$tmpdepfile" | \
## Some versions of the HPUX 10.20 sed can't process this invocation
## correctly. Breaking it into two sed invocations is a workaround.
sed -e 's/^\\$//' -e '/^$/d' -e '/:$/d' | sed -e 's/$/ :/' >> "$depfile"
rm -f "$tmpdepfile"
;;
dashXmstdout)
# This case only exists to satisfy depend.m4. It is never actually
# run, as this mode is specially recognized in the preamble.
exit 1
;;
makedepend)
"$@" || exit $?
# Remove any Libtool call
if test "$libtool" = yes; then
while test "X$1" != 'X--mode=compile'; do
shift
done
shift
fi
# X makedepend
shift
cleared=no eat=no
for arg
do
case $cleared in
no)
set ""; shift
cleared=yes ;;
esac
if test $eat = yes; then
eat=no
continue
fi
case "$arg" in
-D*|-I*)
set fnord "$@" "$arg"; shift ;;
# Strip any option that makedepend may not understand. Remove
# the object too, otherwise makedepend will parse it as a source file.
-arch)
eat=yes ;;
-*|$object)
;;
*)
set fnord "$@" "$arg"; shift ;;
esac
done
obj_suffix=`echo "$object" | sed 's/^.*\././'`
touch "$tmpdepfile"
${MAKEDEPEND-makedepend} -o"$obj_suffix" -f"$tmpdepfile" "$@"
rm -f "$depfile"
# makedepend may prepend the VPATH from the source file name to the object.
# No need to regex-escape $object, excess matching of '.' is harmless.
sed "s|^.*\($object *:\)|\1|" "$tmpdepfile" > "$depfile"
sed '1,2d' "$tmpdepfile" | tr ' ' "$nl" | \
## Some versions of the HPUX 10.20 sed can't process this invocation
## correctly. Breaking it into two sed invocations is a workaround.
sed -e 's/^\\$//' -e '/^$/d' -e '/:$/d' | sed -e 's/$/ :/' >> "$depfile"
rm -f "$tmpdepfile" "$tmpdepfile".bak
;;
cpp)
# Important note: in order to support this mode, a compiler *must*
# always write the preprocessed file to stdout.
"$@" || exit $?
# Remove the call to Libtool.
if test "$libtool" = yes; then
while test "X$1" != 'X--mode=compile'; do
shift
done
shift
fi
# Remove '-o $object'.
IFS=" "
for arg
do
case $arg in
-o)
shift
;;
$object)
shift
;;
*)
set fnord "$@" "$arg"
shift # fnord
shift # $arg
;;
esac
done
"$@" -E |
sed -n -e '/^# [0-9][0-9]* "\([^"]*\)".*/ s:: \1 \\:p' \
-e '/^#line [0-9][0-9]* "\([^"]*\)".*/ s:: \1 \\:p' |
sed '$ s: \\$::' > "$tmpdepfile"
rm -f "$depfile"
echo "$object : \\" > "$depfile"
cat < "$tmpdepfile" >> "$depfile"
sed < "$tmpdepfile" '/^$/d;s/^ //;s/ \\$//;s/$/ :/' >> "$depfile"
rm -f "$tmpdepfile"
;;
msvisualcpp)
# Important note: in order to support this mode, a compiler *must*
# always write the preprocessed file to stdout.
"$@" || exit $?
# Remove the call to Libtool.
if test "$libtool" = yes; then
while test "X$1" != 'X--mode=compile'; do
shift
done
shift
fi
IFS=" "
for arg
do
case "$arg" in
-o)
shift
;;
$object)
shift
;;
"-Gm"|"/Gm"|"-Gi"|"/Gi"|"-ZI"|"/ZI")
set fnord "$@"
shift
shift
;;
*)
set fnord "$@" "$arg"
shift
shift
;;
esac
done
"$@" -E 2>/dev/null |
sed -n '/^#line [0-9][0-9]* "\([^"]*\)"/ s::\1:p' | $cygpath_u | sort -u > "$tmpdepfile"
rm -f "$depfile"
echo "$object : \\" > "$depfile"
sed < "$tmpdepfile" -n -e 's% %\\ %g' -e '/^\(.*\)$/ s::'"$tab"'\1 \\:p' >> "$depfile"
echo "$tab" >> "$depfile"
sed < "$tmpdepfile" -n -e 's% %\\ %g' -e '/^\(.*\)$/ s::\1\::p' >> "$depfile"
rm -f "$tmpdepfile"
;;
msvcmsys)
# This case exists only to let depend.m4 do its work. It works by
# looking at the text of this script. This case will never be run,
# since it is checked for above.
exit 1
;;
none)
exec "$@"
;;
*)
echo "Unknown depmode $depmode" 1>&2
exit 1
;;
esac
exit 0
# Local Variables:
# mode: shell-script
# sh-indentation: 2
# eval: (add-hook 'write-file-hooks 'time-stamp)
# time-stamp-start: "scriptversion="
# time-stamp-format: "%:y-%02m-%02d.%02H"
# time-stamp-time-zone: "UTC"
# time-stamp-end: "; # UTC"
# End:
PHYLIPNEW-3.69.650/m4/ 0002775 0001750 0001750 00000000000 12171071711 010666 5 0000000 0000000 PHYLIPNEW-3.69.650/m4/ltsugar.m4 0000644 0001750 0001750 00000010424 12171071672 012534 0000000 0000000 # ltsugar.m4 -- libtool m4 base layer. -*-Autoconf-*-
#
# Copyright (C) 2004, 2005, 2007, 2008 Free Software Foundation, Inc.
# Written by Gary V. Vaughan, 2004
#
# This file is free software; the Free Software Foundation gives
# unlimited permission to copy and/or distribute it, with or without
# modifications, as long as this notice is preserved.
# serial 6 ltsugar.m4
# This is to help aclocal find these macros, as it can't see m4_define.
AC_DEFUN([LTSUGAR_VERSION], [m4_if([0.1])])
# lt_join(SEP, ARG1, [ARG2...])
# -----------------------------
# Produce ARG1SEPARG2...SEPARGn, omitting [] arguments and their
# associated separator.
# Needed until we can rely on m4_join from Autoconf 2.62, since all earlier
# versions in m4sugar had bugs.
m4_define([lt_join],
[m4_if([$#], [1], [],
[$#], [2], [[$2]],
[m4_if([$2], [], [], [[$2]_])$0([$1], m4_shift(m4_shift($@)))])])
m4_define([_lt_join],
[m4_if([$#$2], [2], [],
[m4_if([$2], [], [], [[$1$2]])$0([$1], m4_shift(m4_shift($@)))])])
# lt_car(LIST)
# lt_cdr(LIST)
# ------------
# Manipulate m4 lists.
# These macros are necessary as long as will still need to support
# Autoconf-2.59 which quotes differently.
m4_define([lt_car], [[$1]])
m4_define([lt_cdr],
[m4_if([$#], 0, [m4_fatal([$0: cannot be called without arguments])],
[$#], 1, [],
[m4_dquote(m4_shift($@))])])
m4_define([lt_unquote], $1)
# lt_append(MACRO-NAME, STRING, [SEPARATOR])
# ------------------------------------------
# Redefine MACRO-NAME to hold its former content plus `SEPARATOR'`STRING'.
# Note that neither SEPARATOR nor STRING are expanded; they are appended
# to MACRO-NAME as is (leaving the expansion for when MACRO-NAME is invoked).
# No SEPARATOR is output if MACRO-NAME was previously undefined (different
# than defined and empty).
#
# This macro is needed until we can rely on Autoconf 2.62, since earlier
# versions of m4sugar mistakenly expanded SEPARATOR but not STRING.
m4_define([lt_append],
[m4_define([$1],
m4_ifdef([$1], [m4_defn([$1])[$3]])[$2])])
# lt_combine(SEP, PREFIX-LIST, INFIX, SUFFIX1, [SUFFIX2...])
# ----------------------------------------------------------
# Produce a SEP delimited list of all paired combinations of elements of
# PREFIX-LIST with SUFFIX1 through SUFFIXn. Each element of the list
# has the form PREFIXmINFIXSUFFIXn.
# Needed until we can rely on m4_combine added in Autoconf 2.62.
m4_define([lt_combine],
[m4_if(m4_eval([$# > 3]), [1],
[m4_pushdef([_Lt_sep], [m4_define([_Lt_sep], m4_defn([lt_car]))])]]dnl
[[m4_foreach([_Lt_prefix], [$2],
[m4_foreach([_Lt_suffix],
]m4_dquote(m4_dquote(m4_shift(m4_shift(m4_shift($@)))))[,
[_Lt_sep([$1])[]m4_defn([_Lt_prefix])[$3]m4_defn([_Lt_suffix])])])])])
# lt_if_append_uniq(MACRO-NAME, VARNAME, [SEPARATOR], [UNIQ], [NOT-UNIQ])
# -----------------------------------------------------------------------
# Iff MACRO-NAME does not yet contain VARNAME, then append it (delimited
# by SEPARATOR if supplied) and expand UNIQ, else NOT-UNIQ.
m4_define([lt_if_append_uniq],
[m4_ifdef([$1],
[m4_if(m4_index([$3]m4_defn([$1])[$3], [$3$2$3]), [-1],
[lt_append([$1], [$2], [$3])$4],
[$5])],
[lt_append([$1], [$2], [$3])$4])])
# lt_dict_add(DICT, KEY, VALUE)
# -----------------------------
m4_define([lt_dict_add],
[m4_define([$1($2)], [$3])])
# lt_dict_add_subkey(DICT, KEY, SUBKEY, VALUE)
# --------------------------------------------
m4_define([lt_dict_add_subkey],
[m4_define([$1($2:$3)], [$4])])
# lt_dict_fetch(DICT, KEY, [SUBKEY])
# ----------------------------------
m4_define([lt_dict_fetch],
[m4_ifval([$3],
m4_ifdef([$1($2:$3)], [m4_defn([$1($2:$3)])]),
m4_ifdef([$1($2)], [m4_defn([$1($2)])]))])
# lt_if_dict_fetch(DICT, KEY, [SUBKEY], VALUE, IF-TRUE, [IF-FALSE])
# -----------------------------------------------------------------
m4_define([lt_if_dict_fetch],
[m4_if(lt_dict_fetch([$1], [$2], [$3]), [$4],
[$5],
[$6])])
# lt_dict_filter(DICT, [SUBKEY], VALUE, [SEPARATOR], KEY, [...])
# --------------------------------------------------------------
m4_define([lt_dict_filter],
[m4_if([$5], [], [],
[lt_join(m4_quote(m4_default([$4], [[, ]])),
lt_unquote(m4_split(m4_normalize(m4_foreach(_Lt_key, lt_car([m4_shiftn(4, $@)]),
[lt_if_dict_fetch([$1], _Lt_key, [$2], [$3], [_Lt_key ])])))))])[]dnl
])
PHYLIPNEW-3.69.650/m4/lf_x11.m4 0000664 0001750 0001750 00000005473 11546377050 012163 0000000 0000000 dnl Copyright (C) 1988 Eleftherios Gkioulekas
dnl
dnl This program is free software; you can redistribute it and/or modify
dnl it under the terms of the GNU General Public License as published by
dnl the Free Software Foundation; either version 2 of the License, or
dnl (at your option) any later version.
dnl
dnl This program is distributed in the hope that it will be useful,
dnl but WITHOUT ANY WARRANTY; without even the implied warranty of
dnl MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
dnl GNU General Public License for more details.
dnl
dnl You should have received a copy of the GNU General Public License
dnl along with this program; if not, write to the Free Software
dnl Foundation, Inc., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
dnl
dnl As a special exception to the GNU General Public License, if you
dnl distribute this file as part of a program that contains a configuration
dnl script generated by Autoconf, you may include it under the same
dnl distribution terms that you use for the rest of that program.
#-----------------------------------------------------------------------
# This macro searches for Xlib and when it finds it it adds the
# appropriate flags to CFLAGS and export the link sequence to
# the variable XLIB.
# In your configure.in file add:
# LF_PATH_XLIB
# In your Makefile.am add
# program_LDADD = .... $(XLIB)
#------------------------------------------------------------------------
#
# Just added EMBOSS into LF_PATH_XLIB so that on the systems where
# LF_PATH_XLIB exists there are no duplication errors.
AC_DEFUN([LF_EMBOSS_PATH_XLIB],[
CFLAGS="$CFLAGS $X_CFLAGS"
case $host_os in
irix*)
XLIB="-lX11 $X_EXTRA_LIBS"
;;
*)
XLIB="$X_LIBS -lX11 $X_EXTRA_LIBS"
;;
esac
AC_SUBST([XLIB])
AC_CHECK_HEADER(X11/Xlib.h,
[
AC_DEFINE([PLD_xwin], [1], [Define to 1 if X11 support is available])
],
[
echo ""
echo "X11 graphics have been selected but no X11 header files"
echo "have been found."
echo ""
echo "This error usually happens on Linux/MacOSX distributions"
echo "where the optional X11 development files have not been installed."
echo "On Linux RPM systems this package is usually called something"
echo "like xorg-x11-proto-devel whereas on Debian/Ubuntu it may"
echo "be called x-dev. On MacOSX installation DVDs the X11 files"
echo "can usually be found as an explicitly named optional"
echo "installation."
echo ""
echo "After installing the X11 development files you should do a"
echo "'make clean' and perform the configure stage again."
echo ""
echo "Alternatively, to install EMBOSS without X11 support, you can add"
echo "the --without-x switch to the configure command."
echo ""
exit $?
])
])
PHYLIPNEW-3.69.650/m4/pngdriver.m4 0000664 0001750 0001750 00000006412 11430325237 013053 0000000 0000000 dnl @synopsis CHECK_PNGDRIVER()
dnl
dnl This macro searches for an installed png/gd/zlib library. If nothing
dnl was specified when calling configure, it searches first in /usr/local
dnl and then in /usr. If the --with-pngdriver=DIR is specified, it will try
dnl to find it in DIR/include/zlib.h and DIR/lib/libz.a. If --without-pngdriver
dnl is specified, the library is not searched at all.
dnl
dnl It defines the symbol PLD_png if the librarys are found. You should
dnl use autoheader to include a definition for this symbol in a config.h
dnl file.
dnl
dnl Sources files should then use something like
dnl
dnl #ifdef PLD_png
dnl #include
dnl #endif /* PLD_png */
dnl
dnl @author Ian Longden
dnl Modified: Alan Bleasby. Corrected library order
dnl
AC_DEFUN([CHECK_PNGDRIVER],
#
# Handle user hints
#
[AC_MSG_CHECKING([if png driver is wanted])
AC_ARG_WITH([pngdriver],
[AS_HELP_STRING([--with-pngdriver=@<:@DIR@:>@],
[root directory path of png/gd/zlib installation (defaults to /usr)])],
[if test "$withval" != no ; then
AC_MSG_RESULT([yes])
ALT_HOME="$withval"
else
AC_MSG_RESULT([no])
fi], [
AC_MSG_RESULT([yes])
ALT_HOME=/usr
])
#
# Locate png/gd/zlib, if wanted
#
if test -d "${ALT_HOME}"
then
#
# Keep a copy if it fails
#
ALT_LDFLAGS="$LDFLAGS"
ALT_CPPFLAGS="$CPPFLAGS"
#
# Set
#
LDFLAGS="${LDFLAGS} -L${ALT_HOME}/lib"
CPPFLAGS="$CPPFLAGS -I$ALT_HOME/include"
ICCHECK=0
case $host_os in
solaris*)
AC_CHECK_LIB(iconv, libiconv_close, ICCHECK=1, ICCHECK=0, -L${ALT_HOME}/lib -liconv)
if test $ICCHECK = "1" ; then
LDFLAGS="${LDFLAGS} -L${ALT_HOME}/lib -liconv"
fi
LDFLAGS="$LDFLAGS -R$ALT_HOME/lib"
;;
esac
#
# Check for zlib in ALT_HOME
#
AC_CHECK_LIB(z, inflateEnd, CHECK=1, CHECK=0, -L${ALT_HOME}/lib -lz)
#
#
# Check for png
#
if test $CHECK = "1" ; then
AC_CHECK_LIB(png, png_destroy_read_struct, CHECK=1, CHECK=0 , -L${ALT_HOME}/lib -lz)
fi
#
# Check for gd
#
if test $CHECK = "1"; then
AC_CHECK_LIB(gd, gdImageCreateFromPng, CHECK=1, CHECK=0 , -L${ALT_HOME}/lib -lgd -lpng -lz -lm)
if test $CHECK = "0"; then
echo need to upgrade gd for png driver for plplot
fi
fi
#
# If everything found okay then proceed to include png driver in config.
#
if test $CHECK = "1" ; then
LIBS="$LIBS -lgd -lpng -lz -lm"
if test $ICCHECK = "1" ; then
LIBS="$LIBS -liconv"
fi
case $host_os in
solaris*)
LDFLAGS="$LDFLAGS -R$ALT_HOME/lib"
;;
esac
AC_DEFINE([PLD_png], [1], [Define to 1 is PNG support is available])
AM_CONDITIONAL(AMPNG, true)
echo PNG libraries found
if test $ALT_HOME = "/usr" ; then
LDFLAGS="$ALT_LDFLAGS"
CPPFLAGS="$ALT_CPPFLAGS"
fi
else
#
# If not okay then reset FLAGS.
#
AM_CONDITIONAL(AMPNG, false)
LDFLAGS="$ALT_LDFLAGS"
CPPFLAGS="$ALT_CPPFLAGS"
echo No png driver will be made due to librarys missing/old.
fi
# echo PNG STUFF FOLLOWS!!!
# echo CHECK = $CHECK
# echo LIBS = $LIBS
# echo LDFLAGS = $LDFLAGS
# echo CPPFLAGS = $CPPFLAGS
else
if test $withval != "no"; then
echo "Directory $ALT_HOME does not exist"
exit 0
fi
fi
])
PHYLIPNEW-3.69.650/m4/postgresql.m4 0000664 0001750 0001750 00000013343 11732713445 013266 0000000 0000000 dnl -*- Autoconf -*-
##### http://autoconf-archive.cryp.to/ax_lib_postgresql.html
#
# SYNOPSIS
#
# AX_LIB_POSTGRESQL([MINIMUM-VERSION])
#
# DESCRIPTION
#
# This macro provides tests of availability of PostgreSQL 'libpq'
# library of particular version or newer.
#
# AX_LIB_POSTGRESQL macro takes only one argument which is optional.
# If there is no required version passed, then macro does not run
# version test.
#
# The --with-postgresql option takes one of three possible values:
#
# no - do not check for PostgreSQL client library
#
# yes - do check for PostgreSQL library in standard locations
# (pg_config should be in the PATH)
#
# path - complete path to pg_config utility, use this option if
# pg_config can't be found in the PATH
#
# This macro calls:
#
# AC_SUBST([POSTGRESQL_CFLAGS])
# AC_SUBST([POSTGRESQL_CPPFLAGS])
# AC_SUBST([POSTGRESQL_LDFLAGS])
# AC_SUBST([POSTGRESQL_VERSION])
#
# And sets:
#
# HAVE_POSTGRESQL
#
# LAST MODIFICATION
#
# 2006-07-16
# 2010-05-14 MKS: Added POSTGRESQL_CPPFLAGS
# 2011-06-21 AJB: Added workaround for Fedora pg_config oddity
# 2011-08-01 MKS: Changed PG_CONFIG to POSTGRESQL_CONFIG
# Made test constructs more portable
#
# COPYLEFT
#
# Copyright (c) 2006 Mateusz Loskot
#
# Copying and distribution of this file, with or without
# modification, are permitted in any medium without royalty provided
# the copyright notice and this notice are preserved.
AC_DEFUN([AX_LIB_POSTGRESQL],
[
POSTGRESQL_CFLAGS=""
POSTGRESQL_CPPFLAGS=""
POSTGRESQL_LDFLAGS=""
POSTGRESQL_CONFIG=""
POSTGRESQL_VERSION=""
AC_ARG_WITH([postgresql],
[AS_HELP_STRING([--with-postgresql@<:=@ARG@:>@],
[use PostgreSQL library @<:@default=yes@:>@, optionally specify path to pg_config])],
[
AS_IF([test "x${withval}" = "xno"],
[want_postgresql="no"],
[test "x${withval}" = "xyes"],
[want_postgresql="yes"],
[
want_postgresql="yes"
POSTGRESQL_CONFIG="${withval}"
])
],
[want_postgresql="yes"])
dnl
dnl Check PostgreSQL libraries (libpq)
dnl
AS_IF([test "x${want_postgresql}" = "xyes"],
[
AS_IF([test -z "${POSTGRESQL_CONFIG}" -o test],
[AC_PATH_PROG([POSTGRESQL_CONFIG], [pg_config], [no])])
AS_IF([test "x${POSTGRESQL_CONFIG}" != "xno"],
[
AC_MSG_CHECKING([for PostgreSQL libraries])
POSTGRESQL_CFLAGS="-I`${POSTGRESQL_CONFIG} --includedir`"
POSTGRESQL_CPPFLAGS="-I`${POSTGRESQL_CONFIG} --includedir`"
POSTGRESQL_LDFLAGS="-L`${POSTGRESQL_CONFIG} --libdir` -lpq"
POSTGRESQL_VERSION=`${POSTGRESQL_CONFIG} --version | sed -e 's#PostgreSQL ##'`
dnl It isn't enough to just test for pg_config as Fedora
dnl provides it in the postgresql RPM even though postgresql-devel may
dnl not be installed
EMBCPPFLAGS="${CPPFLAGS}"
EMBLDFLAGS="${LDFLAGS}"
CPPFLAGS="${POSTGRESQL_CPPFLAGS} ${EMBCPPFLAGS}"
LDFLAGS="${POSTGRESQL_LDFLAGS} ${EMBLDFLAGS}"
AC_LINK_IFELSE([AC_LANG_PROGRAM([[#include
#include "libpq-fe.h"]],
[[PQconnectdb(NULL)]])],
[havepostgresql="yes"],
[havepostgresql="no"])
CPPFLAGS="${EMBCPPFLAGS}"
LDFLAGS="${EMBLDFLAGS}"
AS_IF([test "x${havepostgresql}" = "xyes"],
[
AC_DEFINE([HAVE_POSTGRESQL], [1],
[Define to 1 if PostgreSQL libraries are available.])
found_postgresql="yes"
AC_MSG_RESULT([yes])
],
[
POSTGRESQL_CFLAGS=""
POSTGRESQL_CPPFLAGS=""
POSTGRESQL_LDFLAGS=""
found_postgresql="no"
AC_MSG_RESULT([no])
])
],
[
found_postgresql="no"
])
])
dnl
dnl Check if required version of PostgreSQL is available
dnl
postgresql_version_req=ifelse([$1], [], [], [$1])
AS_IF([test "x${found_postgresql}" = "xyes" -a -n "${postgresql_version_req}"],
[
AC_MSG_CHECKING([if PostgreSQL version is >= ${postgresql_version_req}])
dnl Decompose required version string of PostgreSQL
dnl and calculate its number representation
postgresql_version_req_major=`expr ${postgresql_version_req} : '\([[0-9]]*\)'`
postgresql_version_req_minor=`expr ${postgresql_version_req} : '[[0-9]]*\.\([[0-9]]*\)'`
postgresql_version_req_micro=`expr ${postgresql_version_req} : '[[0-9]]*\.[[0-9]]*\.\([[0-9]]*\)'`
AS_IF([test "x${postgresql_version_req_micro}" = "x"],
[postgresql_version_req_micro="0"])
postgresql_version_req_number=`expr ${postgresql_version_req_major} \* 1000000 \
\+ ${postgresql_version_req_minor} \* 1000 \
\+ ${postgresql_version_req_micro}`
dnl Decompose version string of installed PostgreSQL
dnl and calculate its number representation
postgresql_version_major=`expr ${POSTGRESQL_VERSION} : '\([[0-9]]*\)'`
postgresql_version_minor=`expr ${POSTGRESQL_VERSION} : '[[0-9]]*\.\([[0-9]]*\)'`
postgresql_version_micro=`expr ${POSTGRESQL_VERSION} : '[[0-9]]*\.[[0-9]]*\.\([[0-9]]*\)'`
AS_IF([test "x${postgresql_version_micro}" = "x"],
[postgresql_version_micro="0"])
postgresql_version_number=`expr ${postgresql_version_major} \* 1000000 \
\+ ${postgresql_version_minor} \* 1000 \
\+ ${postgresql_version_micro}`
postgresql_version_check=`expr ${postgresql_version_number} \>\= ${postgresql_version_req_number}`
AS_IF([test "x${postgresql_version_check}" = "x1"],
[AC_MSG_RESULT([yes])],
[AC_MSG_RESULT([no])])
])
AC_SUBST([POSTGRESQL_CFLAGS])
AC_SUBST([POSTGRESQL_CPPFLAGS])
AC_SUBST([POSTGRESQL_LDFLAGS])
AC_SUBST([POSTGRESQL_VERSION])
])
PHYLIPNEW-3.69.650/m4/libtool.m4 0000644 0001750 0001750 00001057432 12171071672 012532 0000000 0000000 # libtool.m4 - Configure libtool for the host system. -*-Autoconf-*-
#
# Copyright (C) 1996, 1997, 1998, 1999, 2000, 2001, 2003, 2004, 2005,
# 2006, 2007, 2008, 2009, 2010, 2011 Free Software
# Foundation, Inc.
# Written by Gordon Matzigkeit, 1996
#
# This file is free software; the Free Software Foundation gives
# unlimited permission to copy and/or distribute it, with or without
# modifications, as long as this notice is preserved.
m4_define([_LT_COPYING], [dnl
# Copyright (C) 1996, 1997, 1998, 1999, 2000, 2001, 2003, 2004, 2005,
# 2006, 2007, 2008, 2009, 2010, 2011 Free Software
# Foundation, Inc.
# Written by Gordon Matzigkeit, 1996
#
# This file is part of GNU Libtool.
#
# GNU Libtool is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License as
# published by the Free Software Foundation; either version 2 of
# the License, or (at your option) any later version.
#
# As a special exception to the GNU General Public License,
# if you distribute this file as part of a program or library that
# is built using GNU Libtool, you may include this file under the
# same distribution terms that you use for the rest of that program.
#
# GNU Libtool is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with GNU Libtool; see the file COPYING. If not, a copy
# can be downloaded from http://www.gnu.org/licenses/gpl.html, or
# obtained by writing to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA.
])
# serial 57 LT_INIT
# LT_PREREQ(VERSION)
# ------------------
# Complain and exit if this libtool version is less that VERSION.
m4_defun([LT_PREREQ],
[m4_if(m4_version_compare(m4_defn([LT_PACKAGE_VERSION]), [$1]), -1,
[m4_default([$3],
[m4_fatal([Libtool version $1 or higher is required],
63)])],
[$2])])
# _LT_CHECK_BUILDDIR
# ------------------
# Complain if the absolute build directory name contains unusual characters
m4_defun([_LT_CHECK_BUILDDIR],
[case `pwd` in
*\ * | *\ *)
AC_MSG_WARN([Libtool does not cope well with whitespace in `pwd`]) ;;
esac
])
# LT_INIT([OPTIONS])
# ------------------
AC_DEFUN([LT_INIT],
[AC_PREREQ([2.58])dnl We use AC_INCLUDES_DEFAULT
AC_REQUIRE([AC_CONFIG_AUX_DIR_DEFAULT])dnl
AC_BEFORE([$0], [LT_LANG])dnl
AC_BEFORE([$0], [LT_OUTPUT])dnl
AC_BEFORE([$0], [LTDL_INIT])dnl
m4_require([_LT_CHECK_BUILDDIR])dnl
dnl Autoconf doesn't catch unexpanded LT_ macros by default:
m4_pattern_forbid([^_?LT_[A-Z_]+$])dnl
m4_pattern_allow([^(_LT_EOF|LT_DLGLOBAL|LT_DLLAZY_OR_NOW|LT_MULTI_MODULE)$])dnl
dnl aclocal doesn't pull ltoptions.m4, ltsugar.m4, or ltversion.m4
dnl unless we require an AC_DEFUNed macro:
AC_REQUIRE([LTOPTIONS_VERSION])dnl
AC_REQUIRE([LTSUGAR_VERSION])dnl
AC_REQUIRE([LTVERSION_VERSION])dnl
AC_REQUIRE([LTOBSOLETE_VERSION])dnl
m4_require([_LT_PROG_LTMAIN])dnl
_LT_SHELL_INIT([SHELL=${CONFIG_SHELL-/bin/sh}])
dnl Parse OPTIONS
_LT_SET_OPTIONS([$0], [$1])
# This can be used to rebuild libtool when needed
LIBTOOL_DEPS="$ltmain"
# Always use our own libtool.
LIBTOOL='$(SHELL) $(top_builddir)/libtool'
AC_SUBST(LIBTOOL)dnl
_LT_SETUP
# Only expand once:
m4_define([LT_INIT])
])# LT_INIT
# Old names:
AU_ALIAS([AC_PROG_LIBTOOL], [LT_INIT])
AU_ALIAS([AM_PROG_LIBTOOL], [LT_INIT])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_PROG_LIBTOOL], [])
dnl AC_DEFUN([AM_PROG_LIBTOOL], [])
# _LT_CC_BASENAME(CC)
# -------------------
# Calculate cc_basename. Skip known compiler wrappers and cross-prefix.
m4_defun([_LT_CC_BASENAME],
[for cc_temp in $1""; do
case $cc_temp in
compile | *[[\\/]]compile | ccache | *[[\\/]]ccache ) ;;
distcc | *[[\\/]]distcc | purify | *[[\\/]]purify ) ;;
\-*) ;;
*) break;;
esac
done
cc_basename=`$ECHO "$cc_temp" | $SED "s%.*/%%; s%^$host_alias-%%"`
])
# _LT_FILEUTILS_DEFAULTS
# ----------------------
# It is okay to use these file commands and assume they have been set
# sensibly after `m4_require([_LT_FILEUTILS_DEFAULTS])'.
m4_defun([_LT_FILEUTILS_DEFAULTS],
[: ${CP="cp -f"}
: ${MV="mv -f"}
: ${RM="rm -f"}
])# _LT_FILEUTILS_DEFAULTS
# _LT_SETUP
# ---------
m4_defun([_LT_SETUP],
[AC_REQUIRE([AC_CANONICAL_HOST])dnl
AC_REQUIRE([AC_CANONICAL_BUILD])dnl
AC_REQUIRE([_LT_PREPARE_SED_QUOTE_VARS])dnl
AC_REQUIRE([_LT_PROG_ECHO_BACKSLASH])dnl
_LT_DECL([], [PATH_SEPARATOR], [1], [The PATH separator for the build system])dnl
dnl
_LT_DECL([], [host_alias], [0], [The host system])dnl
_LT_DECL([], [host], [0])dnl
_LT_DECL([], [host_os], [0])dnl
dnl
_LT_DECL([], [build_alias], [0], [The build system])dnl
_LT_DECL([], [build], [0])dnl
_LT_DECL([], [build_os], [0])dnl
dnl
AC_REQUIRE([AC_PROG_CC])dnl
AC_REQUIRE([LT_PATH_LD])dnl
AC_REQUIRE([LT_PATH_NM])dnl
dnl
AC_REQUIRE([AC_PROG_LN_S])dnl
test -z "$LN_S" && LN_S="ln -s"
_LT_DECL([], [LN_S], [1], [Whether we need soft or hard links])dnl
dnl
AC_REQUIRE([LT_CMD_MAX_LEN])dnl
_LT_DECL([objext], [ac_objext], [0], [Object file suffix (normally "o")])dnl
_LT_DECL([], [exeext], [0], [Executable file suffix (normally "")])dnl
dnl
m4_require([_LT_FILEUTILS_DEFAULTS])dnl
m4_require([_LT_CHECK_SHELL_FEATURES])dnl
m4_require([_LT_PATH_CONVERSION_FUNCTIONS])dnl
m4_require([_LT_CMD_RELOAD])dnl
m4_require([_LT_CHECK_MAGIC_METHOD])dnl
m4_require([_LT_CHECK_SHAREDLIB_FROM_LINKLIB])dnl
m4_require([_LT_CMD_OLD_ARCHIVE])dnl
m4_require([_LT_CMD_GLOBAL_SYMBOLS])dnl
m4_require([_LT_WITH_SYSROOT])dnl
_LT_CONFIG_LIBTOOL_INIT([
# See if we are running on zsh, and set the options which allow our
# commands through without removal of \ escapes INIT.
if test -n "\${ZSH_VERSION+set}" ; then
setopt NO_GLOB_SUBST
fi
])
if test -n "${ZSH_VERSION+set}" ; then
setopt NO_GLOB_SUBST
fi
_LT_CHECK_OBJDIR
m4_require([_LT_TAG_COMPILER])dnl
case $host_os in
aix3*)
# AIX sometimes has problems with the GCC collect2 program. For some
# reason, if we set the COLLECT_NAMES environment variable, the problems
# vanish in a puff of smoke.
if test "X${COLLECT_NAMES+set}" != Xset; then
COLLECT_NAMES=
export COLLECT_NAMES
fi
;;
esac
# Global variables:
ofile=libtool
can_build_shared=yes
# All known linkers require a `.a' archive for static linking (except MSVC,
# which needs '.lib').
libext=a
with_gnu_ld="$lt_cv_prog_gnu_ld"
old_CC="$CC"
old_CFLAGS="$CFLAGS"
# Set sane defaults for various variables
test -z "$CC" && CC=cc
test -z "$LTCC" && LTCC=$CC
test -z "$LTCFLAGS" && LTCFLAGS=$CFLAGS
test -z "$LD" && LD=ld
test -z "$ac_objext" && ac_objext=o
_LT_CC_BASENAME([$compiler])
# Only perform the check for file, if the check method requires it
test -z "$MAGIC_CMD" && MAGIC_CMD=file
case $deplibs_check_method in
file_magic*)
if test "$file_magic_cmd" = '$MAGIC_CMD'; then
_LT_PATH_MAGIC
fi
;;
esac
# Use C for the default configuration in the libtool script
LT_SUPPORTED_TAG([CC])
_LT_LANG_C_CONFIG
_LT_LANG_DEFAULT_CONFIG
_LT_CONFIG_COMMANDS
])# _LT_SETUP
# _LT_PREPARE_SED_QUOTE_VARS
# --------------------------
# Define a few sed substitution that help us do robust quoting.
m4_defun([_LT_PREPARE_SED_QUOTE_VARS],
[# Backslashify metacharacters that are still active within
# double-quoted strings.
sed_quote_subst='s/\([["`$\\]]\)/\\\1/g'
# Same as above, but do not quote variable references.
double_quote_subst='s/\([["`\\]]\)/\\\1/g'
# Sed substitution to delay expansion of an escaped shell variable in a
# double_quote_subst'ed string.
delay_variable_subst='s/\\\\\\\\\\\$/\\\\\\$/g'
# Sed substitution to delay expansion of an escaped single quote.
delay_single_quote_subst='s/'\''/'\'\\\\\\\'\''/g'
# Sed substitution to avoid accidental globbing in evaled expressions
no_glob_subst='s/\*/\\\*/g'
])
# _LT_PROG_LTMAIN
# ---------------
# Note that this code is called both from `configure', and `config.status'
# now that we use AC_CONFIG_COMMANDS to generate libtool. Notably,
# `config.status' has no value for ac_aux_dir unless we are using Automake,
# so we pass a copy along to make sure it has a sensible value anyway.
m4_defun([_LT_PROG_LTMAIN],
[m4_ifdef([AC_REQUIRE_AUX_FILE], [AC_REQUIRE_AUX_FILE([ltmain.sh])])dnl
_LT_CONFIG_LIBTOOL_INIT([ac_aux_dir='$ac_aux_dir'])
ltmain="$ac_aux_dir/ltmain.sh"
])# _LT_PROG_LTMAIN
## ------------------------------------- ##
## Accumulate code for creating libtool. ##
## ------------------------------------- ##
# So that we can recreate a full libtool script including additional
# tags, we accumulate the chunks of code to send to AC_CONFIG_COMMANDS
# in macros and then make a single call at the end using the `libtool'
# label.
# _LT_CONFIG_LIBTOOL_INIT([INIT-COMMANDS])
# ----------------------------------------
# Register INIT-COMMANDS to be passed to AC_CONFIG_COMMANDS later.
m4_define([_LT_CONFIG_LIBTOOL_INIT],
[m4_ifval([$1],
[m4_append([_LT_OUTPUT_LIBTOOL_INIT],
[$1
])])])
# Initialize.
m4_define([_LT_OUTPUT_LIBTOOL_INIT])
# _LT_CONFIG_LIBTOOL([COMMANDS])
# ------------------------------
# Register COMMANDS to be passed to AC_CONFIG_COMMANDS later.
m4_define([_LT_CONFIG_LIBTOOL],
[m4_ifval([$1],
[m4_append([_LT_OUTPUT_LIBTOOL_COMMANDS],
[$1
])])])
# Initialize.
m4_define([_LT_OUTPUT_LIBTOOL_COMMANDS])
# _LT_CONFIG_SAVE_COMMANDS([COMMANDS], [INIT_COMMANDS])
# -----------------------------------------------------
m4_defun([_LT_CONFIG_SAVE_COMMANDS],
[_LT_CONFIG_LIBTOOL([$1])
_LT_CONFIG_LIBTOOL_INIT([$2])
])
# _LT_FORMAT_COMMENT([COMMENT])
# -----------------------------
# Add leading comment marks to the start of each line, and a trailing
# full-stop to the whole comment if one is not present already.
m4_define([_LT_FORMAT_COMMENT],
[m4_ifval([$1], [
m4_bpatsubst([m4_bpatsubst([$1], [^ *], [# ])],
[['`$\]], [\\\&])]m4_bmatch([$1], [[!?.]$], [], [.])
)])
## ------------------------ ##
## FIXME: Eliminate VARNAME ##
## ------------------------ ##
# _LT_DECL([CONFIGNAME], VARNAME, VALUE, [DESCRIPTION], [IS-TAGGED?])
# -------------------------------------------------------------------
# CONFIGNAME is the name given to the value in the libtool script.
# VARNAME is the (base) name used in the configure script.
# VALUE may be 0, 1 or 2 for a computed quote escaped value based on
# VARNAME. Any other value will be used directly.
m4_define([_LT_DECL],
[lt_if_append_uniq([lt_decl_varnames], [$2], [, ],
[lt_dict_add_subkey([lt_decl_dict], [$2], [libtool_name],
[m4_ifval([$1], [$1], [$2])])
lt_dict_add_subkey([lt_decl_dict], [$2], [value], [$3])
m4_ifval([$4],
[lt_dict_add_subkey([lt_decl_dict], [$2], [description], [$4])])
lt_dict_add_subkey([lt_decl_dict], [$2],
[tagged?], [m4_ifval([$5], [yes], [no])])])
])
# _LT_TAGDECL([CONFIGNAME], VARNAME, VALUE, [DESCRIPTION])
# --------------------------------------------------------
m4_define([_LT_TAGDECL], [_LT_DECL([$1], [$2], [$3], [$4], [yes])])
# lt_decl_tag_varnames([SEPARATOR], [VARNAME1...])
# ------------------------------------------------
m4_define([lt_decl_tag_varnames],
[_lt_decl_filter([tagged?], [yes], $@)])
# _lt_decl_filter(SUBKEY, VALUE, [SEPARATOR], [VARNAME1..])
# ---------------------------------------------------------
m4_define([_lt_decl_filter],
[m4_case([$#],
[0], [m4_fatal([$0: too few arguments: $#])],
[1], [m4_fatal([$0: too few arguments: $#: $1])],
[2], [lt_dict_filter([lt_decl_dict], [$1], [$2], [], lt_decl_varnames)],
[3], [lt_dict_filter([lt_decl_dict], [$1], [$2], [$3], lt_decl_varnames)],
[lt_dict_filter([lt_decl_dict], $@)])[]dnl
])
# lt_decl_quote_varnames([SEPARATOR], [VARNAME1...])
# --------------------------------------------------
m4_define([lt_decl_quote_varnames],
[_lt_decl_filter([value], [1], $@)])
# lt_decl_dquote_varnames([SEPARATOR], [VARNAME1...])
# ---------------------------------------------------
m4_define([lt_decl_dquote_varnames],
[_lt_decl_filter([value], [2], $@)])
# lt_decl_varnames_tagged([SEPARATOR], [VARNAME1...])
# ---------------------------------------------------
m4_define([lt_decl_varnames_tagged],
[m4_assert([$# <= 2])dnl
_$0(m4_quote(m4_default([$1], [[, ]])),
m4_ifval([$2], [[$2]], [m4_dquote(lt_decl_tag_varnames)]),
m4_split(m4_normalize(m4_quote(_LT_TAGS)), [ ]))])
m4_define([_lt_decl_varnames_tagged],
[m4_ifval([$3], [lt_combine([$1], [$2], [_], $3)])])
# lt_decl_all_varnames([SEPARATOR], [VARNAME1...])
# ------------------------------------------------
m4_define([lt_decl_all_varnames],
[_$0(m4_quote(m4_default([$1], [[, ]])),
m4_if([$2], [],
m4_quote(lt_decl_varnames),
m4_quote(m4_shift($@))))[]dnl
])
m4_define([_lt_decl_all_varnames],
[lt_join($@, lt_decl_varnames_tagged([$1],
lt_decl_tag_varnames([[, ]], m4_shift($@))))dnl
])
# _LT_CONFIG_STATUS_DECLARE([VARNAME])
# ------------------------------------
# Quote a variable value, and forward it to `config.status' so that its
# declaration there will have the same value as in `configure'. VARNAME
# must have a single quote delimited value for this to work.
m4_define([_LT_CONFIG_STATUS_DECLARE],
[$1='`$ECHO "$][$1" | $SED "$delay_single_quote_subst"`'])
# _LT_CONFIG_STATUS_DECLARATIONS
# ------------------------------
# We delimit libtool config variables with single quotes, so when
# we write them to config.status, we have to be sure to quote all
# embedded single quotes properly. In configure, this macro expands
# each variable declared with _LT_DECL (and _LT_TAGDECL) into:
#
# ='`$ECHO "$" | $SED "$delay_single_quote_subst"`'
m4_defun([_LT_CONFIG_STATUS_DECLARATIONS],
[m4_foreach([_lt_var], m4_quote(lt_decl_all_varnames),
[m4_n([_LT_CONFIG_STATUS_DECLARE(_lt_var)])])])
# _LT_LIBTOOL_TAGS
# ----------------
# Output comment and list of tags supported by the script
m4_defun([_LT_LIBTOOL_TAGS],
[_LT_FORMAT_COMMENT([The names of the tagged configurations supported by this script])dnl
available_tags="_LT_TAGS"dnl
])
# _LT_LIBTOOL_DECLARE(VARNAME, [TAG])
# -----------------------------------
# Extract the dictionary values for VARNAME (optionally with TAG) and
# expand to a commented shell variable setting:
#
# # Some comment about what VAR is for.
# visible_name=$lt_internal_name
m4_define([_LT_LIBTOOL_DECLARE],
[_LT_FORMAT_COMMENT(m4_quote(lt_dict_fetch([lt_decl_dict], [$1],
[description])))[]dnl
m4_pushdef([_libtool_name],
m4_quote(lt_dict_fetch([lt_decl_dict], [$1], [libtool_name])))[]dnl
m4_case(m4_quote(lt_dict_fetch([lt_decl_dict], [$1], [value])),
[0], [_libtool_name=[$]$1],
[1], [_libtool_name=$lt_[]$1],
[2], [_libtool_name=$lt_[]$1],
[_libtool_name=lt_dict_fetch([lt_decl_dict], [$1], [value])])[]dnl
m4_ifval([$2], [_$2])[]m4_popdef([_libtool_name])[]dnl
])
# _LT_LIBTOOL_CONFIG_VARS
# -----------------------
# Produce commented declarations of non-tagged libtool config variables
# suitable for insertion in the LIBTOOL CONFIG section of the `libtool'
# script. Tagged libtool config variables (even for the LIBTOOL CONFIG
# section) are produced by _LT_LIBTOOL_TAG_VARS.
m4_defun([_LT_LIBTOOL_CONFIG_VARS],
[m4_foreach([_lt_var],
m4_quote(_lt_decl_filter([tagged?], [no], [], lt_decl_varnames)),
[m4_n([_LT_LIBTOOL_DECLARE(_lt_var)])])])
# _LT_LIBTOOL_TAG_VARS(TAG)
# -------------------------
m4_define([_LT_LIBTOOL_TAG_VARS],
[m4_foreach([_lt_var], m4_quote(lt_decl_tag_varnames),
[m4_n([_LT_LIBTOOL_DECLARE(_lt_var, [$1])])])])
# _LT_TAGVAR(VARNAME, [TAGNAME])
# ------------------------------
m4_define([_LT_TAGVAR], [m4_ifval([$2], [$1_$2], [$1])])
# _LT_CONFIG_COMMANDS
# -------------------
# Send accumulated output to $CONFIG_STATUS. Thanks to the lists of
# variables for single and double quote escaping we saved from calls
# to _LT_DECL, we can put quote escaped variables declarations
# into `config.status', and then the shell code to quote escape them in
# for loops in `config.status'. Finally, any additional code accumulated
# from calls to _LT_CONFIG_LIBTOOL_INIT is expanded.
m4_defun([_LT_CONFIG_COMMANDS],
[AC_PROVIDE_IFELSE([LT_OUTPUT],
dnl If the libtool generation code has been placed in $CONFIG_LT,
dnl instead of duplicating it all over again into config.status,
dnl then we will have config.status run $CONFIG_LT later, so it
dnl needs to know what name is stored there:
[AC_CONFIG_COMMANDS([libtool],
[$SHELL $CONFIG_LT || AS_EXIT(1)], [CONFIG_LT='$CONFIG_LT'])],
dnl If the libtool generation code is destined for config.status,
dnl expand the accumulated commands and init code now:
[AC_CONFIG_COMMANDS([libtool],
[_LT_OUTPUT_LIBTOOL_COMMANDS], [_LT_OUTPUT_LIBTOOL_COMMANDS_INIT])])
])#_LT_CONFIG_COMMANDS
# Initialize.
m4_define([_LT_OUTPUT_LIBTOOL_COMMANDS_INIT],
[
# The HP-UX ksh and POSIX shell print the target directory to stdout
# if CDPATH is set.
(unset CDPATH) >/dev/null 2>&1 && unset CDPATH
sed_quote_subst='$sed_quote_subst'
double_quote_subst='$double_quote_subst'
delay_variable_subst='$delay_variable_subst'
_LT_CONFIG_STATUS_DECLARATIONS
LTCC='$LTCC'
LTCFLAGS='$LTCFLAGS'
compiler='$compiler_DEFAULT'
# A function that is used when there is no print builtin or printf.
func_fallback_echo ()
{
eval 'cat <<_LTECHO_EOF
\$[]1
_LTECHO_EOF'
}
# Quote evaled strings.
for var in lt_decl_all_varnames([[ \
]], lt_decl_quote_varnames); do
case \`eval \\\\\$ECHO \\\\""\\\\\$\$var"\\\\"\` in
*[[\\\\\\\`\\"\\\$]]*)
eval "lt_\$var=\\\\\\"\\\`\\\$ECHO \\"\\\$\$var\\" | \\\$SED \\"\\\$sed_quote_subst\\"\\\`\\\\\\""
;;
*)
eval "lt_\$var=\\\\\\"\\\$\$var\\\\\\""
;;
esac
done
# Double-quote double-evaled strings.
for var in lt_decl_all_varnames([[ \
]], lt_decl_dquote_varnames); do
case \`eval \\\\\$ECHO \\\\""\\\\\$\$var"\\\\"\` in
*[[\\\\\\\`\\"\\\$]]*)
eval "lt_\$var=\\\\\\"\\\`\\\$ECHO \\"\\\$\$var\\" | \\\$SED -e \\"\\\$double_quote_subst\\" -e \\"\\\$sed_quote_subst\\" -e \\"\\\$delay_variable_subst\\"\\\`\\\\\\""
;;
*)
eval "lt_\$var=\\\\\\"\\\$\$var\\\\\\""
;;
esac
done
_LT_OUTPUT_LIBTOOL_INIT
])
# _LT_GENERATED_FILE_INIT(FILE, [COMMENT])
# ------------------------------------
# Generate a child script FILE with all initialization necessary to
# reuse the environment learned by the parent script, and make the
# file executable. If COMMENT is supplied, it is inserted after the
# `#!' sequence but before initialization text begins. After this
# macro, additional text can be appended to FILE to form the body of
# the child script. The macro ends with non-zero status if the
# file could not be fully written (such as if the disk is full).
m4_ifdef([AS_INIT_GENERATED],
[m4_defun([_LT_GENERATED_FILE_INIT],[AS_INIT_GENERATED($@)])],
[m4_defun([_LT_GENERATED_FILE_INIT],
[m4_require([AS_PREPARE])]dnl
[m4_pushdef([AS_MESSAGE_LOG_FD])]dnl
[lt_write_fail=0
cat >$1 <<_ASEOF || lt_write_fail=1
#! $SHELL
# Generated by $as_me.
$2
SHELL=\${CONFIG_SHELL-$SHELL}
export SHELL
_ASEOF
cat >>$1 <<\_ASEOF || lt_write_fail=1
AS_SHELL_SANITIZE
_AS_PREPARE
exec AS_MESSAGE_FD>&1
_ASEOF
test $lt_write_fail = 0 && chmod +x $1[]dnl
m4_popdef([AS_MESSAGE_LOG_FD])])])# _LT_GENERATED_FILE_INIT
# LT_OUTPUT
# ---------
# This macro allows early generation of the libtool script (before
# AC_OUTPUT is called), incase it is used in configure for compilation
# tests.
AC_DEFUN([LT_OUTPUT],
[: ${CONFIG_LT=./config.lt}
AC_MSG_NOTICE([creating $CONFIG_LT])
_LT_GENERATED_FILE_INIT(["$CONFIG_LT"],
[# Run this file to recreate a libtool stub with the current configuration.])
cat >>"$CONFIG_LT" <<\_LTEOF
lt_cl_silent=false
exec AS_MESSAGE_LOG_FD>>config.log
{
echo
AS_BOX([Running $as_me.])
} >&AS_MESSAGE_LOG_FD
lt_cl_help="\
\`$as_me' creates a local libtool stub from the current configuration,
for use in further configure time tests before the real libtool is
generated.
Usage: $[0] [[OPTIONS]]
-h, --help print this help, then exit
-V, --version print version number, then exit
-q, --quiet do not print progress messages
-d, --debug don't remove temporary files
Report bugs to ."
lt_cl_version="\
m4_ifset([AC_PACKAGE_NAME], [AC_PACKAGE_NAME ])config.lt[]dnl
m4_ifset([AC_PACKAGE_VERSION], [ AC_PACKAGE_VERSION])
configured by $[0], generated by m4_PACKAGE_STRING.
Copyright (C) 2011 Free Software Foundation, Inc.
This config.lt script is free software; the Free Software Foundation
gives unlimited permision to copy, distribute and modify it."
while test $[#] != 0
do
case $[1] in
--version | --v* | -V )
echo "$lt_cl_version"; exit 0 ;;
--help | --h* | -h )
echo "$lt_cl_help"; exit 0 ;;
--debug | --d* | -d )
debug=: ;;
--quiet | --q* | --silent | --s* | -q )
lt_cl_silent=: ;;
-*) AC_MSG_ERROR([unrecognized option: $[1]
Try \`$[0] --help' for more information.]) ;;
*) AC_MSG_ERROR([unrecognized argument: $[1]
Try \`$[0] --help' for more information.]) ;;
esac
shift
done
if $lt_cl_silent; then
exec AS_MESSAGE_FD>/dev/null
fi
_LTEOF
cat >>"$CONFIG_LT" <<_LTEOF
_LT_OUTPUT_LIBTOOL_COMMANDS_INIT
_LTEOF
cat >>"$CONFIG_LT" <<\_LTEOF
AC_MSG_NOTICE([creating $ofile])
_LT_OUTPUT_LIBTOOL_COMMANDS
AS_EXIT(0)
_LTEOF
chmod +x "$CONFIG_LT"
# configure is writing to config.log, but config.lt does its own redirection,
# appending to config.log, which fails on DOS, as config.log is still kept
# open by configure. Here we exec the FD to /dev/null, effectively closing
# config.log, so it can be properly (re)opened and appended to by config.lt.
lt_cl_success=:
test "$silent" = yes &&
lt_config_lt_args="$lt_config_lt_args --quiet"
exec AS_MESSAGE_LOG_FD>/dev/null
$SHELL "$CONFIG_LT" $lt_config_lt_args || lt_cl_success=false
exec AS_MESSAGE_LOG_FD>>config.log
$lt_cl_success || AS_EXIT(1)
])# LT_OUTPUT
# _LT_CONFIG(TAG)
# ---------------
# If TAG is the built-in tag, create an initial libtool script with a
# default configuration from the untagged config vars. Otherwise add code
# to config.status for appending the configuration named by TAG from the
# matching tagged config vars.
m4_defun([_LT_CONFIG],
[m4_require([_LT_FILEUTILS_DEFAULTS])dnl
_LT_CONFIG_SAVE_COMMANDS([
m4_define([_LT_TAG], m4_if([$1], [], [C], [$1]))dnl
m4_if(_LT_TAG, [C], [
# See if we are running on zsh, and set the options which allow our
# commands through without removal of \ escapes.
if test -n "${ZSH_VERSION+set}" ; then
setopt NO_GLOB_SUBST
fi
cfgfile="${ofile}T"
trap "$RM \"$cfgfile\"; exit 1" 1 2 15
$RM "$cfgfile"
cat <<_LT_EOF >> "$cfgfile"
#! $SHELL
# `$ECHO "$ofile" | sed 's%^.*/%%'` - Provide generalized library-building support services.
# Generated automatically by $as_me ($PACKAGE$TIMESTAMP) $VERSION
# Libtool was configured on host `(hostname || uname -n) 2>/dev/null | sed 1q`:
# NOTE: Changes made to this file will be lost: look at ltmain.sh.
#
_LT_COPYING
_LT_LIBTOOL_TAGS
# ### BEGIN LIBTOOL CONFIG
_LT_LIBTOOL_CONFIG_VARS
_LT_LIBTOOL_TAG_VARS
# ### END LIBTOOL CONFIG
_LT_EOF
case $host_os in
aix3*)
cat <<\_LT_EOF >> "$cfgfile"
# AIX sometimes has problems with the GCC collect2 program. For some
# reason, if we set the COLLECT_NAMES environment variable, the problems
# vanish in a puff of smoke.
if test "X${COLLECT_NAMES+set}" != Xset; then
COLLECT_NAMES=
export COLLECT_NAMES
fi
_LT_EOF
;;
esac
_LT_PROG_LTMAIN
# We use sed instead of cat because bash on DJGPP gets confused if
# if finds mixed CR/LF and LF-only lines. Since sed operates in
# text mode, it properly converts lines to CR/LF. This bash problem
# is reportedly fixed, but why not run on old versions too?
sed '$q' "$ltmain" >> "$cfgfile" \
|| (rm -f "$cfgfile"; exit 1)
_LT_PROG_REPLACE_SHELLFNS
mv -f "$cfgfile" "$ofile" ||
(rm -f "$ofile" && cp "$cfgfile" "$ofile" && rm -f "$cfgfile")
chmod +x "$ofile"
],
[cat <<_LT_EOF >> "$ofile"
dnl Unfortunately we have to use $1 here, since _LT_TAG is not expanded
dnl in a comment (ie after a #).
# ### BEGIN LIBTOOL TAG CONFIG: $1
_LT_LIBTOOL_TAG_VARS(_LT_TAG)
# ### END LIBTOOL TAG CONFIG: $1
_LT_EOF
])dnl /m4_if
],
[m4_if([$1], [], [
PACKAGE='$PACKAGE'
VERSION='$VERSION'
TIMESTAMP='$TIMESTAMP'
RM='$RM'
ofile='$ofile'], [])
])dnl /_LT_CONFIG_SAVE_COMMANDS
])# _LT_CONFIG
# LT_SUPPORTED_TAG(TAG)
# ---------------------
# Trace this macro to discover what tags are supported by the libtool
# --tag option, using:
# autoconf --trace 'LT_SUPPORTED_TAG:$1'
AC_DEFUN([LT_SUPPORTED_TAG], [])
# C support is built-in for now
m4_define([_LT_LANG_C_enabled], [])
m4_define([_LT_TAGS], [])
# LT_LANG(LANG)
# -------------
# Enable libtool support for the given language if not already enabled.
AC_DEFUN([LT_LANG],
[AC_BEFORE([$0], [LT_OUTPUT])dnl
m4_case([$1],
[C], [_LT_LANG(C)],
[C++], [_LT_LANG(CXX)],
[Go], [_LT_LANG(GO)],
[Java], [_LT_LANG(GCJ)],
[Fortran 77], [_LT_LANG(F77)],
[Fortran], [_LT_LANG(FC)],
[Windows Resource], [_LT_LANG(RC)],
[m4_ifdef([_LT_LANG_]$1[_CONFIG],
[_LT_LANG($1)],
[m4_fatal([$0: unsupported language: "$1"])])])dnl
])# LT_LANG
# _LT_LANG(LANGNAME)
# ------------------
m4_defun([_LT_LANG],
[m4_ifdef([_LT_LANG_]$1[_enabled], [],
[LT_SUPPORTED_TAG([$1])dnl
m4_append([_LT_TAGS], [$1 ])dnl
m4_define([_LT_LANG_]$1[_enabled], [])dnl
_LT_LANG_$1_CONFIG($1)])dnl
])# _LT_LANG
m4_ifndef([AC_PROG_GO], [
############################################################
# NOTE: This macro has been submitted for inclusion into #
# GNU Autoconf as AC_PROG_GO. When it is available in #
# a released version of Autoconf we should remove this #
# macro and use it instead. #
############################################################
m4_defun([AC_PROG_GO],
[AC_LANG_PUSH(Go)dnl
AC_ARG_VAR([GOC], [Go compiler command])dnl
AC_ARG_VAR([GOFLAGS], [Go compiler flags])dnl
_AC_ARG_VAR_LDFLAGS()dnl
AC_CHECK_TOOL(GOC, gccgo)
if test -z "$GOC"; then
if test -n "$ac_tool_prefix"; then
AC_CHECK_PROG(GOC, [${ac_tool_prefix}gccgo], [${ac_tool_prefix}gccgo])
fi
fi
if test -z "$GOC"; then
AC_CHECK_PROG(GOC, gccgo, gccgo, false)
fi
])#m4_defun
])#m4_ifndef
# _LT_LANG_DEFAULT_CONFIG
# -----------------------
m4_defun([_LT_LANG_DEFAULT_CONFIG],
[AC_PROVIDE_IFELSE([AC_PROG_CXX],
[LT_LANG(CXX)],
[m4_define([AC_PROG_CXX], defn([AC_PROG_CXX])[LT_LANG(CXX)])])
AC_PROVIDE_IFELSE([AC_PROG_F77],
[LT_LANG(F77)],
[m4_define([AC_PROG_F77], defn([AC_PROG_F77])[LT_LANG(F77)])])
AC_PROVIDE_IFELSE([AC_PROG_FC],
[LT_LANG(FC)],
[m4_define([AC_PROG_FC], defn([AC_PROG_FC])[LT_LANG(FC)])])
dnl The call to [A][M_PROG_GCJ] is quoted like that to stop aclocal
dnl pulling things in needlessly.
AC_PROVIDE_IFELSE([AC_PROG_GCJ],
[LT_LANG(GCJ)],
[AC_PROVIDE_IFELSE([A][M_PROG_GCJ],
[LT_LANG(GCJ)],
[AC_PROVIDE_IFELSE([LT_PROG_GCJ],
[LT_LANG(GCJ)],
[m4_ifdef([AC_PROG_GCJ],
[m4_define([AC_PROG_GCJ], defn([AC_PROG_GCJ])[LT_LANG(GCJ)])])
m4_ifdef([A][M_PROG_GCJ],
[m4_define([A][M_PROG_GCJ], defn([A][M_PROG_GCJ])[LT_LANG(GCJ)])])
m4_ifdef([LT_PROG_GCJ],
[m4_define([LT_PROG_GCJ], defn([LT_PROG_GCJ])[LT_LANG(GCJ)])])])])])
AC_PROVIDE_IFELSE([AC_PROG_GO],
[LT_LANG(GO)],
[m4_define([AC_PROG_GO], defn([AC_PROG_GO])[LT_LANG(GO)])])
AC_PROVIDE_IFELSE([LT_PROG_RC],
[LT_LANG(RC)],
[m4_define([LT_PROG_RC], defn([LT_PROG_RC])[LT_LANG(RC)])])
])# _LT_LANG_DEFAULT_CONFIG
# Obsolete macros:
AU_DEFUN([AC_LIBTOOL_CXX], [LT_LANG(C++)])
AU_DEFUN([AC_LIBTOOL_F77], [LT_LANG(Fortran 77)])
AU_DEFUN([AC_LIBTOOL_FC], [LT_LANG(Fortran)])
AU_DEFUN([AC_LIBTOOL_GCJ], [LT_LANG(Java)])
AU_DEFUN([AC_LIBTOOL_RC], [LT_LANG(Windows Resource)])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_LIBTOOL_CXX], [])
dnl AC_DEFUN([AC_LIBTOOL_F77], [])
dnl AC_DEFUN([AC_LIBTOOL_FC], [])
dnl AC_DEFUN([AC_LIBTOOL_GCJ], [])
dnl AC_DEFUN([AC_LIBTOOL_RC], [])
# _LT_TAG_COMPILER
# ----------------
m4_defun([_LT_TAG_COMPILER],
[AC_REQUIRE([AC_PROG_CC])dnl
_LT_DECL([LTCC], [CC], [1], [A C compiler])dnl
_LT_DECL([LTCFLAGS], [CFLAGS], [1], [LTCC compiler flags])dnl
_LT_TAGDECL([CC], [compiler], [1], [A language specific compiler])dnl
_LT_TAGDECL([with_gcc], [GCC], [0], [Is the compiler the GNU compiler?])dnl
# If no C compiler was specified, use CC.
LTCC=${LTCC-"$CC"}
# If no C compiler flags were specified, use CFLAGS.
LTCFLAGS=${LTCFLAGS-"$CFLAGS"}
# Allow CC to be a program name with arguments.
compiler=$CC
])# _LT_TAG_COMPILER
# _LT_COMPILER_BOILERPLATE
# ------------------------
# Check for compiler boilerplate output or warnings with
# the simple compiler test code.
m4_defun([_LT_COMPILER_BOILERPLATE],
[m4_require([_LT_DECL_SED])dnl
ac_outfile=conftest.$ac_objext
echo "$lt_simple_compile_test_code" >conftest.$ac_ext
eval "$ac_compile" 2>&1 >/dev/null | $SED '/^$/d; /^ *+/d' >conftest.err
_lt_compiler_boilerplate=`cat conftest.err`
$RM conftest*
])# _LT_COMPILER_BOILERPLATE
# _LT_LINKER_BOILERPLATE
# ----------------------
# Check for linker boilerplate output or warnings with
# the simple link test code.
m4_defun([_LT_LINKER_BOILERPLATE],
[m4_require([_LT_DECL_SED])dnl
ac_outfile=conftest.$ac_objext
echo "$lt_simple_link_test_code" >conftest.$ac_ext
eval "$ac_link" 2>&1 >/dev/null | $SED '/^$/d; /^ *+/d' >conftest.err
_lt_linker_boilerplate=`cat conftest.err`
$RM -r conftest*
])# _LT_LINKER_BOILERPLATE
# _LT_REQUIRED_DARWIN_CHECKS
# -------------------------
m4_defun_once([_LT_REQUIRED_DARWIN_CHECKS],[
case $host_os in
rhapsody* | darwin*)
AC_CHECK_TOOL([DSYMUTIL], [dsymutil], [:])
AC_CHECK_TOOL([NMEDIT], [nmedit], [:])
AC_CHECK_TOOL([LIPO], [lipo], [:])
AC_CHECK_TOOL([OTOOL], [otool], [:])
AC_CHECK_TOOL([OTOOL64], [otool64], [:])
_LT_DECL([], [DSYMUTIL], [1],
[Tool to manipulate archived DWARF debug symbol files on Mac OS X])
_LT_DECL([], [NMEDIT], [1],
[Tool to change global to local symbols on Mac OS X])
_LT_DECL([], [LIPO], [1],
[Tool to manipulate fat objects and archives on Mac OS X])
_LT_DECL([], [OTOOL], [1],
[ldd/readelf like tool for Mach-O binaries on Mac OS X])
_LT_DECL([], [OTOOL64], [1],
[ldd/readelf like tool for 64 bit Mach-O binaries on Mac OS X 10.4])
AC_CACHE_CHECK([for -single_module linker flag],[lt_cv_apple_cc_single_mod],
[lt_cv_apple_cc_single_mod=no
if test -z "${LT_MULTI_MODULE}"; then
# By default we will add the -single_module flag. You can override
# by either setting the environment variable LT_MULTI_MODULE
# non-empty at configure time, or by adding -multi_module to the
# link flags.
rm -rf libconftest.dylib*
echo "int foo(void){return 1;}" > conftest.c
echo "$LTCC $LTCFLAGS $LDFLAGS -o libconftest.dylib \
-dynamiclib -Wl,-single_module conftest.c" >&AS_MESSAGE_LOG_FD
$LTCC $LTCFLAGS $LDFLAGS -o libconftest.dylib \
-dynamiclib -Wl,-single_module conftest.c 2>conftest.err
_lt_result=$?
# If there is a non-empty error log, and "single_module"
# appears in it, assume the flag caused a linker warning
if test -s conftest.err && $GREP single_module conftest.err; then
cat conftest.err >&AS_MESSAGE_LOG_FD
# Otherwise, if the output was created with a 0 exit code from
# the compiler, it worked.
elif test -f libconftest.dylib && test $_lt_result -eq 0; then
lt_cv_apple_cc_single_mod=yes
else
cat conftest.err >&AS_MESSAGE_LOG_FD
fi
rm -rf libconftest.dylib*
rm -f conftest.*
fi])
AC_CACHE_CHECK([for -exported_symbols_list linker flag],
[lt_cv_ld_exported_symbols_list],
[lt_cv_ld_exported_symbols_list=no
save_LDFLAGS=$LDFLAGS
echo "_main" > conftest.sym
LDFLAGS="$LDFLAGS -Wl,-exported_symbols_list,conftest.sym"
AC_LINK_IFELSE([AC_LANG_PROGRAM([],[])],
[lt_cv_ld_exported_symbols_list=yes],
[lt_cv_ld_exported_symbols_list=no])
LDFLAGS="$save_LDFLAGS"
])
AC_CACHE_CHECK([for -force_load linker flag],[lt_cv_ld_force_load],
[lt_cv_ld_force_load=no
cat > conftest.c << _LT_EOF
int forced_loaded() { return 2;}
_LT_EOF
echo "$LTCC $LTCFLAGS -c -o conftest.o conftest.c" >&AS_MESSAGE_LOG_FD
$LTCC $LTCFLAGS -c -o conftest.o conftest.c 2>&AS_MESSAGE_LOG_FD
echo "$AR cru libconftest.a conftest.o" >&AS_MESSAGE_LOG_FD
$AR cru libconftest.a conftest.o 2>&AS_MESSAGE_LOG_FD
echo "$RANLIB libconftest.a" >&AS_MESSAGE_LOG_FD
$RANLIB libconftest.a 2>&AS_MESSAGE_LOG_FD
cat > conftest.c << _LT_EOF
int main() { return 0;}
_LT_EOF
echo "$LTCC $LTCFLAGS $LDFLAGS -o conftest conftest.c -Wl,-force_load,./libconftest.a" >&AS_MESSAGE_LOG_FD
$LTCC $LTCFLAGS $LDFLAGS -o conftest conftest.c -Wl,-force_load,./libconftest.a 2>conftest.err
_lt_result=$?
if test -s conftest.err && $GREP force_load conftest.err; then
cat conftest.err >&AS_MESSAGE_LOG_FD
elif test -f conftest && test $_lt_result -eq 0 && $GREP forced_load conftest >/dev/null 2>&1 ; then
lt_cv_ld_force_load=yes
else
cat conftest.err >&AS_MESSAGE_LOG_FD
fi
rm -f conftest.err libconftest.a conftest conftest.c
rm -rf conftest.dSYM
])
case $host_os in
rhapsody* | darwin1.[[012]])
_lt_dar_allow_undefined='${wl}-undefined ${wl}suppress' ;;
darwin1.*)
_lt_dar_allow_undefined='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;;
darwin*) # darwin 5.x on
# if running on 10.5 or later, the deployment target defaults
# to the OS version, if on x86, and 10.4, the deployment
# target defaults to 10.4. Don't you love it?
case ${MACOSX_DEPLOYMENT_TARGET-10.0},$host in
10.0,*86*-darwin8*|10.0,*-darwin[[91]]*)
_lt_dar_allow_undefined='${wl}-undefined ${wl}dynamic_lookup' ;;
10.[[012]]*)
_lt_dar_allow_undefined='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;;
10.*)
_lt_dar_allow_undefined='${wl}-undefined ${wl}dynamic_lookup' ;;
esac
;;
esac
if test "$lt_cv_apple_cc_single_mod" = "yes"; then
_lt_dar_single_mod='$single_module'
fi
if test "$lt_cv_ld_exported_symbols_list" = "yes"; then
_lt_dar_export_syms=' ${wl}-exported_symbols_list,$output_objdir/${libname}-symbols.expsym'
else
_lt_dar_export_syms='~$NMEDIT -s $output_objdir/${libname}-symbols.expsym ${lib}'
fi
if test "$DSYMUTIL" != ":" && test "$lt_cv_ld_force_load" = "no"; then
_lt_dsymutil='~$DSYMUTIL $lib || :'
else
_lt_dsymutil=
fi
;;
esac
])
# _LT_DARWIN_LINKER_FEATURES([TAG])
# ---------------------------------
# Checks for linker and compiler features on darwin
m4_defun([_LT_DARWIN_LINKER_FEATURES],
[
m4_require([_LT_REQUIRED_DARWIN_CHECKS])
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_automatic, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=unsupported
if test "$lt_cv_ld_force_load" = "yes"; then
_LT_TAGVAR(whole_archive_flag_spec, $1)='`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience ${wl}-force_load,$conv\"; done; func_echo_all \"$new_convenience\"`'
m4_case([$1], [F77], [_LT_TAGVAR(compiler_needs_object, $1)=yes],
[FC], [_LT_TAGVAR(compiler_needs_object, $1)=yes])
else
_LT_TAGVAR(whole_archive_flag_spec, $1)=''
fi
_LT_TAGVAR(link_all_deplibs, $1)=yes
_LT_TAGVAR(allow_undefined_flag, $1)="$_lt_dar_allow_undefined"
case $cc_basename in
ifort*) _lt_dar_can_shared=yes ;;
*) _lt_dar_can_shared=$GCC ;;
esac
if test "$_lt_dar_can_shared" = "yes"; then
output_verbose_link_cmd=func_echo_all
_LT_TAGVAR(archive_cmds, $1)="\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring $_lt_dar_single_mod${_lt_dsymutil}"
_LT_TAGVAR(module_cmds, $1)="\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dsymutil}"
_LT_TAGVAR(archive_expsym_cmds, $1)="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring ${_lt_dar_single_mod}${_lt_dar_export_syms}${_lt_dsymutil}"
_LT_TAGVAR(module_expsym_cmds, $1)="sed -e 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dar_export_syms}${_lt_dsymutil}"
m4_if([$1], [CXX],
[ if test "$lt_cv_apple_cc_single_mod" != "yes"; then
_LT_TAGVAR(archive_cmds, $1)="\$CC -r -keep_private_externs -nostdlib -o \${lib}-master.o \$libobjs~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \${lib}-master.o \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring${_lt_dsymutil}"
_LT_TAGVAR(archive_expsym_cmds, $1)="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -r -keep_private_externs -nostdlib -o \${lib}-master.o \$libobjs~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \${lib}-master.o \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring${_lt_dar_export_syms}${_lt_dsymutil}"
fi
],[])
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
])
# _LT_SYS_MODULE_PATH_AIX([TAGNAME])
# ----------------------------------
# Links a minimal program and checks the executable
# for the system default hardcoded library path. In most cases,
# this is /usr/lib:/lib, but when the MPI compilers are used
# the location of the communication and MPI libs are included too.
# If we don't find anything, use the default library path according
# to the aix ld manual.
# Store the results from the different compilers for each TAGNAME.
# Allow to override them for all tags through lt_cv_aix_libpath.
m4_defun([_LT_SYS_MODULE_PATH_AIX],
[m4_require([_LT_DECL_SED])dnl
if test "${lt_cv_aix_libpath+set}" = set; then
aix_libpath=$lt_cv_aix_libpath
else
AC_CACHE_VAL([_LT_TAGVAR([lt_cv_aix_libpath_], [$1])],
[AC_LINK_IFELSE([AC_LANG_PROGRAM],[
lt_aix_libpath_sed='[
/Import File Strings/,/^$/ {
/^0/ {
s/^0 *\([^ ]*\) *$/\1/
p
}
}]'
_LT_TAGVAR([lt_cv_aix_libpath_], [$1])=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
# Check for a 64-bit object if we didn't find anything.
if test -z "$_LT_TAGVAR([lt_cv_aix_libpath_], [$1])"; then
_LT_TAGVAR([lt_cv_aix_libpath_], [$1])=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
fi],[])
if test -z "$_LT_TAGVAR([lt_cv_aix_libpath_], [$1])"; then
_LT_TAGVAR([lt_cv_aix_libpath_], [$1])="/usr/lib:/lib"
fi
])
aix_libpath=$_LT_TAGVAR([lt_cv_aix_libpath_], [$1])
fi
])# _LT_SYS_MODULE_PATH_AIX
# _LT_SHELL_INIT(ARG)
# -------------------
m4_define([_LT_SHELL_INIT],
[m4_divert_text([M4SH-INIT], [$1
])])# _LT_SHELL_INIT
# _LT_PROG_ECHO_BACKSLASH
# -----------------------
# Find how we can fake an echo command that does not interpret backslash.
# In particular, with Autoconf 2.60 or later we add some code to the start
# of the generated configure script which will find a shell with a builtin
# printf (which we can use as an echo command).
m4_defun([_LT_PROG_ECHO_BACKSLASH],
[ECHO='\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'
ECHO=$ECHO$ECHO$ECHO$ECHO$ECHO
ECHO=$ECHO$ECHO$ECHO$ECHO$ECHO$ECHO
AC_MSG_CHECKING([how to print strings])
# Test print first, because it will be a builtin if present.
if test "X`( print -r -- -n ) 2>/dev/null`" = X-n && \
test "X`print -r -- $ECHO 2>/dev/null`" = "X$ECHO"; then
ECHO='print -r --'
elif test "X`printf %s $ECHO 2>/dev/null`" = "X$ECHO"; then
ECHO='printf %s\n'
else
# Use this function as a fallback that always works.
func_fallback_echo ()
{
eval 'cat <<_LTECHO_EOF
$[]1
_LTECHO_EOF'
}
ECHO='func_fallback_echo'
fi
# func_echo_all arg...
# Invoke $ECHO with all args, space-separated.
func_echo_all ()
{
$ECHO "$*"
}
case "$ECHO" in
printf*) AC_MSG_RESULT([printf]) ;;
print*) AC_MSG_RESULT([print -r]) ;;
*) AC_MSG_RESULT([cat]) ;;
esac
m4_ifdef([_AS_DETECT_SUGGESTED],
[_AS_DETECT_SUGGESTED([
test -n "${ZSH_VERSION+set}${BASH_VERSION+set}" || (
ECHO='\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'
ECHO=$ECHO$ECHO$ECHO$ECHO$ECHO
ECHO=$ECHO$ECHO$ECHO$ECHO$ECHO$ECHO
PATH=/empty FPATH=/empty; export PATH FPATH
test "X`printf %s $ECHO`" = "X$ECHO" \
|| test "X`print -r -- $ECHO`" = "X$ECHO" )])])
_LT_DECL([], [SHELL], [1], [Shell to use when invoking shell scripts])
_LT_DECL([], [ECHO], [1], [An echo program that protects backslashes])
])# _LT_PROG_ECHO_BACKSLASH
# _LT_WITH_SYSROOT
# ----------------
AC_DEFUN([_LT_WITH_SYSROOT],
[AC_MSG_CHECKING([for sysroot])
AC_ARG_WITH([sysroot],
[ --with-sysroot[=DIR] Search for dependent libraries within DIR
(or the compiler's sysroot if not specified).],
[], [with_sysroot=no])
dnl lt_sysroot will always be passed unquoted. We quote it here
dnl in case the user passed a directory name.
lt_sysroot=
case ${with_sysroot} in #(
yes)
if test "$GCC" = yes; then
lt_sysroot=`$CC --print-sysroot 2>/dev/null`
fi
;; #(
/*)
lt_sysroot=`echo "$with_sysroot" | sed -e "$sed_quote_subst"`
;; #(
no|'')
;; #(
*)
AC_MSG_RESULT([${with_sysroot}])
AC_MSG_ERROR([The sysroot must be an absolute path.])
;;
esac
AC_MSG_RESULT([${lt_sysroot:-no}])
_LT_DECL([], [lt_sysroot], [0], [The root where to search for ]dnl
[dependent libraries, and in which our libraries should be installed.])])
# _LT_ENABLE_LOCK
# ---------------
m4_defun([_LT_ENABLE_LOCK],
[AC_ARG_ENABLE([libtool-lock],
[AS_HELP_STRING([--disable-libtool-lock],
[avoid locking (might break parallel builds)])])
test "x$enable_libtool_lock" != xno && enable_libtool_lock=yes
# Some flags need to be propagated to the compiler or linker for good
# libtool support.
case $host in
ia64-*-hpux*)
# Find out which ABI we are using.
echo 'int i;' > conftest.$ac_ext
if AC_TRY_EVAL(ac_compile); then
case `/usr/bin/file conftest.$ac_objext` in
*ELF-32*)
HPUX_IA64_MODE="32"
;;
*ELF-64*)
HPUX_IA64_MODE="64"
;;
esac
fi
rm -rf conftest*
;;
*-*-irix6*)
# Find out which ABI we are using.
echo '[#]line '$LINENO' "configure"' > conftest.$ac_ext
if AC_TRY_EVAL(ac_compile); then
if test "$lt_cv_prog_gnu_ld" = yes; then
case `/usr/bin/file conftest.$ac_objext` in
*32-bit*)
LD="${LD-ld} -melf32bsmip"
;;
*N32*)
LD="${LD-ld} -melf32bmipn32"
;;
*64-bit*)
LD="${LD-ld} -melf64bmip"
;;
esac
else
case `/usr/bin/file conftest.$ac_objext` in
*32-bit*)
LD="${LD-ld} -32"
;;
*N32*)
LD="${LD-ld} -n32"
;;
*64-bit*)
LD="${LD-ld} -64"
;;
esac
fi
fi
rm -rf conftest*
;;
x86_64-*kfreebsd*-gnu|x86_64-*linux*|ppc*-*linux*|powerpc*-*linux*| \
s390*-*linux*|s390*-*tpf*|sparc*-*linux*)
# Find out which ABI we are using.
echo 'int i;' > conftest.$ac_ext
if AC_TRY_EVAL(ac_compile); then
case `/usr/bin/file conftest.o` in
*32-bit*)
case $host in
x86_64-*kfreebsd*-gnu)
LD="${LD-ld} -m elf_i386_fbsd"
;;
x86_64-*linux*)
LD="${LD-ld} -m elf_i386"
;;
ppc64-*linux*|powerpc64-*linux*)
LD="${LD-ld} -m elf32ppclinux"
;;
s390x-*linux*)
LD="${LD-ld} -m elf_s390"
;;
sparc64-*linux*)
LD="${LD-ld} -m elf32_sparc"
;;
esac
;;
*64-bit*)
case $host in
x86_64-*kfreebsd*-gnu)
LD="${LD-ld} -m elf_x86_64_fbsd"
;;
x86_64-*linux*)
LD="${LD-ld} -m elf_x86_64"
;;
ppc*-*linux*|powerpc*-*linux*)
LD="${LD-ld} -m elf64ppc"
;;
s390*-*linux*|s390*-*tpf*)
LD="${LD-ld} -m elf64_s390"
;;
sparc*-*linux*)
LD="${LD-ld} -m elf64_sparc"
;;
esac
;;
esac
fi
rm -rf conftest*
;;
*-*-sco3.2v5*)
# On SCO OpenServer 5, we need -belf to get full-featured binaries.
SAVE_CFLAGS="$CFLAGS"
CFLAGS="$CFLAGS -belf"
AC_CACHE_CHECK([whether the C compiler needs -belf], lt_cv_cc_needs_belf,
[AC_LANG_PUSH(C)
AC_LINK_IFELSE([AC_LANG_PROGRAM([[]],[[]])],[lt_cv_cc_needs_belf=yes],[lt_cv_cc_needs_belf=no])
AC_LANG_POP])
if test x"$lt_cv_cc_needs_belf" != x"yes"; then
# this is probably gcc 2.8.0, egcs 1.0 or newer; no need for -belf
CFLAGS="$SAVE_CFLAGS"
fi
;;
*-*solaris*)
# Find out which ABI we are using.
echo 'int i;' > conftest.$ac_ext
if AC_TRY_EVAL(ac_compile); then
case `/usr/bin/file conftest.o` in
*64-bit*)
case $lt_cv_prog_gnu_ld in
yes*)
case $host in
i?86-*-solaris*)
LD="${LD-ld} -m elf_x86_64"
;;
sparc*-*-solaris*)
LD="${LD-ld} -m elf64_sparc"
;;
esac
# GNU ld 2.21 introduced _sol2 emulations. Use them if available.
if ${LD-ld} -V | grep _sol2 >/dev/null 2>&1; then
LD="${LD-ld}_sol2"
fi
;;
*)
if ${LD-ld} -64 -r -o conftest2.o conftest.o >/dev/null 2>&1; then
LD="${LD-ld} -64"
fi
;;
esac
;;
esac
fi
rm -rf conftest*
;;
esac
need_locks="$enable_libtool_lock"
])# _LT_ENABLE_LOCK
# _LT_PROG_AR
# -----------
m4_defun([_LT_PROG_AR],
[AC_CHECK_TOOLS(AR, [ar], false)
: ${AR=ar}
: ${AR_FLAGS=cru}
_LT_DECL([], [AR], [1], [The archiver])
_LT_DECL([], [AR_FLAGS], [1], [Flags to create an archive])
AC_CACHE_CHECK([for archiver @FILE support], [lt_cv_ar_at_file],
[lt_cv_ar_at_file=no
AC_COMPILE_IFELSE([AC_LANG_PROGRAM],
[echo conftest.$ac_objext > conftest.lst
lt_ar_try='$AR $AR_FLAGS libconftest.a @conftest.lst >&AS_MESSAGE_LOG_FD'
AC_TRY_EVAL([lt_ar_try])
if test "$ac_status" -eq 0; then
# Ensure the archiver fails upon bogus file names.
rm -f conftest.$ac_objext libconftest.a
AC_TRY_EVAL([lt_ar_try])
if test "$ac_status" -ne 0; then
lt_cv_ar_at_file=@
fi
fi
rm -f conftest.* libconftest.a
])
])
if test "x$lt_cv_ar_at_file" = xno; then
archiver_list_spec=
else
archiver_list_spec=$lt_cv_ar_at_file
fi
_LT_DECL([], [archiver_list_spec], [1],
[How to feed a file listing to the archiver])
])# _LT_PROG_AR
# _LT_CMD_OLD_ARCHIVE
# -------------------
m4_defun([_LT_CMD_OLD_ARCHIVE],
[_LT_PROG_AR
AC_CHECK_TOOL(STRIP, strip, :)
test -z "$STRIP" && STRIP=:
_LT_DECL([], [STRIP], [1], [A symbol stripping program])
AC_CHECK_TOOL(RANLIB, ranlib, :)
test -z "$RANLIB" && RANLIB=:
_LT_DECL([], [RANLIB], [1],
[Commands used to install an old-style archive])
# Determine commands to create old-style static archives.
old_archive_cmds='$AR $AR_FLAGS $oldlib$oldobjs'
old_postinstall_cmds='chmod 644 $oldlib'
old_postuninstall_cmds=
if test -n "$RANLIB"; then
case $host_os in
openbsd*)
old_postinstall_cmds="$old_postinstall_cmds~\$RANLIB -t \$tool_oldlib"
;;
*)
old_postinstall_cmds="$old_postinstall_cmds~\$RANLIB \$tool_oldlib"
;;
esac
old_archive_cmds="$old_archive_cmds~\$RANLIB \$tool_oldlib"
fi
case $host_os in
darwin*)
lock_old_archive_extraction=yes ;;
*)
lock_old_archive_extraction=no ;;
esac
_LT_DECL([], [old_postinstall_cmds], [2])
_LT_DECL([], [old_postuninstall_cmds], [2])
_LT_TAGDECL([], [old_archive_cmds], [2],
[Commands used to build an old-style archive])
_LT_DECL([], [lock_old_archive_extraction], [0],
[Whether to use a lock for old archive extraction])
])# _LT_CMD_OLD_ARCHIVE
# _LT_COMPILER_OPTION(MESSAGE, VARIABLE-NAME, FLAGS,
# [OUTPUT-FILE], [ACTION-SUCCESS], [ACTION-FAILURE])
# ----------------------------------------------------------------
# Check whether the given compiler option works
AC_DEFUN([_LT_COMPILER_OPTION],
[m4_require([_LT_FILEUTILS_DEFAULTS])dnl
m4_require([_LT_DECL_SED])dnl
AC_CACHE_CHECK([$1], [$2],
[$2=no
m4_if([$4], , [ac_outfile=conftest.$ac_objext], [ac_outfile=$4])
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="$3"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
# The option is referenced via a variable to avoid confusing sed.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [[^ ]]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&AS_MESSAGE_LOG_FD)
(eval "$lt_compile" 2>conftest.err)
ac_status=$?
cat conftest.err >&AS_MESSAGE_LOG_FD
echo "$as_me:$LINENO: \$? = $ac_status" >&AS_MESSAGE_LOG_FD
if (exit $ac_status) && test -s "$ac_outfile"; then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings other than the usual output.
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' >conftest.exp
$SED '/^$/d; /^ *+/d' conftest.err >conftest.er2
if test ! -s conftest.er2 || diff conftest.exp conftest.er2 >/dev/null; then
$2=yes
fi
fi
$RM conftest*
])
if test x"[$]$2" = xyes; then
m4_if([$5], , :, [$5])
else
m4_if([$6], , :, [$6])
fi
])# _LT_COMPILER_OPTION
# Old name:
AU_ALIAS([AC_LIBTOOL_COMPILER_OPTION], [_LT_COMPILER_OPTION])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_LIBTOOL_COMPILER_OPTION], [])
# _LT_LINKER_OPTION(MESSAGE, VARIABLE-NAME, FLAGS,
# [ACTION-SUCCESS], [ACTION-FAILURE])
# ----------------------------------------------------
# Check whether the given linker option works
AC_DEFUN([_LT_LINKER_OPTION],
[m4_require([_LT_FILEUTILS_DEFAULTS])dnl
m4_require([_LT_DECL_SED])dnl
AC_CACHE_CHECK([$1], [$2],
[$2=no
save_LDFLAGS="$LDFLAGS"
LDFLAGS="$LDFLAGS $3"
echo "$lt_simple_link_test_code" > conftest.$ac_ext
if (eval $ac_link 2>conftest.err) && test -s conftest$ac_exeext; then
# The linker can only warn and ignore the option if not recognized
# So say no if there are warnings
if test -s conftest.err; then
# Append any errors to the config.log.
cat conftest.err 1>&AS_MESSAGE_LOG_FD
$ECHO "$_lt_linker_boilerplate" | $SED '/^$/d' > conftest.exp
$SED '/^$/d; /^ *+/d' conftest.err >conftest.er2
if diff conftest.exp conftest.er2 >/dev/null; then
$2=yes
fi
else
$2=yes
fi
fi
$RM -r conftest*
LDFLAGS="$save_LDFLAGS"
])
if test x"[$]$2" = xyes; then
m4_if([$4], , :, [$4])
else
m4_if([$5], , :, [$5])
fi
])# _LT_LINKER_OPTION
# Old name:
AU_ALIAS([AC_LIBTOOL_LINKER_OPTION], [_LT_LINKER_OPTION])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_LIBTOOL_LINKER_OPTION], [])
# LT_CMD_MAX_LEN
#---------------
AC_DEFUN([LT_CMD_MAX_LEN],
[AC_REQUIRE([AC_CANONICAL_HOST])dnl
# find the maximum length of command line arguments
AC_MSG_CHECKING([the maximum length of command line arguments])
AC_CACHE_VAL([lt_cv_sys_max_cmd_len], [dnl
i=0
teststring="ABCD"
case $build_os in
msdosdjgpp*)
# On DJGPP, this test can blow up pretty badly due to problems in libc
# (any single argument exceeding 2000 bytes causes a buffer overrun
# during glob expansion). Even if it were fixed, the result of this
# check would be larger than it should be.
lt_cv_sys_max_cmd_len=12288; # 12K is about right
;;
gnu*)
# Under GNU Hurd, this test is not required because there is
# no limit to the length of command line arguments.
# Libtool will interpret -1 as no limit whatsoever
lt_cv_sys_max_cmd_len=-1;
;;
cygwin* | mingw* | cegcc*)
# On Win9x/ME, this test blows up -- it succeeds, but takes
# about 5 minutes as the teststring grows exponentially.
# Worse, since 9x/ME are not pre-emptively multitasking,
# you end up with a "frozen" computer, even though with patience
# the test eventually succeeds (with a max line length of 256k).
# Instead, let's just punt: use the minimum linelength reported by
# all of the supported platforms: 8192 (on NT/2K/XP).
lt_cv_sys_max_cmd_len=8192;
;;
mint*)
# On MiNT this can take a long time and run out of memory.
lt_cv_sys_max_cmd_len=8192;
;;
amigaos*)
# On AmigaOS with pdksh, this test takes hours, literally.
# So we just punt and use a minimum line length of 8192.
lt_cv_sys_max_cmd_len=8192;
;;
netbsd* | freebsd* | openbsd* | darwin* | dragonfly*)
# This has been around since 386BSD, at least. Likely further.
if test -x /sbin/sysctl; then
lt_cv_sys_max_cmd_len=`/sbin/sysctl -n kern.argmax`
elif test -x /usr/sbin/sysctl; then
lt_cv_sys_max_cmd_len=`/usr/sbin/sysctl -n kern.argmax`
else
lt_cv_sys_max_cmd_len=65536 # usable default for all BSDs
fi
# And add a safety zone
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \/ 4`
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \* 3`
;;
interix*)
# We know the value 262144 and hardcode it with a safety zone (like BSD)
lt_cv_sys_max_cmd_len=196608
;;
os2*)
# The test takes a long time on OS/2.
lt_cv_sys_max_cmd_len=8192
;;
osf*)
# Dr. Hans Ekkehard Plesser reports seeing a kernel panic running configure
# due to this test when exec_disable_arg_limit is 1 on Tru64. It is not
# nice to cause kernel panics so lets avoid the loop below.
# First set a reasonable default.
lt_cv_sys_max_cmd_len=16384
#
if test -x /sbin/sysconfig; then
case `/sbin/sysconfig -q proc exec_disable_arg_limit` in
*1*) lt_cv_sys_max_cmd_len=-1 ;;
esac
fi
;;
sco3.2v5*)
lt_cv_sys_max_cmd_len=102400
;;
sysv5* | sco5v6* | sysv4.2uw2*)
kargmax=`grep ARG_MAX /etc/conf/cf.d/stune 2>/dev/null`
if test -n "$kargmax"; then
lt_cv_sys_max_cmd_len=`echo $kargmax | sed 's/.*[[ ]]//'`
else
lt_cv_sys_max_cmd_len=32768
fi
;;
*)
lt_cv_sys_max_cmd_len=`(getconf ARG_MAX) 2> /dev/null`
if test -n "$lt_cv_sys_max_cmd_len"; then
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \/ 4`
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \* 3`
else
# Make teststring a little bigger before we do anything with it.
# a 1K string should be a reasonable start.
for i in 1 2 3 4 5 6 7 8 ; do
teststring=$teststring$teststring
done
SHELL=${SHELL-${CONFIG_SHELL-/bin/sh}}
# If test is not a shell built-in, we'll probably end up computing a
# maximum length that is only half of the actual maximum length, but
# we can't tell.
while { test "X"`env echo "$teststring$teststring" 2>/dev/null` \
= "X$teststring$teststring"; } >/dev/null 2>&1 &&
test $i != 17 # 1/2 MB should be enough
do
i=`expr $i + 1`
teststring=$teststring$teststring
done
# Only check the string length outside the loop.
lt_cv_sys_max_cmd_len=`expr "X$teststring" : ".*" 2>&1`
teststring=
# Add a significant safety factor because C++ compilers can tack on
# massive amounts of additional arguments before passing them to the
# linker. It appears as though 1/2 is a usable value.
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \/ 2`
fi
;;
esac
])
if test -n $lt_cv_sys_max_cmd_len ; then
AC_MSG_RESULT($lt_cv_sys_max_cmd_len)
else
AC_MSG_RESULT(none)
fi
max_cmd_len=$lt_cv_sys_max_cmd_len
_LT_DECL([], [max_cmd_len], [0],
[What is the maximum length of a command?])
])# LT_CMD_MAX_LEN
# Old name:
AU_ALIAS([AC_LIBTOOL_SYS_MAX_CMD_LEN], [LT_CMD_MAX_LEN])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_LIBTOOL_SYS_MAX_CMD_LEN], [])
# _LT_HEADER_DLFCN
# ----------------
m4_defun([_LT_HEADER_DLFCN],
[AC_CHECK_HEADERS([dlfcn.h], [], [], [AC_INCLUDES_DEFAULT])dnl
])# _LT_HEADER_DLFCN
# _LT_TRY_DLOPEN_SELF (ACTION-IF-TRUE, ACTION-IF-TRUE-W-USCORE,
# ACTION-IF-FALSE, ACTION-IF-CROSS-COMPILING)
# ----------------------------------------------------------------
m4_defun([_LT_TRY_DLOPEN_SELF],
[m4_require([_LT_HEADER_DLFCN])dnl
if test "$cross_compiling" = yes; then :
[$4]
else
lt_dlunknown=0; lt_dlno_uscore=1; lt_dlneed_uscore=2
lt_status=$lt_dlunknown
cat > conftest.$ac_ext <<_LT_EOF
[#line $LINENO "configure"
#include "confdefs.h"
#if HAVE_DLFCN_H
#include
#endif
#include
#ifdef RTLD_GLOBAL
# define LT_DLGLOBAL RTLD_GLOBAL
#else
# ifdef DL_GLOBAL
# define LT_DLGLOBAL DL_GLOBAL
# else
# define LT_DLGLOBAL 0
# endif
#endif
/* We may have to define LT_DLLAZY_OR_NOW in the command line if we
find out it does not work in some platform. */
#ifndef LT_DLLAZY_OR_NOW
# ifdef RTLD_LAZY
# define LT_DLLAZY_OR_NOW RTLD_LAZY
# else
# ifdef DL_LAZY
# define LT_DLLAZY_OR_NOW DL_LAZY
# else
# ifdef RTLD_NOW
# define LT_DLLAZY_OR_NOW RTLD_NOW
# else
# ifdef DL_NOW
# define LT_DLLAZY_OR_NOW DL_NOW
# else
# define LT_DLLAZY_OR_NOW 0
# endif
# endif
# endif
# endif
#endif
/* When -fvisbility=hidden is used, assume the code has been annotated
correspondingly for the symbols needed. */
#if defined(__GNUC__) && (((__GNUC__ == 3) && (__GNUC_MINOR__ >= 3)) || (__GNUC__ > 3))
int fnord () __attribute__((visibility("default")));
#endif
int fnord () { return 42; }
int main ()
{
void *self = dlopen (0, LT_DLGLOBAL|LT_DLLAZY_OR_NOW);
int status = $lt_dlunknown;
if (self)
{
if (dlsym (self,"fnord")) status = $lt_dlno_uscore;
else
{
if (dlsym( self,"_fnord")) status = $lt_dlneed_uscore;
else puts (dlerror ());
}
/* dlclose (self); */
}
else
puts (dlerror ());
return status;
}]
_LT_EOF
if AC_TRY_EVAL(ac_link) && test -s conftest${ac_exeext} 2>/dev/null; then
(./conftest; exit; ) >&AS_MESSAGE_LOG_FD 2>/dev/null
lt_status=$?
case x$lt_status in
x$lt_dlno_uscore) $1 ;;
x$lt_dlneed_uscore) $2 ;;
x$lt_dlunknown|x*) $3 ;;
esac
else :
# compilation failed
$3
fi
fi
rm -fr conftest*
])# _LT_TRY_DLOPEN_SELF
# LT_SYS_DLOPEN_SELF
# ------------------
AC_DEFUN([LT_SYS_DLOPEN_SELF],
[m4_require([_LT_HEADER_DLFCN])dnl
if test "x$enable_dlopen" != xyes; then
enable_dlopen=unknown
enable_dlopen_self=unknown
enable_dlopen_self_static=unknown
else
lt_cv_dlopen=no
lt_cv_dlopen_libs=
case $host_os in
beos*)
lt_cv_dlopen="load_add_on"
lt_cv_dlopen_libs=
lt_cv_dlopen_self=yes
;;
mingw* | pw32* | cegcc*)
lt_cv_dlopen="LoadLibrary"
lt_cv_dlopen_libs=
;;
cygwin*)
lt_cv_dlopen="dlopen"
lt_cv_dlopen_libs=
;;
darwin*)
# if libdl is installed we need to link against it
AC_CHECK_LIB([dl], [dlopen],
[lt_cv_dlopen="dlopen" lt_cv_dlopen_libs="-ldl"],[
lt_cv_dlopen="dyld"
lt_cv_dlopen_libs=
lt_cv_dlopen_self=yes
])
;;
*)
AC_CHECK_FUNC([shl_load],
[lt_cv_dlopen="shl_load"],
[AC_CHECK_LIB([dld], [shl_load],
[lt_cv_dlopen="shl_load" lt_cv_dlopen_libs="-ldld"],
[AC_CHECK_FUNC([dlopen],
[lt_cv_dlopen="dlopen"],
[AC_CHECK_LIB([dl], [dlopen],
[lt_cv_dlopen="dlopen" lt_cv_dlopen_libs="-ldl"],
[AC_CHECK_LIB([svld], [dlopen],
[lt_cv_dlopen="dlopen" lt_cv_dlopen_libs="-lsvld"],
[AC_CHECK_LIB([dld], [dld_link],
[lt_cv_dlopen="dld_link" lt_cv_dlopen_libs="-ldld"])
])
])
])
])
])
;;
esac
if test "x$lt_cv_dlopen" != xno; then
enable_dlopen=yes
else
enable_dlopen=no
fi
case $lt_cv_dlopen in
dlopen)
save_CPPFLAGS="$CPPFLAGS"
test "x$ac_cv_header_dlfcn_h" = xyes && CPPFLAGS="$CPPFLAGS -DHAVE_DLFCN_H"
save_LDFLAGS="$LDFLAGS"
wl=$lt_prog_compiler_wl eval LDFLAGS=\"\$LDFLAGS $export_dynamic_flag_spec\"
save_LIBS="$LIBS"
LIBS="$lt_cv_dlopen_libs $LIBS"
AC_CACHE_CHECK([whether a program can dlopen itself],
lt_cv_dlopen_self, [dnl
_LT_TRY_DLOPEN_SELF(
lt_cv_dlopen_self=yes, lt_cv_dlopen_self=yes,
lt_cv_dlopen_self=no, lt_cv_dlopen_self=cross)
])
if test "x$lt_cv_dlopen_self" = xyes; then
wl=$lt_prog_compiler_wl eval LDFLAGS=\"\$LDFLAGS $lt_prog_compiler_static\"
AC_CACHE_CHECK([whether a statically linked program can dlopen itself],
lt_cv_dlopen_self_static, [dnl
_LT_TRY_DLOPEN_SELF(
lt_cv_dlopen_self_static=yes, lt_cv_dlopen_self_static=yes,
lt_cv_dlopen_self_static=no, lt_cv_dlopen_self_static=cross)
])
fi
CPPFLAGS="$save_CPPFLAGS"
LDFLAGS="$save_LDFLAGS"
LIBS="$save_LIBS"
;;
esac
case $lt_cv_dlopen_self in
yes|no) enable_dlopen_self=$lt_cv_dlopen_self ;;
*) enable_dlopen_self=unknown ;;
esac
case $lt_cv_dlopen_self_static in
yes|no) enable_dlopen_self_static=$lt_cv_dlopen_self_static ;;
*) enable_dlopen_self_static=unknown ;;
esac
fi
_LT_DECL([dlopen_support], [enable_dlopen], [0],
[Whether dlopen is supported])
_LT_DECL([dlopen_self], [enable_dlopen_self], [0],
[Whether dlopen of programs is supported])
_LT_DECL([dlopen_self_static], [enable_dlopen_self_static], [0],
[Whether dlopen of statically linked programs is supported])
])# LT_SYS_DLOPEN_SELF
# Old name:
AU_ALIAS([AC_LIBTOOL_DLOPEN_SELF], [LT_SYS_DLOPEN_SELF])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_LIBTOOL_DLOPEN_SELF], [])
# _LT_COMPILER_C_O([TAGNAME])
# ---------------------------
# Check to see if options -c and -o are simultaneously supported by compiler.
# This macro does not hard code the compiler like AC_PROG_CC_C_O.
m4_defun([_LT_COMPILER_C_O],
[m4_require([_LT_DECL_SED])dnl
m4_require([_LT_FILEUTILS_DEFAULTS])dnl
m4_require([_LT_TAG_COMPILER])dnl
AC_CACHE_CHECK([if $compiler supports -c -o file.$ac_objext],
[_LT_TAGVAR(lt_cv_prog_compiler_c_o, $1)],
[_LT_TAGVAR(lt_cv_prog_compiler_c_o, $1)=no
$RM -r conftest 2>/dev/null
mkdir conftest
cd conftest
mkdir out
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="-o out/conftest2.$ac_objext"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [[^ ]]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&AS_MESSAGE_LOG_FD)
(eval "$lt_compile" 2>out/conftest.err)
ac_status=$?
cat out/conftest.err >&AS_MESSAGE_LOG_FD
echo "$as_me:$LINENO: \$? = $ac_status" >&AS_MESSAGE_LOG_FD
if (exit $ac_status) && test -s out/conftest2.$ac_objext
then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' > out/conftest.exp
$SED '/^$/d; /^ *+/d' out/conftest.err >out/conftest.er2
if test ! -s out/conftest.er2 || diff out/conftest.exp out/conftest.er2 >/dev/null; then
_LT_TAGVAR(lt_cv_prog_compiler_c_o, $1)=yes
fi
fi
chmod u+w . 2>&AS_MESSAGE_LOG_FD
$RM conftest*
# SGI C++ compiler will create directory out/ii_files/ for
# template instantiation
test -d out/ii_files && $RM out/ii_files/* && rmdir out/ii_files
$RM out/* && rmdir out
cd ..
$RM -r conftest
$RM conftest*
])
_LT_TAGDECL([compiler_c_o], [lt_cv_prog_compiler_c_o], [1],
[Does compiler simultaneously support -c and -o options?])
])# _LT_COMPILER_C_O
# _LT_COMPILER_FILE_LOCKS([TAGNAME])
# ----------------------------------
# Check to see if we can do hard links to lock some files if needed
m4_defun([_LT_COMPILER_FILE_LOCKS],
[m4_require([_LT_ENABLE_LOCK])dnl
m4_require([_LT_FILEUTILS_DEFAULTS])dnl
_LT_COMPILER_C_O([$1])
hard_links="nottested"
if test "$_LT_TAGVAR(lt_cv_prog_compiler_c_o, $1)" = no && test "$need_locks" != no; then
# do not overwrite the value of need_locks provided by the user
AC_MSG_CHECKING([if we can lock with hard links])
hard_links=yes
$RM conftest*
ln conftest.a conftest.b 2>/dev/null && hard_links=no
touch conftest.a
ln conftest.a conftest.b 2>&5 || hard_links=no
ln conftest.a conftest.b 2>/dev/null && hard_links=no
AC_MSG_RESULT([$hard_links])
if test "$hard_links" = no; then
AC_MSG_WARN([`$CC' does not support `-c -o', so `make -j' may be unsafe])
need_locks=warn
fi
else
need_locks=no
fi
_LT_DECL([], [need_locks], [1], [Must we lock files when doing compilation?])
])# _LT_COMPILER_FILE_LOCKS
# _LT_CHECK_OBJDIR
# ----------------
m4_defun([_LT_CHECK_OBJDIR],
[AC_CACHE_CHECK([for objdir], [lt_cv_objdir],
[rm -f .libs 2>/dev/null
mkdir .libs 2>/dev/null
if test -d .libs; then
lt_cv_objdir=.libs
else
# MS-DOS does not allow filenames that begin with a dot.
lt_cv_objdir=_libs
fi
rmdir .libs 2>/dev/null])
objdir=$lt_cv_objdir
_LT_DECL([], [objdir], [0],
[The name of the directory that contains temporary libtool files])dnl
m4_pattern_allow([LT_OBJDIR])dnl
AC_DEFINE_UNQUOTED(LT_OBJDIR, "$lt_cv_objdir/",
[Define to the sub-directory in which libtool stores uninstalled libraries.])
])# _LT_CHECK_OBJDIR
# _LT_LINKER_HARDCODE_LIBPATH([TAGNAME])
# --------------------------------------
# Check hardcoding attributes.
m4_defun([_LT_LINKER_HARDCODE_LIBPATH],
[AC_MSG_CHECKING([how to hardcode library paths into programs])
_LT_TAGVAR(hardcode_action, $1)=
if test -n "$_LT_TAGVAR(hardcode_libdir_flag_spec, $1)" ||
test -n "$_LT_TAGVAR(runpath_var, $1)" ||
test "X$_LT_TAGVAR(hardcode_automatic, $1)" = "Xyes" ; then
# We can hardcode non-existent directories.
if test "$_LT_TAGVAR(hardcode_direct, $1)" != no &&
# If the only mechanism to avoid hardcoding is shlibpath_var, we
# have to relink, otherwise we might link with an installed library
# when we should be linking with a yet-to-be-installed one
## test "$_LT_TAGVAR(hardcode_shlibpath_var, $1)" != no &&
test "$_LT_TAGVAR(hardcode_minus_L, $1)" != no; then
# Linking always hardcodes the temporary library directory.
_LT_TAGVAR(hardcode_action, $1)=relink
else
# We can link without hardcoding, and we can hardcode nonexisting dirs.
_LT_TAGVAR(hardcode_action, $1)=immediate
fi
else
# We cannot hardcode anything, or else we can only hardcode existing
# directories.
_LT_TAGVAR(hardcode_action, $1)=unsupported
fi
AC_MSG_RESULT([$_LT_TAGVAR(hardcode_action, $1)])
if test "$_LT_TAGVAR(hardcode_action, $1)" = relink ||
test "$_LT_TAGVAR(inherit_rpath, $1)" = yes; then
# Fast installation is not supported
enable_fast_install=no
elif test "$shlibpath_overrides_runpath" = yes ||
test "$enable_shared" = no; then
# Fast installation is not necessary
enable_fast_install=needless
fi
_LT_TAGDECL([], [hardcode_action], [0],
[How to hardcode a shared library path into an executable])
])# _LT_LINKER_HARDCODE_LIBPATH
# _LT_CMD_STRIPLIB
# ----------------
m4_defun([_LT_CMD_STRIPLIB],
[m4_require([_LT_DECL_EGREP])
striplib=
old_striplib=
AC_MSG_CHECKING([whether stripping libraries is possible])
if test -n "$STRIP" && $STRIP -V 2>&1 | $GREP "GNU strip" >/dev/null; then
test -z "$old_striplib" && old_striplib="$STRIP --strip-debug"
test -z "$striplib" && striplib="$STRIP --strip-unneeded"
AC_MSG_RESULT([yes])
else
# FIXME - insert some real tests, host_os isn't really good enough
case $host_os in
darwin*)
if test -n "$STRIP" ; then
striplib="$STRIP -x"
old_striplib="$STRIP -S"
AC_MSG_RESULT([yes])
else
AC_MSG_RESULT([no])
fi
;;
*)
AC_MSG_RESULT([no])
;;
esac
fi
_LT_DECL([], [old_striplib], [1], [Commands to strip libraries])
_LT_DECL([], [striplib], [1])
])# _LT_CMD_STRIPLIB
# _LT_SYS_DYNAMIC_LINKER([TAG])
# -----------------------------
# PORTME Fill in your ld.so characteristics
m4_defun([_LT_SYS_DYNAMIC_LINKER],
[AC_REQUIRE([AC_CANONICAL_HOST])dnl
m4_require([_LT_DECL_EGREP])dnl
m4_require([_LT_FILEUTILS_DEFAULTS])dnl
m4_require([_LT_DECL_OBJDUMP])dnl
m4_require([_LT_DECL_SED])dnl
m4_require([_LT_CHECK_SHELL_FEATURES])dnl
AC_MSG_CHECKING([dynamic linker characteristics])
m4_if([$1],
[], [
if test "$GCC" = yes; then
case $host_os in
darwin*) lt_awk_arg="/^libraries:/,/LR/" ;;
*) lt_awk_arg="/^libraries:/" ;;
esac
case $host_os in
mingw* | cegcc*) lt_sed_strip_eq="s,=\([[A-Za-z]]:\),\1,g" ;;
*) lt_sed_strip_eq="s,=/,/,g" ;;
esac
lt_search_path_spec=`$CC -print-search-dirs | awk $lt_awk_arg | $SED -e "s/^libraries://" -e $lt_sed_strip_eq`
case $lt_search_path_spec in
*\;*)
# if the path contains ";" then we assume it to be the separator
# otherwise default to the standard path separator (i.e. ":") - it is
# assumed that no part of a normal pathname contains ";" but that should
# okay in the real world where ";" in dirpaths is itself problematic.
lt_search_path_spec=`$ECHO "$lt_search_path_spec" | $SED 's/;/ /g'`
;;
*)
lt_search_path_spec=`$ECHO "$lt_search_path_spec" | $SED "s/$PATH_SEPARATOR/ /g"`
;;
esac
# Ok, now we have the path, separated by spaces, we can step through it
# and add multilib dir if necessary.
lt_tmp_lt_search_path_spec=
lt_multi_os_dir=`$CC $CPPFLAGS $CFLAGS $LDFLAGS -print-multi-os-directory 2>/dev/null`
for lt_sys_path in $lt_search_path_spec; do
if test -d "$lt_sys_path/$lt_multi_os_dir"; then
lt_tmp_lt_search_path_spec="$lt_tmp_lt_search_path_spec $lt_sys_path/$lt_multi_os_dir"
else
test -d "$lt_sys_path" && \
lt_tmp_lt_search_path_spec="$lt_tmp_lt_search_path_spec $lt_sys_path"
fi
done
lt_search_path_spec=`$ECHO "$lt_tmp_lt_search_path_spec" | awk '
BEGIN {RS=" "; FS="/|\n";} {
lt_foo="";
lt_count=0;
for (lt_i = NF; lt_i > 0; lt_i--) {
if ($lt_i != "" && $lt_i != ".") {
if ($lt_i == "..") {
lt_count++;
} else {
if (lt_count == 0) {
lt_foo="/" $lt_i lt_foo;
} else {
lt_count--;
}
}
}
}
if (lt_foo != "") { lt_freq[[lt_foo]]++; }
if (lt_freq[[lt_foo]] == 1) { print lt_foo; }
}'`
# AWK program above erroneously prepends '/' to C:/dos/paths
# for these hosts.
case $host_os in
mingw* | cegcc*) lt_search_path_spec=`$ECHO "$lt_search_path_spec" |\
$SED 's,/\([[A-Za-z]]:\),\1,g'` ;;
esac
sys_lib_search_path_spec=`$ECHO "$lt_search_path_spec" | $lt_NL2SP`
else
sys_lib_search_path_spec="/lib /usr/lib /usr/local/lib"
fi])
library_names_spec=
libname_spec='lib$name'
soname_spec=
shrext_cmds=".so"
postinstall_cmds=
postuninstall_cmds=
finish_cmds=
finish_eval=
shlibpath_var=
shlibpath_overrides_runpath=unknown
version_type=none
dynamic_linker="$host_os ld.so"
sys_lib_dlsearch_path_spec="/lib /usr/lib"
need_lib_prefix=unknown
hardcode_into_libs=no
# when you set need_version to no, make sure it does not cause -set_version
# flags to be left without arguments
need_version=unknown
case $host_os in
aix3*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix $libname.a'
shlibpath_var=LIBPATH
# AIX 3 has no versioning support, so we append a major version to the name.
soname_spec='${libname}${release}${shared_ext}$major'
;;
aix[[4-9]]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
hardcode_into_libs=yes
if test "$host_cpu" = ia64; then
# AIX 5 supports IA64
library_names_spec='${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext}$versuffix $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
else
# With GCC up to 2.95.x, collect2 would create an import file
# for dependence libraries. The import file would start with
# the line `#! .'. This would cause the generated library to
# depend on `.', always an invalid library. This was fixed in
# development snapshots of GCC prior to 3.0.
case $host_os in
aix4 | aix4.[[01]] | aix4.[[01]].*)
if { echo '#if __GNUC__ > 2 || (__GNUC__ == 2 && __GNUC_MINOR__ >= 97)'
echo ' yes '
echo '#endif'; } | ${CC} -E - | $GREP yes > /dev/null; then
:
else
can_build_shared=no
fi
;;
esac
# AIX (on Power*) has no versioning support, so currently we can not hardcode correct
# soname into executable. Probably we can add versioning support to
# collect2, so additional links can be useful in future.
if test "$aix_use_runtimelinking" = yes; then
# If using run time linking (on AIX 4.2 or later) use lib.so
# instead of lib.a to let people know that these are not
# typical AIX shared libraries.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
else
# We preserve .a as extension for shared libraries through AIX4.2
# and later when we are not doing run time linking.
library_names_spec='${libname}${release}.a $libname.a'
soname_spec='${libname}${release}${shared_ext}$major'
fi
shlibpath_var=LIBPATH
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# Since July 2007 AmigaOS4 officially supports .so libraries.
# When compiling the executable, add -use-dynld -Lsobjs: to the compileline.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
;;
m68k)
library_names_spec='$libname.ixlibrary $libname.a'
# Create ${libname}_ixlibrary.a entries in /sys/libs.
finish_eval='for lib in `ls $libdir/*.ixlibrary 2>/dev/null`; do libname=`func_echo_all "$lib" | $SED '\''s%^.*/\([[^/]]*\)\.ixlibrary$%\1%'\''`; test $RM /sys/libs/${libname}_ixlibrary.a; $show "cd /sys/libs && $LN_S $lib ${libname}_ixlibrary.a"; cd /sys/libs && $LN_S $lib ${libname}_ixlibrary.a || exit 1; done'
;;
esac
;;
beos*)
library_names_spec='${libname}${shared_ext}'
dynamic_linker="$host_os ld.so"
shlibpath_var=LIBRARY_PATH
;;
bsdi[[45]]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
finish_cmds='PATH="\$PATH:/sbin" ldconfig $libdir'
shlibpath_var=LD_LIBRARY_PATH
sys_lib_search_path_spec="/shlib /usr/lib /usr/X11/lib /usr/contrib/lib /lib /usr/local/lib"
sys_lib_dlsearch_path_spec="/shlib /usr/lib /usr/local/lib"
# the default ld.so.conf also contains /usr/contrib/lib and
# /usr/X11R6/lib (/usr/X11 is a link to /usr/X11R6), but let us allow
# libtool to hard-code these into programs
;;
cygwin* | mingw* | pw32* | cegcc*)
version_type=windows
shrext_cmds=".dll"
need_version=no
need_lib_prefix=no
case $GCC,$cc_basename in
yes,*)
# gcc
library_names_spec='$libname.dll.a'
# DLL is installed to $(libdir)/../bin by postinstall_cmds
postinstall_cmds='base_file=`basename \${file}`~
dlpath=`$SHELL 2>&1 -c '\''. $dir/'\''\${base_file}'\''i; echo \$dlname'\''`~
dldir=$destdir/`dirname \$dlpath`~
test -d \$dldir || mkdir -p \$dldir~
$install_prog $dir/$dlname \$dldir/$dlname~
chmod a+x \$dldir/$dlname~
if test -n '\''$stripme'\'' && test -n '\''$striplib'\''; then
eval '\''$striplib \$dldir/$dlname'\'' || exit \$?;
fi'
postuninstall_cmds='dldll=`$SHELL 2>&1 -c '\''. $file; echo \$dlname'\''`~
dlpath=$dir/\$dldll~
$RM \$dlpath'
shlibpath_overrides_runpath=yes
case $host_os in
cygwin*)
# Cygwin DLLs use 'cyg' prefix rather than 'lib'
soname_spec='`echo ${libname} | sed -e 's/^lib/cyg/'``echo ${release} | $SED -e 's/[[.]]/-/g'`${versuffix}${shared_ext}'
m4_if([$1], [],[
sys_lib_search_path_spec="$sys_lib_search_path_spec /usr/lib/w32api"])
;;
mingw* | cegcc*)
# MinGW DLLs use traditional 'lib' prefix
soname_spec='${libname}`echo ${release} | $SED -e 's/[[.]]/-/g'`${versuffix}${shared_ext}'
;;
pw32*)
# pw32 DLLs use 'pw' prefix rather than 'lib'
library_names_spec='`echo ${libname} | sed -e 's/^lib/pw/'``echo ${release} | $SED -e 's/[[.]]/-/g'`${versuffix}${shared_ext}'
;;
esac
dynamic_linker='Win32 ld.exe'
;;
*,cl*)
# Native MSVC
libname_spec='$name'
soname_spec='${libname}`echo ${release} | $SED -e 's/[[.]]/-/g'`${versuffix}${shared_ext}'
library_names_spec='${libname}.dll.lib'
case $build_os in
mingw*)
sys_lib_search_path_spec=
lt_save_ifs=$IFS
IFS=';'
for lt_path in $LIB
do
IFS=$lt_save_ifs
# Let DOS variable expansion print the short 8.3 style file name.
lt_path=`cd "$lt_path" 2>/dev/null && cmd //C "for %i in (".") do @echo %~si"`
sys_lib_search_path_spec="$sys_lib_search_path_spec $lt_path"
done
IFS=$lt_save_ifs
# Convert to MSYS style.
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | sed -e 's|\\\\|/|g' -e 's| \\([[a-zA-Z]]\\):| /\\1|g' -e 's|^ ||'`
;;
cygwin*)
# Convert to unix form, then to dos form, then back to unix form
# but this time dos style (no spaces!) so that the unix form looks
# like /cygdrive/c/PROGRA~1:/cygdr...
sys_lib_search_path_spec=`cygpath --path --unix "$LIB"`
sys_lib_search_path_spec=`cygpath --path --dos "$sys_lib_search_path_spec" 2>/dev/null`
sys_lib_search_path_spec=`cygpath --path --unix "$sys_lib_search_path_spec" | $SED -e "s/$PATH_SEPARATOR/ /g"`
;;
*)
sys_lib_search_path_spec="$LIB"
if $ECHO "$sys_lib_search_path_spec" | [$GREP ';[c-zC-Z]:/' >/dev/null]; then
# It is most probably a Windows format PATH.
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | $SED -e 's/;/ /g'`
else
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | $SED -e "s/$PATH_SEPARATOR/ /g"`
fi
# FIXME: find the short name or the path components, as spaces are
# common. (e.g. "Program Files" -> "PROGRA~1")
;;
esac
# DLL is installed to $(libdir)/../bin by postinstall_cmds
postinstall_cmds='base_file=`basename \${file}`~
dlpath=`$SHELL 2>&1 -c '\''. $dir/'\''\${base_file}'\''i; echo \$dlname'\''`~
dldir=$destdir/`dirname \$dlpath`~
test -d \$dldir || mkdir -p \$dldir~
$install_prog $dir/$dlname \$dldir/$dlname'
postuninstall_cmds='dldll=`$SHELL 2>&1 -c '\''. $file; echo \$dlname'\''`~
dlpath=$dir/\$dldll~
$RM \$dlpath'
shlibpath_overrides_runpath=yes
dynamic_linker='Win32 link.exe'
;;
*)
# Assume MSVC wrapper
library_names_spec='${libname}`echo ${release} | $SED -e 's/[[.]]/-/g'`${versuffix}${shared_ext} $libname.lib'
dynamic_linker='Win32 ld.exe'
;;
esac
# FIXME: first we should search . and the directory the executable is in
shlibpath_var=PATH
;;
darwin* | rhapsody*)
dynamic_linker="$host_os dyld"
version_type=darwin
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${major}$shared_ext ${libname}$shared_ext'
soname_spec='${libname}${release}${major}$shared_ext'
shlibpath_overrides_runpath=yes
shlibpath_var=DYLD_LIBRARY_PATH
shrext_cmds='`test .$module = .yes && echo .so || echo .dylib`'
m4_if([$1], [],[
sys_lib_search_path_spec="$sys_lib_search_path_spec /usr/local/lib"])
sys_lib_dlsearch_path_spec='/usr/local/lib /lib /usr/lib'
;;
dgux*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname$shared_ext'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
;;
freebsd* | dragonfly*)
# DragonFly does not have aout. When/if they implement a new
# versioning mechanism, adjust this.
if test -x /usr/bin/objformat; then
objformat=`/usr/bin/objformat`
else
case $host_os in
freebsd[[23]].*) objformat=aout ;;
*) objformat=elf ;;
esac
fi
version_type=freebsd-$objformat
case $version_type in
freebsd-elf*)
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext} $libname${shared_ext}'
need_version=no
need_lib_prefix=no
;;
freebsd-*)
library_names_spec='${libname}${release}${shared_ext}$versuffix $libname${shared_ext}$versuffix'
need_version=yes
;;
esac
shlibpath_var=LD_LIBRARY_PATH
case $host_os in
freebsd2.*)
shlibpath_overrides_runpath=yes
;;
freebsd3.[[01]]* | freebsdelf3.[[01]]*)
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
freebsd3.[[2-9]]* | freebsdelf3.[[2-9]]* | \
freebsd4.[[0-5]] | freebsdelf4.[[0-5]] | freebsd4.1.1 | freebsdelf4.1.1)
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
*) # from 4.6 on, and DragonFly
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
esac
;;
gnu*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
haiku*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
dynamic_linker="$host_os runtime_loader"
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LIBRARY_PATH
shlibpath_overrides_runpath=yes
sys_lib_dlsearch_path_spec='/boot/home/config/lib /boot/common/lib /boot/system/lib'
hardcode_into_libs=yes
;;
hpux9* | hpux10* | hpux11*)
# Give a soname corresponding to the major version so that dld.sl refuses to
# link against other versions.
version_type=sunos
need_lib_prefix=no
need_version=no
case $host_cpu in
ia64*)
shrext_cmds='.so'
hardcode_into_libs=yes
dynamic_linker="$host_os dld.so"
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes # Unless +noenvvar is specified.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
if test "X$HPUX_IA64_MODE" = X32; then
sys_lib_search_path_spec="/usr/lib/hpux32 /usr/local/lib/hpux32 /usr/local/lib"
else
sys_lib_search_path_spec="/usr/lib/hpux64 /usr/local/lib/hpux64"
fi
sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec
;;
hppa*64*)
shrext_cmds='.sl'
hardcode_into_libs=yes
dynamic_linker="$host_os dld.sl"
shlibpath_var=LD_LIBRARY_PATH # How should we handle SHLIB_PATH
shlibpath_overrides_runpath=yes # Unless +noenvvar is specified.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
sys_lib_search_path_spec="/usr/lib/pa20_64 /usr/ccs/lib/pa20_64"
sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec
;;
*)
shrext_cmds='.sl'
dynamic_linker="$host_os dld.sl"
shlibpath_var=SHLIB_PATH
shlibpath_overrides_runpath=no # +s is required to enable SHLIB_PATH
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
;;
esac
# HP-UX runs *really* slowly unless shared libraries are mode 555, ...
postinstall_cmds='chmod 555 $lib'
# or fails outright, so override atomically:
install_override_mode=555
;;
interix[[3-9]]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
dynamic_linker='Interix 3.x ld.so.1 (PE, like ELF)'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
irix5* | irix6* | nonstopux*)
case $host_os in
nonstopux*) version_type=nonstopux ;;
*)
if test "$lt_cv_prog_gnu_ld" = yes; then
version_type=linux # correct to gnu/linux during the next big refactor
else
version_type=irix
fi ;;
esac
need_lib_prefix=no
need_version=no
soname_spec='${libname}${release}${shared_ext}$major'
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext} $libname${shared_ext}'
case $host_os in
irix5* | nonstopux*)
libsuff= shlibsuff=
;;
*)
case $LD in # libtool.m4 will add one of these switches to LD
*-32|*"-32 "|*-melf32bsmip|*"-melf32bsmip ")
libsuff= shlibsuff= libmagic=32-bit;;
*-n32|*"-n32 "|*-melf32bmipn32|*"-melf32bmipn32 ")
libsuff=32 shlibsuff=N32 libmagic=N32;;
*-64|*"-64 "|*-melf64bmip|*"-melf64bmip ")
libsuff=64 shlibsuff=64 libmagic=64-bit;;
*) libsuff= shlibsuff= libmagic=never-match;;
esac
;;
esac
shlibpath_var=LD_LIBRARY${shlibsuff}_PATH
shlibpath_overrides_runpath=no
sys_lib_search_path_spec="/usr/lib${libsuff} /lib${libsuff} /usr/local/lib${libsuff}"
sys_lib_dlsearch_path_spec="/usr/lib${libsuff} /lib${libsuff}"
hardcode_into_libs=yes
;;
# No shared lib support for Linux oldld, aout, or coff.
linux*oldld* | linux*aout* | linux*coff*)
dynamic_linker=no
;;
# This must be glibc/ELF.
linux* | k*bsd*-gnu | kopensolaris*-gnu)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -n $libdir'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
# Some binutils ld are patched to set DT_RUNPATH
AC_CACHE_VAL([lt_cv_shlibpath_overrides_runpath],
[lt_cv_shlibpath_overrides_runpath=no
save_LDFLAGS=$LDFLAGS
save_libdir=$libdir
eval "libdir=/foo; wl=\"$_LT_TAGVAR(lt_prog_compiler_wl, $1)\"; \
LDFLAGS=\"\$LDFLAGS $_LT_TAGVAR(hardcode_libdir_flag_spec, $1)\""
AC_LINK_IFELSE([AC_LANG_PROGRAM([],[])],
[AS_IF([ ($OBJDUMP -p conftest$ac_exeext) 2>/dev/null | grep "RUNPATH.*$libdir" >/dev/null],
[lt_cv_shlibpath_overrides_runpath=yes])])
LDFLAGS=$save_LDFLAGS
libdir=$save_libdir
])
shlibpath_overrides_runpath=$lt_cv_shlibpath_overrides_runpath
# This implies no fast_install, which is unacceptable.
# Some rework will be needed to allow for fast_install
# before this can be enabled.
hardcode_into_libs=yes
# Add ABI-specific directories to the system library path.
sys_lib_dlsearch_path_spec="/lib64 /usr/lib64 /lib /usr/lib"
# Append ld.so.conf contents to the search path
if test -f /etc/ld.so.conf; then
lt_ld_extra=`awk '/^include / { system(sprintf("cd /etc; cat %s 2>/dev/null", \[$]2)); skip = 1; } { if (!skip) print \[$]0; skip = 0; }' < /etc/ld.so.conf | $SED -e 's/#.*//;/^[ ]*hwcap[ ]/d;s/[:, ]/ /g;s/=[^=]*$//;s/=[^= ]* / /g;s/"//g;/^$/d' | tr '\n' ' '`
sys_lib_dlsearch_path_spec="$sys_lib_dlsearch_path_spec $lt_ld_extra"
fi
# We used to test for /lib/ld.so.1 and disable shared libraries on
# powerpc, because MkLinux only supported shared libraries with the
# GNU dynamic linker. Since this was broken with cross compilers,
# most powerpc-linux boxes support dynamic linking these days and
# people can always --disable-shared, the test was removed, and we
# assume the GNU/Linux dynamic linker is in use.
dynamic_linker='GNU/Linux ld.so'
;;
netbsd*)
version_type=sunos
need_lib_prefix=no
need_version=no
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -m $libdir'
dynamic_linker='NetBSD (a.out) ld.so'
else
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
dynamic_linker='NetBSD ld.elf_so'
fi
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
newsos6)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
;;
*nto* | *qnx*)
version_type=qnx
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
dynamic_linker='ldqnx.so'
;;
openbsd*)
version_type=sunos
sys_lib_dlsearch_path_spec="/usr/lib"
need_lib_prefix=no
# Some older versions of OpenBSD (3.3 at least) *do* need versioned libs.
case $host_os in
openbsd3.3 | openbsd3.3.*) need_version=yes ;;
*) need_version=no ;;
esac
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -m $libdir'
shlibpath_var=LD_LIBRARY_PATH
if test -z "`echo __ELF__ | $CC -E - | $GREP __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
case $host_os in
openbsd2.[[89]] | openbsd2.[[89]].*)
shlibpath_overrides_runpath=no
;;
*)
shlibpath_overrides_runpath=yes
;;
esac
else
shlibpath_overrides_runpath=yes
fi
;;
os2*)
libname_spec='$name'
shrext_cmds=".dll"
need_lib_prefix=no
library_names_spec='$libname${shared_ext} $libname.a'
dynamic_linker='OS/2 ld.exe'
shlibpath_var=LIBPATH
;;
osf3* | osf4* | osf5*)
version_type=osf
need_lib_prefix=no
need_version=no
soname_spec='${libname}${release}${shared_ext}$major'
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
sys_lib_search_path_spec="/usr/shlib /usr/ccs/lib /usr/lib/cmplrs/cc /usr/lib /usr/local/lib /var/shlib"
sys_lib_dlsearch_path_spec="$sys_lib_search_path_spec"
;;
rdos*)
dynamic_linker=no
;;
solaris*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
# ldd complains unless libraries are executable
postinstall_cmds='chmod +x $lib'
;;
sunos4*)
version_type=sunos
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/usr/etc" ldconfig $libdir'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
if test "$with_gnu_ld" = yes; then
need_lib_prefix=no
fi
need_version=yes
;;
sysv4 | sysv4.3*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
case $host_vendor in
sni)
shlibpath_overrides_runpath=no
need_lib_prefix=no
runpath_var=LD_RUN_PATH
;;
siemens)
need_lib_prefix=no
;;
motorola)
need_lib_prefix=no
need_version=no
shlibpath_overrides_runpath=no
sys_lib_search_path_spec='/lib /usr/lib /usr/ccs/lib'
;;
esac
;;
sysv4*MP*)
if test -d /usr/nec ;then
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='$libname${shared_ext}.$versuffix $libname${shared_ext}.$major $libname${shared_ext}'
soname_spec='$libname${shared_ext}.$major'
shlibpath_var=LD_LIBRARY_PATH
fi
;;
sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX* | sysv4*uw2*)
version_type=freebsd-elf
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext} $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
if test "$with_gnu_ld" = yes; then
sys_lib_search_path_spec='/usr/local/lib /usr/gnu/lib /usr/ccs/lib /usr/lib /lib'
else
sys_lib_search_path_spec='/usr/ccs/lib /usr/lib'
case $host_os in
sco3.2v5*)
sys_lib_search_path_spec="$sys_lib_search_path_spec /lib"
;;
esac
fi
sys_lib_dlsearch_path_spec='/usr/lib'
;;
tpf*)
# TPF is a cross-target only. Preferred cross-host = GNU/Linux.
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
uts4*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
;;
*)
dynamic_linker=no
;;
esac
AC_MSG_RESULT([$dynamic_linker])
test "$dynamic_linker" = no && can_build_shared=no
variables_saved_for_relink="PATH $shlibpath_var $runpath_var"
if test "$GCC" = yes; then
variables_saved_for_relink="$variables_saved_for_relink GCC_EXEC_PREFIX COMPILER_PATH LIBRARY_PATH"
fi
if test "${lt_cv_sys_lib_search_path_spec+set}" = set; then
sys_lib_search_path_spec="$lt_cv_sys_lib_search_path_spec"
fi
if test "${lt_cv_sys_lib_dlsearch_path_spec+set}" = set; then
sys_lib_dlsearch_path_spec="$lt_cv_sys_lib_dlsearch_path_spec"
fi
_LT_DECL([], [variables_saved_for_relink], [1],
[Variables whose values should be saved in libtool wrapper scripts and
restored at link time])
_LT_DECL([], [need_lib_prefix], [0],
[Do we need the "lib" prefix for modules?])
_LT_DECL([], [need_version], [0], [Do we need a version for libraries?])
_LT_DECL([], [version_type], [0], [Library versioning type])
_LT_DECL([], [runpath_var], [0], [Shared library runtime path variable])
_LT_DECL([], [shlibpath_var], [0],[Shared library path variable])
_LT_DECL([], [shlibpath_overrides_runpath], [0],
[Is shlibpath searched before the hard-coded library search path?])
_LT_DECL([], [libname_spec], [1], [Format of library name prefix])
_LT_DECL([], [library_names_spec], [1],
[[List of archive names. First name is the real one, the rest are links.
The last name is the one that the linker finds with -lNAME]])
_LT_DECL([], [soname_spec], [1],
[[The coded name of the library, if different from the real name]])
_LT_DECL([], [install_override_mode], [1],
[Permission mode override for installation of shared libraries])
_LT_DECL([], [postinstall_cmds], [2],
[Command to use after installation of a shared archive])
_LT_DECL([], [postuninstall_cmds], [2],
[Command to use after uninstallation of a shared archive])
_LT_DECL([], [finish_cmds], [2],
[Commands used to finish a libtool library installation in a directory])
_LT_DECL([], [finish_eval], [1],
[[As "finish_cmds", except a single script fragment to be evaled but
not shown]])
_LT_DECL([], [hardcode_into_libs], [0],
[Whether we should hardcode library paths into libraries])
_LT_DECL([], [sys_lib_search_path_spec], [2],
[Compile-time system search path for libraries])
_LT_DECL([], [sys_lib_dlsearch_path_spec], [2],
[Run-time system search path for libraries])
])# _LT_SYS_DYNAMIC_LINKER
# _LT_PATH_TOOL_PREFIX(TOOL)
# --------------------------
# find a file program which can recognize shared library
AC_DEFUN([_LT_PATH_TOOL_PREFIX],
[m4_require([_LT_DECL_EGREP])dnl
AC_MSG_CHECKING([for $1])
AC_CACHE_VAL(lt_cv_path_MAGIC_CMD,
[case $MAGIC_CMD in
[[\\/*] | ?:[\\/]*])
lt_cv_path_MAGIC_CMD="$MAGIC_CMD" # Let the user override the test with a path.
;;
*)
lt_save_MAGIC_CMD="$MAGIC_CMD"
lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR
dnl $ac_dummy forces splitting on constant user-supplied paths.
dnl POSIX.2 word splitting is done only on the output of word expansions,
dnl not every word. This closes a longstanding sh security hole.
ac_dummy="m4_if([$2], , $PATH, [$2])"
for ac_dir in $ac_dummy; do
IFS="$lt_save_ifs"
test -z "$ac_dir" && ac_dir=.
if test -f $ac_dir/$1; then
lt_cv_path_MAGIC_CMD="$ac_dir/$1"
if test -n "$file_magic_test_file"; then
case $deplibs_check_method in
"file_magic "*)
file_magic_regex=`expr "$deplibs_check_method" : "file_magic \(.*\)"`
MAGIC_CMD="$lt_cv_path_MAGIC_CMD"
if eval $file_magic_cmd \$file_magic_test_file 2> /dev/null |
$EGREP "$file_magic_regex" > /dev/null; then
:
else
cat <<_LT_EOF 1>&2
*** Warning: the command libtool uses to detect shared libraries,
*** $file_magic_cmd, produces output that libtool cannot recognize.
*** The result is that libtool may fail to recognize shared libraries
*** as such. This will affect the creation of libtool libraries that
*** depend on shared libraries, but programs linked with such libtool
*** libraries will work regardless of this problem. Nevertheless, you
*** may want to report the problem to your system manager and/or to
*** bug-libtool@gnu.org
_LT_EOF
fi ;;
esac
fi
break
fi
done
IFS="$lt_save_ifs"
MAGIC_CMD="$lt_save_MAGIC_CMD"
;;
esac])
MAGIC_CMD="$lt_cv_path_MAGIC_CMD"
if test -n "$MAGIC_CMD"; then
AC_MSG_RESULT($MAGIC_CMD)
else
AC_MSG_RESULT(no)
fi
_LT_DECL([], [MAGIC_CMD], [0],
[Used to examine libraries when file_magic_cmd begins with "file"])dnl
])# _LT_PATH_TOOL_PREFIX
# Old name:
AU_ALIAS([AC_PATH_TOOL_PREFIX], [_LT_PATH_TOOL_PREFIX])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_PATH_TOOL_PREFIX], [])
# _LT_PATH_MAGIC
# --------------
# find a file program which can recognize a shared library
m4_defun([_LT_PATH_MAGIC],
[_LT_PATH_TOOL_PREFIX(${ac_tool_prefix}file, /usr/bin$PATH_SEPARATOR$PATH)
if test -z "$lt_cv_path_MAGIC_CMD"; then
if test -n "$ac_tool_prefix"; then
_LT_PATH_TOOL_PREFIX(file, /usr/bin$PATH_SEPARATOR$PATH)
else
MAGIC_CMD=:
fi
fi
])# _LT_PATH_MAGIC
# LT_PATH_LD
# ----------
# find the pathname to the GNU or non-GNU linker
AC_DEFUN([LT_PATH_LD],
[AC_REQUIRE([AC_PROG_CC])dnl
AC_REQUIRE([AC_CANONICAL_HOST])dnl
AC_REQUIRE([AC_CANONICAL_BUILD])dnl
m4_require([_LT_DECL_SED])dnl
m4_require([_LT_DECL_EGREP])dnl
m4_require([_LT_PROG_ECHO_BACKSLASH])dnl
AC_ARG_WITH([gnu-ld],
[AS_HELP_STRING([--with-gnu-ld],
[assume the C compiler uses GNU ld @<:@default=no@:>@])],
[test "$withval" = no || with_gnu_ld=yes],
[with_gnu_ld=no])dnl
ac_prog=ld
if test "$GCC" = yes; then
# Check if gcc -print-prog-name=ld gives a path.
AC_MSG_CHECKING([for ld used by $CC])
case $host in
*-*-mingw*)
# gcc leaves a trailing carriage return which upsets mingw
ac_prog=`($CC -print-prog-name=ld) 2>&5 | tr -d '\015'` ;;
*)
ac_prog=`($CC -print-prog-name=ld) 2>&5` ;;
esac
case $ac_prog in
# Accept absolute paths.
[[\\/]]* | ?:[[\\/]]*)
re_direlt='/[[^/]][[^/]]*/\.\./'
# Canonicalize the pathname of ld
ac_prog=`$ECHO "$ac_prog"| $SED 's%\\\\%/%g'`
while $ECHO "$ac_prog" | $GREP "$re_direlt" > /dev/null 2>&1; do
ac_prog=`$ECHO $ac_prog| $SED "s%$re_direlt%/%"`
done
test -z "$LD" && LD="$ac_prog"
;;
"")
# If it fails, then pretend we aren't using GCC.
ac_prog=ld
;;
*)
# If it is relative, then search for the first ld in PATH.
with_gnu_ld=unknown
;;
esac
elif test "$with_gnu_ld" = yes; then
AC_MSG_CHECKING([for GNU ld])
else
AC_MSG_CHECKING([for non-GNU ld])
fi
AC_CACHE_VAL(lt_cv_path_LD,
[if test -z "$LD"; then
lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR
for ac_dir in $PATH; do
IFS="$lt_save_ifs"
test -z "$ac_dir" && ac_dir=.
if test -f "$ac_dir/$ac_prog" || test -f "$ac_dir/$ac_prog$ac_exeext"; then
lt_cv_path_LD="$ac_dir/$ac_prog"
# Check to see if the program is GNU ld. I'd rather use --version,
# but apparently some variants of GNU ld only accept -v.
# Break only if it was the GNU/non-GNU ld that we prefer.
case `"$lt_cv_path_LD" -v 2>&1 &1 /dev/null 2>&1; then
lt_cv_deplibs_check_method='file_magic ^x86 archive import|^x86 DLL'
lt_cv_file_magic_cmd='func_win32_libid'
else
# Keep this pattern in sync with the one in func_win32_libid.
lt_cv_deplibs_check_method='file_magic file format (pei*-i386(.*architecture: i386)?|pe-arm-wince|pe-x86-64)'
lt_cv_file_magic_cmd='$OBJDUMP -f'
fi
;;
cegcc*)
# use the weaker test based on 'objdump'. See mingw*.
lt_cv_deplibs_check_method='file_magic file format pe-arm-.*little(.*architecture: arm)?'
lt_cv_file_magic_cmd='$OBJDUMP -f'
;;
darwin* | rhapsody*)
lt_cv_deplibs_check_method=pass_all
;;
freebsd* | dragonfly*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ > /dev/null; then
case $host_cpu in
i*86 )
# Not sure whether the presence of OpenBSD here was a mistake.
# Let's accept both of them until this is cleared up.
lt_cv_deplibs_check_method='file_magic (FreeBSD|OpenBSD|DragonFly)/i[[3-9]]86 (compact )?demand paged shared library'
lt_cv_file_magic_cmd=/usr/bin/file
lt_cv_file_magic_test_file=`echo /usr/lib/libc.so.*`
;;
esac
else
lt_cv_deplibs_check_method=pass_all
fi
;;
gnu*)
lt_cv_deplibs_check_method=pass_all
;;
haiku*)
lt_cv_deplibs_check_method=pass_all
;;
hpux10.20* | hpux11*)
lt_cv_file_magic_cmd=/usr/bin/file
case $host_cpu in
ia64*)
lt_cv_deplibs_check_method='file_magic (s[[0-9]][[0-9]][[0-9]]|ELF-[[0-9]][[0-9]]) shared object file - IA64'
lt_cv_file_magic_test_file=/usr/lib/hpux32/libc.so
;;
hppa*64*)
[lt_cv_deplibs_check_method='file_magic (s[0-9][0-9][0-9]|ELF[ -][0-9][0-9])(-bit)?( [LM]SB)? shared object( file)?[, -]* PA-RISC [0-9]\.[0-9]']
lt_cv_file_magic_test_file=/usr/lib/pa20_64/libc.sl
;;
*)
lt_cv_deplibs_check_method='file_magic (s[[0-9]][[0-9]][[0-9]]|PA-RISC[[0-9]]\.[[0-9]]) shared library'
lt_cv_file_magic_test_file=/usr/lib/libc.sl
;;
esac
;;
interix[[3-9]]*)
# PIC code is broken on Interix 3.x, that's why |\.a not |_pic\.a here
lt_cv_deplibs_check_method='match_pattern /lib[[^/]]+(\.so|\.a)$'
;;
irix5* | irix6* | nonstopux*)
case $LD in
*-32|*"-32 ") libmagic=32-bit;;
*-n32|*"-n32 ") libmagic=N32;;
*-64|*"-64 ") libmagic=64-bit;;
*) libmagic=never-match;;
esac
lt_cv_deplibs_check_method=pass_all
;;
# This must be glibc/ELF.
linux* | k*bsd*-gnu | kopensolaris*-gnu)
lt_cv_deplibs_check_method=pass_all
;;
netbsd*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ > /dev/null; then
lt_cv_deplibs_check_method='match_pattern /lib[[^/]]+(\.so\.[[0-9]]+\.[[0-9]]+|_pic\.a)$'
else
lt_cv_deplibs_check_method='match_pattern /lib[[^/]]+(\.so|_pic\.a)$'
fi
;;
newos6*)
lt_cv_deplibs_check_method='file_magic ELF [[0-9]][[0-9]]*-bit [[ML]]SB (executable|dynamic lib)'
lt_cv_file_magic_cmd=/usr/bin/file
lt_cv_file_magic_test_file=/usr/lib/libnls.so
;;
*nto* | *qnx*)
lt_cv_deplibs_check_method=pass_all
;;
openbsd*)
if test -z "`echo __ELF__ | $CC -E - | $GREP __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
lt_cv_deplibs_check_method='match_pattern /lib[[^/]]+(\.so\.[[0-9]]+\.[[0-9]]+|\.so|_pic\.a)$'
else
lt_cv_deplibs_check_method='match_pattern /lib[[^/]]+(\.so\.[[0-9]]+\.[[0-9]]+|_pic\.a)$'
fi
;;
osf3* | osf4* | osf5*)
lt_cv_deplibs_check_method=pass_all
;;
rdos*)
lt_cv_deplibs_check_method=pass_all
;;
solaris*)
lt_cv_deplibs_check_method=pass_all
;;
sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX* | sysv4*uw2*)
lt_cv_deplibs_check_method=pass_all
;;
sysv4 | sysv4.3*)
case $host_vendor in
motorola)
lt_cv_deplibs_check_method='file_magic ELF [[0-9]][[0-9]]*-bit [[ML]]SB (shared object|dynamic lib) M[[0-9]][[0-9]]* Version [[0-9]]'
lt_cv_file_magic_test_file=`echo /usr/lib/libc.so*`
;;
ncr)
lt_cv_deplibs_check_method=pass_all
;;
sequent)
lt_cv_file_magic_cmd='/bin/file'
lt_cv_deplibs_check_method='file_magic ELF [[0-9]][[0-9]]*-bit [[LM]]SB (shared object|dynamic lib )'
;;
sni)
lt_cv_file_magic_cmd='/bin/file'
lt_cv_deplibs_check_method="file_magic ELF [[0-9]][[0-9]]*-bit [[LM]]SB dynamic lib"
lt_cv_file_magic_test_file=/lib/libc.so
;;
siemens)
lt_cv_deplibs_check_method=pass_all
;;
pc)
lt_cv_deplibs_check_method=pass_all
;;
esac
;;
tpf*)
lt_cv_deplibs_check_method=pass_all
;;
esac
])
file_magic_glob=
want_nocaseglob=no
if test "$build" = "$host"; then
case $host_os in
mingw* | pw32*)
if ( shopt | grep nocaseglob ) >/dev/null 2>&1; then
want_nocaseglob=yes
else
file_magic_glob=`echo aAbBcCdDeEfFgGhHiIjJkKlLmMnNoOpPqQrRsStTuUvVwWxXyYzZ | $SED -e "s/\(..\)/s\/[[\1]]\/[[\1]]\/g;/g"`
fi
;;
esac
fi
file_magic_cmd=$lt_cv_file_magic_cmd
deplibs_check_method=$lt_cv_deplibs_check_method
test -z "$deplibs_check_method" && deplibs_check_method=unknown
_LT_DECL([], [deplibs_check_method], [1],
[Method to check whether dependent libraries are shared objects])
_LT_DECL([], [file_magic_cmd], [1],
[Command to use when deplibs_check_method = "file_magic"])
_LT_DECL([], [file_magic_glob], [1],
[How to find potential files when deplibs_check_method = "file_magic"])
_LT_DECL([], [want_nocaseglob], [1],
[Find potential files using nocaseglob when deplibs_check_method = "file_magic"])
])# _LT_CHECK_MAGIC_METHOD
# LT_PATH_NM
# ----------
# find the pathname to a BSD- or MS-compatible name lister
AC_DEFUN([LT_PATH_NM],
[AC_REQUIRE([AC_PROG_CC])dnl
AC_CACHE_CHECK([for BSD- or MS-compatible name lister (nm)], lt_cv_path_NM,
[if test -n "$NM"; then
# Let the user override the test.
lt_cv_path_NM="$NM"
else
lt_nm_to_check="${ac_tool_prefix}nm"
if test -n "$ac_tool_prefix" && test "$build" = "$host"; then
lt_nm_to_check="$lt_nm_to_check nm"
fi
for lt_tmp_nm in $lt_nm_to_check; do
lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR
for ac_dir in $PATH /usr/ccs/bin/elf /usr/ccs/bin /usr/ucb /bin; do
IFS="$lt_save_ifs"
test -z "$ac_dir" && ac_dir=.
tmp_nm="$ac_dir/$lt_tmp_nm"
if test -f "$tmp_nm" || test -f "$tmp_nm$ac_exeext" ; then
# Check to see if the nm accepts a BSD-compat flag.
# Adding the `sed 1q' prevents false positives on HP-UX, which says:
# nm: unknown option "B" ignored
# Tru64's nm complains that /dev/null is an invalid object file
case `"$tmp_nm" -B /dev/null 2>&1 | sed '1q'` in
*/dev/null* | *'Invalid file or object type'*)
lt_cv_path_NM="$tmp_nm -B"
break
;;
*)
case `"$tmp_nm" -p /dev/null 2>&1 | sed '1q'` in
*/dev/null*)
lt_cv_path_NM="$tmp_nm -p"
break
;;
*)
lt_cv_path_NM=${lt_cv_path_NM="$tmp_nm"} # keep the first match, but
continue # so that we can try to find one that supports BSD flags
;;
esac
;;
esac
fi
done
IFS="$lt_save_ifs"
done
: ${lt_cv_path_NM=no}
fi])
if test "$lt_cv_path_NM" != "no"; then
NM="$lt_cv_path_NM"
else
# Didn't find any BSD compatible name lister, look for dumpbin.
if test -n "$DUMPBIN"; then :
# Let the user override the test.
else
AC_CHECK_TOOLS(DUMPBIN, [dumpbin "link -dump"], :)
case `$DUMPBIN -symbols /dev/null 2>&1 | sed '1q'` in
*COFF*)
DUMPBIN="$DUMPBIN -symbols"
;;
*)
DUMPBIN=:
;;
esac
fi
AC_SUBST([DUMPBIN])
if test "$DUMPBIN" != ":"; then
NM="$DUMPBIN"
fi
fi
test -z "$NM" && NM=nm
AC_SUBST([NM])
_LT_DECL([], [NM], [1], [A BSD- or MS-compatible name lister])dnl
AC_CACHE_CHECK([the name lister ($NM) interface], [lt_cv_nm_interface],
[lt_cv_nm_interface="BSD nm"
echo "int some_variable = 0;" > conftest.$ac_ext
(eval echo "\"\$as_me:$LINENO: $ac_compile\"" >&AS_MESSAGE_LOG_FD)
(eval "$ac_compile" 2>conftest.err)
cat conftest.err >&AS_MESSAGE_LOG_FD
(eval echo "\"\$as_me:$LINENO: $NM \\\"conftest.$ac_objext\\\"\"" >&AS_MESSAGE_LOG_FD)
(eval "$NM \"conftest.$ac_objext\"" 2>conftest.err > conftest.out)
cat conftest.err >&AS_MESSAGE_LOG_FD
(eval echo "\"\$as_me:$LINENO: output\"" >&AS_MESSAGE_LOG_FD)
cat conftest.out >&AS_MESSAGE_LOG_FD
if $GREP 'External.*some_variable' conftest.out > /dev/null; then
lt_cv_nm_interface="MS dumpbin"
fi
rm -f conftest*])
])# LT_PATH_NM
# Old names:
AU_ALIAS([AM_PROG_NM], [LT_PATH_NM])
AU_ALIAS([AC_PROG_NM], [LT_PATH_NM])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AM_PROG_NM], [])
dnl AC_DEFUN([AC_PROG_NM], [])
# _LT_CHECK_SHAREDLIB_FROM_LINKLIB
# --------------------------------
# how to determine the name of the shared library
# associated with a specific link library.
# -- PORTME fill in with the dynamic library characteristics
m4_defun([_LT_CHECK_SHAREDLIB_FROM_LINKLIB],
[m4_require([_LT_DECL_EGREP])
m4_require([_LT_DECL_OBJDUMP])
m4_require([_LT_DECL_DLLTOOL])
AC_CACHE_CHECK([how to associate runtime and link libraries],
lt_cv_sharedlib_from_linklib_cmd,
[lt_cv_sharedlib_from_linklib_cmd='unknown'
case $host_os in
cygwin* | mingw* | pw32* | cegcc*)
# two different shell functions defined in ltmain.sh
# decide which to use based on capabilities of $DLLTOOL
case `$DLLTOOL --help 2>&1` in
*--identify-strict*)
lt_cv_sharedlib_from_linklib_cmd=func_cygming_dll_for_implib
;;
*)
lt_cv_sharedlib_from_linklib_cmd=func_cygming_dll_for_implib_fallback
;;
esac
;;
*)
# fallback: assume linklib IS sharedlib
lt_cv_sharedlib_from_linklib_cmd="$ECHO"
;;
esac
])
sharedlib_from_linklib_cmd=$lt_cv_sharedlib_from_linklib_cmd
test -z "$sharedlib_from_linklib_cmd" && sharedlib_from_linklib_cmd=$ECHO
_LT_DECL([], [sharedlib_from_linklib_cmd], [1],
[Command to associate shared and link libraries])
])# _LT_CHECK_SHAREDLIB_FROM_LINKLIB
# _LT_PATH_MANIFEST_TOOL
# ----------------------
# locate the manifest tool
m4_defun([_LT_PATH_MANIFEST_TOOL],
[AC_CHECK_TOOL(MANIFEST_TOOL, mt, :)
test -z "$MANIFEST_TOOL" && MANIFEST_TOOL=mt
AC_CACHE_CHECK([if $MANIFEST_TOOL is a manifest tool], [lt_cv_path_mainfest_tool],
[lt_cv_path_mainfest_tool=no
echo "$as_me:$LINENO: $MANIFEST_TOOL '-?'" >&AS_MESSAGE_LOG_FD
$MANIFEST_TOOL '-?' 2>conftest.err > conftest.out
cat conftest.err >&AS_MESSAGE_LOG_FD
if $GREP 'Manifest Tool' conftest.out > /dev/null; then
lt_cv_path_mainfest_tool=yes
fi
rm -f conftest*])
if test "x$lt_cv_path_mainfest_tool" != xyes; then
MANIFEST_TOOL=:
fi
_LT_DECL([], [MANIFEST_TOOL], [1], [Manifest tool])dnl
])# _LT_PATH_MANIFEST_TOOL
# LT_LIB_M
# --------
# check for math library
AC_DEFUN([LT_LIB_M],
[AC_REQUIRE([AC_CANONICAL_HOST])dnl
LIBM=
case $host in
*-*-beos* | *-*-cegcc* | *-*-cygwin* | *-*-haiku* | *-*-pw32* | *-*-darwin*)
# These system don't have libm, or don't need it
;;
*-ncr-sysv4.3*)
AC_CHECK_LIB(mw, _mwvalidcheckl, LIBM="-lmw")
AC_CHECK_LIB(m, cos, LIBM="$LIBM -lm")
;;
*)
AC_CHECK_LIB(m, cos, LIBM="-lm")
;;
esac
AC_SUBST([LIBM])
])# LT_LIB_M
# Old name:
AU_ALIAS([AC_CHECK_LIBM], [LT_LIB_M])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_CHECK_LIBM], [])
# _LT_COMPILER_NO_RTTI([TAGNAME])
# -------------------------------
m4_defun([_LT_COMPILER_NO_RTTI],
[m4_require([_LT_TAG_COMPILER])dnl
_LT_TAGVAR(lt_prog_compiler_no_builtin_flag, $1)=
if test "$GCC" = yes; then
case $cc_basename in
nvcc*)
_LT_TAGVAR(lt_prog_compiler_no_builtin_flag, $1)=' -Xcompiler -fno-builtin' ;;
*)
_LT_TAGVAR(lt_prog_compiler_no_builtin_flag, $1)=' -fno-builtin' ;;
esac
_LT_COMPILER_OPTION([if $compiler supports -fno-rtti -fno-exceptions],
lt_cv_prog_compiler_rtti_exceptions,
[-fno-rtti -fno-exceptions], [],
[_LT_TAGVAR(lt_prog_compiler_no_builtin_flag, $1)="$_LT_TAGVAR(lt_prog_compiler_no_builtin_flag, $1) -fno-rtti -fno-exceptions"])
fi
_LT_TAGDECL([no_builtin_flag], [lt_prog_compiler_no_builtin_flag], [1],
[Compiler flag to turn off builtin functions])
])# _LT_COMPILER_NO_RTTI
# _LT_CMD_GLOBAL_SYMBOLS
# ----------------------
m4_defun([_LT_CMD_GLOBAL_SYMBOLS],
[AC_REQUIRE([AC_CANONICAL_HOST])dnl
AC_REQUIRE([AC_PROG_CC])dnl
AC_REQUIRE([AC_PROG_AWK])dnl
AC_REQUIRE([LT_PATH_NM])dnl
AC_REQUIRE([LT_PATH_LD])dnl
m4_require([_LT_DECL_SED])dnl
m4_require([_LT_DECL_EGREP])dnl
m4_require([_LT_TAG_COMPILER])dnl
# Check for command to grab the raw symbol name followed by C symbol from nm.
AC_MSG_CHECKING([command to parse $NM output from $compiler object])
AC_CACHE_VAL([lt_cv_sys_global_symbol_pipe],
[
# These are sane defaults that work on at least a few old systems.
# [They come from Ultrix. What could be older than Ultrix?!! ;)]
# Character class describing NM global symbol codes.
symcode='[[BCDEGRST]]'
# Regexp to match symbols that can be accessed directly from C.
sympat='\([[_A-Za-z]][[_A-Za-z0-9]]*\)'
# Define system-specific variables.
case $host_os in
aix*)
symcode='[[BCDT]]'
;;
cygwin* | mingw* | pw32* | cegcc*)
symcode='[[ABCDGISTW]]'
;;
hpux*)
if test "$host_cpu" = ia64; then
symcode='[[ABCDEGRST]]'
fi
;;
irix* | nonstopux*)
symcode='[[BCDEGRST]]'
;;
osf*)
symcode='[[BCDEGQRST]]'
;;
solaris*)
symcode='[[BDRT]]'
;;
sco3.2v5*)
symcode='[[DT]]'
;;
sysv4.2uw2*)
symcode='[[DT]]'
;;
sysv5* | sco5v6* | unixware* | OpenUNIX*)
symcode='[[ABDT]]'
;;
sysv4)
symcode='[[DFNSTU]]'
;;
esac
# If we're using GNU nm, then use its standard symbol codes.
case `$NM -V 2>&1` in
*GNU* | *'with BFD'*)
symcode='[[ABCDGIRSTW]]' ;;
esac
# Transform an extracted symbol line into a proper C declaration.
# Some systems (esp. on ia64) link data and code symbols differently,
# so use this general approach.
lt_cv_sys_global_symbol_to_cdecl="sed -n -e 's/^T .* \(.*\)$/extern int \1();/p' -e 's/^$symcode* .* \(.*\)$/extern char \1;/p'"
# Transform an extracted symbol line into symbol name and symbol address
lt_cv_sys_global_symbol_to_c_name_address="sed -n -e 's/^: \([[^ ]]*\)[[ ]]*$/ {\\\"\1\\\", (void *) 0},/p' -e 's/^$symcode* \([[^ ]]*\) \([[^ ]]*\)$/ {\"\2\", (void *) \&\2},/p'"
lt_cv_sys_global_symbol_to_c_name_address_lib_prefix="sed -n -e 's/^: \([[^ ]]*\)[[ ]]*$/ {\\\"\1\\\", (void *) 0},/p' -e 's/^$symcode* \([[^ ]]*\) \(lib[[^ ]]*\)$/ {\"\2\", (void *) \&\2},/p' -e 's/^$symcode* \([[^ ]]*\) \([[^ ]]*\)$/ {\"lib\2\", (void *) \&\2},/p'"
# Handle CRLF in mingw tool chain
opt_cr=
case $build_os in
mingw*)
opt_cr=`$ECHO 'x\{0,1\}' | tr x '\015'` # option cr in regexp
;;
esac
# Try without a prefix underscore, then with it.
for ac_symprfx in "" "_"; do
# Transform symcode, sympat, and symprfx into a raw symbol and a C symbol.
symxfrm="\\1 $ac_symprfx\\2 \\2"
# Write the raw and C identifiers.
if test "$lt_cv_nm_interface" = "MS dumpbin"; then
# Fake it for dumpbin and say T for any non-static function
# and D for any global variable.
# Also find C++ and __fastcall symbols from MSVC++,
# which start with @ or ?.
lt_cv_sys_global_symbol_pipe="$AWK ['"\
" {last_section=section; section=\$ 3};"\
" /^COFF SYMBOL TABLE/{for(i in hide) delete hide[i]};"\
" /Section length .*#relocs.*(pick any)/{hide[last_section]=1};"\
" \$ 0!~/External *\|/{next};"\
" / 0+ UNDEF /{next}; / UNDEF \([^|]\)*()/{next};"\
" {if(hide[section]) next};"\
" {f=0}; \$ 0~/\(\).*\|/{f=1}; {printf f ? \"T \" : \"D \"};"\
" {split(\$ 0, a, /\||\r/); split(a[2], s)};"\
" s[1]~/^[@?]/{print s[1], s[1]; next};"\
" s[1]~prfx {split(s[1],t,\"@\"); print t[1], substr(t[1],length(prfx))}"\
" ' prfx=^$ac_symprfx]"
else
lt_cv_sys_global_symbol_pipe="sed -n -e 's/^.*[[ ]]\($symcode$symcode*\)[[ ]][[ ]]*$ac_symprfx$sympat$opt_cr$/$symxfrm/p'"
fi
lt_cv_sys_global_symbol_pipe="$lt_cv_sys_global_symbol_pipe | sed '/ __gnu_lto/d'"
# Check to see that the pipe works correctly.
pipe_works=no
rm -f conftest*
cat > conftest.$ac_ext <<_LT_EOF
#ifdef __cplusplus
extern "C" {
#endif
char nm_test_var;
void nm_test_func(void);
void nm_test_func(void){}
#ifdef __cplusplus
}
#endif
int main(){nm_test_var='a';nm_test_func();return(0);}
_LT_EOF
if AC_TRY_EVAL(ac_compile); then
# Now try to grab the symbols.
nlist=conftest.nm
if AC_TRY_EVAL(NM conftest.$ac_objext \| "$lt_cv_sys_global_symbol_pipe" \> $nlist) && test -s "$nlist"; then
# Try sorting and uniquifying the output.
if sort "$nlist" | uniq > "$nlist"T; then
mv -f "$nlist"T "$nlist"
else
rm -f "$nlist"T
fi
# Make sure that we snagged all the symbols we need.
if $GREP ' nm_test_var$' "$nlist" >/dev/null; then
if $GREP ' nm_test_func$' "$nlist" >/dev/null; then
cat <<_LT_EOF > conftest.$ac_ext
/* Keep this code in sync between libtool.m4, ltmain, lt_system.h, and tests. */
#if defined(_WIN32) || defined(__CYGWIN__) || defined(_WIN32_WCE)
/* DATA imports from DLLs on WIN32 con't be const, because runtime
relocations are performed -- see ld's documentation on pseudo-relocs. */
# define LT@&t@_DLSYM_CONST
#elif defined(__osf__)
/* This system does not cope well with relocations in const data. */
# define LT@&t@_DLSYM_CONST
#else
# define LT@&t@_DLSYM_CONST const
#endif
#ifdef __cplusplus
extern "C" {
#endif
_LT_EOF
# Now generate the symbol file.
eval "$lt_cv_sys_global_symbol_to_cdecl"' < "$nlist" | $GREP -v main >> conftest.$ac_ext'
cat <<_LT_EOF >> conftest.$ac_ext
/* The mapping between symbol names and symbols. */
LT@&t@_DLSYM_CONST struct {
const char *name;
void *address;
}
lt__PROGRAM__LTX_preloaded_symbols[[]] =
{
{ "@PROGRAM@", (void *) 0 },
_LT_EOF
$SED "s/^$symcode$symcode* \(.*\) \(.*\)$/ {\"\2\", (void *) \&\2},/" < "$nlist" | $GREP -v main >> conftest.$ac_ext
cat <<\_LT_EOF >> conftest.$ac_ext
{0, (void *) 0}
};
/* This works around a problem in FreeBSD linker */
#ifdef FREEBSD_WORKAROUND
static const void *lt_preloaded_setup() {
return lt__PROGRAM__LTX_preloaded_symbols;
}
#endif
#ifdef __cplusplus
}
#endif
_LT_EOF
# Now try linking the two files.
mv conftest.$ac_objext conftstm.$ac_objext
lt_globsym_save_LIBS=$LIBS
lt_globsym_save_CFLAGS=$CFLAGS
LIBS="conftstm.$ac_objext"
CFLAGS="$CFLAGS$_LT_TAGVAR(lt_prog_compiler_no_builtin_flag, $1)"
if AC_TRY_EVAL(ac_link) && test -s conftest${ac_exeext}; then
pipe_works=yes
fi
LIBS=$lt_globsym_save_LIBS
CFLAGS=$lt_globsym_save_CFLAGS
else
echo "cannot find nm_test_func in $nlist" >&AS_MESSAGE_LOG_FD
fi
else
echo "cannot find nm_test_var in $nlist" >&AS_MESSAGE_LOG_FD
fi
else
echo "cannot run $lt_cv_sys_global_symbol_pipe" >&AS_MESSAGE_LOG_FD
fi
else
echo "$progname: failed program was:" >&AS_MESSAGE_LOG_FD
cat conftest.$ac_ext >&5
fi
rm -rf conftest* conftst*
# Do not use the global_symbol_pipe unless it works.
if test "$pipe_works" = yes; then
break
else
lt_cv_sys_global_symbol_pipe=
fi
done
])
if test -z "$lt_cv_sys_global_symbol_pipe"; then
lt_cv_sys_global_symbol_to_cdecl=
fi
if test -z "$lt_cv_sys_global_symbol_pipe$lt_cv_sys_global_symbol_to_cdecl"; then
AC_MSG_RESULT(failed)
else
AC_MSG_RESULT(ok)
fi
# Response file support.
if test "$lt_cv_nm_interface" = "MS dumpbin"; then
nm_file_list_spec='@'
elif $NM --help 2>/dev/null | grep '[[@]]FILE' >/dev/null; then
nm_file_list_spec='@'
fi
_LT_DECL([global_symbol_pipe], [lt_cv_sys_global_symbol_pipe], [1],
[Take the output of nm and produce a listing of raw symbols and C names])
_LT_DECL([global_symbol_to_cdecl], [lt_cv_sys_global_symbol_to_cdecl], [1],
[Transform the output of nm in a proper C declaration])
_LT_DECL([global_symbol_to_c_name_address],
[lt_cv_sys_global_symbol_to_c_name_address], [1],
[Transform the output of nm in a C name address pair])
_LT_DECL([global_symbol_to_c_name_address_lib_prefix],
[lt_cv_sys_global_symbol_to_c_name_address_lib_prefix], [1],
[Transform the output of nm in a C name address pair when lib prefix is needed])
_LT_DECL([], [nm_file_list_spec], [1],
[Specify filename containing input files for $NM])
]) # _LT_CMD_GLOBAL_SYMBOLS
# _LT_COMPILER_PIC([TAGNAME])
# ---------------------------
m4_defun([_LT_COMPILER_PIC],
[m4_require([_LT_TAG_COMPILER])dnl
_LT_TAGVAR(lt_prog_compiler_wl, $1)=
_LT_TAGVAR(lt_prog_compiler_pic, $1)=
_LT_TAGVAR(lt_prog_compiler_static, $1)=
m4_if([$1], [CXX], [
# C++ specific cases for pic, static, wl, etc.
if test "$GXX" = yes; then
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-static'
case $host_os in
aix*)
# All AIX code is PIC.
if test "$host_cpu" = ia64; then
# AIX 5 now supports IA64 processor
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# see comment about AmigaOS4 .so support
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
;;
m68k)
# FIXME: we need at least 68020 code to build shared libraries, but
# adding the `-m68020' flag to GCC prevents building anything better,
# like `-m68040'.
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-m68020 -resident32 -malways-restore-a4'
;;
esac
;;
beos* | irix5* | irix6* | nonstopux* | osf3* | osf4* | osf5*)
# PIC is the default for these OSes.
;;
mingw* | cygwin* | os2* | pw32* | cegcc*)
# This hack is so that the source file can tell whether it is being
# built for inclusion in a dll (and should export symbols for example).
# Although the cygwin gcc ignores -fPIC, still need this for old-style
# (--disable-auto-import) libraries
m4_if([$1], [GCJ], [],
[_LT_TAGVAR(lt_prog_compiler_pic, $1)='-DDLL_EXPORT'])
;;
darwin* | rhapsody*)
# PIC is the default on this platform
# Common symbols not allowed in MH_DYLIB files
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fno-common'
;;
*djgpp*)
# DJGPP does not support shared libraries at all
_LT_TAGVAR(lt_prog_compiler_pic, $1)=
;;
haiku*)
# PIC is the default for Haiku.
# The "-static" flag exists, but is broken.
_LT_TAGVAR(lt_prog_compiler_static, $1)=
;;
interix[[3-9]]*)
# Interix 3.x gcc -fpic/-fPIC options generate broken code.
# Instead, we relocate shared libraries at runtime.
;;
sysv4*MP*)
if test -d /usr/nec; then
_LT_TAGVAR(lt_prog_compiler_pic, $1)=-Kconform_pic
fi
;;
hpux*)
# PIC is the default for 64-bit PA HP-UX, but not for 32-bit
# PA HP-UX. On IA64 HP-UX, PIC is the default but the pic flag
# sets the default TLS model and affects inlining.
case $host_cpu in
hppa*64*)
;;
*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
;;
esac
;;
*qnx* | *nto*)
# QNX uses GNU C++, but need to define -shared option too, otherwise
# it will coredump.
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC -shared'
;;
*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
;;
esac
else
case $host_os in
aix[[4-9]]*)
# All AIX code is PIC.
if test "$host_cpu" = ia64; then
# AIX 5 now supports IA64 processor
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
else
_LT_TAGVAR(lt_prog_compiler_static, $1)='-bnso -bI:/lib/syscalls.exp'
fi
;;
chorus*)
case $cc_basename in
cxch68*)
# Green Hills C++ Compiler
# _LT_TAGVAR(lt_prog_compiler_static, $1)="--no_auto_instantiation -u __main -u __premain -u _abort -r $COOL_DIR/lib/libOrb.a $MVME_DIR/lib/CC/libC.a $MVME_DIR/lib/classix/libcx.s.a"
;;
esac
;;
mingw* | cygwin* | os2* | pw32* | cegcc*)
# This hack is so that the source file can tell whether it is being
# built for inclusion in a dll (and should export symbols for example).
m4_if([$1], [GCJ], [],
[_LT_TAGVAR(lt_prog_compiler_pic, $1)='-DDLL_EXPORT'])
;;
dgux*)
case $cc_basename in
ec++*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
;;
ghcx*)
# Green Hills C++ Compiler
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-pic'
;;
*)
;;
esac
;;
freebsd* | dragonfly*)
# FreeBSD uses GNU C++
;;
hpux9* | hpux10* | hpux11*)
case $cc_basename in
CC*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_static, $1)='${wl}-a ${wl}archive'
if test "$host_cpu" != ia64; then
_LT_TAGVAR(lt_prog_compiler_pic, $1)='+Z'
fi
;;
aCC*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_static, $1)='${wl}-a ${wl}archive'
case $host_cpu in
hppa*64*|ia64*)
# +Z the default
;;
*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='+Z'
;;
esac
;;
*)
;;
esac
;;
interix*)
# This is c89, which is MS Visual C++ (no shared libs)
# Anyone wants to do a port?
;;
irix5* | irix6* | nonstopux*)
case $cc_basename in
CC*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-non_shared'
# CC pic flag -KPIC is the default.
;;
*)
;;
esac
;;
linux* | k*bsd*-gnu | kopensolaris*-gnu)
case $cc_basename in
KCC*)
# KAI C++ Compiler
_LT_TAGVAR(lt_prog_compiler_wl, $1)='--backend -Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
;;
ecpc* )
# old Intel C++ for x86_64 which still supported -KPIC.
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-static'
;;
icpc* )
# Intel C++, used to be incompatible with GCC.
# ICC 10 doesn't accept -KPIC any more.
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-static'
;;
pgCC* | pgcpp*)
# Portland Group C++ compiler
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fpic'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
cxx*)
# Compaq C++
# Make sure the PIC flag is empty. It appears that all Alpha
# Linux and Compaq Tru64 Unix objects are PIC.
_LT_TAGVAR(lt_prog_compiler_pic, $1)=
_LT_TAGVAR(lt_prog_compiler_static, $1)='-non_shared'
;;
xlc* | xlC* | bgxl[[cC]]* | mpixl[[cC]]*)
# IBM XL 8.0, 9.0 on PPC and BlueGene
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-qpic'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-qstaticlink'
;;
*)
case `$CC -V 2>&1 | sed 5q` in
*Sun\ C*)
# Sun C++ 5.9
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Qoption ld '
;;
esac
;;
esac
;;
lynxos*)
;;
m88k*)
;;
mvs*)
case $cc_basename in
cxx*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-W c,exportall'
;;
*)
;;
esac
;;
netbsd*)
;;
*qnx* | *nto*)
# QNX uses GNU C++, but need to define -shared option too, otherwise
# it will coredump.
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC -shared'
;;
osf3* | osf4* | osf5*)
case $cc_basename in
KCC*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='--backend -Wl,'
;;
RCC*)
# Rational C++ 2.4.1
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-pic'
;;
cxx*)
# Digital/Compaq C++
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
# Make sure the PIC flag is empty. It appears that all Alpha
# Linux and Compaq Tru64 Unix objects are PIC.
_LT_TAGVAR(lt_prog_compiler_pic, $1)=
_LT_TAGVAR(lt_prog_compiler_static, $1)='-non_shared'
;;
*)
;;
esac
;;
psos*)
;;
solaris*)
case $cc_basename in
CC* | sunCC*)
# Sun C++ 4.2, 5.x and Centerline C++
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Qoption ld '
;;
gcx*)
# Green Hills C++ Compiler
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-PIC'
;;
*)
;;
esac
;;
sunos4*)
case $cc_basename in
CC*)
# Sun C++ 4.x
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-pic'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
lcc*)
# Lucid
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-pic'
;;
*)
;;
esac
;;
sysv5* | unixware* | sco3.2v5* | sco5v6* | OpenUNIX*)
case $cc_basename in
CC*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
esac
;;
tandem*)
case $cc_basename in
NCC*)
# NonStop-UX NCC 3.20
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
;;
*)
;;
esac
;;
vxworks*)
;;
*)
_LT_TAGVAR(lt_prog_compiler_can_build_shared, $1)=no
;;
esac
fi
],
[
if test "$GCC" = yes; then
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-static'
case $host_os in
aix*)
# All AIX code is PIC.
if test "$host_cpu" = ia64; then
# AIX 5 now supports IA64 processor
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# see comment about AmigaOS4 .so support
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
;;
m68k)
# FIXME: we need at least 68020 code to build shared libraries, but
# adding the `-m68020' flag to GCC prevents building anything better,
# like `-m68040'.
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-m68020 -resident32 -malways-restore-a4'
;;
esac
;;
beos* | irix5* | irix6* | nonstopux* | osf3* | osf4* | osf5*)
# PIC is the default for these OSes.
;;
mingw* | cygwin* | pw32* | os2* | cegcc*)
# This hack is so that the source file can tell whether it is being
# built for inclusion in a dll (and should export symbols for example).
# Although the cygwin gcc ignores -fPIC, still need this for old-style
# (--disable-auto-import) libraries
m4_if([$1], [GCJ], [],
[_LT_TAGVAR(lt_prog_compiler_pic, $1)='-DDLL_EXPORT'])
;;
darwin* | rhapsody*)
# PIC is the default on this platform
# Common symbols not allowed in MH_DYLIB files
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fno-common'
;;
haiku*)
# PIC is the default for Haiku.
# The "-static" flag exists, but is broken.
_LT_TAGVAR(lt_prog_compiler_static, $1)=
;;
hpux*)
# PIC is the default for 64-bit PA HP-UX, but not for 32-bit
# PA HP-UX. On IA64 HP-UX, PIC is the default but the pic flag
# sets the default TLS model and affects inlining.
case $host_cpu in
hppa*64*)
# +Z the default
;;
*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
;;
esac
;;
interix[[3-9]]*)
# Interix 3.x gcc -fpic/-fPIC options generate broken code.
# Instead, we relocate shared libraries at runtime.
;;
msdosdjgpp*)
# Just because we use GCC doesn't mean we suddenly get shared libraries
# on systems that don't support them.
_LT_TAGVAR(lt_prog_compiler_can_build_shared, $1)=no
enable_shared=no
;;
*nto* | *qnx*)
# QNX uses GNU C++, but need to define -shared option too, otherwise
# it will coredump.
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC -shared'
;;
sysv4*MP*)
if test -d /usr/nec; then
_LT_TAGVAR(lt_prog_compiler_pic, $1)=-Kconform_pic
fi
;;
*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
;;
esac
case $cc_basename in
nvcc*) # Cuda Compiler Driver 2.2
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Xlinker '
if test -n "$_LT_TAGVAR(lt_prog_compiler_pic, $1)"; then
_LT_TAGVAR(lt_prog_compiler_pic, $1)="-Xcompiler $_LT_TAGVAR(lt_prog_compiler_pic, $1)"
fi
;;
esac
else
# PORTME Check for flag to pass linker flags through the system compiler.
case $host_os in
aix*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
if test "$host_cpu" = ia64; then
# AIX 5 now supports IA64 processor
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
else
_LT_TAGVAR(lt_prog_compiler_static, $1)='-bnso -bI:/lib/syscalls.exp'
fi
;;
mingw* | cygwin* | pw32* | os2* | cegcc*)
# This hack is so that the source file can tell whether it is being
# built for inclusion in a dll (and should export symbols for example).
m4_if([$1], [GCJ], [],
[_LT_TAGVAR(lt_prog_compiler_pic, $1)='-DDLL_EXPORT'])
;;
hpux9* | hpux10* | hpux11*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
# PIC is the default for IA64 HP-UX and 64-bit HP-UX, but
# not for PA HP-UX.
case $host_cpu in
hppa*64*|ia64*)
# +Z the default
;;
*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='+Z'
;;
esac
# Is there a better lt_prog_compiler_static that works with the bundled CC?
_LT_TAGVAR(lt_prog_compiler_static, $1)='${wl}-a ${wl}archive'
;;
irix5* | irix6* | nonstopux*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
# PIC (with -KPIC) is the default.
_LT_TAGVAR(lt_prog_compiler_static, $1)='-non_shared'
;;
linux* | k*bsd*-gnu | kopensolaris*-gnu)
case $cc_basename in
# old Intel for x86_64 which still supported -KPIC.
ecc*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-static'
;;
# icc used to be incompatible with GCC.
# ICC 10 doesn't accept -KPIC any more.
icc* | ifort*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-static'
;;
# Lahey Fortran 8.1.
lf95*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='--shared'
_LT_TAGVAR(lt_prog_compiler_static, $1)='--static'
;;
nagfor*)
# NAG Fortran compiler
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,-Wl,,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-PIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
pgcc* | pgf77* | pgf90* | pgf95* | pgfortran*)
# Portland Group compilers (*not* the Pentium gcc compiler,
# which looks to be a dead project)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fpic'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
ccc*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
# All Alpha code is PIC.
_LT_TAGVAR(lt_prog_compiler_static, $1)='-non_shared'
;;
xl* | bgxl* | bgf* | mpixl*)
# IBM XL C 8.0/Fortran 10.1, 11.1 on PPC and BlueGene
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-qpic'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-qstaticlink'
;;
*)
case `$CC -V 2>&1 | sed 5q` in
*Sun\ Ceres\ Fortran* | *Sun*Fortran*\ [[1-7]].* | *Sun*Fortran*\ 8.[[0-3]]*)
# Sun Fortran 8.3 passes all unrecognized flags to the linker
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
_LT_TAGVAR(lt_prog_compiler_wl, $1)=''
;;
*Sun\ F* | *Sun*Fortran*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Qoption ld '
;;
*Sun\ C*)
# Sun C 5.9
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
;;
*Intel*\ [[CF]]*Compiler*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-static'
;;
*Portland\ Group*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fpic'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
esac
;;
esac
;;
newsos6)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
*nto* | *qnx*)
# QNX uses GNU C++, but need to define -shared option too, otherwise
# it will coredump.
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-fPIC -shared'
;;
osf3* | osf4* | osf5*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
# All OSF/1 code is PIC.
_LT_TAGVAR(lt_prog_compiler_static, $1)='-non_shared'
;;
rdos*)
_LT_TAGVAR(lt_prog_compiler_static, $1)='-non_shared'
;;
solaris*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
case $cc_basename in
f77* | f90* | f95* | sunf77* | sunf90* | sunf95*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Qoption ld ';;
*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,';;
esac
;;
sunos4*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Qoption ld '
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-PIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
sysv4 | sysv4.2uw2* | sysv4.3*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
sysv4*MP*)
if test -d /usr/nec ;then
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-Kconform_pic'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
fi
;;
sysv5* | unixware* | sco3.2v5* | sco5v6* | OpenUNIX*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-KPIC'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
unicos*)
_LT_TAGVAR(lt_prog_compiler_wl, $1)='-Wl,'
_LT_TAGVAR(lt_prog_compiler_can_build_shared, $1)=no
;;
uts4*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)='-pic'
_LT_TAGVAR(lt_prog_compiler_static, $1)='-Bstatic'
;;
*)
_LT_TAGVAR(lt_prog_compiler_can_build_shared, $1)=no
;;
esac
fi
])
case $host_os in
# For platforms which do not support PIC, -DPIC is meaningless:
*djgpp*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)=
;;
*)
_LT_TAGVAR(lt_prog_compiler_pic, $1)="$_LT_TAGVAR(lt_prog_compiler_pic, $1)@&t@m4_if([$1],[],[ -DPIC],[m4_if([$1],[CXX],[ -DPIC],[])])"
;;
esac
AC_CACHE_CHECK([for $compiler option to produce PIC],
[_LT_TAGVAR(lt_cv_prog_compiler_pic, $1)],
[_LT_TAGVAR(lt_cv_prog_compiler_pic, $1)=$_LT_TAGVAR(lt_prog_compiler_pic, $1)])
_LT_TAGVAR(lt_prog_compiler_pic, $1)=$_LT_TAGVAR(lt_cv_prog_compiler_pic, $1)
#
# Check to make sure the PIC flag actually works.
#
if test -n "$_LT_TAGVAR(lt_prog_compiler_pic, $1)"; then
_LT_COMPILER_OPTION([if $compiler PIC flag $_LT_TAGVAR(lt_prog_compiler_pic, $1) works],
[_LT_TAGVAR(lt_cv_prog_compiler_pic_works, $1)],
[$_LT_TAGVAR(lt_prog_compiler_pic, $1)@&t@m4_if([$1],[],[ -DPIC],[m4_if([$1],[CXX],[ -DPIC],[])])], [],
[case $_LT_TAGVAR(lt_prog_compiler_pic, $1) in
"" | " "*) ;;
*) _LT_TAGVAR(lt_prog_compiler_pic, $1)=" $_LT_TAGVAR(lt_prog_compiler_pic, $1)" ;;
esac],
[_LT_TAGVAR(lt_prog_compiler_pic, $1)=
_LT_TAGVAR(lt_prog_compiler_can_build_shared, $1)=no])
fi
_LT_TAGDECL([pic_flag], [lt_prog_compiler_pic], [1],
[Additional compiler flags for building library objects])
_LT_TAGDECL([wl], [lt_prog_compiler_wl], [1],
[How to pass a linker flag through the compiler])
#
# Check to make sure the static flag actually works.
#
wl=$_LT_TAGVAR(lt_prog_compiler_wl, $1) eval lt_tmp_static_flag=\"$_LT_TAGVAR(lt_prog_compiler_static, $1)\"
_LT_LINKER_OPTION([if $compiler static flag $lt_tmp_static_flag works],
_LT_TAGVAR(lt_cv_prog_compiler_static_works, $1),
$lt_tmp_static_flag,
[],
[_LT_TAGVAR(lt_prog_compiler_static, $1)=])
_LT_TAGDECL([link_static_flag], [lt_prog_compiler_static], [1],
[Compiler flag to prevent dynamic linking])
])# _LT_COMPILER_PIC
# _LT_LINKER_SHLIBS([TAGNAME])
# ----------------------------
# See if the linker supports building shared libraries.
m4_defun([_LT_LINKER_SHLIBS],
[AC_REQUIRE([LT_PATH_LD])dnl
AC_REQUIRE([LT_PATH_NM])dnl
m4_require([_LT_PATH_MANIFEST_TOOL])dnl
m4_require([_LT_FILEUTILS_DEFAULTS])dnl
m4_require([_LT_DECL_EGREP])dnl
m4_require([_LT_DECL_SED])dnl
m4_require([_LT_CMD_GLOBAL_SYMBOLS])dnl
m4_require([_LT_TAG_COMPILER])dnl
AC_MSG_CHECKING([whether the $compiler linker ($LD) supports shared libraries])
m4_if([$1], [CXX], [
_LT_TAGVAR(export_symbols_cmds, $1)='$NM $libobjs $convenience | $global_symbol_pipe | $SED '\''s/.* //'\'' | sort | uniq > $export_symbols'
_LT_TAGVAR(exclude_expsyms, $1)=['_GLOBAL_OFFSET_TABLE_|_GLOBAL__F[ID]_.*']
case $host_os in
aix[[4-9]]*)
# If we're using GNU nm, then we don't want the "-C" option.
# -C means demangle to AIX nm, but means don't demangle with GNU nm
# Also, AIX nm treats weak defined symbols like other global defined
# symbols, whereas GNU nm marks them as "W".
if $NM -V 2>&1 | $GREP 'GNU' > /dev/null; then
_LT_TAGVAR(export_symbols_cmds, $1)='$NM -Bpg $libobjs $convenience | awk '\''{ if (((\$ 2 == "T") || (\$ 2 == "D") || (\$ 2 == "B") || (\$ 2 == "W")) && ([substr](\$ 3,1,1) != ".")) { print \$ 3 } }'\'' | sort -u > $export_symbols'
else
_LT_TAGVAR(export_symbols_cmds, $1)='$NM -BCpg $libobjs $convenience | awk '\''{ if (((\$ 2 == "T") || (\$ 2 == "D") || (\$ 2 == "B")) && ([substr](\$ 3,1,1) != ".")) { print \$ 3 } }'\'' | sort -u > $export_symbols'
fi
;;
pw32*)
_LT_TAGVAR(export_symbols_cmds, $1)="$ltdll_cmds"
;;
cygwin* | mingw* | cegcc*)
case $cc_basename in
cl*)
_LT_TAGVAR(exclude_expsyms, $1)='_NULL_IMPORT_DESCRIPTOR|_IMPORT_DESCRIPTOR_.*'
;;
*)
_LT_TAGVAR(export_symbols_cmds, $1)='$NM $libobjs $convenience | $global_symbol_pipe | $SED -e '\''/^[[BCDGRS]][[ ]]/s/.*[[ ]]\([[^ ]]*\)/\1 DATA/;s/^.*[[ ]]__nm__\([[^ ]]*\)[[ ]][[^ ]]*/\1 DATA/;/^I[[ ]]/d;/^[[AITW]][[ ]]/s/.* //'\'' | sort | uniq > $export_symbols'
_LT_TAGVAR(exclude_expsyms, $1)=['[_]+GLOBAL_OFFSET_TABLE_|[_]+GLOBAL__[FID]_.*|[_]+head_[A-Za-z0-9_]+_dll|[A-Za-z0-9_]+_dll_iname']
;;
esac
;;
*)
_LT_TAGVAR(export_symbols_cmds, $1)='$NM $libobjs $convenience | $global_symbol_pipe | $SED '\''s/.* //'\'' | sort | uniq > $export_symbols'
;;
esac
], [
runpath_var=
_LT_TAGVAR(allow_undefined_flag, $1)=
_LT_TAGVAR(always_export_symbols, $1)=no
_LT_TAGVAR(archive_cmds, $1)=
_LT_TAGVAR(archive_expsym_cmds, $1)=
_LT_TAGVAR(compiler_needs_object, $1)=no
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=no
_LT_TAGVAR(export_dynamic_flag_spec, $1)=
_LT_TAGVAR(export_symbols_cmds, $1)='$NM $libobjs $convenience | $global_symbol_pipe | $SED '\''s/.* //'\'' | sort | uniq > $export_symbols'
_LT_TAGVAR(hardcode_automatic, $1)=no
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_direct_absolute, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)=
_LT_TAGVAR(hardcode_libdir_separator, $1)=
_LT_TAGVAR(hardcode_minus_L, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=unsupported
_LT_TAGVAR(inherit_rpath, $1)=no
_LT_TAGVAR(link_all_deplibs, $1)=unknown
_LT_TAGVAR(module_cmds, $1)=
_LT_TAGVAR(module_expsym_cmds, $1)=
_LT_TAGVAR(old_archive_from_new_cmds, $1)=
_LT_TAGVAR(old_archive_from_expsyms_cmds, $1)=
_LT_TAGVAR(thread_safe_flag_spec, $1)=
_LT_TAGVAR(whole_archive_flag_spec, $1)=
# include_expsyms should be a list of space-separated symbols to be *always*
# included in the symbol list
_LT_TAGVAR(include_expsyms, $1)=
# exclude_expsyms can be an extended regexp of symbols to exclude
# it will be wrapped by ` (' and `)$', so one must not match beginning or
# end of line. Example: `a|bc|.*d.*' will exclude the symbols `a' and `bc',
# as well as any symbol that contains `d'.
_LT_TAGVAR(exclude_expsyms, $1)=['_GLOBAL_OFFSET_TABLE_|_GLOBAL__F[ID]_.*']
# Although _GLOBAL_OFFSET_TABLE_ is a valid symbol C name, most a.out
# platforms (ab)use it in PIC code, but their linkers get confused if
# the symbol is explicitly referenced. Since portable code cannot
# rely on this symbol name, it's probably fine to never include it in
# preloaded symbol tables.
# Exclude shared library initialization/finalization symbols.
dnl Note also adjust exclude_expsyms for C++ above.
extract_expsyms_cmds=
case $host_os in
cygwin* | mingw* | pw32* | cegcc*)
# FIXME: the MSVC++ port hasn't been tested in a loooong time
# When not using gcc, we currently assume that we are using
# Microsoft Visual C++.
if test "$GCC" != yes; then
with_gnu_ld=no
fi
;;
interix*)
# we just hope/assume this is gcc and not c89 (= MSVC++)
with_gnu_ld=yes
;;
openbsd*)
with_gnu_ld=no
;;
esac
_LT_TAGVAR(ld_shlibs, $1)=yes
# On some targets, GNU ld is compatible enough with the native linker
# that we're better off using the native interface for both.
lt_use_gnu_ld_interface=no
if test "$with_gnu_ld" = yes; then
case $host_os in
aix*)
# The AIX port of GNU ld has always aspired to compatibility
# with the native linker. However, as the warning in the GNU ld
# block says, versions before 2.19.5* couldn't really create working
# shared libraries, regardless of the interface used.
case `$LD -v 2>&1` in
*\ \(GNU\ Binutils\)\ 2.19.5*) ;;
*\ \(GNU\ Binutils\)\ 2.[[2-9]]*) ;;
*\ \(GNU\ Binutils\)\ [[3-9]]*) ;;
*)
lt_use_gnu_ld_interface=yes
;;
esac
;;
*)
lt_use_gnu_ld_interface=yes
;;
esac
fi
if test "$lt_use_gnu_ld_interface" = yes; then
# If archive_cmds runs LD, not CC, wlarc should be empty
wlarc='${wl}'
# Set some defaults for GNU ld with shared library support. These
# are reset later if shared libraries are not supported. Putting them
# here allows them to be overridden if necessary.
runpath_var=LD_RUN_PATH
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-dynamic'
# ancient GNU ld didn't support --whole-archive et. al.
if $LD --help 2>&1 | $GREP 'no-whole-archive' > /dev/null; then
_LT_TAGVAR(whole_archive_flag_spec, $1)="$wlarc"'--whole-archive$convenience '"$wlarc"'--no-whole-archive'
else
_LT_TAGVAR(whole_archive_flag_spec, $1)=
fi
supports_anon_versioning=no
case `$LD -v 2>&1` in
*GNU\ gold*) supports_anon_versioning=yes ;;
*\ [[01]].* | *\ 2.[[0-9]].* | *\ 2.10.*) ;; # catch versions < 2.11
*\ 2.11.93.0.2\ *) supports_anon_versioning=yes ;; # RH7.3 ...
*\ 2.11.92.0.12\ *) supports_anon_versioning=yes ;; # Mandrake 8.2 ...
*\ 2.11.*) ;; # other 2.11 versions
*) supports_anon_versioning=yes ;;
esac
# See if GNU ld supports shared libraries.
case $host_os in
aix[[3-9]]*)
# On AIX/PPC, the GNU linker is very broken
if test "$host_cpu" != ia64; then
_LT_TAGVAR(ld_shlibs, $1)=no
cat <<_LT_EOF 1>&2
*** Warning: the GNU linker, at least up to release 2.19, is reported
*** to be unable to reliably create shared libraries on AIX.
*** Therefore, libtool is disabling shared libraries support. If you
*** really care for shared libraries, you may want to install binutils
*** 2.20 or above, or modify your PATH so that a non-GNU linker is found.
*** You will then need to restart the configuration process.
_LT_EOF
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# see comment about AmigaOS4 .so support
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)=''
;;
m68k)
_LT_TAGVAR(archive_cmds, $1)='$RM $output_objdir/a2ixlibrary.data~$ECHO "#define NAME $libname" > $output_objdir/a2ixlibrary.data~$ECHO "#define LIBRARY_ID 1" >> $output_objdir/a2ixlibrary.data~$ECHO "#define VERSION $major" >> $output_objdir/a2ixlibrary.data~$ECHO "#define REVISION $revision" >> $output_objdir/a2ixlibrary.data~$AR $AR_FLAGS $lib $libobjs~$RANLIB $lib~(cd $output_objdir && a2ixlibrary -32)'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(hardcode_minus_L, $1)=yes
;;
esac
;;
beos*)
if $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
# Joseph Beckenbach says some releases of gcc
# support --undefined. This deserves some investigation. FIXME
_LT_TAGVAR(archive_cmds, $1)='$CC -nostart $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
cygwin* | mingw* | pw32* | cegcc*)
# _LT_TAGVAR(hardcode_libdir_flag_spec, $1) is actually meaningless,
# as there is no search path for DLLs.
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-all-symbols'
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
_LT_TAGVAR(always_export_symbols, $1)=no
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=yes
_LT_TAGVAR(export_symbols_cmds, $1)='$NM $libobjs $convenience | $global_symbol_pipe | $SED -e '\''/^[[BCDGRS]][[ ]]/s/.*[[ ]]\([[^ ]]*\)/\1 DATA/;s/^.*[[ ]]__nm__\([[^ ]]*\)[[ ]][[^ ]]*/\1 DATA/;/^I[[ ]]/d;/^[[AITW]][[ ]]/s/.* //'\'' | sort | uniq > $export_symbols'
_LT_TAGVAR(exclude_expsyms, $1)=['[_]+GLOBAL_OFFSET_TABLE_|[_]+GLOBAL__[FID]_.*|[_]+head_[A-Za-z0-9_]+_dll|[A-Za-z0-9_]+_dll_iname']
if $LD --help 2>&1 | $GREP 'auto-import' > /dev/null; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib'
# If the export-symbols file already is a .def file (1st line
# is EXPORTS), use it as is; otherwise, prepend...
_LT_TAGVAR(archive_expsym_cmds, $1)='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then
cp $export_symbols $output_objdir/$soname.def;
else
echo EXPORTS > $output_objdir/$soname.def;
cat $export_symbols >> $output_objdir/$soname.def;
fi~
$CC -shared $output_objdir/$soname.def $libobjs $deplibs $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib'
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
haiku*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(link_all_deplibs, $1)=yes
;;
interix[[3-9]]*)
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
# Hack: On Interix 3.x, we cannot compile PIC because of a broken gcc.
# Instead, shared libraries are loaded at an image base (0x10000000 by
# default) and relocated if they conflict, which is a slow very memory
# consuming and fragmenting process. To avoid this, we pick a random,
# 256 KiB-aligned image base between 0x50000000 and 0x6FFC0000 at link
# time. Moving up from 0x10000000 also allows more sbrk(2) space.
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='sed "s,^,_," $export_symbols >$output_objdir/$soname.expsym~$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--retain-symbols-file,$output_objdir/$soname.expsym ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib'
;;
gnu* | linux* | tpf* | k*bsd*-gnu | kopensolaris*-gnu)
tmp_diet=no
if test "$host_os" = linux-dietlibc; then
case $cc_basename in
diet\ *) tmp_diet=yes;; # linux-dietlibc with static linking (!diet-dyn)
esac
fi
if $LD --help 2>&1 | $EGREP ': supported targets:.* elf' > /dev/null \
&& test "$tmp_diet" = no
then
tmp_addflag=' $pic_flag'
tmp_sharedflag='-shared'
case $cc_basename,$host_cpu in
pgcc*) # Portland Group C compiler
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
tmp_addflag=' $pic_flag'
;;
pgf77* | pgf90* | pgf95* | pgfortran*)
# Portland Group f77 and f90 compilers
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
tmp_addflag=' $pic_flag -Mnomain' ;;
ecc*,ia64* | icc*,ia64*) # Intel C compiler on ia64
tmp_addflag=' -i_dynamic' ;;
efc*,ia64* | ifort*,ia64*) # Intel Fortran compiler on ia64
tmp_addflag=' -i_dynamic -nofor_main' ;;
ifc* | ifort*) # Intel Fortran compiler
tmp_addflag=' -nofor_main' ;;
lf95*) # Lahey Fortran 8.1
_LT_TAGVAR(whole_archive_flag_spec, $1)=
tmp_sharedflag='--shared' ;;
xl[[cC]]* | bgxl[[cC]]* | mpixl[[cC]]*) # IBM XL C 8.0 on PPC (deal with xlf below)
tmp_sharedflag='-qmkshrobj'
tmp_addflag= ;;
nvcc*) # Cuda Compiler Driver 2.2
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
_LT_TAGVAR(compiler_needs_object, $1)=yes
;;
esac
case `$CC -V 2>&1 | sed 5q` in
*Sun\ C*) # Sun C 5.9
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`new_convenience=; for conv in $convenience\"\"; do test -z \"$conv\" || new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
_LT_TAGVAR(compiler_needs_object, $1)=yes
tmp_sharedflag='-G' ;;
*Sun\ F*) # Sun Fortran 8.3
tmp_sharedflag='-G' ;;
esac
_LT_TAGVAR(archive_cmds, $1)='$CC '"$tmp_sharedflag""$tmp_addflag"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
if test "x$supports_anon_versioning" = xyes; then
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $output_objdir/$libname.ver~
cat $export_symbols | sed -e "s/\(.*\)/\1;/" >> $output_objdir/$libname.ver~
echo "local: *; };" >> $output_objdir/$libname.ver~
$CC '"$tmp_sharedflag""$tmp_addflag"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-version-script ${wl}$output_objdir/$libname.ver -o $lib'
fi
case $cc_basename in
xlf* | bgf* | bgxlf* | mpixlf*)
# IBM XL Fortran 10.1 on PPC cannot create shared libs itself
_LT_TAGVAR(whole_archive_flag_spec, $1)='--whole-archive$convenience --no-whole-archive'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(archive_cmds, $1)='$LD -shared $libobjs $deplibs $linker_flags -soname $soname -o $lib'
if test "x$supports_anon_versioning" = xyes; then
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $output_objdir/$libname.ver~
cat $export_symbols | sed -e "s/\(.*\)/\1;/" >> $output_objdir/$libname.ver~
echo "local: *; };" >> $output_objdir/$libname.ver~
$LD -shared $libobjs $deplibs $linker_flags -soname $soname -version-script $output_objdir/$libname.ver -o $lib'
fi
;;
esac
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
netbsd*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
_LT_TAGVAR(archive_cmds, $1)='$LD -Bshareable $libobjs $deplibs $linker_flags -o $lib'
wlarc=
else
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
fi
;;
solaris*)
if $LD -v 2>&1 | $GREP 'BFD 2\.8' > /dev/null; then
_LT_TAGVAR(ld_shlibs, $1)=no
cat <<_LT_EOF 1>&2
*** Warning: The releases 2.8.* of the GNU linker cannot reliably
*** create shared libraries on Solaris systems. Therefore, libtool
*** is disabling shared libraries support. We urge you to upgrade GNU
*** binutils to release 2.9.1 or newer. Another option is to modify
*** your PATH or compiler configuration so that the native linker is
*** used, and then restart.
_LT_EOF
elif $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX*)
case `$LD -v 2>&1` in
*\ [[01]].* | *\ 2.[[0-9]].* | *\ 2.1[[0-5]].*)
_LT_TAGVAR(ld_shlibs, $1)=no
cat <<_LT_EOF 1>&2
*** Warning: Releases of the GNU linker prior to 2.16.91.0.3 can not
*** reliably create shared libraries on SCO systems. Therefore, libtool
*** is disabling shared libraries support. We urge you to upgrade GNU
*** binutils to release 2.16.91.0.3 or newer. Another option is to modify
*** your PATH or compiler configuration so that the native linker is
*** used, and then restart.
_LT_EOF
;;
*)
# For security reasons, it is highly recommended that you always
# use absolute paths for naming shared libraries, and exclude the
# DT_RUNPATH tag from executables and libraries. But doing so
# requires that you compile everything twice, which is a pain.
if $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
esac
;;
sunos4*)
_LT_TAGVAR(archive_cmds, $1)='$LD -assert pure-text -Bshareable -o $lib $libobjs $deplibs $linker_flags'
wlarc=
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
*)
if $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
esac
if test "$_LT_TAGVAR(ld_shlibs, $1)" = no; then
runpath_var=
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)=
_LT_TAGVAR(export_dynamic_flag_spec, $1)=
_LT_TAGVAR(whole_archive_flag_spec, $1)=
fi
else
# PORTME fill in a description of your system's linker (not GNU ld)
case $host_os in
aix3*)
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
_LT_TAGVAR(always_export_symbols, $1)=yes
_LT_TAGVAR(archive_expsym_cmds, $1)='$LD -o $output_objdir/$soname $libobjs $deplibs $linker_flags -bE:$export_symbols -T512 -H512 -bM:SRE~$AR $AR_FLAGS $lib $output_objdir/$soname'
# Note: this linker hardcodes the directories in LIBPATH if there
# are no directories specified by -L.
_LT_TAGVAR(hardcode_minus_L, $1)=yes
if test "$GCC" = yes && test -z "$lt_prog_compiler_static"; then
# Neither direct hardcoding nor static linking is supported with a
# broken collect2.
_LT_TAGVAR(hardcode_direct, $1)=unsupported
fi
;;
aix[[4-9]]*)
if test "$host_cpu" = ia64; then
# On IA64, the linker does run time linking by default, so we don't
# have to do anything special.
aix_use_runtimelinking=no
exp_sym_flag='-Bexport'
no_entry_flag=""
else
# If we're using GNU nm, then we don't want the "-C" option.
# -C means demangle to AIX nm, but means don't demangle with GNU nm
# Also, AIX nm treats weak defined symbols like other global
# defined symbols, whereas GNU nm marks them as "W".
if $NM -V 2>&1 | $GREP 'GNU' > /dev/null; then
_LT_TAGVAR(export_symbols_cmds, $1)='$NM -Bpg $libobjs $convenience | awk '\''{ if (((\$ 2 == "T") || (\$ 2 == "D") || (\$ 2 == "B") || (\$ 2 == "W")) && ([substr](\$ 3,1,1) != ".")) { print \$ 3 } }'\'' | sort -u > $export_symbols'
else
_LT_TAGVAR(export_symbols_cmds, $1)='$NM -BCpg $libobjs $convenience | awk '\''{ if (((\$ 2 == "T") || (\$ 2 == "D") || (\$ 2 == "B")) && ([substr](\$ 3,1,1) != ".")) { print \$ 3 } }'\'' | sort -u > $export_symbols'
fi
aix_use_runtimelinking=no
# Test if we are trying to use run time linking or normal
# AIX style linking. If -brtl is somewhere in LDFLAGS, we
# need to do runtime linking.
case $host_os in aix4.[[23]]|aix4.[[23]].*|aix[[5-9]]*)
for ld_flag in $LDFLAGS; do
if (test $ld_flag = "-brtl" || test $ld_flag = "-Wl,-brtl"); then
aix_use_runtimelinking=yes
break
fi
done
;;
esac
exp_sym_flag='-bexport'
no_entry_flag='-bnoentry'
fi
# When large executables or shared objects are built, AIX ld can
# have problems creating the table of contents. If linking a library
# or program results in "error TOC overflow" add -mminimal-toc to
# CXXFLAGS/CFLAGS for g++/gcc. In the cases where that is not
# enough to fix the problem, add -Wl,-bbigtoc to LDFLAGS.
_LT_TAGVAR(archive_cmds, $1)=''
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_direct_absolute, $1)=yes
_LT_TAGVAR(hardcode_libdir_separator, $1)=':'
_LT_TAGVAR(link_all_deplibs, $1)=yes
_LT_TAGVAR(file_list_spec, $1)='${wl}-f,'
if test "$GCC" = yes; then
case $host_os in aix4.[[012]]|aix4.[[012]].*)
# We only want to do this on AIX 4.2 and lower, the check
# below for broken collect2 doesn't work under 4.3+
collect2name=`${CC} -print-prog-name=collect2`
if test -f "$collect2name" &&
strings "$collect2name" | $GREP resolve_lib_name >/dev/null
then
# We have reworked collect2
:
else
# We have old collect2
_LT_TAGVAR(hardcode_direct, $1)=unsupported
# It fails to find uninstalled libraries when the uninstalled
# path is not listed in the libpath. Setting hardcode_minus_L
# to unsupported forces relinking
_LT_TAGVAR(hardcode_minus_L, $1)=yes
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=
fi
;;
esac
shared_flag='-shared'
if test "$aix_use_runtimelinking" = yes; then
shared_flag="$shared_flag "'${wl}-G'
fi
else
# not using gcc
if test "$host_cpu" = ia64; then
# VisualAge C++, Version 5.5 for AIX 5L for IA-64, Beta 3 Release
# chokes on -Wl,-G. The following line is correct:
shared_flag='-G'
else
if test "$aix_use_runtimelinking" = yes; then
shared_flag='${wl}-G'
else
shared_flag='${wl}-bM:SRE'
fi
fi
fi
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-bexpall'
# It seems that -bexpall does not export symbols beginning with
# underscore (_), so it is better to generate a list of symbols to export.
_LT_TAGVAR(always_export_symbols, $1)=yes
if test "$aix_use_runtimelinking" = yes; then
# Warning - without using the other runtime loading flags (-brtl),
# -berok will link without error, but may produce a broken library.
_LT_TAGVAR(allow_undefined_flag, $1)='-berok'
# Determine the default libpath from the value encoded in an
# empty executable.
_LT_SYS_MODULE_PATH_AIX([$1])
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-blibpath:$libdir:'"$aix_libpath"
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags `if test "x${allow_undefined_flag}" != "x"; then func_echo_all "${wl}${allow_undefined_flag}"; else :; fi` '"\${wl}$exp_sym_flag:\$export_symbols $shared_flag"
else
if test "$host_cpu" = ia64; then
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-R $libdir:/usr/lib:/lib'
_LT_TAGVAR(allow_undefined_flag, $1)="-z nodefs"
_LT_TAGVAR(archive_expsym_cmds, $1)="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags ${wl}${allow_undefined_flag} '"\${wl}$exp_sym_flag:\$export_symbols"
else
# Determine the default libpath from the value encoded in an
# empty executable.
_LT_SYS_MODULE_PATH_AIX([$1])
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-blibpath:$libdir:'"$aix_libpath"
# Warning - without using the other run time loading flags,
# -berok will link without error, but may produce a broken library.
_LT_TAGVAR(no_undefined_flag, $1)=' ${wl}-bernotok'
_LT_TAGVAR(allow_undefined_flag, $1)=' ${wl}-berok'
if test "$with_gnu_ld" = yes; then
# We only use this code for GNU lds that support --whole-archive.
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive$convenience ${wl}--no-whole-archive'
else
# Exported symbols can be pulled into shared objects from archives
_LT_TAGVAR(whole_archive_flag_spec, $1)='$convenience'
fi
_LT_TAGVAR(archive_cmds_need_lc, $1)=yes
# This is similar to how AIX traditionally builds its shared libraries.
_LT_TAGVAR(archive_expsym_cmds, $1)="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs ${wl}-bnoentry $compiler_flags ${wl}-bE:$export_symbols${allow_undefined_flag}~$AR $AR_FLAGS $output_objdir/$libname$release.a $output_objdir/$soname'
fi
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# see comment about AmigaOS4 .so support
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)=''
;;
m68k)
_LT_TAGVAR(archive_cmds, $1)='$RM $output_objdir/a2ixlibrary.data~$ECHO "#define NAME $libname" > $output_objdir/a2ixlibrary.data~$ECHO "#define LIBRARY_ID 1" >> $output_objdir/a2ixlibrary.data~$ECHO "#define VERSION $major" >> $output_objdir/a2ixlibrary.data~$ECHO "#define REVISION $revision" >> $output_objdir/a2ixlibrary.data~$AR $AR_FLAGS $lib $libobjs~$RANLIB $lib~(cd $output_objdir && a2ixlibrary -32)'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(hardcode_minus_L, $1)=yes
;;
esac
;;
bsdi[[45]]*)
_LT_TAGVAR(export_dynamic_flag_spec, $1)=-rdynamic
;;
cygwin* | mingw* | pw32* | cegcc*)
# When not using gcc, we currently assume that we are using
# Microsoft Visual C++.
# hardcode_libdir_flag_spec is actually meaningless, as there is
# no search path for DLLs.
case $cc_basename in
cl*)
# Native MSVC
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)=' '
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
_LT_TAGVAR(always_export_symbols, $1)=yes
_LT_TAGVAR(file_list_spec, $1)='@'
# Tell ltmain to make .lib files, not .a files.
libext=lib
# Tell ltmain to make .dll files, not .so files.
shrext_cmds=".dll"
# FIXME: Setting linknames here is a bad hack.
_LT_TAGVAR(archive_cmds, $1)='$CC -o $output_objdir/$soname $libobjs $compiler_flags $deplibs -Wl,-dll~linknames='
_LT_TAGVAR(archive_expsym_cmds, $1)='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then
sed -n -e 's/\\\\\\\(.*\\\\\\\)/-link\\\ -EXPORT:\\\\\\\1/' -e '1\\\!p' < $export_symbols > $output_objdir/$soname.exp;
else
sed -e 's/\\\\\\\(.*\\\\\\\)/-link\\\ -EXPORT:\\\\\\\1/' < $export_symbols > $output_objdir/$soname.exp;
fi~
$CC -o $tool_output_objdir$soname $libobjs $compiler_flags $deplibs "@$tool_output_objdir$soname.exp" -Wl,-DLL,-IMPLIB:"$tool_output_objdir$libname.dll.lib"~
linknames='
# The linker will not automatically build a static lib if we build a DLL.
# _LT_TAGVAR(old_archive_from_new_cmds, $1)='true'
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=yes
_LT_TAGVAR(exclude_expsyms, $1)='_NULL_IMPORT_DESCRIPTOR|_IMPORT_DESCRIPTOR_.*'
_LT_TAGVAR(export_symbols_cmds, $1)='$NM $libobjs $convenience | $global_symbol_pipe | $SED -e '\''/^[[BCDGRS]][[ ]]/s/.*[[ ]]\([[^ ]]*\)/\1,DATA/'\'' | $SED -e '\''/^[[AITW]][[ ]]/s/.*[[ ]]//'\'' | sort | uniq > $export_symbols'
# Don't use ranlib
_LT_TAGVAR(old_postinstall_cmds, $1)='chmod 644 $oldlib'
_LT_TAGVAR(postlink_cmds, $1)='lt_outputfile="@OUTPUT@"~
lt_tool_outputfile="@TOOL_OUTPUT@"~
case $lt_outputfile in
*.exe|*.EXE) ;;
*)
lt_outputfile="$lt_outputfile.exe"
lt_tool_outputfile="$lt_tool_outputfile.exe"
;;
esac~
if test "$MANIFEST_TOOL" != ":" && test -f "$lt_outputfile.manifest"; then
$MANIFEST_TOOL -manifest "$lt_tool_outputfile.manifest" -outputresource:"$lt_tool_outputfile" || exit 1;
$RM "$lt_outputfile.manifest";
fi'
;;
*)
# Assume MSVC wrapper
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)=' '
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
# Tell ltmain to make .lib files, not .a files.
libext=lib
# Tell ltmain to make .dll files, not .so files.
shrext_cmds=".dll"
# FIXME: Setting linknames here is a bad hack.
_LT_TAGVAR(archive_cmds, $1)='$CC -o $lib $libobjs $compiler_flags `func_echo_all "$deplibs" | $SED '\''s/ -lc$//'\''` -link -dll~linknames='
# The linker will automatically build a .lib file if we build a DLL.
_LT_TAGVAR(old_archive_from_new_cmds, $1)='true'
# FIXME: Should let the user specify the lib program.
_LT_TAGVAR(old_archive_cmds, $1)='lib -OUT:$oldlib$oldobjs$old_deplibs'
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=yes
;;
esac
;;
darwin* | rhapsody*)
_LT_DARWIN_LINKER_FEATURES($1)
;;
dgux*)
_LT_TAGVAR(archive_cmds, $1)='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
# FreeBSD 2.2.[012] allows us to include c++rt0.o to get C++ constructor
# support. Future versions do this automatically, but an explicit c++rt0.o
# does not break anything, and helps significantly (at the cost of a little
# extra space).
freebsd2.2*)
_LT_TAGVAR(archive_cmds, $1)='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags /usr/lib/c++rt0.o'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-R$libdir'
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
# Unfortunately, older versions of FreeBSD 2 do not have this feature.
freebsd2.*)
_LT_TAGVAR(archive_cmds, $1)='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_minus_L, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
# FreeBSD 3 and greater uses gcc -shared to do shared libraries.
freebsd* | dragonfly*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-R$libdir'
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
hpux9*)
if test "$GCC" = yes; then
_LT_TAGVAR(archive_cmds, $1)='$RM $output_objdir/$soname~$CC -shared $pic_flag ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $libobjs $deplibs $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib'
else
_LT_TAGVAR(archive_cmds, $1)='$RM $output_objdir/$soname~$LD -b +b $install_libdir -o $output_objdir/$soname $libobjs $deplibs $linker_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib'
fi
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}+b ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
_LT_TAGVAR(hardcode_direct, $1)=yes
# hardcode_minus_L: Not really in the search PATH,
# but as the default location of the library.
_LT_TAGVAR(hardcode_minus_L, $1)=yes
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
;;
hpux10*)
if test "$GCC" = yes && test "$with_gnu_ld" = no; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags'
else
_LT_TAGVAR(archive_cmds, $1)='$LD -b +h $soname +b $install_libdir -o $lib $libobjs $deplibs $linker_flags'
fi
if test "$with_gnu_ld" = no; then
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}+b ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_direct_absolute, $1)=yes
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
# hardcode_minus_L: Not really in the search PATH,
# but as the default location of the library.
_LT_TAGVAR(hardcode_minus_L, $1)=yes
fi
;;
hpux11*)
if test "$GCC" = yes && test "$with_gnu_ld" = no; then
case $host_cpu in
hppa*64*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
ia64*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags'
;;
*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags'
;;
esac
else
case $host_cpu in
hppa*64*)
_LT_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
ia64*)
_LT_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags'
;;
*)
m4_if($1, [], [
# Older versions of the 11.00 compiler do not understand -b yet
# (HP92453-01 A.11.01.20 doesn't, HP92453-01 B.11.X.35175-35176.GP does)
_LT_LINKER_OPTION([if $CC understands -b],
_LT_TAGVAR(lt_cv_prog_compiler__b, $1), [-b],
[_LT_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags'],
[_LT_TAGVAR(archive_cmds, $1)='$LD -b +h $soname +b $install_libdir -o $lib $libobjs $deplibs $linker_flags'])],
[_LT_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags'])
;;
esac
fi
if test "$with_gnu_ld" = no; then
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}+b ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
case $host_cpu in
hppa*64*|ia64*)
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
*)
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_direct_absolute, $1)=yes
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
# hardcode_minus_L: Not really in the search PATH,
# but as the default location of the library.
_LT_TAGVAR(hardcode_minus_L, $1)=yes
;;
esac
fi
;;
irix5* | irix6* | nonstopux*)
if test "$GCC" = yes; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
# Try to use the -exported_symbol ld option, if it does not
# work, assume that -exports_file does not work either and
# implicitly export all symbols.
# This should be the same for all languages, so no per-tag cache variable.
AC_CACHE_CHECK([whether the $host_os linker accepts -exported_symbol],
[lt_cv_irix_exported_symbol],
[save_LDFLAGS="$LDFLAGS"
LDFLAGS="$LDFLAGS -shared ${wl}-exported_symbol ${wl}foo ${wl}-update_registry ${wl}/dev/null"
AC_LINK_IFELSE(
[AC_LANG_SOURCE(
[AC_LANG_CASE([C], [[int foo (void) { return 0; }]],
[C++], [[int foo (void) { return 0; }]],
[Fortran 77], [[
subroutine foo
end]],
[Fortran], [[
subroutine foo
end]])])],
[lt_cv_irix_exported_symbol=yes],
[lt_cv_irix_exported_symbol=no])
LDFLAGS="$save_LDFLAGS"])
if test "$lt_cv_irix_exported_symbol" = yes; then
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations ${wl}-exports_file ${wl}$export_symbols -o $lib'
fi
else
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -exports_file $export_symbols -o $lib'
fi
_LT_TAGVAR(archive_cmds_need_lc, $1)='no'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
_LT_TAGVAR(inherit_rpath, $1)=yes
_LT_TAGVAR(link_all_deplibs, $1)=yes
;;
netbsd*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
_LT_TAGVAR(archive_cmds, $1)='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' # a.out
else
_LT_TAGVAR(archive_cmds, $1)='$LD -shared -o $lib $libobjs $deplibs $linker_flags' # ELF
fi
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-R$libdir'
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
newsos6)
_LT_TAGVAR(archive_cmds, $1)='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
*nto* | *qnx*)
;;
openbsd*)
if test -f /usr/libexec/ld.so; then
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
_LT_TAGVAR(hardcode_direct_absolute, $1)=yes
if test -z "`echo __ELF__ | $CC -E - | $GREP __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-retain-symbols-file,$export_symbols'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
else
case $host_os in
openbsd[[01]].* | openbsd2.[[0-7]] | openbsd2.[[0-7]].*)
_LT_TAGVAR(archive_cmds, $1)='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-R$libdir'
;;
*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir'
;;
esac
fi
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
os2*)
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(hardcode_minus_L, $1)=yes
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
_LT_TAGVAR(archive_cmds, $1)='$ECHO "LIBRARY $libname INITINSTANCE" > $output_objdir/$libname.def~$ECHO "DESCRIPTION \"$libname\"" >> $output_objdir/$libname.def~echo DATA >> $output_objdir/$libname.def~echo " SINGLE NONSHARED" >> $output_objdir/$libname.def~echo EXPORTS >> $output_objdir/$libname.def~emxexp $libobjs >> $output_objdir/$libname.def~$CC -Zdll -Zcrtdll -o $lib $libobjs $deplibs $compiler_flags $output_objdir/$libname.def'
_LT_TAGVAR(old_archive_from_new_cmds, $1)='emximp -o $output_objdir/$libname.a $output_objdir/$libname.def'
;;
osf3*)
if test "$GCC" = yes; then
_LT_TAGVAR(allow_undefined_flag, $1)=' ${wl}-expect_unresolved ${wl}\*'
_LT_TAGVAR(archive_cmds, $1)='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
else
_LT_TAGVAR(allow_undefined_flag, $1)=' -expect_unresolved \*'
_LT_TAGVAR(archive_cmds, $1)='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
fi
_LT_TAGVAR(archive_cmds_need_lc, $1)='no'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
;;
osf4* | osf5*) # as osf3* with the addition of -msym flag
if test "$GCC" = yes; then
_LT_TAGVAR(allow_undefined_flag, $1)=' ${wl}-expect_unresolved ${wl}\*'
_LT_TAGVAR(archive_cmds, $1)='$CC -shared${allow_undefined_flag} $pic_flag $libobjs $deplibs $compiler_flags ${wl}-msym ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
else
_LT_TAGVAR(allow_undefined_flag, $1)=' -expect_unresolved \*'
_LT_TAGVAR(archive_cmds, $1)='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags -msym -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='for i in `cat $export_symbols`; do printf "%s %s\\n" -exported_symbol "\$i" >> $lib.exp; done; printf "%s\\n" "-hidden">> $lib.exp~
$CC -shared${allow_undefined_flag} ${wl}-input ${wl}$lib.exp $compiler_flags $libobjs $deplibs -soname $soname `test -n "$verstring" && $ECHO "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib~$RM $lib.exp'
# Both c and cxx compiler support -rpath directly
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-rpath $libdir'
fi
_LT_TAGVAR(archive_cmds_need_lc, $1)='no'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
;;
solaris*)
_LT_TAGVAR(no_undefined_flag, $1)=' -z defs'
if test "$GCC" = yes; then
wlarc='${wl}'
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag ${wl}-z ${wl}text ${wl}-h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -shared $pic_flag ${wl}-z ${wl}text ${wl}-M ${wl}$lib.exp ${wl}-h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags~$RM $lib.exp'
else
case `$CC -V 2>&1` in
*"Compilers 5.0"*)
wlarc=''
_LT_TAGVAR(archive_cmds, $1)='$LD -G${allow_undefined_flag} -h $soname -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$LD -G${allow_undefined_flag} -M $lib.exp -h $soname -o $lib $libobjs $deplibs $linker_flags~$RM $lib.exp'
;;
*)
wlarc='${wl}'
_LT_TAGVAR(archive_cmds, $1)='$CC -G${allow_undefined_flag} -h $soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -G${allow_undefined_flag} -M $lib.exp -h $soname -o $lib $libobjs $deplibs $compiler_flags~$RM $lib.exp'
;;
esac
fi
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-R$libdir'
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
case $host_os in
solaris2.[[0-5]] | solaris2.[[0-5]].*) ;;
*)
# The compiler driver will combine and reorder linker options,
# but understands `-z linker_flag'. GCC discards it without `$wl',
# but is careful enough not to reorder.
# Supported since Solaris 2.6 (maybe 2.5.1?)
if test "$GCC" = yes; then
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}-z ${wl}allextract$convenience ${wl}-z ${wl}defaultextract'
else
_LT_TAGVAR(whole_archive_flag_spec, $1)='-z allextract$convenience -z defaultextract'
fi
;;
esac
_LT_TAGVAR(link_all_deplibs, $1)=yes
;;
sunos4*)
if test "x$host_vendor" = xsequent; then
# Use $CC to link under sequent, because it throws in some extra .o
# files that make .init and .fini sections work.
_LT_TAGVAR(archive_cmds, $1)='$CC -G ${wl}-h $soname -o $lib $libobjs $deplibs $compiler_flags'
else
_LT_TAGVAR(archive_cmds, $1)='$LD -assert pure-text -Bstatic -o $lib $libobjs $deplibs $linker_flags'
fi
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_minus_L, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
sysv4)
case $host_vendor in
sni)
_LT_TAGVAR(archive_cmds, $1)='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_direct, $1)=yes # is this really true???
;;
siemens)
## LD is ld it makes a PLAMLIB
## CC just makes a GrossModule.
_LT_TAGVAR(archive_cmds, $1)='$LD -G -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(reload_cmds, $1)='$CC -r -o $output$reload_objs'
_LT_TAGVAR(hardcode_direct, $1)=no
;;
motorola)
_LT_TAGVAR(archive_cmds, $1)='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_direct, $1)=no #Motorola manual says yes, but my tests say they lie
;;
esac
runpath_var='LD_RUN_PATH'
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
sysv4.3*)
_LT_TAGVAR(archive_cmds, $1)='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
_LT_TAGVAR(export_dynamic_flag_spec, $1)='-Bexport'
;;
sysv4*MP*)
if test -d /usr/nec; then
_LT_TAGVAR(archive_cmds, $1)='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
runpath_var=LD_RUN_PATH
hardcode_runpath_var=yes
_LT_TAGVAR(ld_shlibs, $1)=yes
fi
;;
sysv4*uw2* | sysv5OpenUNIX* | sysv5UnixWare7.[[01]].[[10]]* | unixware7* | sco3.2v5.0.[[024]]*)
_LT_TAGVAR(no_undefined_flag, $1)='${wl}-z,text'
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
runpath_var='LD_RUN_PATH'
if test "$GCC" = yes; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
else
_LT_TAGVAR(archive_cmds, $1)='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
fi
;;
sysv5* | sco3.2v5* | sco5v6*)
# Note: We can NOT use -z defs as we might desire, because we do not
# link with -lc, and that would cause any symbols used from libc to
# always be unresolved, which means just about no library would
# ever link correctly. If we're not using GNU ld we use -z text
# though, which does catch some bad symbols but isn't as heavy-handed
# as -z defs.
_LT_TAGVAR(no_undefined_flag, $1)='${wl}-z,text'
_LT_TAGVAR(allow_undefined_flag, $1)='${wl}-z,nodefs'
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-R,$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=':'
_LT_TAGVAR(link_all_deplibs, $1)=yes
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-Bexport'
runpath_var='LD_RUN_PATH'
if test "$GCC" = yes; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
else
_LT_TAGVAR(archive_cmds, $1)='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
fi
;;
uts4*)
_LT_TAGVAR(archive_cmds, $1)='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
*)
_LT_TAGVAR(ld_shlibs, $1)=no
;;
esac
if test x$host_vendor = xsni; then
case $host in
sysv4 | sysv4.2uw2* | sysv4.3* | sysv5*)
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-Blargedynsym'
;;
esac
fi
fi
])
AC_MSG_RESULT([$_LT_TAGVAR(ld_shlibs, $1)])
test "$_LT_TAGVAR(ld_shlibs, $1)" = no && can_build_shared=no
_LT_TAGVAR(with_gnu_ld, $1)=$with_gnu_ld
_LT_DECL([], [libext], [0], [Old archive suffix (normally "a")])dnl
_LT_DECL([], [shrext_cmds], [1], [Shared library suffix (normally ".so")])dnl
_LT_DECL([], [extract_expsyms_cmds], [2],
[The commands to extract the exported symbol list from a shared archive])
#
# Do we need to explicitly link libc?
#
case "x$_LT_TAGVAR(archive_cmds_need_lc, $1)" in
x|xyes)
# Assume -lc should be added
_LT_TAGVAR(archive_cmds_need_lc, $1)=yes
if test "$enable_shared" = yes && test "$GCC" = yes; then
case $_LT_TAGVAR(archive_cmds, $1) in
*'~'*)
# FIXME: we may have to deal with multi-command sequences.
;;
'$CC '*)
# Test whether the compiler implicitly links with -lc since on some
# systems, -lgcc has to come before -lc. If gcc already passes -lc
# to ld, don't add -lc before -lgcc.
AC_CACHE_CHECK([whether -lc should be explicitly linked in],
[lt_cv_]_LT_TAGVAR(archive_cmds_need_lc, $1),
[$RM conftest*
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
if AC_TRY_EVAL(ac_compile) 2>conftest.err; then
soname=conftest
lib=conftest
libobjs=conftest.$ac_objext
deplibs=
wl=$_LT_TAGVAR(lt_prog_compiler_wl, $1)
pic_flag=$_LT_TAGVAR(lt_prog_compiler_pic, $1)
compiler_flags=-v
linker_flags=-v
verstring=
output_objdir=.
libname=conftest
lt_save_allow_undefined_flag=$_LT_TAGVAR(allow_undefined_flag, $1)
_LT_TAGVAR(allow_undefined_flag, $1)=
if AC_TRY_EVAL(_LT_TAGVAR(archive_cmds, $1) 2\>\&1 \| $GREP \" -lc \" \>/dev/null 2\>\&1)
then
lt_cv_[]_LT_TAGVAR(archive_cmds_need_lc, $1)=no
else
lt_cv_[]_LT_TAGVAR(archive_cmds_need_lc, $1)=yes
fi
_LT_TAGVAR(allow_undefined_flag, $1)=$lt_save_allow_undefined_flag
else
cat conftest.err 1>&5
fi
$RM conftest*
])
_LT_TAGVAR(archive_cmds_need_lc, $1)=$lt_cv_[]_LT_TAGVAR(archive_cmds_need_lc, $1)
;;
esac
fi
;;
esac
_LT_TAGDECL([build_libtool_need_lc], [archive_cmds_need_lc], [0],
[Whether or not to add -lc for building shared libraries])
_LT_TAGDECL([allow_libtool_libs_with_static_runtimes],
[enable_shared_with_static_runtimes], [0],
[Whether or not to disallow shared libs when runtime libs are static])
_LT_TAGDECL([], [export_dynamic_flag_spec], [1],
[Compiler flag to allow reflexive dlopens])
_LT_TAGDECL([], [whole_archive_flag_spec], [1],
[Compiler flag to generate shared objects directly from archives])
_LT_TAGDECL([], [compiler_needs_object], [1],
[Whether the compiler copes with passing no objects directly])
_LT_TAGDECL([], [old_archive_from_new_cmds], [2],
[Create an old-style archive from a shared archive])
_LT_TAGDECL([], [old_archive_from_expsyms_cmds], [2],
[Create a temporary old-style archive to link instead of a shared archive])
_LT_TAGDECL([], [archive_cmds], [2], [Commands used to build a shared archive])
_LT_TAGDECL([], [archive_expsym_cmds], [2])
_LT_TAGDECL([], [module_cmds], [2],
[Commands used to build a loadable module if different from building
a shared archive.])
_LT_TAGDECL([], [module_expsym_cmds], [2])
_LT_TAGDECL([], [with_gnu_ld], [1],
[Whether we are building with GNU ld or not])
_LT_TAGDECL([], [allow_undefined_flag], [1],
[Flag that allows shared libraries with undefined symbols to be built])
_LT_TAGDECL([], [no_undefined_flag], [1],
[Flag that enforces no undefined symbols])
_LT_TAGDECL([], [hardcode_libdir_flag_spec], [1],
[Flag to hardcode $libdir into a binary during linking.
This must work even if $libdir does not exist])
_LT_TAGDECL([], [hardcode_libdir_separator], [1],
[Whether we need a single "-rpath" flag with a separated argument])
_LT_TAGDECL([], [hardcode_direct], [0],
[Set to "yes" if using DIR/libNAME${shared_ext} during linking hardcodes
DIR into the resulting binary])
_LT_TAGDECL([], [hardcode_direct_absolute], [0],
[Set to "yes" if using DIR/libNAME${shared_ext} during linking hardcodes
DIR into the resulting binary and the resulting library dependency is
"absolute", i.e impossible to change by setting ${shlibpath_var} if the
library is relocated])
_LT_TAGDECL([], [hardcode_minus_L], [0],
[Set to "yes" if using the -LDIR flag during linking hardcodes DIR
into the resulting binary])
_LT_TAGDECL([], [hardcode_shlibpath_var], [0],
[Set to "yes" if using SHLIBPATH_VAR=DIR during linking hardcodes DIR
into the resulting binary])
_LT_TAGDECL([], [hardcode_automatic], [0],
[Set to "yes" if building a shared library automatically hardcodes DIR
into the library and all subsequent libraries and executables linked
against it])
_LT_TAGDECL([], [inherit_rpath], [0],
[Set to yes if linker adds runtime paths of dependent libraries
to runtime path list])
_LT_TAGDECL([], [link_all_deplibs], [0],
[Whether libtool must link a program against all its dependency libraries])
_LT_TAGDECL([], [always_export_symbols], [0],
[Set to "yes" if exported symbols are required])
_LT_TAGDECL([], [export_symbols_cmds], [2],
[The commands to list exported symbols])
_LT_TAGDECL([], [exclude_expsyms], [1],
[Symbols that should not be listed in the preloaded symbols])
_LT_TAGDECL([], [include_expsyms], [1],
[Symbols that must always be exported])
_LT_TAGDECL([], [prelink_cmds], [2],
[Commands necessary for linking programs (against libraries) with templates])
_LT_TAGDECL([], [postlink_cmds], [2],
[Commands necessary for finishing linking programs])
_LT_TAGDECL([], [file_list_spec], [1],
[Specify filename containing input files])
dnl FIXME: Not yet implemented
dnl _LT_TAGDECL([], [thread_safe_flag_spec], [1],
dnl [Compiler flag to generate thread safe objects])
])# _LT_LINKER_SHLIBS
# _LT_LANG_C_CONFIG([TAG])
# ------------------------
# Ensure that the configuration variables for a C compiler are suitably
# defined. These variables are subsequently used by _LT_CONFIG to write
# the compiler configuration to `libtool'.
m4_defun([_LT_LANG_C_CONFIG],
[m4_require([_LT_DECL_EGREP])dnl
lt_save_CC="$CC"
AC_LANG_PUSH(C)
# Source file extension for C test sources.
ac_ext=c
# Object file extension for compiled C test sources.
objext=o
_LT_TAGVAR(objext, $1)=$objext
# Code to be used in simple compile tests
lt_simple_compile_test_code="int some_variable = 0;"
# Code to be used in simple link tests
lt_simple_link_test_code='int main(){return(0);}'
_LT_TAG_COMPILER
# Save the default compiler, since it gets overwritten when the other
# tags are being tested, and _LT_TAGVAR(compiler, []) is a NOP.
compiler_DEFAULT=$CC
# save warnings/boilerplate of simple test code
_LT_COMPILER_BOILERPLATE
_LT_LINKER_BOILERPLATE
## CAVEAT EMPTOR:
## There is no encapsulation within the following macros, do not change
## the running order or otherwise move them around unless you know exactly
## what you are doing...
if test -n "$compiler"; then
_LT_COMPILER_NO_RTTI($1)
_LT_COMPILER_PIC($1)
_LT_COMPILER_C_O($1)
_LT_COMPILER_FILE_LOCKS($1)
_LT_LINKER_SHLIBS($1)
_LT_SYS_DYNAMIC_LINKER($1)
_LT_LINKER_HARDCODE_LIBPATH($1)
LT_SYS_DLOPEN_SELF
_LT_CMD_STRIPLIB
# Report which library types will actually be built
AC_MSG_CHECKING([if libtool supports shared libraries])
AC_MSG_RESULT([$can_build_shared])
AC_MSG_CHECKING([whether to build shared libraries])
test "$can_build_shared" = "no" && enable_shared=no
# On AIX, shared libraries and static libraries use the same namespace, and
# are all built from PIC.
case $host_os in
aix3*)
test "$enable_shared" = yes && enable_static=no
if test -n "$RANLIB"; then
archive_cmds="$archive_cmds~\$RANLIB \$lib"
postinstall_cmds='$RANLIB $lib'
fi
;;
aix[[4-9]]*)
if test "$host_cpu" != ia64 && test "$aix_use_runtimelinking" = no ; then
test "$enable_shared" = yes && enable_static=no
fi
;;
esac
AC_MSG_RESULT([$enable_shared])
AC_MSG_CHECKING([whether to build static libraries])
# Make sure either enable_shared or enable_static is yes.
test "$enable_shared" = yes || enable_static=yes
AC_MSG_RESULT([$enable_static])
_LT_CONFIG($1)
fi
AC_LANG_POP
CC="$lt_save_CC"
])# _LT_LANG_C_CONFIG
# _LT_LANG_CXX_CONFIG([TAG])
# --------------------------
# Ensure that the configuration variables for a C++ compiler are suitably
# defined. These variables are subsequently used by _LT_CONFIG to write
# the compiler configuration to `libtool'.
m4_defun([_LT_LANG_CXX_CONFIG],
[m4_require([_LT_FILEUTILS_DEFAULTS])dnl
m4_require([_LT_DECL_EGREP])dnl
m4_require([_LT_PATH_MANIFEST_TOOL])dnl
if test -n "$CXX" && ( test "X$CXX" != "Xno" &&
( (test "X$CXX" = "Xg++" && `g++ -v >/dev/null 2>&1` ) ||
(test "X$CXX" != "Xg++"))) ; then
AC_PROG_CXXCPP
else
_lt_caught_CXX_error=yes
fi
AC_LANG_PUSH(C++)
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(allow_undefined_flag, $1)=
_LT_TAGVAR(always_export_symbols, $1)=no
_LT_TAGVAR(archive_expsym_cmds, $1)=
_LT_TAGVAR(compiler_needs_object, $1)=no
_LT_TAGVAR(export_dynamic_flag_spec, $1)=
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_direct_absolute, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)=
_LT_TAGVAR(hardcode_libdir_separator, $1)=
_LT_TAGVAR(hardcode_minus_L, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=unsupported
_LT_TAGVAR(hardcode_automatic, $1)=no
_LT_TAGVAR(inherit_rpath, $1)=no
_LT_TAGVAR(module_cmds, $1)=
_LT_TAGVAR(module_expsym_cmds, $1)=
_LT_TAGVAR(link_all_deplibs, $1)=unknown
_LT_TAGVAR(old_archive_cmds, $1)=$old_archive_cmds
_LT_TAGVAR(reload_flag, $1)=$reload_flag
_LT_TAGVAR(reload_cmds, $1)=$reload_cmds
_LT_TAGVAR(no_undefined_flag, $1)=
_LT_TAGVAR(whole_archive_flag_spec, $1)=
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=no
# Source file extension for C++ test sources.
ac_ext=cpp
# Object file extension for compiled C++ test sources.
objext=o
_LT_TAGVAR(objext, $1)=$objext
# No sense in running all these tests if we already determined that
# the CXX compiler isn't working. Some variables (like enable_shared)
# are currently assumed to apply to all compilers on this platform,
# and will be corrupted by setting them based on a non-working compiler.
if test "$_lt_caught_CXX_error" != yes; then
# Code to be used in simple compile tests
lt_simple_compile_test_code="int some_variable = 0;"
# Code to be used in simple link tests
lt_simple_link_test_code='int main(int, char *[[]]) { return(0); }'
# ltmain only uses $CC for tagged configurations so make sure $CC is set.
_LT_TAG_COMPILER
# save warnings/boilerplate of simple test code
_LT_COMPILER_BOILERPLATE
_LT_LINKER_BOILERPLATE
# Allow CC to be a program name with arguments.
lt_save_CC=$CC
lt_save_CFLAGS=$CFLAGS
lt_save_LD=$LD
lt_save_GCC=$GCC
GCC=$GXX
lt_save_with_gnu_ld=$with_gnu_ld
lt_save_path_LD=$lt_cv_path_LD
if test -n "${lt_cv_prog_gnu_ldcxx+set}"; then
lt_cv_prog_gnu_ld=$lt_cv_prog_gnu_ldcxx
else
$as_unset lt_cv_prog_gnu_ld
fi
if test -n "${lt_cv_path_LDCXX+set}"; then
lt_cv_path_LD=$lt_cv_path_LDCXX
else
$as_unset lt_cv_path_LD
fi
test -z "${LDCXX+set}" || LD=$LDCXX
CC=${CXX-"c++"}
CFLAGS=$CXXFLAGS
compiler=$CC
_LT_TAGVAR(compiler, $1)=$CC
_LT_CC_BASENAME([$compiler])
if test -n "$compiler"; then
# We don't want -fno-exception when compiling C++ code, so set the
# no_builtin_flag separately
if test "$GXX" = yes; then
_LT_TAGVAR(lt_prog_compiler_no_builtin_flag, $1)=' -fno-builtin'
else
_LT_TAGVAR(lt_prog_compiler_no_builtin_flag, $1)=
fi
if test "$GXX" = yes; then
# Set up default GNU C++ configuration
LT_PATH_LD
# Check if GNU C++ uses GNU ld as the underlying linker, since the
# archiving commands below assume that GNU ld is being used.
if test "$with_gnu_ld" = yes; then
_LT_TAGVAR(archive_cmds, $1)='$CC $pic_flag -shared -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC $pic_flag -shared -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-dynamic'
# If archive_cmds runs LD, not CC, wlarc should be empty
# XXX I think wlarc can be eliminated in ltcf-cxx, but I need to
# investigate it a little bit more. (MM)
wlarc='${wl}'
# ancient GNU ld didn't support --whole-archive et. al.
if eval "`$CC -print-prog-name=ld` --help 2>&1" |
$GREP 'no-whole-archive' > /dev/null; then
_LT_TAGVAR(whole_archive_flag_spec, $1)="$wlarc"'--whole-archive$convenience '"$wlarc"'--no-whole-archive'
else
_LT_TAGVAR(whole_archive_flag_spec, $1)=
fi
else
with_gnu_ld=no
wlarc=
# A generic and very simple default shared library creation
# command for GNU C++ for the case where it uses the native
# linker, instead of GNU ld. If possible, this setting should
# overridden to take advantage of the native linker features on
# the platform it is being used on.
_LT_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $lib'
fi
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
output_verbose_link_cmd='$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP -v "^Configured with:" | $GREP "\-L"'
else
GXX=no
with_gnu_ld=no
wlarc=
fi
# PORTME: fill in a description of your system's C++ link characteristics
AC_MSG_CHECKING([whether the $compiler linker ($LD) supports shared libraries])
_LT_TAGVAR(ld_shlibs, $1)=yes
case $host_os in
aix3*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
aix[[4-9]]*)
if test "$host_cpu" = ia64; then
# On IA64, the linker does run time linking by default, so we don't
# have to do anything special.
aix_use_runtimelinking=no
exp_sym_flag='-Bexport'
no_entry_flag=""
else
aix_use_runtimelinking=no
# Test if we are trying to use run time linking or normal
# AIX style linking. If -brtl is somewhere in LDFLAGS, we
# need to do runtime linking.
case $host_os in aix4.[[23]]|aix4.[[23]].*|aix[[5-9]]*)
for ld_flag in $LDFLAGS; do
case $ld_flag in
*-brtl*)
aix_use_runtimelinking=yes
break
;;
esac
done
;;
esac
exp_sym_flag='-bexport'
no_entry_flag='-bnoentry'
fi
# When large executables or shared objects are built, AIX ld can
# have problems creating the table of contents. If linking a library
# or program results in "error TOC overflow" add -mminimal-toc to
# CXXFLAGS/CFLAGS for g++/gcc. In the cases where that is not
# enough to fix the problem, add -Wl,-bbigtoc to LDFLAGS.
_LT_TAGVAR(archive_cmds, $1)=''
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_direct_absolute, $1)=yes
_LT_TAGVAR(hardcode_libdir_separator, $1)=':'
_LT_TAGVAR(link_all_deplibs, $1)=yes
_LT_TAGVAR(file_list_spec, $1)='${wl}-f,'
if test "$GXX" = yes; then
case $host_os in aix4.[[012]]|aix4.[[012]].*)
# We only want to do this on AIX 4.2 and lower, the check
# below for broken collect2 doesn't work under 4.3+
collect2name=`${CC} -print-prog-name=collect2`
if test -f "$collect2name" &&
strings "$collect2name" | $GREP resolve_lib_name >/dev/null
then
# We have reworked collect2
:
else
# We have old collect2
_LT_TAGVAR(hardcode_direct, $1)=unsupported
# It fails to find uninstalled libraries when the uninstalled
# path is not listed in the libpath. Setting hardcode_minus_L
# to unsupported forces relinking
_LT_TAGVAR(hardcode_minus_L, $1)=yes
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=
fi
esac
shared_flag='-shared'
if test "$aix_use_runtimelinking" = yes; then
shared_flag="$shared_flag "'${wl}-G'
fi
else
# not using gcc
if test "$host_cpu" = ia64; then
# VisualAge C++, Version 5.5 for AIX 5L for IA-64, Beta 3 Release
# chokes on -Wl,-G. The following line is correct:
shared_flag='-G'
else
if test "$aix_use_runtimelinking" = yes; then
shared_flag='${wl}-G'
else
shared_flag='${wl}-bM:SRE'
fi
fi
fi
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-bexpall'
# It seems that -bexpall does not export symbols beginning with
# underscore (_), so it is better to generate a list of symbols to
# export.
_LT_TAGVAR(always_export_symbols, $1)=yes
if test "$aix_use_runtimelinking" = yes; then
# Warning - without using the other runtime loading flags (-brtl),
# -berok will link without error, but may produce a broken library.
_LT_TAGVAR(allow_undefined_flag, $1)='-berok'
# Determine the default libpath from the value encoded in an empty
# executable.
_LT_SYS_MODULE_PATH_AIX([$1])
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-blibpath:$libdir:'"$aix_libpath"
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags `if test "x${allow_undefined_flag}" != "x"; then func_echo_all "${wl}${allow_undefined_flag}"; else :; fi` '"\${wl}$exp_sym_flag:\$export_symbols $shared_flag"
else
if test "$host_cpu" = ia64; then
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-R $libdir:/usr/lib:/lib'
_LT_TAGVAR(allow_undefined_flag, $1)="-z nodefs"
_LT_TAGVAR(archive_expsym_cmds, $1)="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags ${wl}${allow_undefined_flag} '"\${wl}$exp_sym_flag:\$export_symbols"
else
# Determine the default libpath from the value encoded in an
# empty executable.
_LT_SYS_MODULE_PATH_AIX([$1])
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-blibpath:$libdir:'"$aix_libpath"
# Warning - without using the other run time loading flags,
# -berok will link without error, but may produce a broken library.
_LT_TAGVAR(no_undefined_flag, $1)=' ${wl}-bernotok'
_LT_TAGVAR(allow_undefined_flag, $1)=' ${wl}-berok'
if test "$with_gnu_ld" = yes; then
# We only use this code for GNU lds that support --whole-archive.
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive$convenience ${wl}--no-whole-archive'
else
# Exported symbols can be pulled into shared objects from archives
_LT_TAGVAR(whole_archive_flag_spec, $1)='$convenience'
fi
_LT_TAGVAR(archive_cmds_need_lc, $1)=yes
# This is similar to how AIX traditionally builds its shared
# libraries.
_LT_TAGVAR(archive_expsym_cmds, $1)="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs ${wl}-bnoentry $compiler_flags ${wl}-bE:$export_symbols${allow_undefined_flag}~$AR $AR_FLAGS $output_objdir/$libname$release.a $output_objdir/$soname'
fi
fi
;;
beos*)
if $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
# Joseph Beckenbach says some releases of gcc
# support --undefined. This deserves some investigation. FIXME
_LT_TAGVAR(archive_cmds, $1)='$CC -nostart $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
chorus*)
case $cc_basename in
*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
esac
;;
cygwin* | mingw* | pw32* | cegcc*)
case $GXX,$cc_basename in
,cl* | no,cl*)
# Native MSVC
# hardcode_libdir_flag_spec is actually meaningless, as there is
# no search path for DLLs.
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)=' '
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
_LT_TAGVAR(always_export_symbols, $1)=yes
_LT_TAGVAR(file_list_spec, $1)='@'
# Tell ltmain to make .lib files, not .a files.
libext=lib
# Tell ltmain to make .dll files, not .so files.
shrext_cmds=".dll"
# FIXME: Setting linknames here is a bad hack.
_LT_TAGVAR(archive_cmds, $1)='$CC -o $output_objdir/$soname $libobjs $compiler_flags $deplibs -Wl,-dll~linknames='
_LT_TAGVAR(archive_expsym_cmds, $1)='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then
$SED -n -e 's/\\\\\\\(.*\\\\\\\)/-link\\\ -EXPORT:\\\\\\\1/' -e '1\\\!p' < $export_symbols > $output_objdir/$soname.exp;
else
$SED -e 's/\\\\\\\(.*\\\\\\\)/-link\\\ -EXPORT:\\\\\\\1/' < $export_symbols > $output_objdir/$soname.exp;
fi~
$CC -o $tool_output_objdir$soname $libobjs $compiler_flags $deplibs "@$tool_output_objdir$soname.exp" -Wl,-DLL,-IMPLIB:"$tool_output_objdir$libname.dll.lib"~
linknames='
# The linker will not automatically build a static lib if we build a DLL.
# _LT_TAGVAR(old_archive_from_new_cmds, $1)='true'
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=yes
# Don't use ranlib
_LT_TAGVAR(old_postinstall_cmds, $1)='chmod 644 $oldlib'
_LT_TAGVAR(postlink_cmds, $1)='lt_outputfile="@OUTPUT@"~
lt_tool_outputfile="@TOOL_OUTPUT@"~
case $lt_outputfile in
*.exe|*.EXE) ;;
*)
lt_outputfile="$lt_outputfile.exe"
lt_tool_outputfile="$lt_tool_outputfile.exe"
;;
esac~
func_to_tool_file "$lt_outputfile"~
if test "$MANIFEST_TOOL" != ":" && test -f "$lt_outputfile.manifest"; then
$MANIFEST_TOOL -manifest "$lt_tool_outputfile.manifest" -outputresource:"$lt_tool_outputfile" || exit 1;
$RM "$lt_outputfile.manifest";
fi'
;;
*)
# g++
# _LT_TAGVAR(hardcode_libdir_flag_spec, $1) is actually meaningless,
# as there is no search path for DLLs.
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-L$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-all-symbols'
_LT_TAGVAR(allow_undefined_flag, $1)=unsupported
_LT_TAGVAR(always_export_symbols, $1)=no
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=yes
if $LD --help 2>&1 | $GREP 'auto-import' > /dev/null; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib'
# If the export-symbols file already is a .def file (1st line
# is EXPORTS), use it as is; otherwise, prepend...
_LT_TAGVAR(archive_expsym_cmds, $1)='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then
cp $export_symbols $output_objdir/$soname.def;
else
echo EXPORTS > $output_objdir/$soname.def;
cat $export_symbols >> $output_objdir/$soname.def;
fi~
$CC -shared -nostdlib $output_objdir/$soname.def $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib'
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
esac
;;
darwin* | rhapsody*)
_LT_DARWIN_LINKER_FEATURES($1)
;;
dgux*)
case $cc_basename in
ec++*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
ghcx*)
# Green Hills C++ Compiler
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
esac
;;
freebsd2.*)
# C++ shared libraries reported to be fairly broken before
# switch to ELF
_LT_TAGVAR(ld_shlibs, $1)=no
;;
freebsd-elf*)
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
;;
freebsd* | dragonfly*)
# FreeBSD 3 and later use GNU C++ and GNU ld with standard ELF
# conventions
_LT_TAGVAR(ld_shlibs, $1)=yes
;;
gnu*)
;;
haiku*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(link_all_deplibs, $1)=yes
;;
hpux9*)
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}+b ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_minus_L, $1)=yes # Not in the search PATH,
# but as the default
# location of the library.
case $cc_basename in
CC*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
aCC*)
_LT_TAGVAR(archive_cmds, $1)='$RM $output_objdir/$soname~$CC -b ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib'
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`($CC -b $CFLAGS -v conftest.$objext 2>&1) | $EGREP "\-L"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "$list"'
;;
*)
if test "$GXX" = yes; then
_LT_TAGVAR(archive_cmds, $1)='$RM $output_objdir/$soname~$CC -shared -nostdlib $pic_flag ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib'
else
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
esac
;;
hpux10*|hpux11*)
if test $with_gnu_ld = no; then
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}+b ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
case $host_cpu in
hppa*64*|ia64*)
;;
*)
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
;;
esac
fi
case $host_cpu in
hppa*64*|ia64*)
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
;;
*)
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_direct_absolute, $1)=yes
_LT_TAGVAR(hardcode_minus_L, $1)=yes # Not in the search PATH,
# but as the default
# location of the library.
;;
esac
case $cc_basename in
CC*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
aCC*)
case $host_cpu in
hppa*64*)
_LT_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
ia64*)
_LT_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
*)
_LT_TAGVAR(archive_cmds, $1)='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
esac
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`($CC -b $CFLAGS -v conftest.$objext 2>&1) | $GREP "\-L"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "$list"'
;;
*)
if test "$GXX" = yes; then
if test $with_gnu_ld = no; then
case $host_cpu in
hppa*64*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib -fPIC ${wl}+h ${wl}$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
ia64*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib $pic_flag ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib $pic_flag ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
esac
fi
else
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
esac
;;
interix[[3-9]]*)
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
# Hack: On Interix 3.x, we cannot compile PIC because of a broken gcc.
# Instead, shared libraries are loaded at an image base (0x10000000 by
# default) and relocated if they conflict, which is a slow very memory
# consuming and fragmenting process. To avoid this, we pick a random,
# 256 KiB-aligned image base between 0x50000000 and 0x6FFC0000 at link
# time. Moving up from 0x10000000 also allows more sbrk(2) space.
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='sed "s,^,_," $export_symbols >$output_objdir/$soname.expsym~$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--retain-symbols-file,$output_objdir/$soname.expsym ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib'
;;
irix5* | irix6*)
case $cc_basename in
CC*)
# SGI C++
_LT_TAGVAR(archive_cmds, $1)='$CC -shared -all -multigot $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
# Archives containing C++ object files must be created using
# "CC -ar", where "CC" is the IRIX C++ compiler. This is
# necessary to make sure instantiated templates are included
# in the archive.
_LT_TAGVAR(old_archive_cmds, $1)='$CC -ar -WR,-u -o $oldlib $oldobjs'
;;
*)
if test "$GXX" = yes; then
if test "$with_gnu_ld" = no; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
else
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` -o $lib'
fi
fi
_LT_TAGVAR(link_all_deplibs, $1)=yes
;;
esac
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
_LT_TAGVAR(inherit_rpath, $1)=yes
;;
linux* | k*bsd*-gnu | kopensolaris*-gnu)
case $cc_basename in
KCC*)
# Kuck and Associates, Inc. (KAI) C++ Compiler
# KCC will only create a shared library if the output file
# ends with ".so" (or ".sl" for HP-UX), so rename the library
# to its proper name (with version) after linking.
_LT_TAGVAR(archive_cmds, $1)='tempext=`echo $shared_ext | $SED -e '\''s/\([[^()0-9A-Za-z{}]]\)/\\\\\1/g'\''`; templib=`echo $lib | $SED -e "s/\${tempext}\..*/.so/"`; $CC $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags --soname $soname -o \$templib; mv \$templib $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='tempext=`echo $shared_ext | $SED -e '\''s/\([[^()0-9A-Za-z{}]]\)/\\\\\1/g'\''`; templib=`echo $lib | $SED -e "s/\${tempext}\..*/.so/"`; $CC $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags --soname $soname -o \$templib ${wl}-retain-symbols-file,$export_symbols; mv \$templib $lib'
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`$CC $CFLAGS -v conftest.$objext -o libconftest$shared_ext 2>&1 | $GREP "ld"`; rm -f libconftest$shared_ext; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "$list"'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-dynamic'
# Archives containing C++ object files must be created using
# "CC -Bstatic", where "CC" is the KAI C++ compiler.
_LT_TAGVAR(old_archive_cmds, $1)='$CC -Bstatic -o $oldlib $oldobjs'
;;
icpc* | ecpc* )
# Intel C++
with_gnu_ld=yes
# version 8.0 and above of icpc choke on multiply defined symbols
# if we add $predep_objects and $postdep_objects, however 7.1 and
# earlier do not add the objects themselves.
case `$CC -V 2>&1` in
*"Version 7."*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
;;
*) # Version 8.0 or newer
tmp_idyn=
case $host_cpu in
ia64*) tmp_idyn=' -i_dynamic';;
esac
_LT_TAGVAR(archive_cmds, $1)='$CC -shared'"$tmp_idyn"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared'"$tmp_idyn"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
;;
esac
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-dynamic'
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive$convenience ${wl}--no-whole-archive'
;;
pgCC* | pgcpp*)
# Portland Group C++ compiler
case `$CC -V` in
*pgCC\ [[1-5]].* | *pgcpp\ [[1-5]].*)
_LT_TAGVAR(prelink_cmds, $1)='tpldir=Template.dir~
rm -rf $tpldir~
$CC --prelink_objects --instantiation_dir $tpldir $objs $libobjs $compile_deplibs~
compile_command="$compile_command `find $tpldir -name \*.o | sort | $NL2SP`"'
_LT_TAGVAR(old_archive_cmds, $1)='tpldir=Template.dir~
rm -rf $tpldir~
$CC --prelink_objects --instantiation_dir $tpldir $oldobjs$old_deplibs~
$AR $AR_FLAGS $oldlib$oldobjs$old_deplibs `find $tpldir -name \*.o | sort | $NL2SP`~
$RANLIB $oldlib'
_LT_TAGVAR(archive_cmds, $1)='tpldir=Template.dir~
rm -rf $tpldir~
$CC --prelink_objects --instantiation_dir $tpldir $predep_objects $libobjs $deplibs $convenience $postdep_objects~
$CC -shared $pic_flag $predep_objects $libobjs $deplibs `find $tpldir -name \*.o | sort | $NL2SP` $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='tpldir=Template.dir~
rm -rf $tpldir~
$CC --prelink_objects --instantiation_dir $tpldir $predep_objects $libobjs $deplibs $convenience $postdep_objects~
$CC -shared $pic_flag $predep_objects $libobjs $deplibs `find $tpldir -name \*.o | sort | $NL2SP` $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname ${wl}-retain-symbols-file ${wl}$export_symbols -o $lib'
;;
*) # Version 6 and above use weak symbols
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $pic_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname ${wl}-retain-symbols-file ${wl}$export_symbols -o $lib'
;;
esac
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}--rpath ${wl}$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-dynamic'
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
;;
cxx*)
# Compaq C++
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib ${wl}-retain-symbols-file $wl$export_symbols'
runpath_var=LD_RUN_PATH
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-rpath $libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP "ld"`; templist=`func_echo_all "$templist" | $SED "s/\(^.*ld.*\)\( .*ld .*$\)/\1/"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "X$list" | $Xsed'
;;
xl* | mpixl* | bgxl*)
# IBM XL 8.0 on PPC, with GNU ld
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}--export-dynamic'
_LT_TAGVAR(archive_cmds, $1)='$CC -qmkshrobj $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
if test "x$supports_anon_versioning" = xyes; then
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $output_objdir/$libname.ver~
cat $export_symbols | sed -e "s/\(.*\)/\1;/" >> $output_objdir/$libname.ver~
echo "local: *; };" >> $output_objdir/$libname.ver~
$CC -qmkshrobj $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-version-script ${wl}$output_objdir/$libname.ver -o $lib'
fi
;;
*)
case `$CC -V 2>&1 | sed 5q` in
*Sun\ C*)
# Sun C++ 5.9
_LT_TAGVAR(no_undefined_flag, $1)=' -zdefs'
_LT_TAGVAR(archive_cmds, $1)='$CC -G${allow_undefined_flag} -h$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -G${allow_undefined_flag} -h$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-retain-symbols-file ${wl}$export_symbols'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-R$libdir'
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}--whole-archive`new_convenience=; for conv in $convenience\"\"; do test -z \"$conv\" || new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
_LT_TAGVAR(compiler_needs_object, $1)=yes
# Not sure whether something based on
# $CC $CFLAGS -v conftest.$objext -o libconftest$shared_ext 2>&1
# would be better.
output_verbose_link_cmd='func_echo_all'
# Archives containing C++ object files must be created using
# "CC -xar", where "CC" is the Sun C++ compiler. This is
# necessary to make sure instantiated templates are included
# in the archive.
_LT_TAGVAR(old_archive_cmds, $1)='$CC -xar -o $oldlib $oldobjs'
;;
esac
;;
esac
;;
lynxos*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
m88k*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
mvs*)
case $cc_basename in
cxx*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
esac
;;
netbsd*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
_LT_TAGVAR(archive_cmds, $1)='$LD -Bshareable -o $lib $predep_objects $libobjs $deplibs $postdep_objects $linker_flags'
wlarc=
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-R$libdir'
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
fi
# Workaround some broken pre-1.5 toolchains
output_verbose_link_cmd='$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP conftest.$objext | $SED -e "s:-lgcc -lc -lgcc::"'
;;
*nto* | *qnx*)
_LT_TAGVAR(ld_shlibs, $1)=yes
;;
openbsd2*)
# C++ shared libraries are fairly broken
_LT_TAGVAR(ld_shlibs, $1)=no
;;
openbsd*)
if test -f /usr/libexec/ld.so; then
_LT_TAGVAR(hardcode_direct, $1)=yes
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
_LT_TAGVAR(hardcode_direct_absolute, $1)=yes
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $lib'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir'
if test -z "`echo __ELF__ | $CC -E - | grep __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared $pic_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-retain-symbols-file,$export_symbols -o $lib'
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-E'
_LT_TAGVAR(whole_archive_flag_spec, $1)="$wlarc"'--whole-archive$convenience '"$wlarc"'--no-whole-archive'
fi
output_verbose_link_cmd=func_echo_all
else
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
osf3* | osf4* | osf5*)
case $cc_basename in
KCC*)
# Kuck and Associates, Inc. (KAI) C++ Compiler
# KCC will only create a shared library if the output file
# ends with ".so" (or ".sl" for HP-UX), so rename the library
# to its proper name (with version) after linking.
_LT_TAGVAR(archive_cmds, $1)='tempext=`echo $shared_ext | $SED -e '\''s/\([[^()0-9A-Za-z{}]]\)/\\\\\1/g'\''`; templib=`echo "$lib" | $SED -e "s/\${tempext}\..*/.so/"`; $CC $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags --soname $soname -o \$templib; mv \$templib $lib'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath,$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
# Archives containing C++ object files must be created using
# the KAI C++ compiler.
case $host in
osf3*) _LT_TAGVAR(old_archive_cmds, $1)='$CC -Bstatic -o $oldlib $oldobjs' ;;
*) _LT_TAGVAR(old_archive_cmds, $1)='$CC -o $oldlib $oldobjs' ;;
esac
;;
RCC*)
# Rational C++ 2.4.1
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
cxx*)
case $host in
osf3*)
_LT_TAGVAR(allow_undefined_flag, $1)=' ${wl}-expect_unresolved ${wl}\*'
_LT_TAGVAR(archive_cmds, $1)='$CC -shared${allow_undefined_flag} $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $soname `test -n "$verstring" && func_echo_all "${wl}-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
;;
*)
_LT_TAGVAR(allow_undefined_flag, $1)=' -expect_unresolved \*'
_LT_TAGVAR(archive_cmds, $1)='$CC -shared${allow_undefined_flag} $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -msym -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='for i in `cat $export_symbols`; do printf "%s %s\\n" -exported_symbol "\$i" >> $lib.exp; done~
echo "-hidden">> $lib.exp~
$CC -shared$allow_undefined_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -msym -soname $soname ${wl}-input ${wl}$lib.exp `test -n "$verstring" && $ECHO "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib~
$RM $lib.exp'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-rpath $libdir'
;;
esac
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP "ld" | $GREP -v "ld:"`; templist=`func_echo_all "$templist" | $SED "s/\(^.*ld.*\)\( .*ld.*$\)/\1/"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "$list"'
;;
*)
if test "$GXX" = yes && test "$with_gnu_ld" = no; then
_LT_TAGVAR(allow_undefined_flag, $1)=' ${wl}-expect_unresolved ${wl}\*'
case $host in
osf3*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared -nostdlib ${allow_undefined_flag} $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
;;
*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag -nostdlib ${allow_undefined_flag} $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-msym ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
;;
esac
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-rpath ${wl}$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=:
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
output_verbose_link_cmd='$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP -v "^Configured with:" | $GREP "\-L"'
else
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
fi
;;
esac
;;
psos*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
sunos4*)
case $cc_basename in
CC*)
# Sun C++ 4.x
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
lcc*)
# Lucid
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
esac
;;
solaris*)
case $cc_basename in
CC* | sunCC*)
# Sun C++ 4.2, 5.x and Centerline C++
_LT_TAGVAR(archive_cmds_need_lc,$1)=yes
_LT_TAGVAR(no_undefined_flag, $1)=' -zdefs'
_LT_TAGVAR(archive_cmds, $1)='$CC -G${allow_undefined_flag} -h$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -G${allow_undefined_flag} ${wl}-M ${wl}$lib.exp -h$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~$RM $lib.exp'
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='-R$libdir'
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
case $host_os in
solaris2.[[0-5]] | solaris2.[[0-5]].*) ;;
*)
# The compiler driver will combine and reorder linker options,
# but understands `-z linker_flag'.
# Supported since Solaris 2.6 (maybe 2.5.1?)
_LT_TAGVAR(whole_archive_flag_spec, $1)='-z allextract$convenience -z defaultextract'
;;
esac
_LT_TAGVAR(link_all_deplibs, $1)=yes
output_verbose_link_cmd='func_echo_all'
# Archives containing C++ object files must be created using
# "CC -xar", where "CC" is the Sun C++ compiler. This is
# necessary to make sure instantiated templates are included
# in the archive.
_LT_TAGVAR(old_archive_cmds, $1)='$CC -xar -o $oldlib $oldobjs'
;;
gcx*)
# Green Hills C++ Compiler
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-h $wl$soname -o $lib'
# The C++ compiler must be used to create the archive.
_LT_TAGVAR(old_archive_cmds, $1)='$CC $LDFLAGS -archive -o $oldlib $oldobjs'
;;
*)
# GNU C++ compiler with Solaris linker
if test "$GXX" = yes && test "$with_gnu_ld" = no; then
_LT_TAGVAR(no_undefined_flag, $1)=' ${wl}-z ${wl}defs'
if $CC --version | $GREP -v '^2\.7' > /dev/null; then
_LT_TAGVAR(archive_cmds, $1)='$CC -shared $pic_flag -nostdlib $LDFLAGS $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-h $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -shared $pic_flag -nostdlib ${wl}-M $wl$lib.exp -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~$RM $lib.exp'
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
output_verbose_link_cmd='$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP -v "^Configured with:" | $GREP "\-L"'
else
# g++ 2.7 appears to require `-G' NOT `-shared' on this
# platform.
_LT_TAGVAR(archive_cmds, $1)='$CC -G -nostdlib $LDFLAGS $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-h $wl$soname -o $lib'
_LT_TAGVAR(archive_expsym_cmds, $1)='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -G -nostdlib ${wl}-M $wl$lib.exp -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~$RM $lib.exp'
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
output_verbose_link_cmd='$CC -G $CFLAGS -v conftest.$objext 2>&1 | $GREP -v "^Configured with:" | $GREP "\-L"'
fi
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-R $wl$libdir'
case $host_os in
solaris2.[[0-5]] | solaris2.[[0-5]].*) ;;
*)
_LT_TAGVAR(whole_archive_flag_spec, $1)='${wl}-z ${wl}allextract$convenience ${wl}-z ${wl}defaultextract'
;;
esac
fi
;;
esac
;;
sysv4*uw2* | sysv5OpenUNIX* | sysv5UnixWare7.[[01]].[[10]]* | unixware7* | sco3.2v5.0.[[024]]*)
_LT_TAGVAR(no_undefined_flag, $1)='${wl}-z,text'
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
runpath_var='LD_RUN_PATH'
case $cc_basename in
CC*)
_LT_TAGVAR(archive_cmds, $1)='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
esac
;;
sysv5* | sco3.2v5* | sco5v6*)
# Note: We can NOT use -z defs as we might desire, because we do not
# link with -lc, and that would cause any symbols used from libc to
# always be unresolved, which means just about no library would
# ever link correctly. If we're not using GNU ld we use -z text
# though, which does catch some bad symbols but isn't as heavy-handed
# as -z defs.
_LT_TAGVAR(no_undefined_flag, $1)='${wl}-z,text'
_LT_TAGVAR(allow_undefined_flag, $1)='${wl}-z,nodefs'
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(hardcode_shlibpath_var, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)='${wl}-R,$libdir'
_LT_TAGVAR(hardcode_libdir_separator, $1)=':'
_LT_TAGVAR(link_all_deplibs, $1)=yes
_LT_TAGVAR(export_dynamic_flag_spec, $1)='${wl}-Bexport'
runpath_var='LD_RUN_PATH'
case $cc_basename in
CC*)
_LT_TAGVAR(archive_cmds, $1)='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(old_archive_cmds, $1)='$CC -Tprelink_objects $oldobjs~
'"$_LT_TAGVAR(old_archive_cmds, $1)"
_LT_TAGVAR(reload_cmds, $1)='$CC -Tprelink_objects $reload_objs~
'"$_LT_TAGVAR(reload_cmds, $1)"
;;
*)
_LT_TAGVAR(archive_cmds, $1)='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
_LT_TAGVAR(archive_expsym_cmds, $1)='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
esac
;;
tandem*)
case $cc_basename in
NCC*)
# NonStop-UX NCC 3.20
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
esac
;;
vxworks*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
*)
# FIXME: insert proper C++ library support
_LT_TAGVAR(ld_shlibs, $1)=no
;;
esac
AC_MSG_RESULT([$_LT_TAGVAR(ld_shlibs, $1)])
test "$_LT_TAGVAR(ld_shlibs, $1)" = no && can_build_shared=no
_LT_TAGVAR(GCC, $1)="$GXX"
_LT_TAGVAR(LD, $1)="$LD"
## CAVEAT EMPTOR:
## There is no encapsulation within the following macros, do not change
## the running order or otherwise move them around unless you know exactly
## what you are doing...
_LT_SYS_HIDDEN_LIBDEPS($1)
_LT_COMPILER_PIC($1)
_LT_COMPILER_C_O($1)
_LT_COMPILER_FILE_LOCKS($1)
_LT_LINKER_SHLIBS($1)
_LT_SYS_DYNAMIC_LINKER($1)
_LT_LINKER_HARDCODE_LIBPATH($1)
_LT_CONFIG($1)
fi # test -n "$compiler"
CC=$lt_save_CC
CFLAGS=$lt_save_CFLAGS
LDCXX=$LD
LD=$lt_save_LD
GCC=$lt_save_GCC
with_gnu_ld=$lt_save_with_gnu_ld
lt_cv_path_LDCXX=$lt_cv_path_LD
lt_cv_path_LD=$lt_save_path_LD
lt_cv_prog_gnu_ldcxx=$lt_cv_prog_gnu_ld
lt_cv_prog_gnu_ld=$lt_save_with_gnu_ld
fi # test "$_lt_caught_CXX_error" != yes
AC_LANG_POP
])# _LT_LANG_CXX_CONFIG
# _LT_FUNC_STRIPNAME_CNF
# ----------------------
# func_stripname_cnf prefix suffix name
# strip PREFIX and SUFFIX off of NAME.
# PREFIX and SUFFIX must not contain globbing or regex special
# characters, hashes, percent signs, but SUFFIX may contain a leading
# dot (in which case that matches only a dot).
#
# This function is identical to the (non-XSI) version of func_stripname,
# except this one can be used by m4 code that may be executed by configure,
# rather than the libtool script.
m4_defun([_LT_FUNC_STRIPNAME_CNF],[dnl
AC_REQUIRE([_LT_DECL_SED])
AC_REQUIRE([_LT_PROG_ECHO_BACKSLASH])
func_stripname_cnf ()
{
case ${2} in
.*) func_stripname_result=`$ECHO "${3}" | $SED "s%^${1}%%; s%\\\\${2}\$%%"`;;
*) func_stripname_result=`$ECHO "${3}" | $SED "s%^${1}%%; s%${2}\$%%"`;;
esac
} # func_stripname_cnf
])# _LT_FUNC_STRIPNAME_CNF
# _LT_SYS_HIDDEN_LIBDEPS([TAGNAME])
# ---------------------------------
# Figure out "hidden" library dependencies from verbose
# compiler output when linking a shared library.
# Parse the compiler output and extract the necessary
# objects, libraries and library flags.
m4_defun([_LT_SYS_HIDDEN_LIBDEPS],
[m4_require([_LT_FILEUTILS_DEFAULTS])dnl
AC_REQUIRE([_LT_FUNC_STRIPNAME_CNF])dnl
# Dependencies to place before and after the object being linked:
_LT_TAGVAR(predep_objects, $1)=
_LT_TAGVAR(postdep_objects, $1)=
_LT_TAGVAR(predeps, $1)=
_LT_TAGVAR(postdeps, $1)=
_LT_TAGVAR(compiler_lib_search_path, $1)=
dnl we can't use the lt_simple_compile_test_code here,
dnl because it contains code intended for an executable,
dnl not a library. It's possible we should let each
dnl tag define a new lt_????_link_test_code variable,
dnl but it's only used here...
m4_if([$1], [], [cat > conftest.$ac_ext <<_LT_EOF
int a;
void foo (void) { a = 0; }
_LT_EOF
], [$1], [CXX], [cat > conftest.$ac_ext <<_LT_EOF
class Foo
{
public:
Foo (void) { a = 0; }
private:
int a;
};
_LT_EOF
], [$1], [F77], [cat > conftest.$ac_ext <<_LT_EOF
subroutine foo
implicit none
integer*4 a
a=0
return
end
_LT_EOF
], [$1], [FC], [cat > conftest.$ac_ext <<_LT_EOF
subroutine foo
implicit none
integer a
a=0
return
end
_LT_EOF
], [$1], [GCJ], [cat > conftest.$ac_ext <<_LT_EOF
public class foo {
private int a;
public void bar (void) {
a = 0;
}
};
_LT_EOF
], [$1], [GO], [cat > conftest.$ac_ext <<_LT_EOF
package foo
func foo() {
}
_LT_EOF
])
_lt_libdeps_save_CFLAGS=$CFLAGS
case "$CC $CFLAGS " in #(
*\ -flto*\ *) CFLAGS="$CFLAGS -fno-lto" ;;
*\ -fwhopr*\ *) CFLAGS="$CFLAGS -fno-whopr" ;;
*\ -fuse-linker-plugin*\ *) CFLAGS="$CFLAGS -fno-use-linker-plugin" ;;
esac
dnl Parse the compiler output and extract the necessary
dnl objects, libraries and library flags.
if AC_TRY_EVAL(ac_compile); then
# Parse the compiler output and extract the necessary
# objects, libraries and library flags.
# Sentinel used to keep track of whether or not we are before
# the conftest object file.
pre_test_object_deps_done=no
for p in `eval "$output_verbose_link_cmd"`; do
case ${prev}${p} in
-L* | -R* | -l*)
# Some compilers place space between "-{L,R}" and the path.
# Remove the space.
if test $p = "-L" ||
test $p = "-R"; then
prev=$p
continue
fi
# Expand the sysroot to ease extracting the directories later.
if test -z "$prev"; then
case $p in
-L*) func_stripname_cnf '-L' '' "$p"; prev=-L; p=$func_stripname_result ;;
-R*) func_stripname_cnf '-R' '' "$p"; prev=-R; p=$func_stripname_result ;;
-l*) func_stripname_cnf '-l' '' "$p"; prev=-l; p=$func_stripname_result ;;
esac
fi
case $p in
=*) func_stripname_cnf '=' '' "$p"; p=$lt_sysroot$func_stripname_result ;;
esac
if test "$pre_test_object_deps_done" = no; then
case ${prev} in
-L | -R)
# Internal compiler library paths should come after those
# provided the user. The postdeps already come after the
# user supplied libs so there is no need to process them.
if test -z "$_LT_TAGVAR(compiler_lib_search_path, $1)"; then
_LT_TAGVAR(compiler_lib_search_path, $1)="${prev}${p}"
else
_LT_TAGVAR(compiler_lib_search_path, $1)="${_LT_TAGVAR(compiler_lib_search_path, $1)} ${prev}${p}"
fi
;;
# The "-l" case would never come before the object being
# linked, so don't bother handling this case.
esac
else
if test -z "$_LT_TAGVAR(postdeps, $1)"; then
_LT_TAGVAR(postdeps, $1)="${prev}${p}"
else
_LT_TAGVAR(postdeps, $1)="${_LT_TAGVAR(postdeps, $1)} ${prev}${p}"
fi
fi
prev=
;;
*.lto.$objext) ;; # Ignore GCC LTO objects
*.$objext)
# This assumes that the test object file only shows up
# once in the compiler output.
if test "$p" = "conftest.$objext"; then
pre_test_object_deps_done=yes
continue
fi
if test "$pre_test_object_deps_done" = no; then
if test -z "$_LT_TAGVAR(predep_objects, $1)"; then
_LT_TAGVAR(predep_objects, $1)="$p"
else
_LT_TAGVAR(predep_objects, $1)="$_LT_TAGVAR(predep_objects, $1) $p"
fi
else
if test -z "$_LT_TAGVAR(postdep_objects, $1)"; then
_LT_TAGVAR(postdep_objects, $1)="$p"
else
_LT_TAGVAR(postdep_objects, $1)="$_LT_TAGVAR(postdep_objects, $1) $p"
fi
fi
;;
*) ;; # Ignore the rest.
esac
done
# Clean up.
rm -f a.out a.exe
else
echo "libtool.m4: error: problem compiling $1 test program"
fi
$RM -f confest.$objext
CFLAGS=$_lt_libdeps_save_CFLAGS
# PORTME: override above test on systems where it is broken
m4_if([$1], [CXX],
[case $host_os in
interix[[3-9]]*)
# Interix 3.5 installs completely hosed .la files for C++, so rather than
# hack all around it, let's just trust "g++" to DTRT.
_LT_TAGVAR(predep_objects,$1)=
_LT_TAGVAR(postdep_objects,$1)=
_LT_TAGVAR(postdeps,$1)=
;;
linux*)
case `$CC -V 2>&1 | sed 5q` in
*Sun\ C*)
# Sun C++ 5.9
# The more standards-conforming stlport4 library is
# incompatible with the Cstd library. Avoid specifying
# it if it's in CXXFLAGS. Ignore libCrun as
# -library=stlport4 depends on it.
case " $CXX $CXXFLAGS " in
*" -library=stlport4 "*)
solaris_use_stlport4=yes
;;
esac
if test "$solaris_use_stlport4" != yes; then
_LT_TAGVAR(postdeps,$1)='-library=Cstd -library=Crun'
fi
;;
esac
;;
solaris*)
case $cc_basename in
CC* | sunCC*)
# The more standards-conforming stlport4 library is
# incompatible with the Cstd library. Avoid specifying
# it if it's in CXXFLAGS. Ignore libCrun as
# -library=stlport4 depends on it.
case " $CXX $CXXFLAGS " in
*" -library=stlport4 "*)
solaris_use_stlport4=yes
;;
esac
# Adding this requires a known-good setup of shared libraries for
# Sun compiler versions before 5.6, else PIC objects from an old
# archive will be linked into the output, leading to subtle bugs.
if test "$solaris_use_stlport4" != yes; then
_LT_TAGVAR(postdeps,$1)='-library=Cstd -library=Crun'
fi
;;
esac
;;
esac
])
case " $_LT_TAGVAR(postdeps, $1) " in
*" -lc "*) _LT_TAGVAR(archive_cmds_need_lc, $1)=no ;;
esac
_LT_TAGVAR(compiler_lib_search_dirs, $1)=
if test -n "${_LT_TAGVAR(compiler_lib_search_path, $1)}"; then
_LT_TAGVAR(compiler_lib_search_dirs, $1)=`echo " ${_LT_TAGVAR(compiler_lib_search_path, $1)}" | ${SED} -e 's! -L! !g' -e 's!^ !!'`
fi
_LT_TAGDECL([], [compiler_lib_search_dirs], [1],
[The directories searched by this compiler when creating a shared library])
_LT_TAGDECL([], [predep_objects], [1],
[Dependencies to place before and after the objects being linked to
create a shared library])
_LT_TAGDECL([], [postdep_objects], [1])
_LT_TAGDECL([], [predeps], [1])
_LT_TAGDECL([], [postdeps], [1])
_LT_TAGDECL([], [compiler_lib_search_path], [1],
[The library search path used internally by the compiler when linking
a shared library])
])# _LT_SYS_HIDDEN_LIBDEPS
# _LT_LANG_F77_CONFIG([TAG])
# --------------------------
# Ensure that the configuration variables for a Fortran 77 compiler are
# suitably defined. These variables are subsequently used by _LT_CONFIG
# to write the compiler configuration to `libtool'.
m4_defun([_LT_LANG_F77_CONFIG],
[AC_LANG_PUSH(Fortran 77)
if test -z "$F77" || test "X$F77" = "Xno"; then
_lt_disable_F77=yes
fi
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(allow_undefined_flag, $1)=
_LT_TAGVAR(always_export_symbols, $1)=no
_LT_TAGVAR(archive_expsym_cmds, $1)=
_LT_TAGVAR(export_dynamic_flag_spec, $1)=
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_direct_absolute, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)=
_LT_TAGVAR(hardcode_libdir_separator, $1)=
_LT_TAGVAR(hardcode_minus_L, $1)=no
_LT_TAGVAR(hardcode_automatic, $1)=no
_LT_TAGVAR(inherit_rpath, $1)=no
_LT_TAGVAR(module_cmds, $1)=
_LT_TAGVAR(module_expsym_cmds, $1)=
_LT_TAGVAR(link_all_deplibs, $1)=unknown
_LT_TAGVAR(old_archive_cmds, $1)=$old_archive_cmds
_LT_TAGVAR(reload_flag, $1)=$reload_flag
_LT_TAGVAR(reload_cmds, $1)=$reload_cmds
_LT_TAGVAR(no_undefined_flag, $1)=
_LT_TAGVAR(whole_archive_flag_spec, $1)=
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=no
# Source file extension for f77 test sources.
ac_ext=f
# Object file extension for compiled f77 test sources.
objext=o
_LT_TAGVAR(objext, $1)=$objext
# No sense in running all these tests if we already determined that
# the F77 compiler isn't working. Some variables (like enable_shared)
# are currently assumed to apply to all compilers on this platform,
# and will be corrupted by setting them based on a non-working compiler.
if test "$_lt_disable_F77" != yes; then
# Code to be used in simple compile tests
lt_simple_compile_test_code="\
subroutine t
return
end
"
# Code to be used in simple link tests
lt_simple_link_test_code="\
program t
end
"
# ltmain only uses $CC for tagged configurations so make sure $CC is set.
_LT_TAG_COMPILER
# save warnings/boilerplate of simple test code
_LT_COMPILER_BOILERPLATE
_LT_LINKER_BOILERPLATE
# Allow CC to be a program name with arguments.
lt_save_CC="$CC"
lt_save_GCC=$GCC
lt_save_CFLAGS=$CFLAGS
CC=${F77-"f77"}
CFLAGS=$FFLAGS
compiler=$CC
_LT_TAGVAR(compiler, $1)=$CC
_LT_CC_BASENAME([$compiler])
GCC=$G77
if test -n "$compiler"; then
AC_MSG_CHECKING([if libtool supports shared libraries])
AC_MSG_RESULT([$can_build_shared])
AC_MSG_CHECKING([whether to build shared libraries])
test "$can_build_shared" = "no" && enable_shared=no
# On AIX, shared libraries and static libraries use the same namespace, and
# are all built from PIC.
case $host_os in
aix3*)
test "$enable_shared" = yes && enable_static=no
if test -n "$RANLIB"; then
archive_cmds="$archive_cmds~\$RANLIB \$lib"
postinstall_cmds='$RANLIB $lib'
fi
;;
aix[[4-9]]*)
if test "$host_cpu" != ia64 && test "$aix_use_runtimelinking" = no ; then
test "$enable_shared" = yes && enable_static=no
fi
;;
esac
AC_MSG_RESULT([$enable_shared])
AC_MSG_CHECKING([whether to build static libraries])
# Make sure either enable_shared or enable_static is yes.
test "$enable_shared" = yes || enable_static=yes
AC_MSG_RESULT([$enable_static])
_LT_TAGVAR(GCC, $1)="$G77"
_LT_TAGVAR(LD, $1)="$LD"
## CAVEAT EMPTOR:
## There is no encapsulation within the following macros, do not change
## the running order or otherwise move them around unless you know exactly
## what you are doing...
_LT_COMPILER_PIC($1)
_LT_COMPILER_C_O($1)
_LT_COMPILER_FILE_LOCKS($1)
_LT_LINKER_SHLIBS($1)
_LT_SYS_DYNAMIC_LINKER($1)
_LT_LINKER_HARDCODE_LIBPATH($1)
_LT_CONFIG($1)
fi # test -n "$compiler"
GCC=$lt_save_GCC
CC="$lt_save_CC"
CFLAGS="$lt_save_CFLAGS"
fi # test "$_lt_disable_F77" != yes
AC_LANG_POP
])# _LT_LANG_F77_CONFIG
# _LT_LANG_FC_CONFIG([TAG])
# -------------------------
# Ensure that the configuration variables for a Fortran compiler are
# suitably defined. These variables are subsequently used by _LT_CONFIG
# to write the compiler configuration to `libtool'.
m4_defun([_LT_LANG_FC_CONFIG],
[AC_LANG_PUSH(Fortran)
if test -z "$FC" || test "X$FC" = "Xno"; then
_lt_disable_FC=yes
fi
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(allow_undefined_flag, $1)=
_LT_TAGVAR(always_export_symbols, $1)=no
_LT_TAGVAR(archive_expsym_cmds, $1)=
_LT_TAGVAR(export_dynamic_flag_spec, $1)=
_LT_TAGVAR(hardcode_direct, $1)=no
_LT_TAGVAR(hardcode_direct_absolute, $1)=no
_LT_TAGVAR(hardcode_libdir_flag_spec, $1)=
_LT_TAGVAR(hardcode_libdir_separator, $1)=
_LT_TAGVAR(hardcode_minus_L, $1)=no
_LT_TAGVAR(hardcode_automatic, $1)=no
_LT_TAGVAR(inherit_rpath, $1)=no
_LT_TAGVAR(module_cmds, $1)=
_LT_TAGVAR(module_expsym_cmds, $1)=
_LT_TAGVAR(link_all_deplibs, $1)=unknown
_LT_TAGVAR(old_archive_cmds, $1)=$old_archive_cmds
_LT_TAGVAR(reload_flag, $1)=$reload_flag
_LT_TAGVAR(reload_cmds, $1)=$reload_cmds
_LT_TAGVAR(no_undefined_flag, $1)=
_LT_TAGVAR(whole_archive_flag_spec, $1)=
_LT_TAGVAR(enable_shared_with_static_runtimes, $1)=no
# Source file extension for fc test sources.
ac_ext=${ac_fc_srcext-f}
# Object file extension for compiled fc test sources.
objext=o
_LT_TAGVAR(objext, $1)=$objext
# No sense in running all these tests if we already determined that
# the FC compiler isn't working. Some variables (like enable_shared)
# are currently assumed to apply to all compilers on this platform,
# and will be corrupted by setting them based on a non-working compiler.
if test "$_lt_disable_FC" != yes; then
# Code to be used in simple compile tests
lt_simple_compile_test_code="\
subroutine t
return
end
"
# Code to be used in simple link tests
lt_simple_link_test_code="\
program t
end
"
# ltmain only uses $CC for tagged configurations so make sure $CC is set.
_LT_TAG_COMPILER
# save warnings/boilerplate of simple test code
_LT_COMPILER_BOILERPLATE
_LT_LINKER_BOILERPLATE
# Allow CC to be a program name with arguments.
lt_save_CC="$CC"
lt_save_GCC=$GCC
lt_save_CFLAGS=$CFLAGS
CC=${FC-"f95"}
CFLAGS=$FCFLAGS
compiler=$CC
GCC=$ac_cv_fc_compiler_gnu
_LT_TAGVAR(compiler, $1)=$CC
_LT_CC_BASENAME([$compiler])
if test -n "$compiler"; then
AC_MSG_CHECKING([if libtool supports shared libraries])
AC_MSG_RESULT([$can_build_shared])
AC_MSG_CHECKING([whether to build shared libraries])
test "$can_build_shared" = "no" && enable_shared=no
# On AIX, shared libraries and static libraries use the same namespace, and
# are all built from PIC.
case $host_os in
aix3*)
test "$enable_shared" = yes && enable_static=no
if test -n "$RANLIB"; then
archive_cmds="$archive_cmds~\$RANLIB \$lib"
postinstall_cmds='$RANLIB $lib'
fi
;;
aix[[4-9]]*)
if test "$host_cpu" != ia64 && test "$aix_use_runtimelinking" = no ; then
test "$enable_shared" = yes && enable_static=no
fi
;;
esac
AC_MSG_RESULT([$enable_shared])
AC_MSG_CHECKING([whether to build static libraries])
# Make sure either enable_shared or enable_static is yes.
test "$enable_shared" = yes || enable_static=yes
AC_MSG_RESULT([$enable_static])
_LT_TAGVAR(GCC, $1)="$ac_cv_fc_compiler_gnu"
_LT_TAGVAR(LD, $1)="$LD"
## CAVEAT EMPTOR:
## There is no encapsulation within the following macros, do not change
## the running order or otherwise move them around unless you know exactly
## what you are doing...
_LT_SYS_HIDDEN_LIBDEPS($1)
_LT_COMPILER_PIC($1)
_LT_COMPILER_C_O($1)
_LT_COMPILER_FILE_LOCKS($1)
_LT_LINKER_SHLIBS($1)
_LT_SYS_DYNAMIC_LINKER($1)
_LT_LINKER_HARDCODE_LIBPATH($1)
_LT_CONFIG($1)
fi # test -n "$compiler"
GCC=$lt_save_GCC
CC=$lt_save_CC
CFLAGS=$lt_save_CFLAGS
fi # test "$_lt_disable_FC" != yes
AC_LANG_POP
])# _LT_LANG_FC_CONFIG
# _LT_LANG_GCJ_CONFIG([TAG])
# --------------------------
# Ensure that the configuration variables for the GNU Java Compiler compiler
# are suitably defined. These variables are subsequently used by _LT_CONFIG
# to write the compiler configuration to `libtool'.
m4_defun([_LT_LANG_GCJ_CONFIG],
[AC_REQUIRE([LT_PROG_GCJ])dnl
AC_LANG_SAVE
# Source file extension for Java test sources.
ac_ext=java
# Object file extension for compiled Java test sources.
objext=o
_LT_TAGVAR(objext, $1)=$objext
# Code to be used in simple compile tests
lt_simple_compile_test_code="class foo {}"
# Code to be used in simple link tests
lt_simple_link_test_code='public class conftest { public static void main(String[[]] argv) {}; }'
# ltmain only uses $CC for tagged configurations so make sure $CC is set.
_LT_TAG_COMPILER
# save warnings/boilerplate of simple test code
_LT_COMPILER_BOILERPLATE
_LT_LINKER_BOILERPLATE
# Allow CC to be a program name with arguments.
lt_save_CC=$CC
lt_save_CFLAGS=$CFLAGS
lt_save_GCC=$GCC
GCC=yes
CC=${GCJ-"gcj"}
CFLAGS=$GCJFLAGS
compiler=$CC
_LT_TAGVAR(compiler, $1)=$CC
_LT_TAGVAR(LD, $1)="$LD"
_LT_CC_BASENAME([$compiler])
# GCJ did not exist at the time GCC didn't implicitly link libc in.
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(old_archive_cmds, $1)=$old_archive_cmds
_LT_TAGVAR(reload_flag, $1)=$reload_flag
_LT_TAGVAR(reload_cmds, $1)=$reload_cmds
## CAVEAT EMPTOR:
## There is no encapsulation within the following macros, do not change
## the running order or otherwise move them around unless you know exactly
## what you are doing...
if test -n "$compiler"; then
_LT_COMPILER_NO_RTTI($1)
_LT_COMPILER_PIC($1)
_LT_COMPILER_C_O($1)
_LT_COMPILER_FILE_LOCKS($1)
_LT_LINKER_SHLIBS($1)
_LT_LINKER_HARDCODE_LIBPATH($1)
_LT_CONFIG($1)
fi
AC_LANG_RESTORE
GCC=$lt_save_GCC
CC=$lt_save_CC
CFLAGS=$lt_save_CFLAGS
])# _LT_LANG_GCJ_CONFIG
# _LT_LANG_GO_CONFIG([TAG])
# --------------------------
# Ensure that the configuration variables for the GNU Go compiler
# are suitably defined. These variables are subsequently used by _LT_CONFIG
# to write the compiler configuration to `libtool'.
m4_defun([_LT_LANG_GO_CONFIG],
[AC_REQUIRE([LT_PROG_GO])dnl
AC_LANG_SAVE
# Source file extension for Go test sources.
ac_ext=go
# Object file extension for compiled Go test sources.
objext=o
_LT_TAGVAR(objext, $1)=$objext
# Code to be used in simple compile tests
lt_simple_compile_test_code="package main; func main() { }"
# Code to be used in simple link tests
lt_simple_link_test_code='package main; func main() { }'
# ltmain only uses $CC for tagged configurations so make sure $CC is set.
_LT_TAG_COMPILER
# save warnings/boilerplate of simple test code
_LT_COMPILER_BOILERPLATE
_LT_LINKER_BOILERPLATE
# Allow CC to be a program name with arguments.
lt_save_CC=$CC
lt_save_CFLAGS=$CFLAGS
lt_save_GCC=$GCC
GCC=yes
CC=${GOC-"gccgo"}
CFLAGS=$GOFLAGS
compiler=$CC
_LT_TAGVAR(compiler, $1)=$CC
_LT_TAGVAR(LD, $1)="$LD"
_LT_CC_BASENAME([$compiler])
# Go did not exist at the time GCC didn't implicitly link libc in.
_LT_TAGVAR(archive_cmds_need_lc, $1)=no
_LT_TAGVAR(old_archive_cmds, $1)=$old_archive_cmds
_LT_TAGVAR(reload_flag, $1)=$reload_flag
_LT_TAGVAR(reload_cmds, $1)=$reload_cmds
## CAVEAT EMPTOR:
## There is no encapsulation within the following macros, do not change
## the running order or otherwise move them around unless you know exactly
## what you are doing...
if test -n "$compiler"; then
_LT_COMPILER_NO_RTTI($1)
_LT_COMPILER_PIC($1)
_LT_COMPILER_C_O($1)
_LT_COMPILER_FILE_LOCKS($1)
_LT_LINKER_SHLIBS($1)
_LT_LINKER_HARDCODE_LIBPATH($1)
_LT_CONFIG($1)
fi
AC_LANG_RESTORE
GCC=$lt_save_GCC
CC=$lt_save_CC
CFLAGS=$lt_save_CFLAGS
])# _LT_LANG_GO_CONFIG
# _LT_LANG_RC_CONFIG([TAG])
# -------------------------
# Ensure that the configuration variables for the Windows resource compiler
# are suitably defined. These variables are subsequently used by _LT_CONFIG
# to write the compiler configuration to `libtool'.
m4_defun([_LT_LANG_RC_CONFIG],
[AC_REQUIRE([LT_PROG_RC])dnl
AC_LANG_SAVE
# Source file extension for RC test sources.
ac_ext=rc
# Object file extension for compiled RC test sources.
objext=o
_LT_TAGVAR(objext, $1)=$objext
# Code to be used in simple compile tests
lt_simple_compile_test_code='sample MENU { MENUITEM "&Soup", 100, CHECKED }'
# Code to be used in simple link tests
lt_simple_link_test_code="$lt_simple_compile_test_code"
# ltmain only uses $CC for tagged configurations so make sure $CC is set.
_LT_TAG_COMPILER
# save warnings/boilerplate of simple test code
_LT_COMPILER_BOILERPLATE
_LT_LINKER_BOILERPLATE
# Allow CC to be a program name with arguments.
lt_save_CC="$CC"
lt_save_CFLAGS=$CFLAGS
lt_save_GCC=$GCC
GCC=
CC=${RC-"windres"}
CFLAGS=
compiler=$CC
_LT_TAGVAR(compiler, $1)=$CC
_LT_CC_BASENAME([$compiler])
_LT_TAGVAR(lt_cv_prog_compiler_c_o, $1)=yes
if test -n "$compiler"; then
:
_LT_CONFIG($1)
fi
GCC=$lt_save_GCC
AC_LANG_RESTORE
CC=$lt_save_CC
CFLAGS=$lt_save_CFLAGS
])# _LT_LANG_RC_CONFIG
# LT_PROG_GCJ
# -----------
AC_DEFUN([LT_PROG_GCJ],
[m4_ifdef([AC_PROG_GCJ], [AC_PROG_GCJ],
[m4_ifdef([A][M_PROG_GCJ], [A][M_PROG_GCJ],
[AC_CHECK_TOOL(GCJ, gcj,)
test "x${GCJFLAGS+set}" = xset || GCJFLAGS="-g -O2"
AC_SUBST(GCJFLAGS)])])[]dnl
])
# Old name:
AU_ALIAS([LT_AC_PROG_GCJ], [LT_PROG_GCJ])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([LT_AC_PROG_GCJ], [])
# LT_PROG_GO
# ----------
AC_DEFUN([LT_PROG_GO],
[AC_CHECK_TOOL(GOC, gccgo,)
])
# LT_PROG_RC
# ----------
AC_DEFUN([LT_PROG_RC],
[AC_CHECK_TOOL(RC, windres,)
])
# Old name:
AU_ALIAS([LT_AC_PROG_RC], [LT_PROG_RC])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([LT_AC_PROG_RC], [])
# _LT_DECL_EGREP
# --------------
# If we don't have a new enough Autoconf to choose the best grep
# available, choose the one first in the user's PATH.
m4_defun([_LT_DECL_EGREP],
[AC_REQUIRE([AC_PROG_EGREP])dnl
AC_REQUIRE([AC_PROG_FGREP])dnl
test -z "$GREP" && GREP=grep
_LT_DECL([], [GREP], [1], [A grep program that handles long lines])
_LT_DECL([], [EGREP], [1], [An ERE matcher])
_LT_DECL([], [FGREP], [1], [A literal string matcher])
dnl Non-bleeding-edge autoconf doesn't subst GREP, so do it here too
AC_SUBST([GREP])
])
# _LT_DECL_OBJDUMP
# --------------
# If we don't have a new enough Autoconf to choose the best objdump
# available, choose the one first in the user's PATH.
m4_defun([_LT_DECL_OBJDUMP],
[AC_CHECK_TOOL(OBJDUMP, objdump, false)
test -z "$OBJDUMP" && OBJDUMP=objdump
_LT_DECL([], [OBJDUMP], [1], [An object symbol dumper])
AC_SUBST([OBJDUMP])
])
# _LT_DECL_DLLTOOL
# ----------------
# Ensure DLLTOOL variable is set.
m4_defun([_LT_DECL_DLLTOOL],
[AC_CHECK_TOOL(DLLTOOL, dlltool, false)
test -z "$DLLTOOL" && DLLTOOL=dlltool
_LT_DECL([], [DLLTOOL], [1], [DLL creation program])
AC_SUBST([DLLTOOL])
])
# _LT_DECL_SED
# ------------
# Check for a fully-functional sed program, that truncates
# as few characters as possible. Prefer GNU sed if found.
m4_defun([_LT_DECL_SED],
[AC_PROG_SED
test -z "$SED" && SED=sed
Xsed="$SED -e 1s/^X//"
_LT_DECL([], [SED], [1], [A sed program that does not truncate output])
_LT_DECL([], [Xsed], ["\$SED -e 1s/^X//"],
[Sed that helps us avoid accidentally triggering echo(1) options like -n])
])# _LT_DECL_SED
m4_ifndef([AC_PROG_SED], [
############################################################
# NOTE: This macro has been submitted for inclusion into #
# GNU Autoconf as AC_PROG_SED. When it is available in #
# a released version of Autoconf we should remove this #
# macro and use it instead. #
############################################################
m4_defun([AC_PROG_SED],
[AC_MSG_CHECKING([for a sed that does not truncate output])
AC_CACHE_VAL(lt_cv_path_SED,
[# Loop through the user's path and test for sed and gsed.
# Then use that list of sed's as ones to test for truncation.
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for lt_ac_prog in sed gsed; do
for ac_exec_ext in '' $ac_executable_extensions; do
if $as_executable_p "$as_dir/$lt_ac_prog$ac_exec_ext"; then
lt_ac_sed_list="$lt_ac_sed_list $as_dir/$lt_ac_prog$ac_exec_ext"
fi
done
done
done
IFS=$as_save_IFS
lt_ac_max=0
lt_ac_count=0
# Add /usr/xpg4/bin/sed as it is typically found on Solaris
# along with /bin/sed that truncates output.
for lt_ac_sed in $lt_ac_sed_list /usr/xpg4/bin/sed; do
test ! -f $lt_ac_sed && continue
cat /dev/null > conftest.in
lt_ac_count=0
echo $ECHO_N "0123456789$ECHO_C" >conftest.in
# Check for GNU sed and select it if it is found.
if "$lt_ac_sed" --version 2>&1 < /dev/null | grep 'GNU' > /dev/null; then
lt_cv_path_SED=$lt_ac_sed
break
fi
while true; do
cat conftest.in conftest.in >conftest.tmp
mv conftest.tmp conftest.in
cp conftest.in conftest.nl
echo >>conftest.nl
$lt_ac_sed -e 's/a$//' < conftest.nl >conftest.out || break
cmp -s conftest.out conftest.nl || break
# 10000 chars as input seems more than enough
test $lt_ac_count -gt 10 && break
lt_ac_count=`expr $lt_ac_count + 1`
if test $lt_ac_count -gt $lt_ac_max; then
lt_ac_max=$lt_ac_count
lt_cv_path_SED=$lt_ac_sed
fi
done
done
])
SED=$lt_cv_path_SED
AC_SUBST([SED])
AC_MSG_RESULT([$SED])
])#AC_PROG_SED
])#m4_ifndef
# Old name:
AU_ALIAS([LT_AC_PROG_SED], [AC_PROG_SED])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([LT_AC_PROG_SED], [])
# _LT_CHECK_SHELL_FEATURES
# ------------------------
# Find out whether the shell is Bourne or XSI compatible,
# or has some other useful features.
m4_defun([_LT_CHECK_SHELL_FEATURES],
[AC_MSG_CHECKING([whether the shell understands some XSI constructs])
# Try some XSI features
xsi_shell=no
( _lt_dummy="a/b/c"
test "${_lt_dummy##*/},${_lt_dummy%/*},${_lt_dummy#??}"${_lt_dummy%"$_lt_dummy"}, \
= c,a/b,b/c, \
&& eval 'test $(( 1 + 1 )) -eq 2 \
&& test "${#_lt_dummy}" -eq 5' ) >/dev/null 2>&1 \
&& xsi_shell=yes
AC_MSG_RESULT([$xsi_shell])
_LT_CONFIG_LIBTOOL_INIT([xsi_shell='$xsi_shell'])
AC_MSG_CHECKING([whether the shell understands "+="])
lt_shell_append=no
( foo=bar; set foo baz; eval "$[1]+=\$[2]" && test "$foo" = barbaz ) \
>/dev/null 2>&1 \
&& lt_shell_append=yes
AC_MSG_RESULT([$lt_shell_append])
_LT_CONFIG_LIBTOOL_INIT([lt_shell_append='$lt_shell_append'])
if ( (MAIL=60; unset MAIL) || exit) >/dev/null 2>&1; then
lt_unset=unset
else
lt_unset=false
fi
_LT_DECL([], [lt_unset], [0], [whether the shell understands "unset"])dnl
# test EBCDIC or ASCII
case `echo X|tr X '\101'` in
A) # ASCII based system
# \n is not interpreted correctly by Solaris 8 /usr/ucb/tr
lt_SP2NL='tr \040 \012'
lt_NL2SP='tr \015\012 \040\040'
;;
*) # EBCDIC based system
lt_SP2NL='tr \100 \n'
lt_NL2SP='tr \r\n \100\100'
;;
esac
_LT_DECL([SP2NL], [lt_SP2NL], [1], [turn spaces into newlines])dnl
_LT_DECL([NL2SP], [lt_NL2SP], [1], [turn newlines into spaces])dnl
])# _LT_CHECK_SHELL_FEATURES
# _LT_PROG_FUNCTION_REPLACE (FUNCNAME, REPLACEMENT-BODY)
# ------------------------------------------------------
# In `$cfgfile', look for function FUNCNAME delimited by `^FUNCNAME ()$' and
# '^} FUNCNAME ', and replace its body with REPLACEMENT-BODY.
m4_defun([_LT_PROG_FUNCTION_REPLACE],
[dnl {
sed -e '/^$1 ()$/,/^} # $1 /c\
$1 ()\
{\
m4_bpatsubsts([$2], [$], [\\], [^\([ ]\)], [\\\1])
} # Extended-shell $1 implementation' "$cfgfile" > $cfgfile.tmp \
&& mv -f "$cfgfile.tmp" "$cfgfile" \
|| (rm -f "$cfgfile" && cp "$cfgfile.tmp" "$cfgfile" && rm -f "$cfgfile.tmp")
test 0 -eq $? || _lt_function_replace_fail=:
])
# _LT_PROG_REPLACE_SHELLFNS
# -------------------------
# Replace existing portable implementations of several shell functions with
# equivalent extended shell implementations where those features are available..
m4_defun([_LT_PROG_REPLACE_SHELLFNS],
[if test x"$xsi_shell" = xyes; then
_LT_PROG_FUNCTION_REPLACE([func_dirname], [dnl
case ${1} in
*/*) func_dirname_result="${1%/*}${2}" ;;
* ) func_dirname_result="${3}" ;;
esac])
_LT_PROG_FUNCTION_REPLACE([func_basename], [dnl
func_basename_result="${1##*/}"])
_LT_PROG_FUNCTION_REPLACE([func_dirname_and_basename], [dnl
case ${1} in
*/*) func_dirname_result="${1%/*}${2}" ;;
* ) func_dirname_result="${3}" ;;
esac
func_basename_result="${1##*/}"])
_LT_PROG_FUNCTION_REPLACE([func_stripname], [dnl
# pdksh 5.2.14 does not do ${X%$Y} correctly if both X and Y are
# positional parameters, so assign one to ordinary parameter first.
func_stripname_result=${3}
func_stripname_result=${func_stripname_result#"${1}"}
func_stripname_result=${func_stripname_result%"${2}"}])
_LT_PROG_FUNCTION_REPLACE([func_split_long_opt], [dnl
func_split_long_opt_name=${1%%=*}
func_split_long_opt_arg=${1#*=}])
_LT_PROG_FUNCTION_REPLACE([func_split_short_opt], [dnl
func_split_short_opt_arg=${1#??}
func_split_short_opt_name=${1%"$func_split_short_opt_arg"}])
_LT_PROG_FUNCTION_REPLACE([func_lo2o], [dnl
case ${1} in
*.lo) func_lo2o_result=${1%.lo}.${objext} ;;
*) func_lo2o_result=${1} ;;
esac])
_LT_PROG_FUNCTION_REPLACE([func_xform], [ func_xform_result=${1%.*}.lo])
_LT_PROG_FUNCTION_REPLACE([func_arith], [ func_arith_result=$(( $[*] ))])
_LT_PROG_FUNCTION_REPLACE([func_len], [ func_len_result=${#1}])
fi
if test x"$lt_shell_append" = xyes; then
_LT_PROG_FUNCTION_REPLACE([func_append], [ eval "${1}+=\\${2}"])
_LT_PROG_FUNCTION_REPLACE([func_append_quoted], [dnl
func_quote_for_eval "${2}"
dnl m4 expansion turns \\\\ into \\, and then the shell eval turns that into \
eval "${1}+=\\\\ \\$func_quote_for_eval_result"])
# Save a `func_append' function call where possible by direct use of '+='
sed -e 's%func_append \([[a-zA-Z_]]\{1,\}\) "%\1+="%g' $cfgfile > $cfgfile.tmp \
&& mv -f "$cfgfile.tmp" "$cfgfile" \
|| (rm -f "$cfgfile" && cp "$cfgfile.tmp" "$cfgfile" && rm -f "$cfgfile.tmp")
test 0 -eq $? || _lt_function_replace_fail=:
else
# Save a `func_append' function call even when '+=' is not available
sed -e 's%func_append \([[a-zA-Z_]]\{1,\}\) "%\1="$\1%g' $cfgfile > $cfgfile.tmp \
&& mv -f "$cfgfile.tmp" "$cfgfile" \
|| (rm -f "$cfgfile" && cp "$cfgfile.tmp" "$cfgfile" && rm -f "$cfgfile.tmp")
test 0 -eq $? || _lt_function_replace_fail=:
fi
if test x"$_lt_function_replace_fail" = x":"; then
AC_MSG_WARN([Unable to substitute extended shell functions in $ofile])
fi
])
# _LT_PATH_CONVERSION_FUNCTIONS
# -----------------------------
# Determine which file name conversion functions should be used by
# func_to_host_file (and, implicitly, by func_to_host_path). These are needed
# for certain cross-compile configurations and native mingw.
m4_defun([_LT_PATH_CONVERSION_FUNCTIONS],
[AC_REQUIRE([AC_CANONICAL_HOST])dnl
AC_REQUIRE([AC_CANONICAL_BUILD])dnl
AC_MSG_CHECKING([how to convert $build file names to $host format])
AC_CACHE_VAL(lt_cv_to_host_file_cmd,
[case $host in
*-*-mingw* )
case $build in
*-*-mingw* ) # actually msys
lt_cv_to_host_file_cmd=func_convert_file_msys_to_w32
;;
*-*-cygwin* )
lt_cv_to_host_file_cmd=func_convert_file_cygwin_to_w32
;;
* ) # otherwise, assume *nix
lt_cv_to_host_file_cmd=func_convert_file_nix_to_w32
;;
esac
;;
*-*-cygwin* )
case $build in
*-*-mingw* ) # actually msys
lt_cv_to_host_file_cmd=func_convert_file_msys_to_cygwin
;;
*-*-cygwin* )
lt_cv_to_host_file_cmd=func_convert_file_noop
;;
* ) # otherwise, assume *nix
lt_cv_to_host_file_cmd=func_convert_file_nix_to_cygwin
;;
esac
;;
* ) # unhandled hosts (and "normal" native builds)
lt_cv_to_host_file_cmd=func_convert_file_noop
;;
esac
])
to_host_file_cmd=$lt_cv_to_host_file_cmd
AC_MSG_RESULT([$lt_cv_to_host_file_cmd])
_LT_DECL([to_host_file_cmd], [lt_cv_to_host_file_cmd],
[0], [convert $build file names to $host format])dnl
AC_MSG_CHECKING([how to convert $build file names to toolchain format])
AC_CACHE_VAL(lt_cv_to_tool_file_cmd,
[#assume ordinary cross tools, or native build.
lt_cv_to_tool_file_cmd=func_convert_file_noop
case $host in
*-*-mingw* )
case $build in
*-*-mingw* ) # actually msys
lt_cv_to_tool_file_cmd=func_convert_file_msys_to_w32
;;
esac
;;
esac
])
to_tool_file_cmd=$lt_cv_to_tool_file_cmd
AC_MSG_RESULT([$lt_cv_to_tool_file_cmd])
_LT_DECL([to_tool_file_cmd], [lt_cv_to_tool_file_cmd],
[0], [convert $build files to toolchain format])dnl
])# _LT_PATH_CONVERSION_FUNCTIONS
PHYLIPNEW-3.69.650/m4/java.m4 0000664 0001750 0001750 00000015055 11732713220 011775 0000000 0000000 dnl -*- Autoconf -*-
dnl @synopsis CHECK_JAVA()
dnl
dnl Need to specify --with-java and --with-javaos
dnl @author Alan Bleasby
dnl
dnl This macro calls:
dnl
dnl AC_SUBST([JAVA_CFLAGS])
dnl AC_SUBST([JAVA_CPPFLAGS])
dnl AC_SUBST([JAVA_LDFLAGS])
dnl
dnl AM_CONDITIONAL([JAVA_BUILD], ...)
dnl
dnl And sets:
dnl
dnl AC_DEFINE([HAVE_JAVA], ...)
dnl
dnl AC_PATH_PROG([ANT], ...)
dnl AC_PATH_PROG([JAR], ...)
dnl AC_PATH_PROG([JAVA], ...)
dnl AC_PATH_PROG([JAVAC], ...)
AC_DEFUN([CHECK_JAVA],
[
JAVA_CFLAGS=""
JAVA_CPPFLAGS=""
JAVA_LDFLAGS=""
have_java="yes"
auth_java=""
AC_MSG_CHECKING([for Java JNI])
AC_ARG_WITH([java],
[AS_HELP_STRING([--with-java@<:@=ARG@:>@],
[root directory path of Java installation])],
[
AC_MSG_RESULT([${withval}])
AS_IF([test "x${withval}" = "xno"], [have_java="no"])
],
[
AC_MSG_RESULT([no])
have_java="no"
])
AS_IF([test "x${have_java}" = "xyes"],
[
# If specified, the Java JNI include directory has to exist.
AS_IF([test -d ${with_java}],
[AS_VAR_SET([JAVA_CPPFLAGS], ["-I${withval}"])],
[
have_java="no"
AC_MSG_ERROR([Java include directory ${withval} does not exist])
])
])
AC_MSG_CHECKING([for Java JNI OS])
AC_ARG_WITH([javaos],
[AS_HELP_STRING([--with-javaos@<:@=ARG@:>@],
[root directory path of Java OS include])],
[
AC_MSG_RESULT([${withval}])
AS_IF([test "x${withval}" != "xno"],
[
# If specified, the Java JNI OS include directory has to exist.
AS_IF([test "x${have_java}" = "xyes" && test -d ${withval}],
[AS_VAR_APPEND([JAVA_CPPFLAGS], [" -I${withval}"])],
[
have_java="no"
AC_MSG_ERROR([Java OS include directory ${withval} does not exist])
])
])
],
[
AC_MSG_RESULT([no])
])
# Authorisation type
AC_MSG_CHECKING([for authorisation type])
AC_ARG_WITH([auth],
[AS_HELP_STRING([--with-auth@<:@=ARG@:>@],
[authorisation mechanism for Jemboss server @<:@default=PAM@:>@])],
[
AS_IF([test "x${withval}" != "xno"],
[
AC_MSG_RESULT([yes])
AS_CASE([${withval}],
[yes],
[
auth_java="PAM"
AC_CHECK_LIB([pam], [main],
[AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpam"])])
],
[pam],
[
auth_java="PAM"
AC_CHECK_LIB([pam], [main],
[AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpam"])])
],
[shadow],
[
auth_java="N_SHADOW"
AC_CHECK_LIB([crypy], [main],
[AS_VAR_APPEND([JAVA_LDFLAGS], [" -lcrypt"])])
],
[rshadow],
[
auth_java="R_SHADOW"
AC_CHECK_LIB([crypy], [main],
[AS_VAR_APPEND([JAVA_LDFLAGS], [" -lcrypt"])])
],
[noshadow],
[auth_java="NO_SHADOW"],
[rnoshadow],
[auth_java="RNO_SHADOW"],
[aixshadow],
[auth_java="AIX_SHADOW"],
[hpuxshadow],
[auth_java="HPUX_SHADOW"])
],
[AC_MSG_RESULT([no])])
],
[AC_MSG_RESULT([no])])
AS_IF([test -n "${auth_java}"],
[AS_VAR_APPEND([JAVA_CPPFLAGS], [" -D${auth_java}"])],
[AS_VAR_APPEND([JAVA_CPPFLAGS], [" -DNO_AUTH"])])
# Threading type
AC_MSG_CHECKING([for threading type])
AC_ARG_WITH([thread],
[AS_HELP_STRING([--with-thread@<:@=ARG@:>@],
[thread type @<:@default=linux@:>@])],
[
AS_IF([test "x${withval}" != "xno"],
[
AC_MSG_RESULT([yes])
AS_CASE([${withval}],
[yes],
[
AS_VAR_APPEND([JAVA_CPPFLAGS], [" -D_REENTRANT"])
AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpthread"])
# AS_VAR_APPEND([LIBS], [" -lpthread"])
],
[freebsd],
[
AS_VAR_APPEND([JAVA_CPPFLAGS], [" -D_THREAD_SAFE"])
AS_VAR_APPEND([JAVA_LDFLAGS], [" -pthread"])
# AS_VAR_APPEND([LIBS], [" -lc_r"])
],
[linux],
[
AS_VAR_APPEND([JAVA_CPPFLAGS], [" -D_REENTRANT"])
AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpthread"])
# AS_VAR_APPEND([LIBS], [" -lpthread"])
],
[solaris],
[
AS_VAR_APPEND([JAVA_CPPFLAGS], [" -D_POSIX_C_SOURCE=199506L"])
AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpthread"])
# AS_VAR_APPEND([LIBS], [" -lpthread"])
],
[macos],
[
# AS_VAR_APPEND([JAVA_CPPFLAGS], [""])
# AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpthread"])
# AS_VAR_APPEND([LIBS], [" -lpthread"])
],
[hpux],
[
AS_VAR_APPEND([JAVA_CFLAGS], [" -Ae +z"])
AS_VAR_APPEND([JAVA CPPFLAGS], [" -DNATIVE -D_POSIX_C_SOURCE=199506L"])
AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpthread"])
# AS_VAR_APPEND([LIBS], [" -lpthread"])
],
[irix],
[
# AS_VAR_APPEND([JAVA_CFLAGS], [""])
AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpthread"])
AS_VAR_APPEND([LIBS], [" -lpthread"])
],
[aix],
[
AS_VAR_APPEND([JAVA_CPPFLAGS], [" -D_REENTRANT"])
AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpthread"])
AS_VAR_APPEND([LIBS], [" -lpthread"])
],
[osf],
[
AS_VAR_APPEND([JAVA_CPPFLAGS], [" -D_REENTRANT -D_OSF_SOURCE"])
AS_VAR_APPEND([JAVA_LDFLAGS], [" -lpthread"])
AS_VAR_APPEND([LIBS], [" -lpthread"])
])
],
[AC_MSG_RESULT([no])])
],
[AC_MSG_RESULT([no])])
# Test for programs ant, jar, java and javac.
AS_IF([test "x${have_java}" = "xyes"],
[
AC_PATH_PROG([ANT], [ant], [no])
AS_IF([test "x${ANT}" = "xno"], [have_java="no"])
AC_PATH_PROG([JAR], [jar], [no])
AS_IF([test "x${JAR}" = "xno"], [have_java="no"])
AC_PATH_PROG([JAVA], [java], [no])
AS_IF([test "x${JAVA}" = "xno"], [have_java="no"])
AC_PATH_PROG([JAVAC], [javac], [no])
AS_IF([test "x${JAVAC}" = "xno"], [have_java="no"])
])
AS_IF([test "x${have_java}" = "xyes"],
[
AC_DEFINE([HAVE_JAVA], [1],
[Define to 1 if the Java Native Interface (JNI) is available.])
### FIXME: Append -DDEBIAN for the moment.
# Debian uses PAM service "ssh" instead of "login", see ajjava.c
# This could use AC_DEFINE() if no better option was avialable.
# Ultimately, this should be configurable via server configuration
# files.
AS_IF([test -f "/etc/debian_release" || test -f /etc/debian_version],
[AS_VAR_APPEND([JAVA_CPPFLAGS], [" -DDEBIAN"])])
])
AC_ARG_VAR([ANT], [Path to the Apache Ant make tool])
AC_ARG_VAR([JAR], [Path to the Java archive tool])
AC_ARG_VAR([JAVA], [Path to the Java application launcher])
AC_ARG_VAR([JAVAC], [Path to the Java compiler])
AC_SUBST([JAVA_CFLAGS])
AC_SUBST([JAVA_CPPFLAGS])
AC_SUBST([JAVA_LDFLAGS])
AM_CONDITIONAL([JAVA_BUILD], [test "x${have_java}" = "xyes"])
])
PHYLIPNEW-3.69.650/m4/ltversion.m4 0000644 0001750 0001750 00000001262 12171071672 013100 0000000 0000000 # ltversion.m4 -- version numbers -*- Autoconf -*-
#
# Copyright (C) 2004 Free Software Foundation, Inc.
# Written by Scott James Remnant, 2004
#
# This file is free software; the Free Software Foundation gives
# unlimited permission to copy and/or distribute it, with or without
# modifications, as long as this notice is preserved.
# @configure_input@
# serial 3337 ltversion.m4
# This file is part of GNU Libtool
m4_define([LT_PACKAGE_VERSION], [2.4.2])
m4_define([LT_PACKAGE_REVISION], [1.3337])
AC_DEFUN([LTVERSION_VERSION],
[macro_version='2.4.2'
macro_revision='1.3337'
_LT_DECL(, macro_version, 0, [Which release of libtool.m4 was used?])
_LT_DECL(, macro_revision, 0)
])
PHYLIPNEW-3.69.650/m4/general.m4 0000664 0001750 0001750 00000001253 11374607601 012473 0000000 0000000 AC_DEFUN([CHECK_GENERAL],
#
# Handle general setup e.g. documentation directory
#
[AC_MSG_CHECKING(if docroot is given)
AC_ARG_WITH([docroot],
[AS_HELP_STRING([--with-docroot=DIR],
[root directory path of documentation (defaults to none)])],
[if test "$withval" != no ; then
AC_MSG_RESULT(yes)
CPPFLAGS="$CPPFLAGS -DDOC_ROOT=\\\"$withval\\\""
fi], [
AC_MSG_RESULT(no)
])
]
# GCC profiling
[AC_MSG_CHECKING(if gcc profiling is selected)
AC_ARG_WITH([gccprofile],
[AS_HELP_STRING([--with-gccprofile], [selects profiling])],
[if test "$withval" != no ; then
AC_MSG_RESULT(yes)
CFLAGS="$CFLAGS -g -pg"
LDFLAGS="$LDFLAGS -pg"
fi], [
AC_MSG_RESULT(no)
])
]
)
PHYLIPNEW-3.69.650/m4/mysql.m4 0000664 0001750 0001750 00000012663 11732713347 012235 0000000 0000000 dnl -*- Autoconf -*-
##### http://autoconf-archive.cryp.to/ax_lib_mysql.html
#
# SYNOPSIS
#
# AX_LIB_MYSQL([MINIMUM-VERSION])
#
# DESCRIPTION
#
# This macro provides tests of availability of MySQL 'libmysqlclient'
# library of particular version or newer.
#
# AX_LIB_MYSQL macro takes only one argument which is optional.
# If there is no required version passed, then macro does not run
# version test.
#
# The --with-mysql option takes one of three possible values:
#
# no - do not check for MySQL client library
#
# yes - do check for MySQL library in standard locations
# (mysql_config should be in the PATH)
#
# path - complete path to mysql_config utility, use this option if
# mysql_config can't be found in the PATH
#
# This macro calls:
#
# AC_SUBST([MYSQL_CFLAGS])
# AC_SUBST([MYSQL_CPPFLAGS])
# AC_SUBST([MYSQL_LDFLAGS])
# AC_SUBST([MYSQL_VERSION])
#
# And sets:
#
# HAVE_MYSQL
#
# LAST MODIFICATION
#
# 2006-07-16
# 2007-01-09 MKS: mysql_config --cflags may set gcc -fomit-frame-pointers,
# which prevents gdb from displaying stack traces.
# Changed mysql_config --cflags to mysql_config --include
# 2009-09-23 AJB: Checking for availability of both, include files and
# library files.
# 2010-06-14 MKS: Added MYSQL_CPPFLAGS
# 2011-08-01 MKS: Made test constructs more portable
#
# COPYLEFT
#
# Copyright (c) 2006 Mateusz Loskot
#
# Copying and distribution of this file, with or without
# modification, are permitted in any medium without royalty provided
# the copyright notice and this notice are preserved.
AC_DEFUN([AX_LIB_MYSQL],
[
MYSQL_CFLAGS=""
MYSQL_CPPFLAGS=""
MYSQL_LDFLAGS=""
MYSQL_CONFIG=""
MYSQL_VERSION=""
AC_ARG_WITH([mysql],
[AS_HELP_STRING([--with-mysql@<:@=ARG@:>@],
[use MySQL client library @<:@default=yes@:>@, optionally specify path to mysql_config])],
[
AS_IF([test "x${withval}" = "xno"],
[want_mysql="no"],
[test "x${withval}" = "xyes"],
[want_mysql="yes"],
[
want_mysql="yes"
MYSQL_CONFIG="${withval}"
])
],
[want_mysql="yes"])
dnl
dnl Check MySQL libraries (libmysqlclient)
dnl
AS_IF([test "x${want_mysql}" = "xyes"],
[
AS_IF([test -z "${MYSQL_CONFIG}" -o test],
[AC_PATH_PROG([MYSQL_CONFIG], [mysql_config], [no])])
AS_IF([test "x${MYSQL_CONFIG}" != "xno"],
[
AC_MSG_CHECKING([for MySQL libraries])
MYSQL_CFLAGS="`${MYSQL_CONFIG} --cflags`"
MYSQL_CPPFLAGS="`${MYSQL_CONFIG} --include`"
MYSQL_LDFLAGS="`${MYSQL_CONFIG} --libs`"
MYSQL_VERSION=`${MYSQL_CONFIG} --version`
dnl It isn't enough to just test for mysql_config as Fedora
dnl provides it in the mysql RPM even though mysql-devel may
dnl not be installed
EMBCPPFLAGS="${CPPFLAGS}"
EMBLDFLAGS="${LDFLAGS}"
CPPFLAGS="${MYSQL_CPPFLAGS} ${EMBCPPFLAGS}"
LDFLAGS="${MYSQL_LDFLAGS} ${EMBLDFLAGS}"
AC_LINK_IFELSE([AC_LANG_PROGRAM([[#include
#include "mysql.h"]],
[[mysql_info(NULL)]])],
[havemysql="yes"],
[havemysql="no"])
CPPFLAGS="${EMBCPPFLAGS}"
LDFLAGS="${EMBLDFLAGS}"
AS_IF([test "x${havemysql}" = "xyes"],
[
AC_DEFINE([HAVE_MYSQL], [1],
[Define to 1 if MySQL libraries are available.])
found_mysql="yes"
AC_MSG_RESULT([yes])
],
[
MYSQL_CFLAGS=""
MYSQL_CPPFLAGS=""
MYSQL_LDFLAGS=""
found_mysql="no"
AC_MSG_RESULT([no])
])
],
[
found_mysql="no"
])
])
dnl
dnl Check if required version of MySQL is available
dnl
mysql_version_req=ifelse([$1], [], [], [$1])
AS_IF([test "x${found_mysql}" = "xyes" -a -n "${mysql_version_req}"],
[
AC_MSG_CHECKING([if MySQL version is >= ${mysql_version_req}])
dnl Decompose required version string of MySQL
dnl and calculate its number representation
mysql_version_req_major=`expr ${mysql_version_req} : '\([[0-9]]*\)'`
mysql_version_req_minor=`expr ${mysql_version_req} : '[[0-9]]*\.\([[0-9]]*\)'`
mysql_version_req_micro=`expr ${mysql_version_req} : '[[0-9]]*\.[[0-9]]*\.\([[0-9]]*\)'`
AS_IF([test "x${mysql_version_req_micro}" = "x"],
[mysql_version_req_micro="0"])
mysql_version_req_number=`expr ${mysql_version_req_major} \* 1000000 \
\+ ${mysql_version_req_minor} \* 1000 \
\+ ${mysql_version_req_micro}`
dnl Decompose version string of installed MySQL
dnl and calculate its number representation
mysql_version_major=`expr ${MYSQL_VERSION} : '\([[0-9]]*\)'`
mysql_version_minor=`expr ${MYSQL_VERSION} : '[[0-9]]*\.\([[0-9]]*\)'`
mysql_version_micro=`expr ${MYSQL_VERSION} : '[[0-9]]*\.[[0-9]]*\.\([[0-9]]*\)'`
AS_IF([test "x${mysql_version_micro}" = "x"],
[mysql_version_micro="0"])
mysql_version_number=`expr ${mysql_version_major} \* 1000000 \
\+ ${mysql_version_minor} \* 1000 \
\+ ${mysql_version_micro}`
mysql_version_check=`expr ${mysql_version_number} \>\= ${mysql_version_req_number}`
AS_IF([test "x${mysql_version_check}" = "x1"],
[AC_MSG_RESULT([yes])],
[AC_MSG_RESULT([no])])
])
AC_SUBST([MYSQL_CFLAGS])
AC_SUBST([MYSQL_CPPFLAGS])
AC_SUBST([MYSQL_LDFLAGS])
AC_SUBST([MYSQL_VERSION])
])
PHYLIPNEW-3.69.650/m4/hpdf.m4 0000664 0001750 0001750 00000003530 11430325237 011772 0000000 0000000 dnl @synopsis CHECK_HPDF()
dnl
dnl This macro searches for an installed libhpdf (libharu) library. If nothing
dnl was specified when calling configure, it first searches in /usr/local
dnl and then in /usr. If the --with-hpdf=DIR is specified, it will try
dnl to find it in DIR/include and DIR/lib.
dnl
dnl It defines the symbol PLD_pdf if the library is found.
dnl
AC_DEFUN([CHECK_HPDF],
#
# Handle user hints
#
[AC_MSG_CHECKING([whether to look for pdf support])
AC_ARG_WITH([hpdf],
[AS_HELP_STRING([--with-hpdf=DIR],
[root directory path of hpdf installation @<:@defaults to /usr@:>@])],
[if test "$withval" != no ; then
AC_MSG_RESULT(yes)
ALT_HOME="$withval"
else
AC_MSG_RESULT([no])
fi], [
AC_MSG_RESULT([yes])
ALT_HOME=/usr
])
#
# Locate hpdf
#
if test -d "${ALT_HOME}"
then
#
# Keep a copy if it fails
#
ALT_LDFLAGS="$LDFLAGS"
ALT_CPPFLAGS="$CPPFLAGS"
#
# Set
#
LDFLAGS="${LDFLAGS} -L${ALT_HOME}/lib"
CPPFLAGS="$CPPFLAGS -I$ALT_HOME/include"
#
# Check for libharu in ALT_HOME
#
AC_CHECK_LIB(hpdf, HPDF_New, CHECK=1, CHECK=0, -L${ALT_HOME}/lib)
#
#
# If everything found okay then proceed to include png driver in config.
#
if test $CHECK = "1" ; then
LIBS="$LIBS -lhpdf"
case $host_os in
solaris*)
LDFLAGS="$LDFLAGS -R$ALT_HOME/lib"
;;
esac
AC_DEFINE([PLD_pdf], [1], [Define to 1 if PDF support is available])
AM_CONDITIONAL(AMPDF, true)
echo PDF support found
if test $ALT_HOME = "/usr" ; then
LDFLAGS="$ALT_LDFLAGS"
CPPFLAGS="$ALT_CPPFLAGS"
fi
else
#
# If not okay then reset FLAGS.
#
AM_CONDITIONAL(AMPDF, false)
LDFLAGS="$ALT_LDFLAGS"
CPPFLAGS="$ALT_CPPFLAGS"
echo "No pdf support (libhpdf) found."
fi
else
if test $withval != "no"; then
echo "Directory $ALT_HOME does not exist"
exit 0
fi
fi
])
PHYLIPNEW-3.69.650/m4/lt~obsolete.m4 0000644 0001750 0001750 00000013756 12171071672 013440 0000000 0000000 # lt~obsolete.m4 -- aclocal satisfying obsolete definitions. -*-Autoconf-*-
#
# Copyright (C) 2004, 2005, 2007, 2009 Free Software Foundation, Inc.
# Written by Scott James Remnant, 2004.
#
# This file is free software; the Free Software Foundation gives
# unlimited permission to copy and/or distribute it, with or without
# modifications, as long as this notice is preserved.
# serial 5 lt~obsolete.m4
# These exist entirely to fool aclocal when bootstrapping libtool.
#
# In the past libtool.m4 has provided macros via AC_DEFUN (or AU_DEFUN)
# which have later been changed to m4_define as they aren't part of the
# exported API, or moved to Autoconf or Automake where they belong.
#
# The trouble is, aclocal is a bit thick. It'll see the old AC_DEFUN
# in /usr/share/aclocal/libtool.m4 and remember it, then when it sees us
# using a macro with the same name in our local m4/libtool.m4 it'll
# pull the old libtool.m4 in (it doesn't see our shiny new m4_define
# and doesn't know about Autoconf macros at all.)
#
# So we provide this file, which has a silly filename so it's always
# included after everything else. This provides aclocal with the
# AC_DEFUNs it wants, but when m4 processes it, it doesn't do anything
# because those macros already exist, or will be overwritten later.
# We use AC_DEFUN over AU_DEFUN for compatibility with aclocal-1.6.
#
# Anytime we withdraw an AC_DEFUN or AU_DEFUN, remember to add it here.
# Yes, that means every name once taken will need to remain here until
# we give up compatibility with versions before 1.7, at which point
# we need to keep only those names which we still refer to.
# This is to help aclocal find these macros, as it can't see m4_define.
AC_DEFUN([LTOBSOLETE_VERSION], [m4_if([1])])
m4_ifndef([AC_LIBTOOL_LINKER_OPTION], [AC_DEFUN([AC_LIBTOOL_LINKER_OPTION])])
m4_ifndef([AC_PROG_EGREP], [AC_DEFUN([AC_PROG_EGREP])])
m4_ifndef([_LT_AC_PROG_ECHO_BACKSLASH], [AC_DEFUN([_LT_AC_PROG_ECHO_BACKSLASH])])
m4_ifndef([_LT_AC_SHELL_INIT], [AC_DEFUN([_LT_AC_SHELL_INIT])])
m4_ifndef([_LT_AC_SYS_LIBPATH_AIX], [AC_DEFUN([_LT_AC_SYS_LIBPATH_AIX])])
m4_ifndef([_LT_PROG_LTMAIN], [AC_DEFUN([_LT_PROG_LTMAIN])])
m4_ifndef([_LT_AC_TAGVAR], [AC_DEFUN([_LT_AC_TAGVAR])])
m4_ifndef([AC_LTDL_ENABLE_INSTALL], [AC_DEFUN([AC_LTDL_ENABLE_INSTALL])])
m4_ifndef([AC_LTDL_PREOPEN], [AC_DEFUN([AC_LTDL_PREOPEN])])
m4_ifndef([_LT_AC_SYS_COMPILER], [AC_DEFUN([_LT_AC_SYS_COMPILER])])
m4_ifndef([_LT_AC_LOCK], [AC_DEFUN([_LT_AC_LOCK])])
m4_ifndef([AC_LIBTOOL_SYS_OLD_ARCHIVE], [AC_DEFUN([AC_LIBTOOL_SYS_OLD_ARCHIVE])])
m4_ifndef([_LT_AC_TRY_DLOPEN_SELF], [AC_DEFUN([_LT_AC_TRY_DLOPEN_SELF])])
m4_ifndef([AC_LIBTOOL_PROG_CC_C_O], [AC_DEFUN([AC_LIBTOOL_PROG_CC_C_O])])
m4_ifndef([AC_LIBTOOL_SYS_HARD_LINK_LOCKS], [AC_DEFUN([AC_LIBTOOL_SYS_HARD_LINK_LOCKS])])
m4_ifndef([AC_LIBTOOL_OBJDIR], [AC_DEFUN([AC_LIBTOOL_OBJDIR])])
m4_ifndef([AC_LTDL_OBJDIR], [AC_DEFUN([AC_LTDL_OBJDIR])])
m4_ifndef([AC_LIBTOOL_PROG_LD_HARDCODE_LIBPATH], [AC_DEFUN([AC_LIBTOOL_PROG_LD_HARDCODE_LIBPATH])])
m4_ifndef([AC_LIBTOOL_SYS_LIB_STRIP], [AC_DEFUN([AC_LIBTOOL_SYS_LIB_STRIP])])
m4_ifndef([AC_PATH_MAGIC], [AC_DEFUN([AC_PATH_MAGIC])])
m4_ifndef([AC_PROG_LD_GNU], [AC_DEFUN([AC_PROG_LD_GNU])])
m4_ifndef([AC_PROG_LD_RELOAD_FLAG], [AC_DEFUN([AC_PROG_LD_RELOAD_FLAG])])
m4_ifndef([AC_DEPLIBS_CHECK_METHOD], [AC_DEFUN([AC_DEPLIBS_CHECK_METHOD])])
m4_ifndef([AC_LIBTOOL_PROG_COMPILER_NO_RTTI], [AC_DEFUN([AC_LIBTOOL_PROG_COMPILER_NO_RTTI])])
m4_ifndef([AC_LIBTOOL_SYS_GLOBAL_SYMBOL_PIPE], [AC_DEFUN([AC_LIBTOOL_SYS_GLOBAL_SYMBOL_PIPE])])
m4_ifndef([AC_LIBTOOL_PROG_COMPILER_PIC], [AC_DEFUN([AC_LIBTOOL_PROG_COMPILER_PIC])])
m4_ifndef([AC_LIBTOOL_PROG_LD_SHLIBS], [AC_DEFUN([AC_LIBTOOL_PROG_LD_SHLIBS])])
m4_ifndef([AC_LIBTOOL_POSTDEP_PREDEP], [AC_DEFUN([AC_LIBTOOL_POSTDEP_PREDEP])])
m4_ifndef([LT_AC_PROG_EGREP], [AC_DEFUN([LT_AC_PROG_EGREP])])
m4_ifndef([LT_AC_PROG_SED], [AC_DEFUN([LT_AC_PROG_SED])])
m4_ifndef([_LT_CC_BASENAME], [AC_DEFUN([_LT_CC_BASENAME])])
m4_ifndef([_LT_COMPILER_BOILERPLATE], [AC_DEFUN([_LT_COMPILER_BOILERPLATE])])
m4_ifndef([_LT_LINKER_BOILERPLATE], [AC_DEFUN([_LT_LINKER_BOILERPLATE])])
m4_ifndef([_AC_PROG_LIBTOOL], [AC_DEFUN([_AC_PROG_LIBTOOL])])
m4_ifndef([AC_LIBTOOL_SETUP], [AC_DEFUN([AC_LIBTOOL_SETUP])])
m4_ifndef([_LT_AC_CHECK_DLFCN], [AC_DEFUN([_LT_AC_CHECK_DLFCN])])
m4_ifndef([AC_LIBTOOL_SYS_DYNAMIC_LINKER], [AC_DEFUN([AC_LIBTOOL_SYS_DYNAMIC_LINKER])])
m4_ifndef([_LT_AC_TAGCONFIG], [AC_DEFUN([_LT_AC_TAGCONFIG])])
m4_ifndef([AC_DISABLE_FAST_INSTALL], [AC_DEFUN([AC_DISABLE_FAST_INSTALL])])
m4_ifndef([_LT_AC_LANG_CXX], [AC_DEFUN([_LT_AC_LANG_CXX])])
m4_ifndef([_LT_AC_LANG_F77], [AC_DEFUN([_LT_AC_LANG_F77])])
m4_ifndef([_LT_AC_LANG_GCJ], [AC_DEFUN([_LT_AC_LANG_GCJ])])
m4_ifndef([AC_LIBTOOL_LANG_C_CONFIG], [AC_DEFUN([AC_LIBTOOL_LANG_C_CONFIG])])
m4_ifndef([_LT_AC_LANG_C_CONFIG], [AC_DEFUN([_LT_AC_LANG_C_CONFIG])])
m4_ifndef([AC_LIBTOOL_LANG_CXX_CONFIG], [AC_DEFUN([AC_LIBTOOL_LANG_CXX_CONFIG])])
m4_ifndef([_LT_AC_LANG_CXX_CONFIG], [AC_DEFUN([_LT_AC_LANG_CXX_CONFIG])])
m4_ifndef([AC_LIBTOOL_LANG_F77_CONFIG], [AC_DEFUN([AC_LIBTOOL_LANG_F77_CONFIG])])
m4_ifndef([_LT_AC_LANG_F77_CONFIG], [AC_DEFUN([_LT_AC_LANG_F77_CONFIG])])
m4_ifndef([AC_LIBTOOL_LANG_GCJ_CONFIG], [AC_DEFUN([AC_LIBTOOL_LANG_GCJ_CONFIG])])
m4_ifndef([_LT_AC_LANG_GCJ_CONFIG], [AC_DEFUN([_LT_AC_LANG_GCJ_CONFIG])])
m4_ifndef([AC_LIBTOOL_LANG_RC_CONFIG], [AC_DEFUN([AC_LIBTOOL_LANG_RC_CONFIG])])
m4_ifndef([_LT_AC_LANG_RC_CONFIG], [AC_DEFUN([_LT_AC_LANG_RC_CONFIG])])
m4_ifndef([AC_LIBTOOL_CONFIG], [AC_DEFUN([AC_LIBTOOL_CONFIG])])
m4_ifndef([_LT_AC_FILE_LTDLL_C], [AC_DEFUN([_LT_AC_FILE_LTDLL_C])])
m4_ifndef([_LT_REQUIRED_DARWIN_CHECKS], [AC_DEFUN([_LT_REQUIRED_DARWIN_CHECKS])])
m4_ifndef([_LT_AC_PROG_CXXCPP], [AC_DEFUN([_LT_AC_PROG_CXXCPP])])
m4_ifndef([_LT_PREPARE_SED_QUOTE_VARS], [AC_DEFUN([_LT_PREPARE_SED_QUOTE_VARS])])
m4_ifndef([_LT_PROG_ECHO_BACKSLASH], [AC_DEFUN([_LT_PROG_ECHO_BACKSLASH])])
m4_ifndef([_LT_PROG_F77], [AC_DEFUN([_LT_PROG_F77])])
m4_ifndef([_LT_PROG_FC], [AC_DEFUN([_LT_PROG_FC])])
m4_ifndef([_LT_PROG_CXX], [AC_DEFUN([_LT_PROG_CXX])])
PHYLIPNEW-3.69.650/m4/sgi.m4 0000664 0001750 0001750 00000002343 11430325237 011634 0000000 0000000 AC_DEFUN([CHECK_SGI],
#
# Handle SGI compiler flags
#
[AC_MSG_CHECKING([for sgiabi])
AC_ARG_WITH([sgiabi],
[AS_HELP_STRING([--with-sgiabi=@<:@ARG@:>@],
[SGI compiler flags @<:@default=no@:>@])],
[if test "$withval" != no ; then
AC_MSG_RESULT([yes])
case $host_os in
irix*)
if test "$withval" = n32m3 ; then
CFLAGS="-n32 -mips3 $CFLAGS"
LD="/usr/bin/ld -n32 -mips3 -IPA -L/usr/lib32"
if test -d /usr/freeware ; then
LDFLAGS="-L/usr/freeware/lib32 $LDFLAGS"
fi
fi
if test "$withval" = n32m4 ; then
CFLAGS="-n32 -mips4 $CFLAGS"
LD="/usr/bin/ld -n32 -mips4 -IPA -L/usr/lib32"
if test -d /usr/freeware ; then
LDFLAGS="-L/usr/freeware/lib32 $LDFLAGS"
fi
fi
if test "$withval" = 64m3 ; then
CFLAGS="-64 -mips3 $CFLAGS"
LD="/usr/bin/ld -64 -mips3 -IPA -L/usr/lib64"
if test -d /usr/freeware ; then
LDFLAGS="-L/usr/freeware/lib64 $LDFLAGS"
fi
fi
if test "$withval" = 64m4 ; then
CFLAGS="-64 -mips4 $CFLAGS"
LD="/usr/bin/ld -64 -mips4 -IPA -L/usr/lib64"
if test -d /usr/freeware ; then
LDFLAGS="-L/usr/freeware/lib64 $LDFLAGS"
fi
fi
;;
esac
fi], [
AC_MSG_RESULT([no])
])
]
)
PHYLIPNEW-3.69.650/m4/ltoptions.m4 0000644 0001750 0001750 00000030073 12171071672 013110 0000000 0000000 # Helper functions for option handling. -*- Autoconf -*-
#
# Copyright (C) 2004, 2005, 2007, 2008, 2009 Free Software Foundation,
# Inc.
# Written by Gary V. Vaughan, 2004
#
# This file is free software; the Free Software Foundation gives
# unlimited permission to copy and/or distribute it, with or without
# modifications, as long as this notice is preserved.
# serial 7 ltoptions.m4
# This is to help aclocal find these macros, as it can't see m4_define.
AC_DEFUN([LTOPTIONS_VERSION], [m4_if([1])])
# _LT_MANGLE_OPTION(MACRO-NAME, OPTION-NAME)
# ------------------------------------------
m4_define([_LT_MANGLE_OPTION],
[[_LT_OPTION_]m4_bpatsubst($1__$2, [[^a-zA-Z0-9_]], [_])])
# _LT_SET_OPTION(MACRO-NAME, OPTION-NAME)
# ---------------------------------------
# Set option OPTION-NAME for macro MACRO-NAME, and if there is a
# matching handler defined, dispatch to it. Other OPTION-NAMEs are
# saved as a flag.
m4_define([_LT_SET_OPTION],
[m4_define(_LT_MANGLE_OPTION([$1], [$2]))dnl
m4_ifdef(_LT_MANGLE_DEFUN([$1], [$2]),
_LT_MANGLE_DEFUN([$1], [$2]),
[m4_warning([Unknown $1 option `$2'])])[]dnl
])
# _LT_IF_OPTION(MACRO-NAME, OPTION-NAME, IF-SET, [IF-NOT-SET])
# ------------------------------------------------------------
# Execute IF-SET if OPTION is set, IF-NOT-SET otherwise.
m4_define([_LT_IF_OPTION],
[m4_ifdef(_LT_MANGLE_OPTION([$1], [$2]), [$3], [$4])])
# _LT_UNLESS_OPTIONS(MACRO-NAME, OPTION-LIST, IF-NOT-SET)
# -------------------------------------------------------
# Execute IF-NOT-SET unless all options in OPTION-LIST for MACRO-NAME
# are set.
m4_define([_LT_UNLESS_OPTIONS],
[m4_foreach([_LT_Option], m4_split(m4_normalize([$2])),
[m4_ifdef(_LT_MANGLE_OPTION([$1], _LT_Option),
[m4_define([$0_found])])])[]dnl
m4_ifdef([$0_found], [m4_undefine([$0_found])], [$3
])[]dnl
])
# _LT_SET_OPTIONS(MACRO-NAME, OPTION-LIST)
# ----------------------------------------
# OPTION-LIST is a space-separated list of Libtool options associated
# with MACRO-NAME. If any OPTION has a matching handler declared with
# LT_OPTION_DEFINE, dispatch to that macro; otherwise complain about
# the unknown option and exit.
m4_defun([_LT_SET_OPTIONS],
[# Set options
m4_foreach([_LT_Option], m4_split(m4_normalize([$2])),
[_LT_SET_OPTION([$1], _LT_Option)])
m4_if([$1],[LT_INIT],[
dnl
dnl Simply set some default values (i.e off) if boolean options were not
dnl specified:
_LT_UNLESS_OPTIONS([LT_INIT], [dlopen], [enable_dlopen=no
])
_LT_UNLESS_OPTIONS([LT_INIT], [win32-dll], [enable_win32_dll=no
])
dnl
dnl If no reference was made to various pairs of opposing options, then
dnl we run the default mode handler for the pair. For example, if neither
dnl `shared' nor `disable-shared' was passed, we enable building of shared
dnl archives by default:
_LT_UNLESS_OPTIONS([LT_INIT], [shared disable-shared], [_LT_ENABLE_SHARED])
_LT_UNLESS_OPTIONS([LT_INIT], [static disable-static], [_LT_ENABLE_STATIC])
_LT_UNLESS_OPTIONS([LT_INIT], [pic-only no-pic], [_LT_WITH_PIC])
_LT_UNLESS_OPTIONS([LT_INIT], [fast-install disable-fast-install],
[_LT_ENABLE_FAST_INSTALL])
])
])# _LT_SET_OPTIONS
## --------------------------------- ##
## Macros to handle LT_INIT options. ##
## --------------------------------- ##
# _LT_MANGLE_DEFUN(MACRO-NAME, OPTION-NAME)
# -----------------------------------------
m4_define([_LT_MANGLE_DEFUN],
[[_LT_OPTION_DEFUN_]m4_bpatsubst(m4_toupper([$1__$2]), [[^A-Z0-9_]], [_])])
# LT_OPTION_DEFINE(MACRO-NAME, OPTION-NAME, CODE)
# -----------------------------------------------
m4_define([LT_OPTION_DEFINE],
[m4_define(_LT_MANGLE_DEFUN([$1], [$2]), [$3])[]dnl
])# LT_OPTION_DEFINE
# dlopen
# ------
LT_OPTION_DEFINE([LT_INIT], [dlopen], [enable_dlopen=yes
])
AU_DEFUN([AC_LIBTOOL_DLOPEN],
[_LT_SET_OPTION([LT_INIT], [dlopen])
AC_DIAGNOSE([obsolete],
[$0: Remove this warning and the call to _LT_SET_OPTION when you
put the `dlopen' option into LT_INIT's first parameter.])
])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_LIBTOOL_DLOPEN], [])
# win32-dll
# ---------
# Declare package support for building win32 dll's.
LT_OPTION_DEFINE([LT_INIT], [win32-dll],
[enable_win32_dll=yes
case $host in
*-*-cygwin* | *-*-mingw* | *-*-pw32* | *-*-cegcc*)
AC_CHECK_TOOL(AS, as, false)
AC_CHECK_TOOL(DLLTOOL, dlltool, false)
AC_CHECK_TOOL(OBJDUMP, objdump, false)
;;
esac
test -z "$AS" && AS=as
_LT_DECL([], [AS], [1], [Assembler program])dnl
test -z "$DLLTOOL" && DLLTOOL=dlltool
_LT_DECL([], [DLLTOOL], [1], [DLL creation program])dnl
test -z "$OBJDUMP" && OBJDUMP=objdump
_LT_DECL([], [OBJDUMP], [1], [Object dumper program])dnl
])# win32-dll
AU_DEFUN([AC_LIBTOOL_WIN32_DLL],
[AC_REQUIRE([AC_CANONICAL_HOST])dnl
_LT_SET_OPTION([LT_INIT], [win32-dll])
AC_DIAGNOSE([obsolete],
[$0: Remove this warning and the call to _LT_SET_OPTION when you
put the `win32-dll' option into LT_INIT's first parameter.])
])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_LIBTOOL_WIN32_DLL], [])
# _LT_ENABLE_SHARED([DEFAULT])
# ----------------------------
# implement the --enable-shared flag, and supports the `shared' and
# `disable-shared' LT_INIT options.
# DEFAULT is either `yes' or `no'. If omitted, it defaults to `yes'.
m4_define([_LT_ENABLE_SHARED],
[m4_define([_LT_ENABLE_SHARED_DEFAULT], [m4_if($1, no, no, yes)])dnl
AC_ARG_ENABLE([shared],
[AS_HELP_STRING([--enable-shared@<:@=PKGS@:>@],
[build shared libraries @<:@default=]_LT_ENABLE_SHARED_DEFAULT[@:>@])],
[p=${PACKAGE-default}
case $enableval in
yes) enable_shared=yes ;;
no) enable_shared=no ;;
*)
enable_shared=no
# Look at the argument we got. We use all the common list separators.
lt_save_ifs="$IFS"; IFS="${IFS}$PATH_SEPARATOR,"
for pkg in $enableval; do
IFS="$lt_save_ifs"
if test "X$pkg" = "X$p"; then
enable_shared=yes
fi
done
IFS="$lt_save_ifs"
;;
esac],
[enable_shared=]_LT_ENABLE_SHARED_DEFAULT)
_LT_DECL([build_libtool_libs], [enable_shared], [0],
[Whether or not to build shared libraries])
])# _LT_ENABLE_SHARED
LT_OPTION_DEFINE([LT_INIT], [shared], [_LT_ENABLE_SHARED([yes])])
LT_OPTION_DEFINE([LT_INIT], [disable-shared], [_LT_ENABLE_SHARED([no])])
# Old names:
AC_DEFUN([AC_ENABLE_SHARED],
[_LT_SET_OPTION([LT_INIT], m4_if([$1], [no], [disable-])[shared])
])
AC_DEFUN([AC_DISABLE_SHARED],
[_LT_SET_OPTION([LT_INIT], [disable-shared])
])
AU_DEFUN([AM_ENABLE_SHARED], [AC_ENABLE_SHARED($@)])
AU_DEFUN([AM_DISABLE_SHARED], [AC_DISABLE_SHARED($@)])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AM_ENABLE_SHARED], [])
dnl AC_DEFUN([AM_DISABLE_SHARED], [])
# _LT_ENABLE_STATIC([DEFAULT])
# ----------------------------
# implement the --enable-static flag, and support the `static' and
# `disable-static' LT_INIT options.
# DEFAULT is either `yes' or `no'. If omitted, it defaults to `yes'.
m4_define([_LT_ENABLE_STATIC],
[m4_define([_LT_ENABLE_STATIC_DEFAULT], [m4_if($1, no, no, yes)])dnl
AC_ARG_ENABLE([static],
[AS_HELP_STRING([--enable-static@<:@=PKGS@:>@],
[build static libraries @<:@default=]_LT_ENABLE_STATIC_DEFAULT[@:>@])],
[p=${PACKAGE-default}
case $enableval in
yes) enable_static=yes ;;
no) enable_static=no ;;
*)
enable_static=no
# Look at the argument we got. We use all the common list separators.
lt_save_ifs="$IFS"; IFS="${IFS}$PATH_SEPARATOR,"
for pkg in $enableval; do
IFS="$lt_save_ifs"
if test "X$pkg" = "X$p"; then
enable_static=yes
fi
done
IFS="$lt_save_ifs"
;;
esac],
[enable_static=]_LT_ENABLE_STATIC_DEFAULT)
_LT_DECL([build_old_libs], [enable_static], [0],
[Whether or not to build static libraries])
])# _LT_ENABLE_STATIC
LT_OPTION_DEFINE([LT_INIT], [static], [_LT_ENABLE_STATIC([yes])])
LT_OPTION_DEFINE([LT_INIT], [disable-static], [_LT_ENABLE_STATIC([no])])
# Old names:
AC_DEFUN([AC_ENABLE_STATIC],
[_LT_SET_OPTION([LT_INIT], m4_if([$1], [no], [disable-])[static])
])
AC_DEFUN([AC_DISABLE_STATIC],
[_LT_SET_OPTION([LT_INIT], [disable-static])
])
AU_DEFUN([AM_ENABLE_STATIC], [AC_ENABLE_STATIC($@)])
AU_DEFUN([AM_DISABLE_STATIC], [AC_DISABLE_STATIC($@)])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AM_ENABLE_STATIC], [])
dnl AC_DEFUN([AM_DISABLE_STATIC], [])
# _LT_ENABLE_FAST_INSTALL([DEFAULT])
# ----------------------------------
# implement the --enable-fast-install flag, and support the `fast-install'
# and `disable-fast-install' LT_INIT options.
# DEFAULT is either `yes' or `no'. If omitted, it defaults to `yes'.
m4_define([_LT_ENABLE_FAST_INSTALL],
[m4_define([_LT_ENABLE_FAST_INSTALL_DEFAULT], [m4_if($1, no, no, yes)])dnl
AC_ARG_ENABLE([fast-install],
[AS_HELP_STRING([--enable-fast-install@<:@=PKGS@:>@],
[optimize for fast installation @<:@default=]_LT_ENABLE_FAST_INSTALL_DEFAULT[@:>@])],
[p=${PACKAGE-default}
case $enableval in
yes) enable_fast_install=yes ;;
no) enable_fast_install=no ;;
*)
enable_fast_install=no
# Look at the argument we got. We use all the common list separators.
lt_save_ifs="$IFS"; IFS="${IFS}$PATH_SEPARATOR,"
for pkg in $enableval; do
IFS="$lt_save_ifs"
if test "X$pkg" = "X$p"; then
enable_fast_install=yes
fi
done
IFS="$lt_save_ifs"
;;
esac],
[enable_fast_install=]_LT_ENABLE_FAST_INSTALL_DEFAULT)
_LT_DECL([fast_install], [enable_fast_install], [0],
[Whether or not to optimize for fast installation])dnl
])# _LT_ENABLE_FAST_INSTALL
LT_OPTION_DEFINE([LT_INIT], [fast-install], [_LT_ENABLE_FAST_INSTALL([yes])])
LT_OPTION_DEFINE([LT_INIT], [disable-fast-install], [_LT_ENABLE_FAST_INSTALL([no])])
# Old names:
AU_DEFUN([AC_ENABLE_FAST_INSTALL],
[_LT_SET_OPTION([LT_INIT], m4_if([$1], [no], [disable-])[fast-install])
AC_DIAGNOSE([obsolete],
[$0: Remove this warning and the call to _LT_SET_OPTION when you put
the `fast-install' option into LT_INIT's first parameter.])
])
AU_DEFUN([AC_DISABLE_FAST_INSTALL],
[_LT_SET_OPTION([LT_INIT], [disable-fast-install])
AC_DIAGNOSE([obsolete],
[$0: Remove this warning and the call to _LT_SET_OPTION when you put
the `disable-fast-install' option into LT_INIT's first parameter.])
])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_ENABLE_FAST_INSTALL], [])
dnl AC_DEFUN([AM_DISABLE_FAST_INSTALL], [])
# _LT_WITH_PIC([MODE])
# --------------------
# implement the --with-pic flag, and support the `pic-only' and `no-pic'
# LT_INIT options.
# MODE is either `yes' or `no'. If omitted, it defaults to `both'.
m4_define([_LT_WITH_PIC],
[AC_ARG_WITH([pic],
[AS_HELP_STRING([--with-pic@<:@=PKGS@:>@],
[try to use only PIC/non-PIC objects @<:@default=use both@:>@])],
[lt_p=${PACKAGE-default}
case $withval in
yes|no) pic_mode=$withval ;;
*)
pic_mode=default
# Look at the argument we got. We use all the common list separators.
lt_save_ifs="$IFS"; IFS="${IFS}$PATH_SEPARATOR,"
for lt_pkg in $withval; do
IFS="$lt_save_ifs"
if test "X$lt_pkg" = "X$lt_p"; then
pic_mode=yes
fi
done
IFS="$lt_save_ifs"
;;
esac],
[pic_mode=default])
test -z "$pic_mode" && pic_mode=m4_default([$1], [default])
_LT_DECL([], [pic_mode], [0], [What type of objects to build])dnl
])# _LT_WITH_PIC
LT_OPTION_DEFINE([LT_INIT], [pic-only], [_LT_WITH_PIC([yes])])
LT_OPTION_DEFINE([LT_INIT], [no-pic], [_LT_WITH_PIC([no])])
# Old name:
AU_DEFUN([AC_LIBTOOL_PICMODE],
[_LT_SET_OPTION([LT_INIT], [pic-only])
AC_DIAGNOSE([obsolete],
[$0: Remove this warning and the call to _LT_SET_OPTION when you
put the `pic-only' option into LT_INIT's first parameter.])
])
dnl aclocal-1.4 backwards compatibility:
dnl AC_DEFUN([AC_LIBTOOL_PICMODE], [])
## ----------------- ##
## LTDL_INIT Options ##
## ----------------- ##
m4_define([_LTDL_MODE], [])
LT_OPTION_DEFINE([LTDL_INIT], [nonrecursive],
[m4_define([_LTDL_MODE], [nonrecursive])])
LT_OPTION_DEFINE([LTDL_INIT], [recursive],
[m4_define([_LTDL_MODE], [recursive])])
LT_OPTION_DEFINE([LTDL_INIT], [subproject],
[m4_define([_LTDL_MODE], [subproject])])
m4_define([_LTDL_TYPE], [])
LT_OPTION_DEFINE([LTDL_INIT], [installable],
[m4_define([_LTDL_TYPE], [installable])])
LT_OPTION_DEFINE([LTDL_INIT], [convenience],
[m4_define([_LTDL_TYPE], [convenience])])
PHYLIPNEW-3.69.650/test/ 0002775 0001750 0001750 00000000000 12171071713 011327 5 0000000 0000000 PHYLIPNEW-3.69.650/test/qatest.dat 0000664 0001750 0001750 00000060523 11616234343 013251 0000000 0000000 #######################################
# PHYLIP 3.6
#######################################
ID fclique-ex
AB phylipnew
AA fclique
IN ../../data/evolution/clique.dat
IN
FI clique.fclique
FC = 31
FP /^Characters: \( 1 2 3 6\)\n/
FP /^ 2 1 3 6\n/
FI clique.treefile
FC = 1
FP /^\(\(\(Delta,Epsilon\),Gamma\),Alpha,Beta\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 7
FP 3 /^./
//
ID fclique-all
AB phylipnew
AA fclique
CL -ancfile ../../data/evolution/clique.ancestral
CL -factorfile ../../data/evolution/clique.factors
CL -weights ../../data/evolution/clique.weights
IN ../../data/evolution/clique.dat
IN
FI clique.fclique
FC = 35
FP /^ 11223 4\n/
FP /^Actual Characters: \( 1 4\)\n/
FP /^Binary Characters: \( 1 2 6\)\n/
FP 1 /Tree and binary characters:/
FI clique.treefile
FC = 1
FP /^\(\(\(\(Alpha,Beta\),Gamma\),Epsilon\),Delta\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 7
FP 3 /^./
//
ID fconsense-ex
AB phylipnew
AA fconsense
IN ../../data/evolution/consense.dat
IN
FI consense.fconsense
FC = 77
FP /^ 10\. C\n/
FP /^\.\.\*\.\*\.\.\.\.\.\s+4\.00\n/
FI consense.treefile
FC = 2
FP /^E:9\.00\):9\.00,B:9\.00\):9\.00,A:9\.00\);\n/
FP /\(\(H:9\.00,J:9\.00\):4\.00,D:9\.00\)/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 7
FP 3 /^./
//
ID fcontml-ex
AB phylipnew
AA fcontml
CL -printdata
IN ../../data/evolution/contml.dat
IN
IN
FI contml.fcontml
FC = 67
FP /^Ln Likelihood = 38\.7191[0-9]\n/
FP /^ 2 Chinese 0\.00208822 \( -0\.00960622, 0\.02017433\)\n/
FI contml.treefile
FC = 2
FP /\(African:0\.09693444,\(Australian:0\.05247405,\(American:0\.03806240,Chinese:0\.00208822\):0\.00945315\):0\.02252816,/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 14
FP 9 /^./
//
ID fcontrast-ex
AB phylipnew
AA fcontrast
IN ../../data/evolution/contrast.dat
IN ../../data/evolution/contrast.tree
IN
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI contrast.fcontrast
FC = 19
FP /^ 3\.9423 1\.7028\n/
FP /^ 1\.0000 0\.4319\n/
FP /^ 1\.0000 0\.6566\n/
FI stdout
FC = 5
FP 2 /^./
//
ID fdiscboot-ex
AB phylipnew
AA fdiscboot
CL -seed 3
IN ../../data/evolution/discboot.dat
IN
IN
IN
IN
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 16
FP 12 /^./
FI discboot.ancfile
FZ = 0
FI discboot.factfile
FZ = 0
FI discboot.mixfile
FZ = 0
FI discboot.fdiscboot
FC = 600
FP 100 /^Alpha/
FP 10 /^Alpha 111100\n/
//
ID fdnacomp-ex
AB phylipnew
AA fdnacomp
CL -ancseq -stepbox -printdata
IN ../../data/evolution/dnacomp.dat
IN
IN
IN
FI dnacomp.fdnacomp
FC = 62
FP /total number of compatible sites is 11\.0\n/
FP / 4 Epsilon maybe GGGATCTCGG CCC\n/
FP / 0[|] 2 1 3 2 0 2 1 1 1\n/
FP / 0 [!] YYNYYYYYY\n/
FP /One most parsimonious tree found:\n/
FI dnacomp.treefile
FC = 1
FP /\(\(\(\(Epsilon,Delta\),Gamma\),Beta\),Alpha\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 15
FP 11 /^./
//
ID fdnacomp-ex2
AB phylipnew
AA fdnacomp
IN ../../data/evolution/dnacomp.dat
IN ../../data/evolution/dnacomptree.dat
IN
IN
FI dnacomp.fdnacomp
FC = 23
FP /^User-defined tree:\n/
FP /^total number of compatible sites is 11\.0\n/
FI dnacomp.treefile
FC = 1
FP /^\(\(\(\(Epsilon,Delta\),Gamma\),Beta\),Alpha\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 4
FP 2 /^./
//
ID fdnadist-ex
AB phylipnew
AA fdnadist
IN ../../data/evolution/dnadist.dat
IN
IN
FI dnadist.fdnadist
FC = 6
FP / 5\n/
FP /^Alpha 0\.000000 0\.303900 0\.857544 1\.158927 1\.542899\n/
FI stderr
FC = 8
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 11
FP 8 /^./
//
ID fdnainvar-ex
AB phylipnew
AA fdnainvar
CL -printdata
IN ../../data/evolution/dnainvar.dat
IN
IN
FI dnainvar.fdnainvar
FC = 120
FP /^ AAAG 2\n/
FP /^ 1113 3\n/
FP /^ III: \(\(Alpha,Delta\),\(Beta,Gamma\)\)\n/
FP /^ III 0 - 0 = 0 1\.0000 no\n/
FP /^ Quadratic invariant = 4\.0\n/
FP 3 /^ Quadratic invariant =/
FP / Tree III: 5\.0\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 5
FP 2 /^./
//
ID fdnaml-ex
AB phylipnew
AA fdnaml
CL -printdata
CL -ncategories 2 -categories "1111112222222" -rate "1.0 2.0"
CL -gammatype h
CL -nhmmcategories 5 -hmmrates "0.264 1.413 3.596 7.086 12.641"
CL -hmmprobabilities "0.522 0.399 0.076 0.0036 0.000023"
CL -lambda 1.5
CL -weight "0111111111110"
IN ../../data/evolution/dnaml.dat
IN
IN
FI dnaml.fdnaml
FC = 91
FP /^ 1 0\.264 0\.522\n/
FP /^ 2 2\.000\n/
FP /^Ln Likelihood = -57\.87892\n/
FP /^ 1 Alpha 0\.26766 \( zero, 0\.80513\) \*\n/
FP /^ 1132121111 211\n/
FI dnaml.treefile
FC = 2
FP /^\(\(\(Epsilon:0\.00006,Delta:0\.27319\):7\.59821,Beta:0\.00006\):0\.04687,\n/
FP /^Gamma:0\.95677,Alpha:0\.26766\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 53
FP 45 /^./
//
ID fdnaml-ex2
AB phylipnew
AA fdnaml
CL -printdata
CL -njumble 3 -seed 3
IN ../../data/evolution/dnaml.dat
IN
IN
FI dnaml.fdnaml
FC = 57
FP /^ A 0\.24615\n/
FP /^Ln Likelihood = -72\.25088\n/
FP /^ 1 Epsilon 0\.00006 \( zero, 0\.34299\)\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 67
FP 57 /^./
FI dnaml.treefile
FC = 2
FP /^Gamma:1\.01651,Alpha:0\.20745\);\n/
//
ID fdnamlk-ex
AB phylipnew
AA fdnamlk
CL -printdata
CL -ncategories 2 -categories "1111112222222" -rate "1.0 2.0"
CL -gammatype h
CL -nhmmcategories 5 -hmmrates "0.264 1.413 3.596 7.086 12.641"
CL -hmmprobabilities "0.522 0.399 0.076 0.0036 0.000023"
CL -lambda 1.5
CL -weight "0111111111110"
IN ../../data/evolution/dnaml.dat
IN
IN
CC likelihood value differs on Linux.
FI dnaml.fdnamlk
FC = 90
FP /^ 1 0\.264 0\.522\n/
FP /^ 2 2\.000\n/
FP /^Ln Likelihood = -57\.98242\n/
FP /^ 2 Gamma 4\.15060 0\.55971\n/
FP /^ 1132121111 211\n/
FI dnaml.treefile
FC = 2
FP /^\(\(Epsilon:0\.13456,Delta:0\.13456\):4\.01604,\(Gamma:0\.55971,\n/
FP /^\(Beta:0\.15731,Alpha:0\.15731\):0\.40240\):3\.59089\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 14
FP 9 /^./
//
ID fdnamove-ex
AB phylipnew
AA fdnamove
IN ../../data/evolution/dnamove.dat
IN
IN Q
IN Y
FI dnamove.treefile
FC = 1
FP /^\(Epsilon,\(Delta,\(Gamma,\(Beta,Alpha\)\)\)\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 20
FP 14 /^./
//
ID fdnapars-ex
AB phylipnew
AA fdnapars
IN ../../data/evolution/dnapars.dat
IN
IN
FI dnapars.fdnapars
FC = 30
FP /^requires a total of 19\.000\n/
FP /^ 3 Epsilon 0\.096154\n/
FI dnapars.treefile
FC = 2
FP /^\(\(\(Epsilon:0\.09615,Delta:0\.13462\):0\.48718,Gamma:0\.27564\):0\.21795,\n/
FP /^Beta:0\.07692,Alpha:0\.17308\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 21
FP 15 /^./
//
ID fdnapenny-ex
AB phylipnew
AA fdnapenny
IN ../../data/evolution/dnapenny.dat
IN
FI dnapenny.fdnapenny
FC = 207
FP /^ 9 trees in all found\n/
FP /^ 1 \+-----4 \+--Epsilon \n/
FI dnapenny.treefile
FC = 9
FP /^\(Alpha1,\(\(Alpha2,\(\(Epsilon,Delta\),\(Gamma2,Gamma1\)\)\),\(Beta2,Beta1\)\)\)\[0\.1111\];\n/
FP 3 /\(Gamma2,Gamma1\)/
FP 6 /\(Epsilon,Delta\),/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 18
FP 14 /^./
//
ID fdollop-ex
AB phylipnew
AA fdollop
IN ../../data/evolution/dollop.dat
IN
IN
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI dollop.fdollop
FC = 24
FP /^One most parsimonious tree found:\n/
FP 1 /^requires a total of 3\.000\n/
FI dollop.treefile
FC = 1
FP /^\(Delta,\(Epsilon,\(Gamma,\(Beta,Alpha\)\)\)\);\n/
FI stdout
FC = 19
FP 13 /^./
//
ID fdolmove-ex
AB phylipnew
AA fdolmove
IN ../../data/evolution/dolmove.dat
IN
IN Q
IN Y
FI dolmove.treefile
FC = 1
FP /^\(Epsilon,\(Delta,\(Gamma,\(Beta,Alpha\)\)\)\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 24
FP 15 /^./
//
ID fdolpenny-ex
AB phylipnew
AA fdolpenny
IN ../../data/evolution/dolpenny.dat
IN
FI dolpenny.fdolpenny
FC = 63
FP /^ 3 trees in all found\n/
FP 1 /^ \+--6 \+--5 \n/
FI dolpenny.treefile
FC = 3
FP /^\(Delta,\(Epsilon,\(Gamma1,\(Alpha2,\(\(Beta2,Beta1\),Alpha1\)\)\)\)\)\[0\.3333\];\n/
FP /^\(Delta,\(Epsilon,\(Gamma1,\(\(Beta2,Beta1\),\(Alpha2,Alpha1\)\)\)\)\)\[0\.3333\];\n/
FP /^\(Delta,\(Epsilon,\(Gamma1,\(\(\(Beta2,Beta1\),Alpha2\),Alpha1\)\)\)\)\[0\.3333\];\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 13
FP 9 /^./
//
ID fdrawgram-ex
AB phylipnew
AA fdrawgram
CL -previewer n
IN ../../data/evolution/drawgram.tree
IN
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 12
FP 8 /^./
FI drawgram.fdrawgram
FC = 76
FP /\%\!PS-Adobe-2\.0\n/
FP 5 /show\n/
//
ID fdrawtree-ex
AB phylipnew
AA fdrawtree
CL -previewer n
IN ../../data/evolution/drawgram.tree
IN
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 12
FP 8 /^./
FI drawgram.fdrawtree
FC = 67
FP /\%\!PS-Adobe-2\.0\n/
FP 5 /show\n/
//
ID ffactor-ex
AB phylipnew
AA ffactor
CC output fails to match documentation, also reports failure
IN ../../data/evolution/factor.dat
IN
FI factor.ffactor
FC = 5
FP /^ +4 +5\n/
FP /^Alpha CA00\#\n/
FP /^Beta BB01\%\n/
FP /^Gamma AB12\#\n/
FP /^Epsilon CA01\$\n/
FI factor.factor
FC = 0
FI factor.ancestor
FC = 0
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 5
FP 2 /^./
//
ID ffitch-ex
AB phylipnew
AA ffitch
IN ../../data/evolution/fitch.dat
IN
IN
FI fitch.ffitch
FC = 50
FP /^ 7 Populations\n/
FP /^Sum of squares = 0\.01375\n/
FP /^Average percent standard deviation = 1\.85418\n/
FP /^ 1 Mouse 0\.76985\n/
FP /^ 1 2 0\.41983\n/
FP /^ 2 Gibbon 0\.35537\n/
FI fitch.treefile
FC = 2
FP /^\(Mouse:0\.76985,\(\(\(\(Human:0\.11449,Chimp:0\.15471\):0\.03695,\n/
FP /^Gorilla:0\.15680\):0\.02121,Orang:0\.29209\):0\.04986,Gibbon:0\.35537\):0\.41983,Bovine:0\.91675\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 15
FP 11 /^./
//
ID ffreqboot-ex
AB phylipnew
AA ffreqboot
CL -seed 3
IN ../../data/evolution/freqboot.dat
IN
FI freqboot.ffreqboot
FC = 1700
FP 100 /^European/
FP 57 /^European 0\.28680 /
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 16
FP 12 /^./
//
ID fgendist-ex
AB phylipnew
AA fgendist
IN ../../data/evolution/gendist.dat
IN
FI gendist.fgendist
FC = 6
FP /^ 5\n/
FP /^Chinese 0\.080749 0\.234698 0\.000000 0\.053879 0\.063275\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 11
FP 8 /^./
//
ID fkitsch-ex
AB phylipnew
AA fkitsch
IN ../../data/evolution/kitsch.dat
IN
IN
FI kitsch.fkitsch
FC = 49
FP /^ 7 Populations\n/
FP /^Sum of squares = 0\.107\n/
FP /^Average percent standard deviation = 5\.16213\n/
FP /^ 6 Human 0\.13460 0\.81285\n/
FP /^ 5 6 0\.02836 0\.67825\n/
FP /^ 6 Chimp 0\.13460 0\.81285\n/
FI kitsch.treefile
FC = 3
FP /^\(\(\(\(\(\(Human:0\.13460,Chimp:0\.13460\):0\.02836,Gorilla:0\.16296\):0\.07638,\n/
FP /^Orang:0\.23933\):0\.06639,Gibbon:0\.30572\):0\.42923,Mouse:0\.73495\):0\.07790,\n/
FP /^Bovine:0\.81285\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 19
FP 14 /^./
//
ID fmix-ex
AB phylipnew
AA fmix
IN ../../data/evolution/mix.dat
IN
IN
FI mix.fmix
FC = 86
FP 4 /^requires a total of 9\.000\n/
FP /^ 4 trees in all found\n/
FP 2 /^--1 \! \+--Delta +\n/
FI mix.treefile
FC = 4
FP /^\(\(\(Epsilon,Gamma\),\(Delta,Beta\)\),Alpha\)\[0\.2500\];\n/
FP /^\(\(Gamma,\(\(Epsilon,Delta\),Beta\)\),Alpha\)\[0\.2500\];\n/
FP /^\(\(Epsilon,\(Gamma,\(Delta,Beta\)\)\),Alpha\)\[0\.2500\];\n/
FP /^\(\(Gamma,\(Epsilon,\(Delta,Beta\)\)\),Alpha\)\[0\.2500\];\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 16
FP 11 /^./
//
ID fmix-ex2
AB phylipnew
AA fmix
CL -printdata -ancfile ../../data/evolution/mixancfile.dat
IN ../../data/evolution/mix.dat
IN
IN
FI mix.fmix
FC = 46
FP /^ Ancestral states:\n/
FP /^ 001\?\? 1\n/
FP /^One most parsimonious tree found:\n/
FP /^requires a total of 8\.000\n/
FI mix.treefile
FC = 1
FP /^\(Delta,\(Epsilon,\(Gamma,\(Beta,Alpha\)\)\)\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 16
FP 11 /^./
//
ID fmove-ex
AB phylipnew
AA fmove
IN ../../data/evolution/move.dat
IN
IN Q
IN Y
FI move.treefile
FC = 1
FP /^\(Epsilon,\(Delta,\(Gamma,\(Beta,Alpha\)\)\)\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 23
FP 15 /^./
//
ID fneighbor-ex
AB phylipnew
AA fneighbor
IN ../../data/evolution/neighbor.dat
IN
FI neighbor.fneighbor
FC = 43
FP /^ 7 Populations\n/
FP /^ \! \! \+--------Gorilla \n/
FP /^ 1 Mouse 0\.76891\n/
FP /^ 1 2 0\.42027\n/
FP /^ 2 Gibbon 0\.35793\n/
FI neighbor.treefile
FC = 2
FP /^\(Mouse:0\.76891,\(Gibbon:0\.35793,\(Orang:0\.28469,\(Gorilla:0\.15393,\n/
FP /^\(Chimp:0\.15168,Human:0\.11752\):0\.03982\):0\.02696\):0\.04648\):0\.42027,Bovine:0\.91769\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 15
FP 9 /^./
//
ID fpars-ex
AB phylipnew
AA fpars
IN ../../data/evolution/pars.dat
IN
IN
FI pars.fpars
FC = 30
FP /^One most parsimonious tree found:\n/
FP /^requires a total of 8\.000\n/
FP /^ 3 Epsilon 0\.00\n/
FP /^ 3 Delta 3\.00\n/
FI pars.treefile
FC = 1
FP /^\(\(\(Epsilon:0\.00,Delta:3\.00\):2\.00,Gamma:0\.00\):1\.00,Beta:2\.00,Alpha:0\.00\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 21
FP 15 /^./
//
ID fpenny-ex
AB phylipnew
AA fpenny
IN ../../data/evolution/penny.dat
IN
FI penny.fpenny
FC = 70
FP /^ 3 trees in all found\n/
FP 3 /^ remember: this is an unrooted tree\!\n/
FP /^ \! \+-----Alpha2 \n/
FI penny.treefile
FC = 3
FP /^\(Alpha1,\(\(Alpha2,\(\(Epsilon,Delta\),Gamma1\)\),\(Beta2,Beta1\)\)\)\[0\.3333\];\n/
FP /^\(Alpha1,\(Alpha2,\(\(\(Epsilon,Delta\),Gamma1\),\(Beta2,Beta1\)\)\)\)\[0\.3333\];\n/
FP /^\(Alpha1,\(\(Alpha2,\(Beta2,Beta1\)\),\(\(Epsilon,Delta\),Gamma1\)\)\)\[0\.3333\];\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 16
FP 12 /^./
//
ID fproml-ex
AB phylipnew
AA fproml
IN ../../data/evolution/proml.dat
IN
IN
FI proml.fproml
FC = 36
FP /^Ln Likelihood = -131\.55052\n/
FP /^ 1------2 \+------------Delta \n/
FP /^ 1 +Alpha +0\.31006 +\( +zero, +0\.66806\) \*\*\n/
FI proml.treefile
FC = 2
FP /^\(Beta:0\.00010,\(\(Epsilon:0\.00010,Delta:0\.41176\):1\.00907,\n/
FP /^Gamma:0\.68569\):0\.22206,Alpha:0\.31006\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 14
FP 9 /^./
//
ID fpromlk-ex
AB phylipnew
AA fpromlk
IN ../../data/evolution/promlk.dat
IN
IN
FI promlk.fpromlk
FC = 38
FP /^Ln Likelihood = -134\.70332\n/
FP /^ root 3 \n/
FP /^ 3 4 0\.66464 0\.66464\n/
FP /^ 4 Epsilon 0.85971 0.19507\n/
FI promlk.treefile
FC = 2
FP /^\(\(Epsilon:0\.19507,Delta:0\.19507\):0\.66464,\(Gamma:0\.48551,\n/
FP /^\(Beta:0\.15763,Alpha:0\.15763\):0\.32788\):0\.37420\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 14
FP 9 /^./
//
ID fprotdist-ex
AB phylipnew
AA fprotdist
IN ../../data/evolution/protdist.dat
IN
FI protdist.fprotdist
FC = 6
FP /^Gamma 0.628142 0.377406 0.000000 0.979550 0.866781\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 12
FP 8 /^./
//
ID fprotpars-ex
AB phylipnew
AA fprotpars
IN ../../data/evolution/protpars.dat
IN
IN
FI protpars.fprotpars
FC = 61
FP /^ 3 trees in all found\n/
FP 1 /^ \! \+--Beta \n/
FP 2 /^ \! +\+-+Beta +\n/
FI protpars.treefile
FC = 3
FP /^\(\(Gamma,\(\(Epsilon,Delta\),Beta\)\),Alpha\)\[0\.3333\];\n/
FP /^\(\(\(\(Epsilon,Delta\),Gamma\),Beta\),Alpha\)\[0\.3333\];\n/
FP /^\(\(\(Epsilon,Delta\),\(Gamma,Beta\)\),Alpha\)\[0\.3333\];\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 19
FP 13 /^./
//
ID fprotpars-ex2
AB phylipnew
AA fprotpars
CL -njumble 3 -seed 3
CL -printdata
CL -ancseq
CL -whichcode m
CL -stepbox
CL -outgrno 2
CL -dothreshold -threshold 3
IN ../../data/evolution/protpars.dat
IN
IN
FI protpars.fprotpars
FC = 137
FP /^ 3 trees in all found\n/
FP 3 /^requires a total of 14\.000\n/
FI protpars.treefile
FC = 3
FP /^\(Beta,\(Gamma,\(\(Epsilon,Delta\),Alpha\)\)\)\[0\.3333\];\n/
FP /^\(Beta,\(\(\(Epsilon,Delta\),Gamma\),Alpha\)\)\[0\.3333\];\n/
FP /^\(Beta,\(\(Epsilon,Delta\),\(Gamma,Alpha\)\)\)\[0\.3333\];\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 43
FP 31 /^./
//
ID fprotpars-ex3
AB phylipnew
AA fprotpars
CL -njumble 3 -seed 3
IN ../../data/evolution/protpars2.dat
IN
IN
FI protpars2.fprotpars
FC = 435
FP /^Data set # 1:\n/
FP /^ 3 trees in all found\n/
FP 3 /^requires a total of 25\.000\n/
FP /^Data set # 2:\n/
FP /^ 15 trees in all found\n/
FP 15 /^requires a total of 14\.000\n/
FP /^Data set # 3:\n/
FP /^ 5 trees in all found\n/
FP 5 /^requires a total of 24\.000\n/
FI protpars2.treefile
FC = 23
FP /^\(\(Gamma,\(\(Epsilon,Delta\),Beta\)\),Alpha\)\[0\.3333\];\n/
FP /^\(\(\(\(Epsilon,Delta\),Gamma\),Beta\),Alpha\)\[0\.3333\];\n/
FP /^\(\(\(Epsilon,Delta\),\(Gamma,Beta\)\),Alpha\)\[0\.3333\];\n/
FP /^\(\(Gamma,\(Delta,\(Epsilon,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Epsilon,Gamma\),\(Delta,Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Gamma,\(\(Epsilon,Delta\),Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Epsilon,\(Gamma,\(Delta,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Gamma,\(Epsilon,\(Delta,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Delta,Gamma\),\(Epsilon,Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Delta,\(Epsilon,Gamma\)\),Beta\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(\(Epsilon,Delta\),Gamma\),Beta\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Epsilon,\(\(Delta,Gamma\),Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Epsilon,\(Delta,Gamma\)\),Beta\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Delta,\(Gamma,\(Epsilon,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Delta,\(\(Epsilon,Gamma\),Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Epsilon,Delta\),\(Gamma,Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Delta,\(Epsilon,\(Gamma,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Epsilon,\(Delta,\(Gamma,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Gamma,\(Delta,\(Epsilon,Beta\)\)\),Alpha\)\[0\.2000\];\n/
FP /^\(\(Gamma,\(\(Epsilon,Delta\),Beta\)\),Alpha\)\[0\.2000\];\n/
FP /^\(\(Gamma,\(Epsilon,\(Delta,Beta\)\)\),Alpha\)\[0\.2000\];\n/
FP /^\(\(\(\(Epsilon,Delta\),Gamma\),Beta\),Alpha\)\[0\.2000\];\n/
FP /^\(\(\(Epsilon,Delta\),\(Gamma,Beta\)\),Alpha\)\[0\.2000\];\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 129
FP 94 /^./
//
ID fprotpars-ex4
AB phylipnew
AA fprotpars
CL -option
IN ../../data/evolution/protpars.dat
IN
IN ../../data/evolution/protparswts.dat
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
FI protpars.fprotpars
FC = 342
FP /^Weights set # 1:\n/
FP /^ 3 trees in all found\n/
FP 3 /^requires a total of 14\.000\n/
FP /^Weights set # 2:\n/
FP /^ 15 trees in all found\n/
FP 15 /^requires a total of 2\.000\n/
FI protpars.treefile
FC = 18
FP /^\(\(Gamma,\(\(Epsilon,Delta\),Beta\)\),Alpha\)\[0\.3333\];\n/
FP /^\(\(\(\(Epsilon,Delta\),Gamma\),Beta\),Alpha\)\[0\.3333\];\n/
FP /^\(\(\(Epsilon,Delta\),\(Gamma,Beta\)\),Alpha\)\[0\.3333\];\n/
FP /^\(\(Gamma,\(Delta,\(Epsilon,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Epsilon,Gamma\),\(Delta,Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Gamma,\(\(Epsilon,Delta\),Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Epsilon,\(Gamma,\(Delta,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Gamma,\(Epsilon,\(Delta,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Delta,Gamma\),\(Epsilon,Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Delta,\(Epsilon,Gamma\)\),Beta\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(\(Epsilon,Delta\),Gamma\),Beta\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Epsilon,\(\(Delta,Gamma\),Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Epsilon,\(Delta,Gamma\)\),Beta\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Delta,\(Gamma,\(Epsilon,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Delta,\(\(Epsilon,Gamma\),Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(\(Epsilon,Delta\),\(Gamma,Beta\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Delta,\(Epsilon,\(Gamma,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FP /^\(\(Epsilon,\(Delta,\(Gamma,Beta\)\)\),Alpha\)\[0\.0667\];\n/
FI stderr
FC = 8
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 41
FP 27 /^./
//
ID frestboot-ex
AB phylipnew
AA frestboot
CL -seed 3
IN ../../data/evolution/restboot.dat
IN
FI restboot.frestboot
FC = 600
FP 100 /^Gamma/
FP 3 /^Gamma \-\+\-\-\-\+\+\+\+\+\ \+\+\+/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 16
FP 12 /^./
//
ID frestdist-ex
AB phylipnew
AA frestdist
IN ../../data/evolution/restdist.dat
IN
FI restdist.frestdist
FC = 6
## This is what we get from a fixed frestdist
## phylip-3.6b restdist has the same valgrind error
## Need to check current release to see if it is fixed
FP /^Gamma 0\.107681 0\.107681 0\.000000 0\.192466 0\.207319\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 14
FP 9 /^./
//
ID frestml-ex
AB phylipnew
AA frestml
IN ../../data/evolution/restml.dat
IN
IN
FI restml.frestml
FC = 41
FP /^Ln Likelihood = -40\.47082\n/
FP /^ 1 Gamma 0\.10794 \( 0\.01144, 0\.21872\) \*\*\n/
FI restml.treefile
FC = 2
FP /^\(Gamma:0\.10794,\(Beta:0\.00100,\(Epsilon:0\.00022,\n/
FP /^Delta:0\.01451\):0\.05878\):0\.01244,Alpha:0\.01244\);\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 15
FP 10 /^./
//
ID fretree-ex
AB phylipnew
AA fretree
CC First prompt only needed until it can read
CC the number of species from the input tree
IN 10
IN ../../data/evolution/retree.dat
IN
IN Q
IN Y
IN U
FI retree.treefile
FC = 2
FP /^\(\(\(\(\(\(\(Human,Chimp\),Gorilla\),Orang\),Gibbon\),\(Barbary_Ma,\(Crab-e\._Ma,\n/
FP /^\(Rhesus_Mac,Jpn_Macaq\)\)\)\),Squir\._Mon\),\(\(Tarsier,Lemur\),Bovine\),Mouse\);\n/
FI stderr
FC = 4
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 27
FP 23 /^./
//
ID fseqboot-ex
AB phylipnew
AA fseqboot
CL -seed 3
IN ../../data/evolution/seqboot.dat
IN
FI seqboot.fseqboot
FC = 600
FP 7 /^Alpha AAAAAA\n/
FP 14 /^Beta AAACCC\n/
FP 21 /^\S+ +AAACCC\n/
FP 100 /^Alpha/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 16
FP 12 /^./
//
ID fseqbootall-ex
AB phylipnew
AA fseqbootall
CL -seed 3
IN ../../data/evolution/seqboot.dat
IN
FI seqboot.fseqbootall
FC = 600
FP 7 /^Alpha AAAAAA\n/
FP 14 /^Beta AAACCC\n/
FP 21 /^\S+ +AAACCC\n/
FP 100 /^Alpha/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 23
FP 18 /^./
//
ID ftreedist-ex
AB phylipnew
AA ftreedist
IN ../../data/evolution/treedist.dat
IN
FI treedist.ftreedist
FC = 11
FP /Trees 3 and 4: 3\.162278e\-01/
FP 6 /Trees \d+ and \d+:\s+\d+/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 5
FP 2 /^./
//
ID ftreedist-ex2
AB phylipnew
AA ftreedist
CL -dtype s
IN ../../data/evolution/treedist2.dat
IN
FI treedist2.ftreedist
FC = 11
FP /Trees 1 and 2: 4/
FP 6 /Trees \d+ and \d+:\s+\d+/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 5
FP 2 /^./
//
ID ftreedist-sparse
AB phylipnew
AA ftreedist
CL -style s
IN ../../data/evolution/treedist.dat
IN
IN
FI treedist.ftreedist
FC = 6
FP /3 4 3\.162278e\-01/
FP 6 /\d+\s+\d+\s+\d+/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 5
FP 2 /^./
//
ID ftreedist-listall
AB phylipnew
AA ftreedist
CL -dtype s
IN ../../data/evolution/treedist.dat
IN
FI treedist.ftreedist
FC = 11
FP /Trees 11 and 12: 10\n/
FP 6 /Trees \d+ and \d+:\s+\d+/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 5
FP 2 /^./
//
ID ftreedistpair-ex
AB phylipnew
AA ftreedistpair
CL -style s
IN ../../data/evolution/treedist.dat
IN ../../data/evolution/treedist.dat
IN
FI treedist.ftreedistpair
FC = 288
FP /^1 14 2\.000000e-01\n/
FP /^2 13 2\.000000e-01\n/
FI stderr
FC = 2
FP 0 /Warning: /
FP 0 /Error: /
FP 0 /Died: /
FI stdout
FC = 2
FP 1 /^./
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# any later version.
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License
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You might have modified some files without having the
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You can get '$1' as part of Autoconf from any GNU
archive site."
file=`echo "$*" | sed -n "$sed_output"`
test -z "$file" && file=`echo "$*" | sed -n "$sed_minuso"`
if test -f "$file"; then
touch $file
else
test -z "$file" || exec >$file
echo "#! /bin/sh"
echo "# Created by GNU Automake missing as a replacement of"
echo "# $ $@"
echo "exit 0"
chmod +x $file
exit 1
fi
;;
bison*|yacc*)
echo 1>&2 "\
WARNING: '$1' $msg. You should only need it if
you modified a '.y' file. You may need the Bison package
in order for those modifications to take effect. You can get
Bison from any GNU archive site."
rm -f y.tab.c y.tab.h
if test $# -ne 1; then
eval LASTARG=\${$#}
case $LASTARG in
*.y)
SRCFILE=`echo "$LASTARG" | sed 's/y$/c/'`
if test -f "$SRCFILE"; then
cp "$SRCFILE" y.tab.c
fi
SRCFILE=`echo "$LASTARG" | sed 's/y$/h/'`
if test -f "$SRCFILE"; then
cp "$SRCFILE" y.tab.h
fi
;;
esac
fi
if test ! -f y.tab.h; then
echo >y.tab.h
fi
if test ! -f y.tab.c; then
echo 'main() { return 0; }' >y.tab.c
fi
;;
lex*|flex*)
echo 1>&2 "\
WARNING: '$1' is $msg. You should only need it if
you modified a '.l' file. You may need the Flex package
in order for those modifications to take effect. You can get
Flex from any GNU archive site."
rm -f lex.yy.c
if test $# -ne 1; then
eval LASTARG=\${$#}
case $LASTARG in
*.l)
SRCFILE=`echo "$LASTARG" | sed 's/l$/c/'`
if test -f "$SRCFILE"; then
cp "$SRCFILE" lex.yy.c
fi
;;
esac
fi
if test ! -f lex.yy.c; then
echo 'main() { return 0; }' >lex.yy.c
fi
;;
help2man*)
echo 1>&2 "\
WARNING: '$1' is $msg. You should only need it if
you modified a dependency of a manual page. You may need the
Help2man package in order for those modifications to take
effect. You can get Help2man from any GNU archive site."
file=`echo "$*" | sed -n "$sed_output"`
test -z "$file" && file=`echo "$*" | sed -n "$sed_minuso"`
if test -f "$file"; then
touch $file
else
test -z "$file" || exec >$file
echo ".ab help2man is required to generate this page"
exit $?
fi
;;
makeinfo*)
echo 1>&2 "\
WARNING: '$1' is $msg. You should only need it if
you modified a '.texi' or '.texinfo' file, or any other file
indirectly affecting the aspect of the manual. The spurious
call might also be the consequence of using a buggy 'make' (AIX,
DU, IRIX). You might want to install the Texinfo package or
the GNU make package. Grab either from any GNU archive site."
# The file to touch is that specified with -o ...
file=`echo "$*" | sed -n "$sed_output"`
test -z "$file" && file=`echo "$*" | sed -n "$sed_minuso"`
if test -z "$file"; then
# ... or it is the one specified with @setfilename ...
infile=`echo "$*" | sed 's/.* \([^ ]*\) *$/\1/'`
file=`sed -n '
/^@setfilename/{
s/.* \([^ ]*\) *$/\1/
p
q
}' $infile`
# ... or it is derived from the source name (dir/f.texi becomes f.info)
test -z "$file" && file=`echo "$infile" | sed 's,.*/,,;s,.[^.]*$,,'`.info
fi
# If the file does not exist, the user really needs makeinfo;
# let's fail without touching anything.
test -f $file || exit 1
touch $file
;;
*)
echo 1>&2 "\
WARNING: '$1' is needed, and is $msg.
You might have modified some files without having the
proper tools for further handling them. Check the 'README' file,
it often tells you about the needed prerequisites for installing
this package. You may also peek at any GNU archive site, in case
some other package would contain this missing '$1' program."
exit 1
;;
esac
exit 0
# Local variables:
# eval: (add-hook 'write-file-hooks 'time-stamp)
# time-stamp-start: "scriptversion="
# time-stamp-format: "%:y-%02m-%02d.%02H"
# time-stamp-time-zone: "UTC"
# time-stamp-end: "; # UTC"
# End:
PHYLIPNEW-3.69.650/Makefile.am 0000664 0001750 0001750 00000001271 11614226107 012323 0000000 0000000 #
ACLOCAL_AMFLAGS = -I m4
SUBDIRS = src emboss_acd data emboss_doc
EXTRA_DIST = depcomp ltmain.sh install-sh config.sub config.guess
# tar to pick up the other directories
# then remove any CVS subdirectories
dist-hook:
tar cBf - emboss_acd | ( cd $(distdir); tar xBf - ; cd emboss_acd; rm -rf CVS )
tar cBf - emboss_doc | ( cd $(distdir); tar xBf - ; cd emboss_doc; rm -rf CVS; rm -rf master)
tar cBf - doc | ( cd $(distdir); tar xBf - ; cd doc; rm -rf CVS )
tar cBf - include | ( cd $(distdir); tar xBf - ; cd include; rm -rf CVS )
tar cBf - data | ( cd $(distdir); tar xBf - ; cd data; rm -rf CVS )
tar cBf - test | ( cd $(distdir); tar xBf - ; cd test; rm -rf CVS)
PHYLIPNEW-3.69.650/emboss_doc/ 0002775 0001750 0001750 00000000000 12171071712 012464 5 0000000 0000000 PHYLIPNEW-3.69.650/emboss_doc/text/ 0002775 0001750 0001750 00000000000 12171071711 013447 5 0000000 0000000 PHYLIPNEW-3.69.650/emboss_doc/text/fdiscboot.txt 0000664 0001750 0001750 00000047575 12171064331 016124 0000000 0000000 fdiscboot
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped discrete sites algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of the
package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
SEQBOOT is a general bootstrapping and data set translation tool. It is
intended to allow you to generate multiple data sets that are resampled
versions of the input data set. Since almost all programs in the
package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or permuted.
SEQBOOT can handle molecular sequences, binary characters, restriction
sites, or gene frequencies. It can also convert data sets between
Sequential and Interleaved format, and into the NEXUS format or into a
new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of interest.
For example, if you were using DNAPARS you would first run SEQBOOT and
make a file with 100 bootstrapped data sets. Then you would give this
file the proper name to have it be the input file for DNAPARS. Running
DNAPARS with the M (Multiple Data Sets) menu choice and informing it to
expect 100 data sets, you would generate a big output file as well as a
treefile with the trees from the 100 data sets. This treefile could be
renamed so that it would serve as the input for CONSENSE. When CONSENSE
is run the majority rule consensus tree will result, showing the
outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this package.
The same steps are necessary with all of them. Doing things this way
some of the intermediate files (the tree file from the DNAPARS run, for
example) can be used to summarize the results of the bootstrap in other
ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add one
extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
* The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me
(Felsenstein, 1985b; see also Penny and Hendy, 1985). It involves
creating a new data set by sampling N characters randomly with
replacement, so that the resulting data set has the same size as
the original, but some characters have been left out and others are
duplicated. The random variation of the results from analyzing
these bootstrapped data sets can be shown statistically to be
typical of the variation that you would get from collecting new
data sets. The method assumes that the characters evolve
independently, an assumption that may not be realistic for many
kinds of data.
* The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial
Bootstrap method, and Shimodaira's (2002) AU method, both of which
correct the bias of bootstrap P values.
* Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct
for it by samopling, not individual characters, but blocks of
adjacent characters. This is called a block bootstrap and was
introduced by Kuensch (1989). If the correlations are believed to
extend over some number of characters, you choose a block size, B,
that is larger than this, and choose N/B blocks of size B. In its
implementation here the block bootstrap "wraps around" at the end
of the characters (so that if a block starts in the last B-1
characters, it continues by wrapping around to the first character
after it reaches the last character). Note also that if you have a
DNA sequence data set of an exon of a coding region, you can ensure
that equal numbers of first, second, and third coding positions are
sampled by using the block bootstrap with B = 3.
* Partial block-bootstrapping. Similar to partial bootstrapping
except sampling blocks rather than single characters.
* Delete-half-jackknifing.. This alternative to the bootstrap
involves sampling a random half of the characters, and including
them in the data but dropping the others. The resulting data sets
are half the size of the original, and no characters are
duplicated. The random variation from doing this should be very
similar to that obtained from the bootstrap. The method is
advocated by Wu (1986). It was mentioned by me in my bootstrapping
paper (Felsenstein, 1985b), and has been available for many years
in this program as an option. Note that, for the present,
block-jackknifing is not available, because I cannot figure out how
to do it straightforwardly when the block size is not a divisor of
the number of characters.
* Delete-fraction jackknifing. Jackknifing is advocated by Farris et.
al. (1996) but as deleting a fraction 1/e (1/2.71828). This retains
too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it
is made available here as an option, with the user asked to supply
the fraction of characters that are to be retained.
* Permuting species within characters. This method of resampling
(well, OK, it may not be best to call it resampling) was introduced
by Archie (1989) and Faith (1990; see also Faith and Cranston,
1991). It involves permuting the columns of the data matrix
separately. This produces data matrices that have the same number
and kinds of characters but no taxonomic structure. It is used for
different purposes than the bootstrap, as it tests not the
variation around an estimated tree but the hypothesis that there is
no taxonomic structure in the data: if a statistic such as number
of steps is significantly smaller in the actual data than it is in
replicates that are permuted, then we can argue that there is some
taxonomic structure in the data (though perhaps it might be just
the presence of aa pair of sibling species).
* Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For
many methods of tree inference this will make no difference to the
outcome (unless one has rates of evolution correlated among
adjacent sites). It is included as a possible step in carrying out
a permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
* Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so
as to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
* Rewriting. This is not a resampling or permutation method: it
simply rewrites the data set into a different format. That format
can be the PHYLIP format. For molecular sequences and discrete
morphological character it can also be the NEXUS format. For
molecular sequences one other format is available, a new (and
nonstandard) XML format of our own devising. When the PHYLIP format
is chosen the data set is coverted between Interleaved and
Sequential format. If it was read in as Interleaved sequences, it
will be written out as Sequential format, and vice versa. The NEXUS
format for molecular sequences is always written as interleaved
sequences. The XML format is different from (though similar to) a
number of other XML sequence alignment formats. An example will be
found below. Here is a table to links to those other XML alignment
formats:
Andrew Rambaut's BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html and
http://evolve.zoo.ox.ac.uk/beast/referenindex.html A format for
alignments. There is also a format for phylogenies described there.
MSAML M http://xml.coverpages.org/msaml-desc-dec.html Defined by Paul
Gordon of University of Calgary. See his big list of molecular biology
XML projects.
BSML http://www.bsml.org/resources/default.asp Bioinformatic Sequence
Markup Language includes a multiple sequence alignment XML format
Usage
Here is a sample session with fdiscboot
% fdiscboot -seed 3
Bootstrapped discrete sites algorithm
Input file: discboot.dat
Phylip seqboot_disc program output file [discboot.fdiscboot]:
Phylip ancestor data output file (optional) [discboot.ancfile]:
Phylip mix data output file (optional) [discboot.mixfile]:
Phylip factor data output file (optional) [discboot.factfile]:
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "discboot.fdiscboot"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Bootstrapped discrete sites algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates (no help text) discretestates value
[-outfile] outfile [*.fdiscboot] Phylip seqboot_disc program
output file
[-outancfile] outfile [*.fdiscboot] Phylip ancestor data output
file (optional)
[-outmixfile] outfile [*.fdiscboot] Phylip mix data output file
(optional)
[-outfactfile] outfile [*.fdiscboot] Phylip factor data output file
(optional)
Additional (Optional) qualifiers (* if not always prompted):
-mixfile properties File of mixtures
-ancfile properties File of ancestors
-weights properties Weights file
-factorfile properties Factors file
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -morphseqtype menu [p] Output format (Values: p (PHYLIP); n
(NEXUS))
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outancfile" associated qualifiers
-odirectory3 string Output directory
"-outmixfile" associated qualifiers
-odirectory4 string Output directory
"-outfactfile" associated qualifiers
-odirectory5 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdiscboot reads discrete character data
Input files for usage example
File: discboot.dat
5 6
Alpha 110110
Beta 110000
Gamma 100110
Delta 001001
Epsilon 001110
Output file format
fdiscboot writes a bootstrap multiple set of discrete character data
Output files for usage example
File: discboot.ancfile
File: discboot.factfile
File: discboot.mixfile
File: discboot.fdiscboot
5 6
Alpha 111001
Beta 111000
Gamma 100001
Delta 000110
Epsilon 000111
5 6
Alpha 111011
Beta 111000
Gamma 100011
Delta 000100
Epsilon 000111
5 6
Alpha 111110
Beta 111000
Gamma 110110
Delta 000001
Epsilon 000110
5 6
Alpha 000001
Beta 000000
Gamma 000001
Delta 111110
Epsilon 111111
5 6
Alpha 111100
Beta 111000
Gamma 110100
Delta 000011
Epsilon 000100
5 6
Alpha 111100
Beta 100000
Gamma 111100
Delta 000011
Epsilon 011100
5 6
Alpha 110011
Beta 110000
Gamma 100011
Delta 001100
Epsilon 001111
5 6
Alpha 111100
Beta 100000
Gamma 111100
Delta 000011
Epsilon 011100
5 6
Alpha 110100
[Part of this file has been deleted for brevity]
Gamma 101111
Delta 000000
Epsilon 001111
5 6
Alpha 110110
Beta 110000
Gamma 110110
Delta 001001
Epsilon 001110
5 6
Alpha 110111
Beta 110000
Gamma 000111
Delta 001000
Epsilon 001111
5 6
Alpha 101111
Beta 100000
Gamma 001111
Delta 010000
Epsilon 011111
5 6
Alpha 011111
Beta 000000
Gamma 011111
Delta 100000
Epsilon 111111
5 6
Alpha 011000
Beta 000000
Gamma 011000
Delta 100111
Epsilon 111000
5 6
Alpha 101100
Beta 100000
Gamma 101100
Delta 010011
Epsilon 011100
5 6
Alpha 111111
Beta 111110
Gamma 100001
Delta 000000
Epsilon 000001
5 6
Alpha 110110
Beta 110000
Gamma 000110
Delta 001001
Epsilon 001110
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/CVS/ 0002775 0001750 0001750 00000000000 12171064331 014102 5 0000000 0000000 PHYLIPNEW-3.69.650/emboss_doc/text/CVS/Entries 0000664 0001750 0001750 00000003610 12171064331 015354 0000000 0000000 /.cvsignore/1.1/Thu Jan 21 17:05:10 2010/-kk/
/Makefile.am/1.2/Mon Jan 26 14:45:07 2009//
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/ftreedist.txt/1.24/Mon Jul 15 21:25:45 2013//
/ftreedistpair.txt/1.24/Mon Jul 15 21:25:45 2013//
D
PHYLIPNEW-3.69.650/emboss_doc/text/CVS/Root 0000664 0001750 0001750 00000000056 12000651530 014661 0000000 0000000 rice@dev.open-bio.org:/home/repository/emboss
PHYLIPNEW-3.69.650/emboss_doc/text/CVS/Repository 0000664 0001750 0001750 00000000060 12000651530 016110 0000000 0000000 emboss/emboss/embassy/phylipnew/emboss_doc/text
PHYLIPNEW-3.69.650/emboss_doc/text/fproml.txt 0000664 0001750 0001750 00000067240 12171064331 015436 0000000 0000000 fproml
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Protein phylogeny by maximum likelihood
Description
Estimates phylogenies from protein amino acid sequences by maximum
likelihood. The PAM, JTT, or PMB models can be employed, and also use
of a Hidden Markov model of rates, with the program inferring which
sites have which rates. This also allows gamma-distribution and
gamma-plus-invariant sites distributions of rates across sites. It also
allows different rates of change at known sites.
Algorithm
This program implements the maximum likelihood method for protein amino
acid sequences. It uses the either the Jones-Taylor-Thornton or the
Dayhoff probability model of change between amino acids. The
assumptions of these present models are:
1. Each position in the sequence evolves independently.
2. Different lineages evolve independently.
3. Each position undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of
occurrence) which we specify.
4. All relevant positions are included in the sequence, not just those
that have changed or those that are "phylogenetically informative".
5. The probabilities of change between amino acids are given by the
model of Jones, Taylor, and Thornton (1992), the PMB model of
Veerassamy, Smith and Tillier (2004), or the PAM model of Dayhoff
(Dayhoff and Eck, 1968; Dayhoff et. al., 1979).
Note the assumption that we are looking at all positions, including
those that have not changed at all. It is important not to restrict
attention to some positions based on whether or not they have changed;
doing that would bias branch lengths by making them too long, and that
in turn would cause the method to misinterpret the meaning of those
positions that had changed.
This program uses a Hidden Markov Model (HMM) method of inferring
different rates of evolution at different amino acid positions. This
was described in a paper by me and Gary Churchill (1996). It allows us
to specify to the program that there will be a number of different
possible evolutionary rates, what the prior probabilities of occurrence
of each is, and what the average length of a patch of positions all
having the same rate. The rates can also be chosen by the program to
approximate a Gamma distribution of rates, or a Gamma distribution plus
a class of invariant positions. The program computes the the likelihood
by summing it over all possible assignments of rates to positions,
weighting each by its prior probability of occurrence.
For example, if we have used the C and A options (described below) to
specify that there are three possible rates of evolution, 1.0, 2.4, and
0.0, that the prior probabilities of a position having these rates are
0.4, 0.3, and 0.3, and that the average patch length (number of
consecutive positions with the same rate) is 2.0, the program will sum
the likelihood over all possibilities, but giving less weight to those
that (say) assign all positions to rate 2.4, or that fail to have
consecutive positions that have the same rate.
The Hidden Markov Model framework for rate variation among positions
was independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of rates; we
allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant positions.
This feature effectively removes the artificial assumption that all
positions have the same rate, and also means that we need not know in
advance the identities of the positions that have a particular rate of
evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each positions (for example, we might want amino
acid positions in the active site of a protein to change more slowly
than other positions. This is done with the categories input file and
the C option. We then specify (using the menu) the relative rates of
evolution of amino acid positions in the different categories. For
example, we might specify that positions in the active site evolve at
relative rates of 0.2 compared to 1.0 at other positions. If we are
assuming that a particular position maintains a cysteine bridge to
another, we may want to put it in a category of positions (including
perhaps the initial position of the protein sequence which maintains
methionine) which changes at a rate of 0.0.
If both user-assigned rate categories and Hidden Markov Model rates are
allowed, the program assumes that the actual rate at a position is the
product of the user-assigned category rate and the Hidden Markov Model
regional rate. (This may not always make perfect biological sense: it
would be more natural to assume some upper bound to the rate, as we
have discussed in the Felsenstein and Churchill paper). Nevertheless
you may want to use both types of rate variation.
Usage
Here is a sample session with fproml
% fproml
Protein phylogeny by maximum likelihood
Input (aligned) protein sequence set(s): proml.dat
Phylip tree file (optional):
Phylip proml program output file [proml.fproml]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "proml.fproml"
Tree also written onto file "proml.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Protein phylogeny by maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fproml] Phylip proml program output file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
* -lengths boolean [N] Use branch lengths from user trees
-model menu [Jones-Taylor-Thornton] Probability model
for amino acid change (Values: j
(Jones-Taylor-Thornton); h (Henikoff/Tillier
PMBs); d (Dayhoff PAM))
-gammatype menu [Constant rate] Rate variation among sites
(Values: g (Gamma distributed rates); i
(Gamma+invariant sites); h (User defined HMM
of rates); n (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ngammacat integer [1] Number of categories (1-9) (Integer from
1 to 9)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ninvarcat integer [1] Number of categories (1-9) including one
for invariant sites (Integer from 1 to 9)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -nhmmcategories integer [1] Number of HMM rate categories (Integer
from 1 to 9)
* -hmmrates array [1.0] HMM category rates
* -hmmprobabilities array [1.0] Probability for each HMM category
* -adjsite boolean [N] Rates at adjacent sites correlated
* -lambda float [1.0] Mean block length of sites having the
same rate (Number 1.000 or more)
* -njumble integer [0] Number of times to randomise, choose 0
if you don't want to randomise (Integer 0 or
more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]rough boolean [Y] Speedier but rougher analysis
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fproml] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-hypstate boolean [N] Reconstruct hypothetical sequence
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fproml reads any normal sequence USAs.
Input files for usage example
File: proml.dat
5 13
Alpha AACGTGGCCAAAT
Beta AAGGTCGCCAAAC
Gamma CATTTCGTCACAA
Delta GGTATTTCGGCCT
Epsilon GGGATCTCGGCCC
Output file format
fproml output starts by giving the number of species and the number of
amino acid positions.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of positions is printed, as well
as the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the menu
option to print them, with the sequences printed in groups of ten amino
acids. The trees found are printed as an unrooted tree topology
(possibly rooted by outgroup if so requested). The internal nodes are
numbered arbitrarily for the sake of identification. The number of
trees evaluated so far and the log likelihood of the tree are also
given. Note that the trees printed out have a trifurcation at the base.
The branch lengths in the diagram are roughly proportional to the
estimated branch lengths, except that very short branches are printed
out at least three characters in length so that the connections can be
seen. The unit of branch length is the expected fraction of amino acids
changed (so that 1.0 is 100 PAMs).
A table is printed showing the length of each tree segment (in units of
expected amino acid substitutions per position), as well as (very)
rough confidence limits on their lengths. If a confidence limit is
negative, this indicates that rearrangement of the tree in that region
is not excluded, while if both limits are positive, rearrangement is
still not necessarily excluded because the variance calculation on
which the confidence limits are based results in an underestimate,
which makes the confidence limits too narrow.
In addition to the confidence limits, the program performs a crude
Likelihood Ratio Test (LRT) for each branch of the tree. The program
computes the ratio of likelihoods with and without this branch length
forced to zero length. This done by comparing the likelihoods changing
only that branch length. A truly correct LRT would force that branch
length to zero and also allow the other branch lengths to adjust to
that. The result would be a likelihood ratio closer to 1. Therefore the
present LRT will err on the side of being too significant. YOU ARE
WARNED AGAINST TAKING IT TOO SERIOUSLY. If you want to get a better
likelihood curve for a branch length you can do multiple runs with
different prespecified lengths for that branch, as discussed above in
the discussion of the L option.
One should also realize that if you are looking not at a
previously-chosen branch but at all branches, that you are seeing the
results of multiple tests. With 20 tests, one is expected to reach
significance at the P = .05 level purely by chance. You should
therefore use a much more conservative significance level, such as .05
divided by the number of tests. The significance of these tests is
shown by printing asterisks next to the confidence interval on each
branch length. It is important to keep in mind that both the confidence
limits and the tests are very rough and approximate, and probably
indicate more significance than they should. Nevertheless, maximum
likelihood is one of the few methods that can give you any indication
of its own error; most other methods simply fail to warn the user that
there is any error! (In fact, whole philosophical schools of
taxonomists exist whose main point seems to be that there isn't any
error, that the "most parsimonious" tree is the best tree by definition
and that's that).
The log likelihood printed out with the final tree can be used to
perform various likelihood ratio tests. One can, for example, compare
runs with different values of the relative rate of change in the active
site and in the rest of the protein to determine which value is the
maximum likelihood estimate, and what is the allowable range of values
(using a likelihood ratio test, which you will find described in
mathematical statistics books). One could also estimate the base
frequencies in the same way. Both of these, particularly the latter,
require multiple runs of the program to evaluate different possible
values, and this might get expensive.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the rates
at different amino acid positions, the program also performs a
statistical test of each of these trees against the one with highest
likelihood. If there are two user trees, the test done is one which is
due to Kishino and Hasegawa (1989), a version of a test originally
introduced by Templeton (1983). In this implementation it uses the mean
and variance of log-likelihood differences between trees, taken across
amino acid positions. If the two trees' means are more than 1.96
standard deviations different then the trees are declared significantly
different. This use of the empirical variance of log-likelihood
differences is more robust and nonparametric than the classical
likelihood ratio test, and may to some extent compensate for the any
lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. In the version used here
the variances and covariances of the sum of log likelihoods across
amino acid positions are computed for all pairs of trees. To test
whether the difference between each tree and the best one is larger
than could have been expected if they all had the same expected
log-likelihood, log-likelihoods for all trees are sampled with these
covariances and equal means (Shimodaira and Hasegawa's "least favorable
hypothesis"), and a P value is computed from the fraction of times the
difference between the tree's value and the highest log-likelihood
exceeds that actually observed. Note that this sampling needs random
numbers, and so the program will prompt the user for a random number
seed if one has not already been supplied. With the two-tree KHT test
no random numbers are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one. However the
test is not available if we assume that there is autocorrelation of
rates at neighboring positions (option A) and is not done in those
cases.
The branch lengths printed out are scaled in terms of 100 times the
expected numbers of amino acid substitutions, scaled so that the
average rate of change, averaged over all the positions analyzed, is
set to 100.0, if there are multiple categories of positions. This means
that whether or not there are multiple categories of positions, the
expected percentage of change for very small branches is equal to the
branch length. Of course, when a branch is twice as long this does not
mean that there will be twice as much net change expected along it,
since some of the changes occur in the same position and overlie or
even reverse each other. underlying numbers of changes. That means that
a branch of length 26 is 26 times as long as one which would show a 1%
difference between the amino acid sequences at the beginning and end of
the branch, but we would not expect the sequences at the beginning and
end of the branch to be 26% different, as there would be some
overlaying of changes.
Confidence limits on the branch lengths are also given. Of course a
negative value of the branch length is meaningless, and a confidence
limit overlapping zero simply means that the branch length is not
necessarily significantly different from zero. Because of limitations
of the numerical algorithm, branch length estimates of zero will often
print out as small numbers such as 0.00001. If you see a branch length
that small, it is really estimated to be of zero length.
Another possible source of confusion is the existence of negative
values for the log likelihood. This is not really a problem; the log
likelihood is not a probability but the logarithm of a probability.
When it is negative it simply means that the corresponding probability
is less than one (since we are seeing its logarithm). The log
likelihood is maximized by being made more positive: -30.23 is worse
than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what amino acid position
categories contributed the most to the final likelihood. This
combination of HMM rate categories need not have contributed a majority
of the likelihood, just a plurality. Still, it will be helpful as a
view of where the program infers that the higher and lower rates are.
Note that the use in this calculations of the prior probabilities of
different rates, and the average patch length, gives this inference a
"smoothed" appearance: some other combination of rates might make a
greater contribution to the likelihood, but be discounted because it
conflicts with this prior information. See the example output below to
see what this printout of rate categories looks like. A second list
will also be printed out, showing for each position which rate
accounted for the highest fraction of the likelihood. If the fraction
of the likelihood accounted for is less than 95%, a dot is printed
instead.
Option 3 in the menu controls whether the tree is printed out into the
output file. This is on by default, and usually you will want to leave
it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees which
are written onto the output tree file, rather than the trees printed on
the output file. To keep the output file from becoming too large, it
may be wisest to use option 3 to prevent trees being printed onto the
output file.
Option 4 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined trees
are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated at
each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species
which are the input sequences). The symbol printed out is for the amino
acid which accounts for the largest fraction of the likelihood at that
position. In that table, if a position has an amino acid which accounts
for more than 95% of the likelihood, its symbol printed in capital
letters (W rather than w). One limitation of the current version of the
program is that when there are multiple HMM rates (option R) the
reconstructed amino acids are based on only the single assignment of
rates to positions which accounts for the largest amount of the
likelihood. Thus the assessment of 95% of the likelihood, in tabulating
the ancestral states, refers to 95% of the likelihood that is accounted
for by that particular combination of rates.
Output files for usage example
File: proml.fproml
Amino acid sequence Maximum Likelihood method, version 3.69.650
Jones-Taylor-Thornton model of amino acid change
+Beta
|
| +Epsilon
| +------------------------------3
1------2 +------------Delta
| |
| +--------------------Gamma
|
+---------Alpha
remember: this is an unrooted tree!
Ln Likelihood = -131.55052
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
1 Alpha 0.31006 ( zero, 0.66806) **
1 Beta 0.00010 ( zero, infinity)
1 2 0.22206 ( zero, 0.62979) *
2 3 1.00907 ( 0.13965, 1.87849) **
3 Epsilon 0.00010 ( zero, infinity)
3 Delta 0.41176 ( zero, 0.86685) **
2 Gamma 0.68569 ( 0.01628, 1.35510) **
* = significantly positive, P < 0.05
** = significantly positive, P < 0.01
File: proml.treefile
(Beta:0.00010,((Epsilon:0.00010,Delta:0.41176):1.00907,
Gamma:0.68569):0.22206,Alpha:0.31006);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/frestboot.txt 0000664 0001750 0001750 00000055075 12171064331 016151 0000000 0000000 frestboot
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped restriction sites algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of the
package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
FRESTBOOT is a restriction site specific version of SEQBOOT.
SEQBOOT is a general bootstrapping and data set translation tool. It is
intended to allow you to generate multiple data sets that are resampled
versions of the input data set. Since almost all programs in the
package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or permuted.
SEQBOOT can handle molecular sequences, binary characters, restriction
sites, or gene frequencies. It can also convert data sets between
Sequential and Interleaved format, and into the NEXUS format or into a
new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of interest.
For example, if you were using DNAPARS you would first run SEQBOOT and
make a file with 100 bootstrapped data sets. Then you would give this
file the proper name to have it be the input file for DNAPARS. Running
DNAPARS with the M (Multiple Data Sets) menu choice and informing it to
expect 100 data sets, you would generate a big output file as well as a
treefile with the trees from the 100 data sets. This treefile could be
renamed so that it would serve as the input for CONSENSE. When CONSENSE
is run the majority rule consensus tree will result, showing the
outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this package.
The same steps are necessary with all of them. Doing things this way
some of the intermediate files (the tree file from the DNAPARS run, for
example) can be used to summarize the results of the bootstrap in other
ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add one
extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
* The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me
(Felsenstein, 1985b; see also Penny and Hendy, 1985). It involves
creating a new data set by sampling N characters randomly with
replacement, so that the resulting data set has the same size as
the original, but some characters have been left out and others are
duplicated. The random variation of the results from analyzing
these bootstrapped data sets can be shown statistically to be
typical of the variation that you would get from collecting new
data sets. The method assumes that the characters evolve
independently, an assumption that may not be realistic for many
kinds of data.
* The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial
Bootstrap method, and Shimodaira's (2002) AU method, both of which
correct the bias of bootstrap P values.
* Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct
for it by samopling, not individual characters, but blocks of
adjacent characters. This is called a block bootstrap and was
introduced by Kuensch (1989). If the correlations are believed to
extend over some number of characters, you choose a block size, B,
that is larger than this, and choose N/B blocks of size B. In its
implementation here the block bootstrap "wraps around" at the end
of the characters (so that if a block starts in the last B-1
characters, it continues by wrapping around to the first character
after it reaches the last character). Note also that if you have a
DNA sequence data set of an exon of a coding region, you can ensure
that equal numbers of first, second, and third coding positions are
sampled by using the block bootstrap with B = 3.
* Partial block-bootstrapping. Similar to partial bootstrapping
except sampling blocks rather than single characters.
* Delete-half-jackknifing.. This alternative to the bootstrap
involves sampling a random half of the characters, and including
them in the data but dropping the others. The resulting data sets
are half the size of the original, and no characters are
duplicated. The random variation from doing this should be very
similar to that obtained from the bootstrap. The method is
advocated by Wu (1986). It was mentioned by me in my bootstrapping
paper (Felsenstein, 1985b), and has been available for many years
in this program as an option. Note that, for the present,
block-jackknifing is not available, because I cannot figure out how
to do it straightforwardly when the block size is not a divisor of
the number of characters.
* Delete-fraction jackknifing. Jackknifing is advocated by Farris et.
al. (1996) but as deleting a fraction 1/e (1/2.71828). This retains
too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it
is made available here as an option, with the user asked to supply
the fraction of characters that are to be retained.
* Permuting species within characters. This method of resampling
(well, OK, it may not be best to call it resampling) was introduced
by Archie (1989) and Faith (1990; see also Faith and Cranston,
1991). It involves permuting the columns of the data matrix
separately. This produces data matrices that have the same number
and kinds of characters but no taxonomic structure. It is used for
different purposes than the bootstrap, as it tests not the
variation around an estimated tree but the hypothesis that there is
no taxonomic structure in the data: if a statistic such as number
of steps is significantly smaller in the actual data than it is in
replicates that are permuted, then we can argue that there is some
taxonomic structure in the data (though perhaps it might be just
the presence of aa pair of sibling species).
* Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For
many methods of tree inference this will make no difference to the
outcome (unless one has rates of evolution correlated among
adjacent sites). It is included as a possible step in carrying out
a permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
* Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so
as to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
* Rewriting. This is not a resampling or permutation method: it
simply rewrites the data set into a different format. That format
can be the PHYLIP format. For molecular sequences and discrete
morphological character it can also be the NEXUS format. For
molecular sequences one other format is available, a new (and
nonstandard) XML format of our own devising. When the PHYLIP format
is chosen the data set is coverted between Interleaved and
Sequential format. If it was read in as Interleaved sequences, it
will be written out as Sequential format, and vice versa. The NEXUS
format for molecular sequences is always written as interleaved
sequences. The XML format is different from (though similar to) a
number of other XML sequence alignment formats. An example will be
found below. Here is a table to links to those other XML alignment
formats:
Andrew Rambaut's BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html and
http://evolve.zoo.ox.ac.uk/beast/referenindex.html A format for
alignments. There is also a format for phylogenies described there.
MSAML M http://xml.coverpages.org/msaml-desc-dec.html Defined by Paul
Gordon of University of Calgary. See his big list of molecular biology
XML projects.
BSML http://www.bsml.org/resources/default.asp Bioinformatic Sequence
Markup Language includes a multiple sequence alignment XML format
Usage
Here is a sample session with frestboot
% frestboot -seed 3
Bootstrapped restriction sites algorithm
Input file: restboot.dat
Phylip seqboot_rest program output file [restboot.frestboot]:
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "restboot.frestboot"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Bootstrapped restriction sites algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more sets of
restriction data
[-outfile] outfile [*.frestboot] Phylip seqboot_rest program
output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -rewriteformat menu [p] Output format (Values: p (PHYLIP); n
(NEXUS); x (XML))
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
-enzymes boolean [N] Is the number of enzymes present in
input file
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
frestboot data files read by SEQBOOT are the standard ones for the
various kinds of data. For molecular sequences the sequences may be
either interleaved or sequential, and similarly for restriction sites.
Restriction sites data may either have or not have the third argument,
the number of restriction enzymes used. Discrete morphological
characters are always assumed to be in sequential format. Gene
frequencies data start with the number of species and the number of
loci, and then follow that by a line with the number of alleles at each
locus. The data for each locus may either have one entry for each
allele, or omit one allele at each locus. The details of the formats
are given in the main documentation file, and in the documentation
files for the groups of programsreads any normal sequence USAs.
Input files for usage example
File: restboot.dat
5 13 2
Alpha ++-+-++--+++-
Beta ++++--+--+++-
Gamma -+--+-++-+-++
Delta ++-+----++---
Epsilon ++++----++---
Output file format
frestboot output will contain the data sets generated by the resampling
process. Note that, when Gene Frequencies data is used or when Discrete
Morphological characters with the Factors option are used, the number
of characters in each data set may vary. It may also vary if there are
an odd number of characters or sites and the Delete-Half-Jackknife
resampling method is used, for then there will be a 50% chance of
choosing (n+1)/2 characters and a 50% chance of choosing (n-1)/2
characters.
The Factors option causes the characters to be resampled together. If
(say) three adjacent characters all have the same factors characters,
so that they all are understood to be recoding one multistate
character, they will be resampled together as a group.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these
data avoid any result which is sensitive to the input order of species
from showing up repeatedly and thus appearing to have evidence in its
favor.
The numerical options 1 and 2 in the menu also affect the output file.
If 1 is chosen (it is off by default) the program will print the
original input data set on the output file before the resampled data
sets. I cannot actually see why anyone would want to do this. Option 2
toggles the feature (on by default) that prints out up to 20 times
during the resampling process a notification that the program has
completed a certain number of data sets. Thus if 100 resampled data
sets are being produced, every 5 data sets a line is printed saying
which data set has just been completed. This option should be turned
off if the program is running in background and silence is desirable.
At the end of execution the program will always (whatever the setting
of option 2) print a couple of lines saying that output has been
written to the output file.
Output files for usage example
File: restboot.frestboot
5 13
Alpha +--++-+++- -++
Beta +++++----- -++
Gamma -----+---+ +++
Delta +--++----- -+-
Epsilon +++++----- -+-
5 13
Alpha ++----+++- +++
Beta +++-----+- +++
Gamma -+-+++--++ ++-
Delta ++-------- ++-
Epsilon +++------- ++-
5 13
Alpha ++++++-+++ ---
Beta ++++++-+++ ---
Gamma --++-++--- +++
Delta +++++----- ---
Epsilon +++++----- ---
5 13
Alpha ++++-+++++ ---
Beta ++-+-+++++ ---
Gamma ---+-++--- +++
Delta ++--+++--- ---
Epsilon ++--+++--- ---
5 13
Alpha +-+++-++++ +--
Beta +++++-++++ +--
Gamma ----+----- +++
Delta +-++-+---- ---
Epsilon ++++-+---- ---
5 13
Alpha +++------- +++
Beta +++------- +++
Gamma +--++++++- +-+
Delta +++------+ +--
Epsilon +++------+ +--
5 13
Alpha ++++-+--++ ++-
Beta ++++----++ ++-
Gamma --+++---+- -++
Delta ++++--+++- ---
Epsilon ++++--+++- ---
5 13
Alpha +--+---+++ +--
Beta ++++---+++ +--
Gamma ----++-+-+ +++
Delta +--+--++-- ---
Epsilon ++++--++-- ---
5 13
Alpha +++--++--+ ++-
[Part of this file has been deleted for brevity]
Gamma -+--++-+++ -++
Delta ++++------ +++
Epsilon ++++------ +++
5 13
Alpha +++---+-++ +++
Beta +++---+-++ +++
Gamma ---++++-++ -++
Delta +++----+++ ---
Epsilon +++----+++ ---
5 13
Alpha ++++--+--+ +--
Beta +++++----+ +--
Gamma ---+-+-+++ +++
Delta ++++-----+ +--
Epsilon +++++----+ +--
5 13
Alpha +-----+--- +++
Beta +++++++--- +++
Gamma +------+++ +--
Delta +-----+--- +--
Epsilon +++++++--- +--
5 13
Alpha +-++--+-++ +--
Beta ++++--+-++ +--
Gamma +---++++-- -++
Delta +-++------ ---
Epsilon ++++------ ---
5 13
Alpha +++-+-++++ ++-
Beta +++---++++ ++-
Gamma --++--++-- +++
Delta +++--+++-- ---
Epsilon +++--+++-- ---
5 13
Alpha ++-+++--++ +--
Beta +++-++--++ +--
Gamma ----+++--- +++
Delta ++-----+-- ---
Epsilon +++----+-- ---
5 13
Alpha +---++---- ++-
Beta ++---+---- ++-
Gamma --++-+---- -++
Delta +-----++++ ---
Epsilon ++----++++ ---
5 13
Alpha +++-++++-+ +++
Beta +++++----+ +++
Gamma -++------+ +++
Delta +++-+---++ ---
Epsilon +++++---++ ---
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdnapars.txt 0000664 0001750 0001750 00000044213 12171064331 015730 0000000 0000000 fdnapars
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
DNA parsimony algorithm
Description
Estimates phylogenies by the parsimony method using nucleic acid
sequences. Allows use the full IUB ambiguity codes, and estimates
ancestral nucleotide states. Gaps treated as a fifth nucleotide state.
It can also do transversion parsimony. Can cope with multifurcations,
reconstruct ancestral states, use 0/1 character weights, and infer
branch lengths
Algorithm
This program carries out unrooted parsimony (analogous to Wagner trees)
(Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA sequences. The
method of Fitch (1971) is used to count the number of changes of base
needed on a given tree. The assumptions of this method are analogous to
those of MIX:
1. Each site evolves independently.
2. Different lineages evolve independently.
3. The probability of a base substitution at a given site is small
over the lengths of time involved in a branch of the phylogeny.
4. The expected amounts of change in different branches of the
phylogeny do not vary by so much that two changes in a high-rate
branch are more probable than one change in a low-rate branch.
5. The expected amounts of change do not vary enough among sites that
two changes in one site are more probable than one change in
another.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b,
1988b). For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b, 1988), but also read the exchange between
Felsenstein and Sober (1986).
Change from an occupied site to a deletion is counted as one change.
Reversion from a deletion to an occupied site is allowed and is also
counted as one change. Note that this in effect assumes that a deletion
N bases long is N separate events.
Dnapars can handle both bifurcating and multifurcating trees. In doing
its search for most parsimonious trees, it adds species not only by
creating new forks in the middle of existing branches, but it also
tries putting them at the end of new branches which are added to
existing forks. Thus it searches among both bifurcating and
multifurcating trees. If a branch in a tree does not have any
characters which might change in that branch in the most parsimonious
tree, it does not save that tree. Thus in any tree that results, a
branch exists only if some character has a most parsimonious
reconstruction that would involve change in that branch. It also saves
a number of trees tied for best (you can alter the
number it saves using the V option in the menu). When rearranging
trees, it tries rearrangements of all of the saved trees. This makes
the algorithm slower than earlier versions of Dnapars.
The input data is standard. The first line of the input file contains
the number of species and the number of sites.
Next come the species data. Each sequence starts on a new line, has a
ten-character species name that must be blank-filled to be of that
length, followed immediately by the species data in the one-letter
code. The sequences must either be in the "interleaved" or "sequential"
formats described in the Molecular Sequence Programs document. The I
option selects between them. The sequences can have internal blanks in
the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a
deletion.
Usage
Here is a sample session with fdnapars
% fdnapars
DNA parsimony algorithm
Input (aligned) nucleotide sequence set(s): dnapars.dat
Phylip tree file (optional):
Phylip dnapars program output file [dnapars.fdnapars]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements on the first of the trees tied for best
!---------!
.........
.........
Collapsing best trees
.
Output written to file "dnapars.fdnapars"
Tree also written onto file "dnapars.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
DNA parsimony algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fdnapars] Phylip dnapars program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-maxtrees integer [10000] Number of trees to save (Integer
from 1 to 1000000)
* -[no]thorough toggle [Y] More thorough search
* -[no]rearrange boolean [Y] Rearrange on just one best tree
-transversion boolean [N] Use transversion parsimony
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1.0] Threshold value (Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnapars] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-stepbox boolean [N] Print out steps in each site
-ancseq boolean [N] Print sequences at all nodes of tree
-[no]treeprint boolean [Y] Print out tree
* -[no]dotdiff boolean [Y] Use dot differencing to display results
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdnapars reads any normal sequence USAs.
Input files for usage example
File: dnapars.dat
5 13
Alpha AACGUGGCCAAAU
Beta AAGGUCGCCAAAC
Gamma CAUUUCGUCACAA
Delta GGUAUUUCGGCCU
Epsilon GGGAUCUCGGCCC
Output file format
fdnapars output is standard: if option 1 is toggled on, the data is
printed out, with the convention that "." means "the same as in the
first species". Then comes a list of equally parsimonious trees. Each
tree has branch lengths. These are computed using an algorithm
published by Hochbaum and Pathria (1997) which I first heard of from
Wayne Maddison who invented it independently of them. This algorithm
averages the number of reconstructed changes of state over all sites a
over all possible most parsimonious placements of the changes of state
among branches. Note that it does not correct in any way for multiple
changes that overlay each other. If option 2 is toggled on a table of
the number of changes of state required in each character is also
printed. If option 5 is toggled on, a table is printed out after each
tree, showing for each branch whether there are known to be changes in
the branch, and what the states are inferred to have been at the top
end of the branch. This is a reconstruction of the ancestral sequences
in the tree. If you choose option 5, a menu item "." appears which
gives you the opportunity to turn off dot-differencing so that complete
ancestral sequences are shown. If the inferred state is a "?" or one of
the IUB ambiguity symbols, there will be multiple equally-parsimonious
assignments of states; the user must work these out for themselves by
hand. A "?" in the reconstructed states means that in addition to one
or more bases, a deletion may or may not be present. If option 6 is
left in its default state the trees found will be written to a tree
file, so that they are available to be used in other programs. If the U
(User Tree) option is used and more than one tree is supplied, the
program also performs a statistical test of each of these trees against
the best tree. This test, which is a version of the test proposed by
Alan Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences due to
Kishino and Hasegawa (1989), and uses the mean and variance of step
differences between trees, taken across sites. If the mean is more than
1.96 standard deviations different then the trees are declared
significantly different. The program prints out a table of the steps
for each tree, the differences of each from the best one, the variance
of that quantity as determined by the step differences at individual
sites, and a conclusion as to whether that tree is or is not
significantly worse than the best one. If the U (User Tree) option is
used and more than one tree is supplied, and the program is not told to
assume autocorrelation between the rates at different sites, the
program also performs a statistical test of each of these trees against
the one with highest likelihood. If there are two user trees, this is a
version of the test proposed by Alan Templeton (1983) and evaluated in
a test case by me (1985a). It is closely parallel to a test using log
likelihood differences due to Kishino and Hasegawa (1989) It uses the
mean and variance of the differences in the number of steps between
trees, taken across sites. If the two trees' means are more than 1.96
standard deviations different, then the trees are declared
significantly different. If there are more than two trees, the test
done is an extension of the KHT test, due to Shimodaira and Hasegawa
(1999). They pointed out that a correction for the number of trees was
necessary, and they introduced a resampling method to make this
correction. In the version used here the variances and covariances of
the sums of steps across sites are computed for all pairs of trees. To
test whether the difference between each tree and the best one is
larger than could have been expected if they all had the same expected
number of steps, numbers of steps for all trees are sampled with these
covariances and equal means (Shimodaira and Hasegawa's "least favorable
hypothesis"), and a P value is computed from the fraction of times the
difference between the tree's value and the lowest number of steps
exceeds that actually observed. Note that this sampling needs random
numbers, and so the program will prompt the user for a random number
seed if one has not already been supplied. With the two-tree KHT test
no random numbers are used. In either the KHT or the SH test the
program prints out a table of the number of steps for each tree, the
differences of each from the lowest one, the variance of that quantity
as determined by the differences of the numbers of steps at individual
sites, and a conclusion as to whether that tree is or is not
significantly worse than the best one. Option 6 in the menu controls
whether the tree estimated by the program is written onto a tree file.
The default name of this output tree file is "outtree". If the U option
is in effect, all the user-defined trees are written to the output tree
file. If the program finds multiple trees tied for best, all of these
are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is needed
when we use the trees to make a consensus tree of the results of
bootstrapping or jackknifing, to avoid overrepresenting replicates that
find many tied trees.
Output files for usage example
File: dnapars.fdnapars
DNA parsimony algorithm, version 3.69.650
One most parsimonious tree found:
+-----Epsilon
+----------------------------3
+------------2 +-------Delta
| |
| +----------------Gamma
|
1----Beta
|
+---------Alpha
requires a total of 19.000
between and length
------- --- ------
1 2 0.217949
2 3 0.487179
3 Epsilon 0.096154
3 Delta 0.134615
2 Gamma 0.275641
1 Beta 0.076923
1 Alpha 0.173077
File: dnapars.treefile
(((Epsilon:0.09615,Delta:0.13462):0.48718,Gamma:0.27564):0.21795,
Beta:0.07692,Alpha:0.17308);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdrawtree.txt 0000664 0001750 0001750 00000024571 12171064331 016122 0000000 0000000 fdrawtree
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Plots an unrooted tree diagram
Description
Plots unrooted phylogenies, cladograms, circular trees and phenograms
in a wide variety of user-controllable formats. The program is
interactive and allows previewing of the tree on PC, Macintosh, or X
Windows screens, or on Tektronix or Digital graphics terminals. Final
output can be to a file formatted for one of the drawing programs, for
a ray-tracing or VRML browser, or one at can be sent to a laser printer
(such as Postscript or PCL-compatible printers), on graphics screens or
terminals, on pen plotters or on dot matrix printers capable of
graphics.
Similar to DRAWGRAM but plots unrooted phylogenies.
Algorithm
DRAWTREE interactively plots an unrooted tree diagram, with many
options including orientation of tree and branches, label sizes and
angles, margin sizes. Particularly if you can use your computer screen
to preview the plot, you can very effectively adjust the details of the
plotting to get just the kind of plot you want.
To understand the working of DRAWGRAM and DRAWTREE, you should first
read the Tree Drawing Programs web page in this documentation.
As with DRAWGRAM, to run DRAWTREE you need a compiled copy of the
program, a font file, and a tree file. The tree file has a default name
of intree. The font file has a default name of "fontfile". If there is
no file of that name, the program will ask you for the name of a font
file (we provide ones that have the names font1 through font6). Once
you decide on a favorite one of these, you could make a copy of it and
call it fontfile, and it will then be used by default. Note that the
program will get confused if the input tree file has the number of
trees on the first line of the file, so that number may have to be
removed.
Usage
Here is a sample session with fdrawtree
% fdrawtree -previewer n
Plots an unrooted tree diagram
Phylip tree file: drawgram.tree
Phylip drawtree output file [drawgram.fdrawtree]:
DRAWTREE from PHYLIP version 3.69.650
Reading tree ...
Tree has been read.
Loading the font ...
Font loaded.
Writing plot file ...
Plot written to file "drawgram.fdrawtree"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Plots an unrooted tree diagram
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-plotfile] outfile [*.fdrawtree] Phylip drawtree output file
Additional (Optional) qualifiers (* if not always prompted):
-plotter menu [l] Plotter or printer the tree will be
drawn on (Values: l (Postscript printer file
format); m (PICT format (for drawing
programs)); j (HP Laserjet 75 dpi PCL file
format); s (HP Laserjet 150 dpi PCL file
format); y (HP Laserjet 300 dpi PCL file
format); w (MS-Windows Bitmap); f (FIG 2.0
drawing program format); a (Idraw drawing
program format); z (VRML Virtual Reality
Markup Language file); n (PCX 640x350 file
format (for drawing programs)); p (PCX
800x600 file format (for drawing programs));
q (PCX 1024x768 file format (for drawing
programs)); k (TeKtronix 4010 graphics
terminal); x (X Bitmap format); v (POVRAY 3D
rendering program file); r (Rayshade 3D
rendering program file); h (Hewlett-Packard
pen plotter (HPGL file format)); d (DEC
ReGIS graphics (VT240 terminal)); e (Epson
MX-80 dot-matrix printer); c
(Prowriter/Imagewriter dot-matrix printer);
t (Toshiba 24-pin dot-matrix printer); o
(Okidata dot-matrix printer); b (Houston
Instruments plotter); u (other (one you have
inserted code for)))
-previewer menu [x] Previewing device (Values: n (Will not
be previewed); I i (MSDOS graphics screen
m:Macintosh screens); x (X Windows display);
w (MS Windows display); k (TeKtronix 4010
graphics terminal); d (DEC ReGIS graphics
(VT240 terminal)); o (Other (one you have
inserted code for)))
-iterate menu [e] Iterate to improve tree (Values: n (No);
e (Equal-Daylight algorithm); b (n-Body
algorithm))
-lengths boolean [N] Use branch lengths from user trees
-labeldirection menu [m] Label direction (Values: a (along); f
(fixed); r (radial); m (middle))
-treeangle float [90.0] Angle the tree is to be plotted
(Number from -360.000 to 360.000)
-arc float [360] Degrees the arc should occupy (Number
from 0.000 to 360.000)
* -labelrotation float [90.0] Angle of labels (0 degrees is
horizontal for a tree growing vertically)
(Number from 0.000 to 360.000)
-[no]rescaled toggle [Y] Automatically rescale branch lengths
* -bscale float [1.0] Centimeters per unit branch length
(Any numeric value)
-treedepth float [0.53] Depth of tree as fraction of its
breadth (Number from 0.100 to 100.000)
* -xmargin float [1.65] Horizontal margin (cm) (Number 0.100
or more)
* -ymargin float [2.16] Vertical margin (cm) (Number 0.100 or
more)
* -xrayshade float [1.65] Horizontal margin (pixels) (Number
0.100 or more)
* -yrayshade float [2.16] Vertical margin (pixels) (Number
0.100 or more)
-paperx float [20.63750] Paper width (Any numeric value)
-papery float [26.98750] Paper height (Number 0.100 or
more)
-pagesheight float [1] Number of trees across height of page
(Number 1.000 or more)
-pageswidth float [1] Number of trees across width of page
(Number 1.000 or more)
-hpmargin float [0.41275] Horizontal overlap (cm) (Number
0.001 or more)
-vpmargin float [0.53975] Vertical overlap (cm) (Number
0.001 or more)
Advanced (Unprompted) qualifiers:
-fontfile string [font1] Fontfile name (Any string)
Associated qualifiers:
"-plotfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdrawtree input ...
Input files for usage example
File: drawgram.tree
(Delta,(Epsilon,(Gamma,(Beta,Alpha))));
Output file format
fdrawtree outputs ...
Output files for usage example
Graphics File: drawgram.fdrawtree
[fdrawtree results]
Data files
The font file has a default name of "fontfile". If there is no file of
that name, the program will ask you for the name of a font file (we
provide ones that have the names font1 through font6). Once you decide
on a favorite one of these, you could make a copy of it and call it
fontfile, and it will then be used by default.
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
fdrawgram Plots a cladogram- or phenogram-like rooted tree diagram
fretree Interactive tree rearrangement
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdolmove.txt 0000664 0001750 0001750 00000032710 12171064331 015744 0000000 0000000 fdolmove
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Interactive Dollo or polymorphism parsimony
Description
Interactive construction of phylogenies from discrete character data
with two states (0 and 1) using the Dollo or polymorphism parsimony
criteria. Evaluates parsimony and compatibility criteria for those
phylogenies and displays reconstructed states throughout the tree. This
can be used to find parsimony or compatibility estimates by hand.
Algorithm
DOLMOVE is an interactive parsimony program which uses the Dollo and
Polymorphism parsimony criteria. It is inspired on Wayne Maddison and
David Maddison's marvellous program MacClade, which is written for
Apple MacIntosh computers. DOLMOVE reads in a data set which is
prepared in almost the same format as one for the Dollo and polymorhism
parsimony program DOLLOP. It allows the user to choose an initial tree,
and displays this tree on the screen. The user can look at different
characters and the way their states are distributed on that tree, given
the most parsimonious reconstruction of state changes for that
particular tree. The user then can specify how the tree is to be
rearraranged, rerooted or written out to a file. By looking at
different rearrangements of the tree the user can manually search for
the most parsimonious tree, and can get a feel for how different
characters are affected by changes in the tree topology.
This program is compatible with fewer computer systems than the other
programs in PHYLIP. It can be adapted to PCDOS systems or to any system
whose screen or terminals emulate DEC VT100 terminals (such as Telnet
programs for logging in to remote computers over a TCP/IP network,
VT100-compatible windows in the X windowing system, and any terminal
compatible with ANSI standard terminals). For any other screen types,
there is a generic option which does not make use of screen graphics
characters to display the character states. This will be less
effective, as the states will be less easy to see when displayed.
Usage
Here is a sample session with fdolmove
% fdolmove
Interactive Dollo or polymorphism parsimony
Phylip character discrete states file: dolmove.dat
Phylip tree file (optional):
NEXT? (R # + - S . T U W O F H J K L C ? X Q) (? for Help): Q
Do you want to write out the tree to a file? (Y or N): Y
Interactive Dollo or polymorphism parsimony, version 3.69.650
5 species, 6 characters
Computing steps needed for compatibility in sites ...
(unrooted) 5.0 Steps 4 chars compatible
Dollo
,-----------5:Epsilon
--9
! ,--------4:Delta
`--8
! ,-----3:Gamma
`--7
! ,--2:Beta
`--6
`--1:Alpha
Tree written to file "dolmove.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
Interactive Dollo or polymorphism parsimony
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing data set
[-intreefile] tree Phylip tree file (optional)
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-ancfile properties Ancestral states file
-factorfile properties Factors file
-method menu [d] Parsimony method (Values: d (Dollo); p
(Polymorphism))
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 0.000 or more)
-initialtree menu [Arbitary] Initial tree (Values: a
(Arbitary); u (User); s (Specify))
-screenwidth integer [80] Width of terminal screen in characters
(Any integer value)
-screenlines integer [24] Number of lines on screen (Any integer
value)
-outtreefile outfile [*.fdolmove] Phylip tree output file
(optional)
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdolmove reads discrete character data with "?", "P", "B" states
allowed. .
(0,1) Discrete character data
These programs are intended for the use of morphological systematists
who are dealing with discrete characters, or by molecular evolutionists
dealing with presence-absence data on restriction sites. One of the
programs (PARS) allows multistate characters, with up to 8 states, plus
the unknown state symbol "?". For the others, the characters are
assumed to be coded into a series of (0,1) two-state characters. For
most of the programs there are two other states possible, "P", which
stands for the state of Polymorphism for both states (0 and 1), and
"?", which stands for the state of ignorance: it is the state
"unknown", or "does not apply". The state "P" can also be denoted by
"B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding a
multistate character into a series of two-state (0,1) characters.
Suppose we had a character with four states whose character-state tree
had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We can
represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE, DOLPENNY
and DOLBOOT the multistate recoding does not necessarily work properly,
as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected in
a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for unordered
character states.
Input files for usage example
File: dolmove.dat
5 6
Alpha 110110
Beta 110000
Gamma 100110
Delta 001001
Epsilon 001110
Output file format
fdolmove output:
If the A option is used, then the program will infer, for any character
whose ancestral state is unknown ("?") whether the ancestral state 0 or
1 will give the fewest changes (according to the criterion in use). If
these are tied, then it may not be possible for the program to infer
the state in the internal nodes, and many of these will be shown as
"?". If the A option is not used, then the program will assume 0 as the
ancestral state.
When reconstructing the placement of forward changes and reversions
under the Dollo method, keep in mind that each polymorphic state in the
input data will require one "last minute" reversion. This is included
in the counts. Thus if we have both states 0 and 1 at a tip of the tree
the program will assume that the lineage had state 1 up to the last
minute, and then state 0 arose in that population by reversion, without
loss of state 1.
When DOLMOVE calculates the number of characters compatible with the
tree, it will take the F option into account and count the multistate
characters as units, counting a character as compatible with the tree
only when all of the binary characters corresponding to it are
compatible with the tree.
Output files for usage example
File: dolmove.treefile
(Epsilon,(Delta,(Gamma,(Beta,Alpha))));
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fkitsch.txt 0000664 0001750 0001750 00000044037 12171064331 015571 0000000 0000000 fkitsch
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Fitch-Margoliash method with contemporary tips
Description
Estimates phylogenies from distance matrix data under the "ultrametric"
model which is the same as the additive tree model except that an
evolutionary clock is assumed. The Fitch-Margoliash criterion and other
least squares criteria, or the Minimum Evolution criterion are
possible. This program will be useful with distances computed from
molecular sequences, restriction sites or fragments distances, with
distances from DNA hybridization measurements, and with genetic
distances computed from gene frequencies.
Algorithm
This program carries out the Fitch-Margoliash and Least Squares
methods, plus a variety of others of the same family, with the
assumption that all tip species are contemporaneous, and that there is
an evolutionary clock (in effect, a molecular clock). This means that
branches of the tree cannot be of arbitrary length, but are constrained
so that the total length from the root of the tree to any species is
the same. The quantity minimized is the same weighted sum of squares
described in the Distance Matrix Methods documentation file.
The programs FITCH, KITSCH, and NEIGHBOR are for dealing with data
which comes in the form of a matrix of pairwise distances between all
pairs of taxa, such as distances based on molecular sequence data, gene
frequency genetic distances, amounts of DNA hybridization, or
immunological distances. In analyzing these data, distance matrix
programs implicitly assume that:
* Each distance is measured independently from the others: no item of
data contributes to more than one distance.
* The distance between each pair of taxa is drawn from a distribution
with an expectation which is the sum of values (in effect amounts
of evolution) along the tree from one tip to the other. The
variance of the distribution is proportional to a power p of the
expectation.
These assumptions can be traced in the least squares methods of
programs FITCH and KITSCH but it is not quite so easy to see them in
operation in the Neighbor-Joining method of NEIGHBOR, where the
independence assumptions is less obvious.
THESE TWO ASSUMPTIONS ARE DUBIOUS IN MOST CASES: independence will not
be expected to be true in most kinds of data, such as genetic distances
from gene frequency data. For genetic distance data in which pure
genetic drift without mutation can be assumed to be the mechanism of
change CONTML may be more appropriate. However, FITCH, KITSCH, and
NEIGHBOR will not give positively misleading results (they will not
make a statistically inconsistent estimate) provided that additivity
holds, which it will if the distance is computed from the original data
by a method which corrects for reversals and parallelisms in evolution.
If additivity is not expected to hold, problems are more severe. A
short discussion of these matters will be found in a review article of
mine (1984a). For detailed, if sometimes irrelevant, controversy see
the papers by Farris (1981, 1985, 1986) and myself (1986, 1988b).
For genetic distances from gene frequencies, FITCH, KITSCH, and
NEIGHBOR may be appropriate if a neutral mutation model can be assumed
and Nei's genetic distance is used, or if pure drift can be assumed and
either Cavalli-Sforza's chord measure or Reynolds, Weir, and
Cockerham's (1983) genetic distance is used. However, in the latter
case (pure drift) CONTML should be better.
Restriction site and restriction fragment data can be treated by
distance matrix methods if a distance such as that of Nei and Li (1979)
is used. Distances of this sort can be computed in PHYLIp by the
program RESTDIST.
For nucleic acid sequences, the distances computed in DNADIST allow
correction for multiple hits (in different ways) and should allow one
to analyse the data under the presumption of additivity. In all of
these cases independence will not be expected to hold. DNA
hybridization and immunological distances may be additive and
independent if transformed properly and if (and only if) the standards
against which each value is measured are independent. (This is rarely
exactly true).
FITCH and the Neighbor-Joining option of NEIGHBOR fit a tree which has
the branch lengths unconstrained. KITSCH and the UPGMA option of
NEIGHBOR, by contrast, assume that an "evolutionary clock" is valid,
according to which the true branch lengths from the root of the tree to
each tip are the same: the expected amount of evolution in any lineage
is proportional to elapsed time.
The method may be considered as providing an estimate of the phylogeny.
Alternatively, it can be considered as a phenetic clustering of the tip
species. This method minimizes an objective function, the sum of
squares, not only setting the levels of the clusters so as to do so,
but rearranging the hierarchy of clusters to try to find alternative
clusterings that give a lower overall sum of squares. When the power
option P is set to a value of P = 0.0, so that we are minimizing a
simple sum of squares of the differences between the observed distance
matrix and the expected one, the method is very close in spirit to
Unweighted Pair Group Arithmetic Average Clustering (UPGMA), also
called Average-Linkage Clustering. If the topology of the tree is fixed
and there turn out to be no branches of negative length, its result
should be the same as UPGMA in that case. But since it tries
alternative topologies and (unless the N option is set) it combines
nodes that otherwise could result in a reversal of levels, it is
possible for it to give a different, and better, result than simple
sequential clustering. Of course UPGMA itself is available as an option
in program NEIGHBOR.
An important use of this method will be to do a formal statistical test
of the evolutionary clock hypothesis. This can be done by comparing the
sums of squares achieved by FITCH and by KITSCH, BUT SOME CAVEATS ARE
NECESSARY. First, the assumption is that the observed distances are
truly independent, that no original data item contributes to more than
one of them (not counting the two reciprocal distances from i to j and
from j to i). THIS WILL NOT HOLD IF THE DISTANCES ARE OBTAINED FROM
GENE FREQUENCIES, FROM MORPHOLOGICAL CHARACTERS, OR FROM MOLECULAR
SEQUENCES. It may be invalid even for immunological distances and
levels of DNA hybridization, provided that the use of common standard
for all members of a row or column allows an error in the measurement
of the standard to affect all these distances simultaneously. It will
also be invalid if the numbers have been collected in experimental
groups, each measured by taking differences from a common standard
which itself is measured with error. Only if the numbers in different
cells are measured from independent standards can we depend on the
statistical model. The details of the test and the assumptions are
discussed in my review paper on distance methods (Felsenstein, 1984a).
For further and sometimes irrelevant controversy on these matters see
the papers by Farris (1981, 1985, 1986) and myself (Felsenstein, 1986,
1988b).
A second caveat is that the distances must be expected to rise linearly
with time, not according to any other curve. Thus it may be necessary
to transform the distances to achieve an expected linearity. If the
distances have an upper limit beyond which they could not go, this is a
signal that linearity may not hold. It is also VERY important to choose
the power P at a value that results in the standard deviation of the
variation of the observed from the expected distances being the P/2-th
power of the expected distance.
To carry out the test, fit the same data with both FITCH and KITSCH,
and record the two sums of squares. If the topology has turned out the
same, we have N = n(n-1)/2 distances which have been fit with 2n-3
parameters in FITCH, and with n-1 parameters in KITSCH. Then the
difference between S(K) and S(F) has d1 = n-2 degrees of freedom. It is
statistically independent of the value of S(F), which has d2 = N-(2n-3)
degrees of freedom. The ratio of mean squares
[S(K)-S(F)]/d1
----------------
S(F)/d2
should, under the evolutionary clock, have an F distribution with n-2
and N-(2n-3) degrees of freedom respectively. The test desired is that
the F ratio is in the upper tail (say the upper 5%) of its
distribution. If the S (subreplication) option is in effect, the above
degrees of freedom must be modified by noting that N is not n(n-1)/2
but is the sum of the numbers of replicates of all cells in the
distance matrix read in, which may be either square or triangular. A
further explanation of the statistical test of the clock is given in a
paper of mine (Felsenstein, 1986).
The program uses a similar tree construction method to the other
programs in the package and, like them, is not guaranteed to give the
best-fitting tree. The assignment of the branch lengths for a given
topology is a least squares fit, subject to the constraints against
negative branch lengths, and should not be able to be improved upon.
KITSCH runs more quickly than FITCH.
Usage
Here is a sample session with fkitsch
% fkitsch
Fitch-Margoliash method with contemporary tips
Phylip distance matrix file: kitsch.dat
Phylip tree file (optional):
Phylip kitsch program output file [kitsch.fkitsch]:
Adding species:
1. Bovine
2. Mouse
3. Gibbon
4. Orang
5. Gorilla
6. Chimp
7. Human
Doing global rearrangements
!-------------!
.............
Output written to file "kitsch.fkitsch"
Tree also written onto file "kitsch.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Fitch-Margoliash method with contemporary tips
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-datafile] distances File containing one or more distance
matrices
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fkitsch] Phylip kitsch program output
file
Additional (Optional) qualifiers (* if not always prompted):
-matrixtype menu [s] Type of data matrix (Values: s (Square);
u (Upper triangular); l (Lower triangular))
-minev boolean [N] Minimum evolution
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-power float [2.0] Power (Any numeric value)
-negallowed boolean [N] Negative branch lengths allowed
-replicates boolean [N] Subreplicates
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fkitsch] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fkitsch requires a bifurcating tree, unlike FITCH, which requires an
unrooted tree with a trifurcation at its base. Thus the tree shown
below would be written:
((D,E),(C,(A,B)));
If a tree with a trifurcation at the base is by mistake fed into the U
option of KITSCH then some of its species (the entire rightmost furc,
in fact) will be ignored and too small a tree read in. This should
result in an error message and the program should stop. It is important
to understand the difference between the User Tree formats for KITSCH
and FITCH. You may want to use RETREE to convert a user tree that is
suitable for FITCH into one suitable for KITSCH or vice versa.
Input files for usage example
File: kitsch.dat
7
Bovine 0.0000 1.6866 1.7198 1.6606 1.5243 1.6043 1.5905
Mouse 1.6866 0.0000 1.5232 1.4841 1.4465 1.4389 1.4629
Gibbon 1.7198 1.5232 0.0000 0.7115 0.5958 0.6179 0.5583
Orang 1.6606 1.4841 0.7115 0.0000 0.4631 0.5061 0.4710
Gorilla 1.5243 1.4465 0.5958 0.4631 0.0000 0.3484 0.3083
Chimp 1.6043 1.4389 0.6179 0.5061 0.3484 0.0000 0.2692
Human 1.5905 1.4629 0.5583 0.4710 0.3083 0.2692 0.0000
Output file format
fkitsch output is a rooted tree, together with the sum of squares, the
number of tree topologies searched, and, if the power P is at its
default value of 2.0, the Average Percent Standard Deviation is also
supplied. The lengths of the branches of the tree are given in a table,
that also shows for each branch the time at the upper end of the
branch. "Time" here really means cumulative branch length from the
root, going upwards (on the printed diagram, rightwards). For each
branch, the "time" given is for the node at the right (upper) end of
the branch. It is important to realize that the branch lengths are not
exactly proportional to the lengths drawn on the printed tree diagram!
In particular, short branches are exaggerated in the length on that
diagram so that they are more visible.
Output files for usage example
File: kitsch.fkitsch
7 Populations
Fitch-Margoliash method with contemporary tips, version 3.69.650
__ __ 2
\ \ (Obs - Exp)
Sum of squares = /_ /_ ------------
2
i j Obs
negative branch lengths not allowed
+-------Human
+-6
+----5 +-------Chimp
! !
+---4 +---------Gorilla
! !
+------------------------3 +--------------Orang
! !
+----2 +------------------Gibbon
! !
--1 +-------------------------------------------Mouse
!
+------------------------------------------------Bovine
Sum of squares = 0.107
Average percent standard deviation = 5.16213
From To Length Height
---- -- ------ ------
6 Human 0.13460 0.81285
5 6 0.02836 0.67825
6 Chimp 0.13460 0.81285
4 5 0.07638 0.64990
5 Gorilla 0.16296 0.81285
3 4 0.06639 0.57352
4 Orang 0.23933 0.81285
2 3 0.42923 0.50713
3 Gibbon 0.30572 0.81285
1 2 0.07790 0.07790
2 Mouse 0.73495 0.81285
1 Bovine 0.81285 0.81285
File: kitsch.treefile
((((((Human:0.13460,Chimp:0.13460):0.02836,Gorilla:0.16296):0.07638,
Orang:0.23933):0.06639,Gibbon:0.30572):0.42923,Mouse:0.73495):0.07790,
Bovine:0.81285);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
efitch Fitch-Margoliash and least-squares distance methods
ekitsch Fitch-Margoliash method with contemporary tips
eneighbor Phylogenies from distance matrix by N-J or UPGMA method
ffitch Fitch-Margoliash and least-squares distance methods
fneighbor Phylogenies from distance matrix by N-J or UPGMA method
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/ftreedist.txt 0000664 0001750 0001750 00000040422 12171064331 016121 0000000 0000000 ftreedist
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Calculate distances between trees
Description
Computes the Branch Score distance between trees, which allows for
differences in tree topology and which also makes use of branch
lengths. Also computes the Robinson-Foulds symmetric difference
distance between trees, which allows for differences in tree topology
but does not use branch lengths.
Algorithm
This program computes distances between trees. Two distances are
computed, the Branch Score Distance of Kuhner and Felsenstein (1994),
and the more widely known Symmetric Difference of Robinson and Foulds
(1981). The Branch Score Distance uses branch lengths, and can only be
calculated when the trees have lengths on all branches. The Symmetric
Difference does not use branch length information, only the tree
topologies. It must also be borne in mind that neither distance has any
immediate statistical interpretation -- we cannot say whether a larger
distance is significantly larger than a smaller one.
These distances are computed by considering all possible branches that
could exist on the the two trees. Each branch divides the set of
species into two groups -- the ones connected to one end of the branch
and the ones connected to the other. This makes a partition of the full
set of species. (in Newick notation)
((A,C),(D,(B,E)))
has two internal branches. One induces the partition {A, C | B, D, E}
and the other induces the partition {A, C, D | B, E}. A different tree
with the same set of species,
(((A,D),C),(B,E))
has internal branches that correspond to the two partitions {A, C, D |
B, E} and {A, D | B, C, E}. Note that the other branches, all of which
are external branches, induce partitions that separate one species from
all the others. Thus there are 5 partitions like this: {C | A, B, D, E}
on each of these trees. These are always present on all trees, provided
that each tree has each species at the end of its own branch.
In the case of the Branch Score distance, each partition that does
exist on a tree also has a branch length associated with it. Thus if
the tree is
(((A:0.1,D:0.25):0.05,C:0.01):0.2,(B:0.3,E:0.8):0.2)
The list of partitions and their branch lengths is:
{A | B, C, D, E} 0.1
{D | A, B, C, E} 0.25
{A, D | B, C, E} 0.05
{C | A, B, D, E} 0.01
{A, D, C | B, E} 0.4
{B | A, C, D, E} 0.3
{E | A, B, C, D} 0.8
Note that the tree is being treated as unrooted here, so that the
branch lengths on either side of the rootmost node are summed up to get
a branch length of 0.4.
The Branch Score Distance imagines us as having made a list of all
possible partitions, the ones shown above and also all 7 other possible
partitions, which correspond to branches that are not found in this
tree. These are assigned branch lengths of 0. For two trees, we imagine
constructing these lists, and then summing the squared differences
between the branch lengths. Thus if both trees have branches {A, D | B,
C, E}, the sum contains the square of the difference between the branch
lengths. If one tree has the branch and the other doesn't, it contains
the square of the difference between the branch length and zero (in
other words, the square of that branch length). If both trees do not
have a particular branch, nothing is added to the sum because the
difference is then between 0 and 0.
The Branch Score Distance takes this sum of squared differences and
computes its square root. Note that it has some desirable properties.
When small branches differ in tree topology, it is not very big. When
branches are both present but differ in length, it is affected.
The Symmetric Difference is simply a count of how many partitions there
are, among the two trees, that are on one tree and not on the other. In
the example above there are two partitions, {A, C | B, D, E} and {A, D
| B, C, E}, each of which is present on only one of the two trees. The
Symmetric Difference between the two trees is therefore 2. When the two
trees are fully resolved bifurcating trees, their symmetric distance
must be an even number; it can range from 0 to twice the number of
internal branches, which for n species is 4n-6.
Note the relationship between the two distances. If all trees have all
their branches have length 1.0, the Branch Score Distance is the square
of the Symmetric Difference, as each branch that is present in one but
not in the other results in 1.0 being added to the sum of squared
differences.
We have assumed that nothing is lost if the trees are treated as
unrooted trees. It is easy to define a counterpart to the Branch Score
Distance and one to the Symmetric Difference for these rooted trees.
Each branch then defines a set of species, namely the clade defined by
that branch. Thus if the first of the two trees above were considered
as a rooted tree it would define the three clades {A, C}, {B, D, E},
and {B, E}. The Branch Score Distance is computed from the branch
lengths for all possible sets of species, with 0 put for each set that
does not occur on that tree. The table above will be nearly the same,
but with two entries instead of one for the sets on either side of the
root, {A C D} and {B E}. The Symmetric Difference between two rooted
trees is simply the count of the number of clades that are defined by
one but not by the other. For the second tree the clades would be {A,
D}, {B, C, E}, and {B, E}. The Symmetric Difference between thee two
rooted trees would then be 4.
Although the examples we have discussed have involved fully bifurcating
trees, the input trees can have multifurcations. This does not cause
any complication for the Branch Score Distance. For the Symmetric
Difference, it can lead to distances that are odd numbers.
However, note one strong restriction. The trees should all have the
same list of species. If you use one set of species in the first two
trees, and another in the second two, and choose distances for adjacent
pairs, the distances will be incorrect and will depend on the order of
these pairs in the input tree file, in odd ways.
Usage
Here is a sample session with ftreedist
% ftreedist
Calculate distances between trees
Phylip tree file: treedist.dat
Phylip treedist program output file [treedist.ftreedist]:
Output written to file "treedist.ftreedist"
Done.
Go to the input files for this example
Go to the output files for this example
Example 2
% ftreedist -dtype s
Calculate distances between trees
Phylip tree file: treedist2.dat
Phylip treedist program output file [treedist2.ftreedist]:
Output written to file "treedist2.ftreedist"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Calculate distances between trees
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-outfile] outfile [*.ftreedist] Phylip treedist program output
file
Additional (Optional) qualifiers:
-dtype menu [b] Distance type (Values: s (Symmetric
difference); b (Branch score distance))
-pairing menu [a] Tree pairing method (Values: a
(Distances between adjacent pairs in tree
file); p (Distances between all possible
pairs in tree file))
-style menu [v] Distances output option (Values: f (Full
matrix); v (Verbose, one pair per line); s
(Sparse, one pair per line))
-noroot boolean [N] Trees to be treated as rooted
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
ftreedist reads one input tree file. If the number of trees is given,
it is actually ignored and all trees in the tree file are considered,
even if there are more trees than indicated by the number. There is no
maximum number of trees that can be processed but, if you feed in too
many, there may be an error message about running out of memory. The
problem is particularly acute if you choose the option to examine all
possible pairs of trees in an input tree file. Thus if there are 1,000
trees in the input tree file, keep in mind that all possible pairs
means 1,000,000 pairs to be examined!
Input files for usage example
File: treedist.dat
(A:0.1,(B:0.1,(H:0.1,(D:0.1,(J:0.1,(((G:0.1,E:0.1):0.1,(F:0.1,I:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(D:0.1,((J:0.1,H:0.1):0.1,(((G:0.1,E:0.1):0.1,
(F:0.1,I:0.1):0.1):0.1,C:0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(D:0.1,(H:0.1,(J:0.1,(((G:0.1,E:0.1):0.1,(F:0.1,I:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,(G:0.1,((F:0.1,I:0.1):0.1,((J:0.1,(H:0.1,D:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,(G:0.1,((F:0.1,I:0.1):0.1,(((J:0.1,H:0.1):0.1,D:0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((F:0.1,I:0.1):0.1,(G:0.1,((J:0.1,(H:0.1,D:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((F:0.1,I:0.1):0.1,(G:0.1,(((J:0.1,H:0.1):0.1,D:0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((G:0.1,(F:0.1,I:0.1):0.1):0.1,((J:0.1,(H:0.1,
D:0.1):0.1):0.1,C:0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((G:0.1,(F:0.1,I:0.1):0.1):0.1,(((J:0.1,H:0.1):0.1,
D:0.1):0.1,C:0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,(G:0.1,((F:0.1,I:0.1):0.1,((J:0.1,(H:0.1,D:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(D:0.1,(H:0.1,(J:0.1,(((G:0.1,E:0.1):0.1,(F:0.1,I:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((G:0.1,(F:0.1,I:0.1):0.1):0.1,((J:0.1,(H:0.1,
D:0.1):0.1):0.1,C:0.1):0.1):0.1):0.1):0.1);
Input files for usage example 2
File: treedist2.dat
(A,(B,(H,(D,(J,(((G,E),(F,I)),C))))));
(A,(B,(D,((J,H),(((G,E),(F,I)),C)))));
(A,(B,(D,(H,(J,(((G,E),(F,I)),C))))));
(A,(B,(E,(G,((F,I),((J,(H,D)),C))))));
(A,(B,(E,(G,((F,I),(((J,H),D),C))))));
(A,(B,(E,((F,I),(G,((J,(H,D)),C))))));
(A,(B,(E,((F,I),(G,(((J,H),D),C))))));
(A,(B,(E,((G,(F,I)),((J,(H,D)),C)))));
(A,(B,(E,((G,(F,I)),(((J,H),D),C)))));
(A,(B,(E,(G,((F,I),((J,(H,D)),C))))));
(A,(B,(D,(H,(J,(((G,E),(F,I)),C))))));
(A,(B,(E,((G,(F,I)),((J,(H,D)),C)))));
Output file format
If any of the four types of analysis are selected, the user must
specify how they want the results presented.
The Full matrix (choice F) is a table showing all distances. It is
written onto the output file. The table is presented as groups of 10
columns. Here is the Full matrix for the 12 trees in the input tree
file which is given as an example at the end of this page.
Tree distance program, version 3.6
Symmetric differences between all pairs of trees in tree file:
1 2 3 4 5 6 7 8 9 10
\------------------------------------------------------------
1 | 0 4 2 10 10 10 10 10 10 10
2 | 4 0 2 10 8 10 8 10 8 10
3 | 2 2 0 10 10 10 10 10 10 10
4 | 10 10 10 0 2 2 4 2 4 0
5 | 10 8 10 2 0 4 2 4 2 2
6 | 10 10 10 2 4 0 2 2 4 2
7 | 10 8 10 4 2 2 0 4 2 4
8 | 10 10 10 2 4 2 4 0 2 2
9 | 10 8 10 4 2 4 2 2 0 4
10 | 10 10 10 0 2 2 4 2 4 0
11 | 2 2 0 10 10 10 10 10 10 10
12 | 10 10 10 2 4 2 4 0 2 2
11 12
\------------
1 | 2 10
2 | 2 10
3 | 0 10
4 | 10 2
5 | 10 4
6 | 10 2
7 | 10 4
8 | 10 0
9 | 10 2
10 | 10 2
11 | 0 10
12 | 10 0
The Full matrix is only available for analyses P and L (not for A or
C).
Option V (Verbose) writes one distance per line. The Verbose output is
the default. Here it is for the example data set given below:
Tree distance program, version 3.6
Symmetric differences between adjacent pairs of trees:
Trees 1 and 2: 4
Trees 3 and 4: 10
Trees 5 and 6: 4
Trees 7 and 8: 4
Trees 9 and 10: 4
Trees 11 and 12: 10
Option S (Sparse or terse) is similar except that all that is given on
each line are the numbers of the two trees and the distance, separated
by blanks. This may be a convenient format if you want to write a
program to read these numbers in, and you want to spare yourself the
effort of having the program wade through the words on each line in the
Verbose output. The first four lines of the Sparse output are titles
that your program would want to skip past. Here is the Sparse output
for the example trees.
1 2 4
3 4 10
5 6 4
7 8 4
9 10 4
11 12 10
Output files for usage example
File: treedist.ftreedist
Tree distance program, version 3.69.650
Branch score distances between adjacent pairs of trees:
Trees 1 and 2: 2.000000e-01
Trees 3 and 4: 3.162278e-01
Trees 5 and 6: 2.000000e-01
Trees 7 and 8: 2.000000e-01
Trees 9 and 10: 2.000000e-01
Trees 11 and 12: 3.162278e-01
Output files for usage example 2
File: treedist2.ftreedist
Tree distance program, version 3.69.650
Symmetric differences between adjacent pairs of trees:
Trees 1 and 2: 4
Trees 3 and 4: 10
Trees 5 and 6: 4
Trees 7 and 8: 4
Trees 9 and 10: 4
Trees 11 and 12: 10
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
econsense Majority-rule and strict consensus tree
fconsense Majority-rule and strict consensus tree
ftreedistpair Calculate distance between two sets of trees
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdnacomp.txt 0000664 0001750 0001750 00000042351 12171064331 015722 0000000 0000000 fdnacomp
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
DNA compatibility algorithm
Description
Estimates phylogenies from nucleic acid sequence data using the
compatibility criterion, which searches for the largest number of sites
which could have all states (nucleotides) uniquely evolved on the same
tree. Compatibility is particularly appropriate when sites vary greatly
in their rates of evolution, but we do not know in advance which are
the less reliable ones.
Algorithm
This program implements the compatibility method for DNA sequence data.
For a four-state character without a character-state tree, as in DNA
sequences, the usual clique theorems cannot be applied. The approach
taken in this program is to directly evaluate each tree topology by
counting how many substitutions are needed in each site, comparing this
to the minimum number that might be needed (one less than the number of
bases observed at that site), and then evaluating the number of sites
which achieve the minimum number. This is the evaluation of the tree
(the number of compatible sites), and the topology is chosen so as to
maximize that number.
Compatibility methods originated with Le Quesne's (1969) suggestion
that one ought to look for trees supported by the largest number of
perfectly fitting (compatible) characters. Fitch (1975) showed by
counterexample that one could not use the pairwise compatibility
methods used in CLIQUE to discover the largest clique of jointly
compatible characters.
The assumptions of this method are similar to those of CLIQUE. In a
paper in the Biological Journal of the Linnean Society (1981b) I
discuss this matter extensively. In effect, the assumptions are that:
1. Each character evolves independently.
2. Different lineages evolve independently.
3. The ancestral base at each site is unknown.
4. The rates of change in most sites over the time spans involved in
the the divergence of the group are very small.
5. A few of the sites have very high rates of change.
6. We do not know in advance which are the high and which the low rate
sites.
That these are the assumptions of compatibility methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that arguments such as mine
are invalid and that parsimony (and perhaps compatibility) methods make
no substantive assumptions such as these, see the papers by Farris
(1983) and Sober (1983a, 1983b, 1988), but also read the exchange
between Felsenstein and Sober (1986).
There is, however, some reason to believe that the present criterion is
not the proper way to correct for the presence of some sites with high
rates of change in nucleotide sequence data. It can be argued that
sites showing more than two nucleotide states, even if those are
compatible with the other sites, are also candidates for sites with
high rates of change. It might then be more proper to use DNAPARS with
the Threshold option with a threshold value of 2.
Change from an occupied site to a gap is counted as one change.
Reversion from a gap to an occupied site is allowed and is also counted
as one change. Note that this in effect assumes that a gap N bases long
is N separate events. This may be an overcorrection. When we have
nonoverlapping gaps, we could instead code a gap as a single event by
changing all but the first "-" in the gap into "?" characters. In this
way only the first base of the gap causes the program to infer a
change.
If the U (User Tree) option is used and more than one tree is supplied,
the program also performs a statistical test of each of these trees
against the one with highest likelihood. If there are two user trees,
the test done is one which is due to Kishino and Hasegawa (1989), a
version of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of weighted compatibility
differences between trees, taken across sites. If the two trees
compatibilities are more than 1.96 standard deviations different then
the trees are declared significantly different.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. In the version used here
the variances and covariances of the sum of weighted compatibilities of
sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected compatibility,
compatibilities for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the highest compatibility exceeds that
actually observed. Note that this sampling needs random numbers, and so
the program will prompt the user for a random number seed if one has
not already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program prints out a table of the
compatibility of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the compatibility
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one.
The algorithm is a straightforward modification of DNAPARS, but with
some extra machinery added to calculate, as each species is added, how
many base changes are the minimum which could be required at that site.
The program runs fairly quickly.
Usage
Here is a sample session with fdnacomp
% fdnacomp -ancseq -stepbox -printdata
DNA compatibility algorithm
Input (aligned) nucleotide sequence set(s): dnacomp.dat
Phylip tree file (optional):
Phylip weights file (optional):
Phylip dnacomp program output file [dnacomp.fdnacomp]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
Output written to file "dnacomp.fdnacomp"
Trees also written onto file "dnacomp.treefile"
Go to the input files for this example
Go to the output files for this example
Example 2
% fdnacomp
DNA compatibility algorithm
Input (aligned) nucleotide sequence set(s): dnacomp.dat
Phylip tree file (optional): dnacomptree.dat
Phylip weights file (optional):
Phylip dnacomp program output file [dnacomp.fdnacomp]:
Output written to file "dnacomp.fdnacomp"
Trees also written onto file "dnacomp.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
DNA compatibility algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
-weights properties Phylip weights file (optional)
[-outfile] outfile [*.fdnacomp] Phylip dnacomp program output
file
Additional (Optional) qualifiers (* if not always prompted):
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnacomp] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print steps & compatibility at sites
-ancseq boolean [N] Print sequences at all nodes of tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdnacomp reads any normal sequence USAs.
Input files for usage example
File: dnacomp.dat
5 13
Alpha AACGUGGCCAAAU
Beta AAGGUCGCCAAAC
Gamma CAUUUCGUCACAA
Delta GGUAUUUCGGCCU
Epsilon GGGAUCUCGGCCC
Input files for usage example 2
File: dnacomptree.dat
((((Epsilon,Delta),Gamma),Beta),Alpha);
Output file format
fdnacomp output is standard: if option 1 is toggled on, the data is
printed out, with the convention that "." means "the same as in the
first species". Then comes a list of equally parsimonious trees, and
(if option 2 is toggled on) a table of the number of changes of state
required in each character. If option 5 is toggled on, a table is
printed out after each tree, showing for each branch whether there are
known to be changes in the branch, and what the states are inferred to
have been at the top end of the branch. If the inferred state is a "?"
or one of the IUB ambiguity symbols, there will be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand. A "?" in the reconstructed states means
that in addition to one or more bases, a gap may or may not be present.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is needed
when we use the trees to make a consensus tree of the results of
bootstrapping or jackknifing, to avoid overrepresenting replicates that
find many tied trees.
Output files for usage example
File: dnacomp.fdnacomp
DNA compatibility algorithm, version 3.69.650
5 species, 13 sites
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
One most parsimonious tree found:
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
total number of compatible sites is 11.0
steps in each site:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0| 2 1 3 2 0 2 1 1 1
10| 1 1 1 3
compatibility (Y or N) of each site with this tree:
0123456789
*----------
0 ! YYNYYYYYY
10 !YYYN
From To Any Steps? State at upper node
1 AABGTSGCCA AAY
1 2 maybe AABGTCGCCA AAY
2 3 yes VAKDTCGCCA CAY
3 4 yes GGKATCTCGG CCY
4 Epsilon maybe GGGATCTCGG CCC
4 Delta yes GGTATTTCGG CCT
3 Gamma yes CATTTCGTCA CAA
2 Beta maybe AAGGTCGCCA AAC
1 Alpha maybe AACGTGGCCA AAT
File: dnacomp.treefile
((((Epsilon,Delta),Gamma),Beta),Alpha);
Output files for usage example 2
File: dnacomp.fdnacomp
DNA compatibility algorithm, version 3.69.650
User-defined tree:
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
total number of compatible sites is 11.0
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/frestdist.txt 0000664 0001750 0001750 00000042532 12171064331 016143 0000000 0000000 frestdist
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Calculate distance matrix from restriction sites or fragments
Description
Distances calculated from restriction sites data or restriction
fragments data. The restriction sites option is the one to use to also
make distances for RAPDs or AFLPs.
Algorithm
Restdist reads the same restriction sites format as RESTML and computes
a restriction sites distance. It can also compute a restriction
fragments distance. The original restriction fragments and restriction
sites distance methods were introduced by Nei and Li (1979). Their
original method for restriction fragments is also available in this
program, although its default methods are my modifications of the
original Nei and Li methods.
These two distances assume that the restriction sites are accidental
byproducts of random change of nucleotide sequences. For my restriction
sites distance the DNA sequences are assumed to be changing according
to the Kimura 2-parameter model of DNA change (Kimura, 1980). The user
can set the transition/transversion rate for the model. For my
restriction fragments distance there is there is an implicit assumption
of a Jukes-Cantor (1969) model of change, The user can also set the
parameter of a correction for unequal rates of evolution between sites
in the DNA sequences, using a Gamma distribution of rates among sites.
The Jukes-Cantor model is also implicit in the restriction fragments
distance of Nei and Li(1979). It does not allow us to correct for a
Gamma distribution of rates among sites.
Restriction Sites Distance
The restriction sites distances use data coded for the presence of
absence of individual restriction sites (usually as + and - or 0 and
1). My distance is based on the proportion, out of all sites observed
in one species or the other, which are present in both species. This is
done to correct for the ascertainment of sites, for the fact that we
are not aware of many sites because they do not appear in any species.
My distance starts by computing from the particular pair of species the
fraction
n++
f = ---------------------
n++ + 1/2 (n+- + n-+)
where n++ is the number of sites contained in both species, n+- is the
number of sites contained in the first of the two species but not in
the second, and n-+ is the number of sites contained in the second of
the two species but not in the first. This is the fraction of sites
that are present in one species which are present in both. Since the
number of sites present in the two species will often differ, the
denominator is the average of the number of sites found in the two
species.
If each restriction site is s nucleotides long, the probability that a
restriction site is present in the other species, given that it is
present in a species, is
Qs,
`where Q is the probability that a nucleotide has no net change as one
goes from the one species to the other. It may have changed in between;
we are interested in the probability that that nucleotide site is in
the same base in both species, irrespective of what has happened in
between. The distance is then computed by finding the branch length of
a two-species tree (connecting these two species with a single branch)
such that Q equals the s-th root of f. For this the program computes Q
for various values of branch length, iterating them by a Newton-Raphson
algorithm until the two quantities are equal.
The resulting distance should be numerically close to the original
restriction sites distance of Nei and Li (1979) when divergence is
small. Theirs computes the probability of retention of a site in a way
that assumes that the site is present in the common ancestor of the two
species. Ours does not make this assumption. It is inspired by theirs,
but differs in this detail. Their distance also assumes a Jukes-Cantor
(1969) model of base change, and does not allow for transitions being
more frequent than transversions. In this sense mine generalizes theres
somewhat. Their distance does include, as mine does as well, a
correction for Gamma distribution of rate of change among nucleotide
sites.
I have made their original distance available here
Restriction Fragments Distance
For restriction fragments data we use a different distance. If we
average over all restriction fragment lengths, each at its own expected
frequency, the probability that the fragment will still be in existence
after a certain amount of branch length, we must take into account the
probability that the two restriction sites at the ends of the fragment
do not mutate, and the probability that no new restriction site occurs
within the fragment in that amount of branch length. The result for a
restriction site length of s is:
Q2s
f = --------
2 - Qs
(The details of the derivation will be given in my forthcoming book
Inferring Phylogenies (to be published by Sinauer Associates in 2001).
Given the observed fraction of restriction sites retained, f, we can
solve a quadratic equation from the above expression for Qs. That makes
it easy to obtain a value of Q, and the branch length can then be
estimated by adjusting it so the probability of a base not changing is
equal to that value. Alternatively, if we use the Nei and Li (1979)
restriction fragments distance, this involves solving for g in the
nonlinear equation
g = [ f (3 - 2g) ]1/4
and then the distance is given by
d = - (2/r) loge(g)
where r is the length of the restriction site.
Comparing these two restriction fragments distances in a case where
their underlying DNA model is the same (which is when the
transition/transversion ratio of the modified model is set to 0.5), you
will find that they are very close to each other, differing very little
at small distances, with the modified distance become smaller than the
Nei/Li distance at larger distances. It will therefore matter very
little which one you use.
A Comment About RAPDs and AFLPs
Although these distances are designed for restriction sites and
restriction fragments data, they can be applied to RAPD and AFLP data
as well. RAPD (Randomly Amplified Polymorphic DNA) and AFLP (Amplified
Fragment Length Polymorphism) data consist of presence or absence of
individual bands on a gel. The bands are segments of DNA with PCR
primers at each end. These primers are defined sequences of known
length (often about 10 nucleotides each). For AFLPs the reolevant
length is the primer length, plus three nucleotides. Mutation in these
sequences makes them no longer be primers, just as in the case of
restriction sites. Thus a pair of 10-nucleotide primers will behave
much the same as a 20-nucleotide restriction site, for RAPDs (26 for
AFLPs). You can use the restriction sites distance as the distance
between RAPD or AFLP patterns if you set the proper value for the total
length of the site to the total length of the primers (plus 6 in the
case of AFLPs). Of course there are many possible sources of noise in
these data, including confusing fragments of similar length for each
other and having primers near each other in the genome, and these are
not taken into account in the statistical model used here.
Usage
Here is a sample session with frestdist
% frestdist
Calculate distance matrix from restriction sites or fragments
Input file: restdist.dat
Phylip restdist program output file [restdist.frestdist]:
Restriction site or fragment distances, version 3.69.650
Distances calculated for species
Alpha ....
Beta ...
Gamma ..
Delta .
Epsilon
Distances written to file "restdist.frestdist"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Calculate distance matrix from restriction sites or fragments
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-data] discretestates File containing one or more sets of
restriction data
[-outfile] outfile [*.frestdist] Phylip restdist program output
file
Additional (Optional) qualifiers (* if not always prompted):
-[no]restsites boolean [Y] Restriction sites (put N if you want
restriction fragments)
-neili boolean [N] Use original Nei/Li model (default uses
modified Nei/Li model)
* -gammatype boolean [N] Gamma distributed rates among sites
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
-ttratio float [2.0] Transition/transversion ratio (Number
0.001 or more)
-sitelength integer [6] Site length (Integer 1 or more)
-lower boolean [N] Lower triangular distance matrix
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
frestdist input is fairly standard, with one addition. As usual the
first line of the file gives the number of species and the number of
sites, but there is also a third number, which is the number of
different restriction enzymes that were used to detect the restriction
sites. Thus a data set with 10 species and 35 different sites,
representing digestion with 4 different enzymes, would have the first
line of the data file look like this:
10 35 4
The site data are in standard form. Each species starts with a species
name whose maximum length is given by the constant "nmlngth" (whose
value in the program as distributed is 10 characters). The name should,
as usual, be padded out to that length with blanks if necessary. The
sites data then follows, one character per site (any blanks will be
skipped and ignored). Like the DNA and protein sequence data, the
restriction sites data may be either in the "interleaved" form or the
"sequential" form. Note that if you are analyzing restriction sites
data with the programs DOLLOP or MIX or other discrete character
programs, at the moment those programs do not use the "aligned" or
"interleaved" data format. Therefore you may want to avoid that format
when you have restriction sites data that you will want to feed into
those programs.
The presence of a site is indicated by a "+" and the absence by a "-".
I have also allowed the use of "1" and "0" as synonyms for "+" and "-",
for compatibility with MIX and DOLLOP which do not allow "+" and "-".
If the presence of the site is unknown (for example, if the DNA
containing it has been deleted so that one does not know whether it
would have contained the site) then the state "?" can be used to
indicate that the state of this site is unknown.
Input files for usage example
File: restdist.dat
5 13 2
Alpha ++-+-++--+++-
Beta ++++--+--+++-
Gamma -+--+-++-+-++
Delta ++-+----++---
Epsilon ++++----++---
Output file format
frestdist output contains on its first line the number of species. The
distance matrix is then printed in standard form, with each species
starting on a new line with the species name, followed by the distances
to the species in order. These continue onto a new line after every
nine distances. If the L option is used, the matrix or distances is in
lower triangular form, so that only the distances to the other species
that precede each species are printed. Otherwise the distance matrix is
square with zero distances on the diagonal. In general the format of
the distance matrix is such that it can serve as input to any of the
distance matrix programs.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the menu
selections. The output file begins by giving the number of species and
the number of characters.
The distances printed out are scaled in terms of expected numbers of
substitutions per DNA site, counting both transitions and transversions
but not replacements of a base by itself, and scaled so that the
average rate of change, averaged over all sites analyzed, is set to
1.0. Thus when the G option is used, the rate of change at one site may
be higher than at another, but their mean is expected to be 1.
Output files for usage example
File: restdist.frestdist
5
Alpha 0.000000 0.022368 0.107681 0.082639 0.095581
Beta 0.022368 0.000000 0.107681 0.082639 0.056895
Gamma 0.107681 0.107681 0.000000 0.192466 0.207319
Delta 0.082639 0.082639 0.192466 0.000000 0.015945
Epsilon 0.095581 0.056895 0.207319 0.015945 0.000000
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdnamove.txt 0000664 0001750 0001750 00000026257 12171064331 015741 0000000 0000000 fdnamove
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Interactive DNA parsimony
Description
Interactive construction of phylogenies from nucleic acid sequences,
with their evaluation by parsimony and compatibility and the display of
reconstructed ancestral bases. This can be used to find parsimony or
compatibility estimates by hand.
Algorithm
DNAMOVE is an interactive DNA parsimony program, inspired by Wayne
Maddison and David and Wayne Maddison's marvellous program MacClade,
which is written for Macintosh computers. DNAMOVE reads in a data set
which is prepared in almost the same format as one for the DNA
parsimony program DNAPARS. It allows the user to choose an initial
tree, and displays this tree on the screen. The user can look at
different sites and the way the nucleotide states are distributed on
that tree, given the most parsimonious reconstruction of state changes
for that particular tree. The user then can specify how the tree is to
be rearraranged, rerooted or written out to a file. By looking at
different rearrangements of the tree the user can manually search for
the most parsimonious tree, and can get a feel for how different sites
are affected by changes in the tree topology.
This program uses graphic characters that show the tree to best
advantage on some computer systems. Its graphic characters will work
best on MSDOS systems or MSDOS windows in Windows, and to any system
whose screen or terminals emulate ANSI standard terminals such as old
Digital VT100 terminals, Telnet programs, or VT100-compatible windows
in the X windowing system. For any other screen types, (such as
Macintosh windows) there is a generic option which does not make use of
screen graphics characters. The program will work well in those cases,
but the tree it displays will look a bit uglier.
This program carries out unrooted parsimony (analogous to Wagner trees)
(Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA sequences. The
method of Fitch (1971) is used to count the number of changes of base
needed on a given tree.
The assumptions of this method are exactly analogous to those of MIX:
1. Each site evolves independently.
2. Different lineages evolve independently.
3. The probability of a base substitution at a given site is small
over the lengths of time involved in a branch of the phylogeny.
4. The expected amounts of change in different branches of the
phylogeny do not vary by so much that two changes in a high-rate
branch are more probable than one change in a low-rate branch.
5. The expected amounts of change do not vary enough among sites that
two changes in one site are more probable than one change in
another.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b,
1988b). For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
Change from an occupied site to a deletion is counted as one change.
Reversion from a deletion to an occupied site is allowed and is also
counted as one change.
Usage
Here is a sample session with fdnamove
% fdnamove
Interactive DNA parsimony
Input (aligned) nucleotide sequence set(s): dnamove.dat
Phylip tree file (optional):
NEXT (R # + - S . T U W O F H J K L C ? X Q) (? for Help): Q
Do you want to write out the tree to a file? (Y or N): Y
5 species, 13 sites
Computing steps needed for compatibility in sites ...
(unrooted) 19.0 Steps 11 sites compatible
,-----------5:Epsilon
--9
! ,--------4:Delta
`--8
! ,-----3:Gamma
`--7
! ,--2:Beta
`--6
`--1:Alpha
Tree written to file "dnamove.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
Interactive DNA parsimony
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall (Aligned) nucleotide sequence set(s)
filename and optional format, or reference
(input USA)
[-intreefile] tree Phylip tree file (optional)
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file - ignore sites with weight zero
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 1.000 or more)
-initialtree menu [Arbitary] Initial tree (Values: a
(Arbitary); u (User); s (Specify))
-screenwidth integer [80] Width of terminal screen in characters
(Any integer value)
-screenlines integer [24] Number of lines on screen (Any integer
value)
-outtreefile outfile [*.fdnamove] Phylip tree output file
(optional)
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdnamove reads any normal sequence USAs.
Input files for usage example
File: dnamove.dat
5 13
Alpha AACGUGGCCA AAU
Beta AAGGUCGCCA AAC
Gamma CAUUUCGUCA CAA
Delta GGUAUUUCGG CCU
Epsilon GGGAUCUCGG CCC
Output file format
fdnamove outputs a graph to the specified graphics device. outputs a
report format file. The default format is ...
Output files for usage example
File: dnamove.treefile
(Epsilon,(Delta,(Gamma,(Beta,Alpha))));
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdolpenny.txt 0000664 0001750 0001750 00000066430 12171064331 016135 0000000 0000000 fdolpenny
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Penny algorithm Dollo or polymorphism
Description
Finds all most parsimonious phylogenies for discrete-character data
with two states, for the Dollo or polymorphism parsimony criteria using
the branch-and-bound method of exact search. May be impractical
(depending on the data) for more than 10-11 species.
Algorithm
DOLPENNY is a program that will find all of the most parsimonious trees
implied by your data when the Dollo or polymorphism parsimony criteria
are employed. It does so not by examining all possible trees, but by
using the more sophisticated "branch and bound" algorithm, a standard
computer science search strategy first applied to phylogenetic
inference by Hendy and Penny (1982). (J. S. Farris [personal
communication, 1975] had also suggested that this strategy, which is
well-known in computer science, might be applied to phylogenies, but he
did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem of
finding these has been shown (Graham and Foulds, 1982; Day, 1983) to be
NP-complete, which is equivalent to saying that there is no fast
algorithm that is guaranteed to solve the problem in all cases (for a
discussion of NP-completeness, see the Scientific American article by
Lewis and Papadimitriou, 1978). The result is that this program,
despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs in
the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of
someone who can let a microcomputer grind all night than for someone
who has the "benefit" of paying for time on the campus mainframe
computer). IT IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE
PROGRAM WILL TAKE ON YOUR DATA. This can be done by running it on
subsets of the species, increasing the number of species in the run
until you either are able to treat the full data set or know that the
program will take unacceptably long on it. (Making a plot of the
logarithm of run time against species number may help to project run
times).
The Algorithm
The search strategy used by DOLPENNY starts by making a tree consisting
of the first two species (the first three if the tree is to be
unrooted). Then it tries to add the next species in all possible places
(there are three of these). For each of the resulting trees it
evaluates the number of losses. It adds the next species to each of
these, again in all possible spaces. If this process would continue it
would simply generate all possible trees, of which there are a very
large number even when the number of species is moderate (34,459,425
with 10 species). Actually it does not do this, because the trees are
generated in a particular order and some of them are never generated.
Actually the order in which trees are generated is not quite as implied
above, but is a "depth-first search". This means that first one adds
the third species in the first possible place, then the fourth species
in its first possible place, then the fifth and so on until the first
possible tree has been produced. Its number of steps is evaluated. Then
one "backtracks" by trying the alternative placements of the last
species. When these are exhausted one tries the next placement of the
next-to-last species. The order of placement in a depth-first search is
like this for a four-species case (parentheses enclose monophyletic
groups):
Make tree of first two species (A,B)
Add C in first place ((A,B),C)
Add D in first place (((A,D),B),C)
Add D in second place ((A,(B,D)),C)
Add D in third place (((A,B),D),C)
Add D in fourth place ((A,B),(C,D))
Add D in fifth place (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place (((A,D),C),B)
Add D in second place ((A,(C,D)),B)
Add D in third place (((A,C),D),B)
Add D in fourth place ((A,C),(B,D))
Add D in fifth place (((A,C),B),D)
Add C in third place (A,(B,C))
Add D in first place ((A,D),(B,C))
Add D in second place (A,((B,D),C))
Add D in third place (A,(B,(C,D)))
Add D in fourth place (A,((B,C),D))
Add D in fifth place ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species rooted
bifurcating trees, each exactly once (the parentheses each enclose a
monophyletic group). As displayed above, the backtracking depth-first
search algorithm is just another way of producing all possible trees
one at a time. The branch and bound algorithm consists of this with one
change. As each tree is constructed, including the partial trees such
as (A,(B,C)), its number of losses (or retentions of polymorphism) is
evaluated.
The point of this is that if a previously-found tree such as
((A,B),(C,D)) required fewer losses, then we know that there is no
point in even trying to add D to ((A,C),B). We have computed the bound
that enables us to cut off a whole line of inquiry (in this case five
trees) and avoid going down that particular branch any farther.
The branch-and-bound algorithm thus allows us to find all most
parsimonious trees without generating all possible trees. How much of a
saving this is depends strongly on the data. For very clean (nearly
"Hennigian") data, it saves much time, but on very messy data it will
still take a very long time.
The algorithm in the program differs from the one outlined here in some
essential details: it investigates possibilities in the order of their
apparent promise. This applies to the order of addition of species, and
to the places where they are added to the tree. After the first
two-species tree is constructed, the program tries adding each of the
remaining species in turn, each in the best possible place it can find.
Whichever of those species adds (at a minimum) the most additional
steps is taken to be the one to be added next to the tree. When it is
added, it is added in turn to places which cause the fewest additional
steps to be added. This sounds a bit complex, but it is done with the
intention of eliminating regions of the search of all possible trees as
soon as possible, and lowering the bound on tree length as quickly as
possible.
The program keeps a list of all the most parsimonious trees found so
far. Whenever it finds one that has fewer losses than these, it clears
out the list and restarts the list with that tree. In the process the
bound tightens and fewer possibilities need be investigated. At the end
the list contains all the shortest trees. These are then printed out.
It should be mentioned that the program CLIQUE for finding all largest
cliques also works by branch-and-bound. Both problems are NP-complete
but for some reason CLIQUE runs far faster. Although their worst-case
behavior is bad for both programs, those worst cases occur far more
frequently in parsimony problems than in compatibility problems.
Controlling Run Times
Among the quantities available to be set at the beginning of a run of
DOLPENNY, two (howoften and howmany) are of particular importance. As
DOLPENNY goes along it will keep count of how many trees it has
examined. Suppose that howoften is 100 and howmany is 300, the default
settings. Every time 100 trees have been examined, DOLPENNY will print
out a line saying how many multiples of 100 trees have now been
examined, how many steps the most parsimonious tree found so far has,
how many trees of with that number of steps have been found, and a very
rough estimate of what fraction of all trees have been looked at so
far.
When the number of these multiples printed out reaches the number
howmany (say 1000), the whole algorithm aborts and prints out that it
has not found all most parsimonious trees, but prints out what is has
got so far anyway. These trees need not be any of the most parsimonious
trees: they are simply the most parsimonious ones found so far. By
setting the product (howoften X howmany) large you can make the
algorithm less likely to abort, but then you risk getting bogged down
in a gigantic computation. You should adjust these constants so that
the program cannot go beyond examining the number of trees you are
reasonably willing to pay for (or wait for). In their initial setting
the program will abort after looking at 100,000 trees. Obviously you
may want to adjust howoften in order to get more or fewer lines of
intermediate notice of how many trees have been looked at so far. Of
course, in small cases you may never even reach the first multiple of
howoften and nothing will be printed out except some headings and then
the final trees.
The indication of the approximate percentage of trees searched so far
will be helpful in judging how much farther you would have to go to get
the full search. Actually, since that fraction is the fraction of the
set of all possible trees searched or ruled out so far, and since the
search becomes progressively more efficient, the approximate fraction
printed out will usually be an underestimate of how far along the
program is, sometimes a serious underestimate.
A constant that affects the result is "maxtrees", which controls the
maximum number of trees that can be stored. Thus if "maxtrees" is 25,
and 32 most parsimonious trees are found, only the first 25 of these
are stored and printed out. If "maxtrees" is increased, the program
does not run any slower but requires a little more intermediate storage
space. I recommend that "maxtrees" be kept as large as you can,
provided you are willing to look at an output with that many trees on
it! Initially, "maxtrees" is set to 100 in the distribution copy.
Methods and Options
The counting of the length of trees is done by an algorithm nearly
identical to the corresponding algorithms in DOLLOP, and thus the
remainder of this document will be nearly identical to the DOLLOP
document. The Dollo parsimony method was first suggested in print in
verbal form by Le Quesne (1974) and was first well-specified by Farris
(1977). The method is named after Louis Dollo since he was one of the
first to assert that in evolution it is harder to gain a complex
feature than to lose it. The algorithm explains the presence of the
state 1 by allowing up to one forward change 0-->1 and as many
reversions 1-->0 as are necessary to explain the pattern of states
seen. The program attempts to minimize the number of 1-->0 reversions
necessary.
The assumptions of this method are in effect:
1. We know which state is the ancestral one (state 0).
2. The characters are evolving independently.
3. Different lineages evolve independently.
4. The probability of a forward change (0-->1) is small over the
evolutionary times involved.
5. The probability of a reversion (1-->0) is also small, but still far
larger than the probability of a forward change, so that many
reversions are easier to envisage than even one extra forward
change.
6. Retention of polymorphism for both states (0 and 1) is highly
improbable.
7. The lengths of the segments of the true tree are not so unequal
that two changes in a long segment are as probable as one in a
short segment.
That these are the assumptions is established in several of my papers
(1973a, 1978b, 1979, 1981b, 1983). For an opposing view arguing that
the parsimony methods make no substantive assumptions such as these,
see the papers by Farris (1983) and Sober (1983a, 1983b), but also read
the exchange between Felsenstein and Sober (1986).
One problem can arise when using additive binary recoding to represent
a multistate character as a series of two-state characters. Unlike the
Camin-Sokal, Wagner, and Polymorphism methods, the Dollo method can
reconstruct ancestral states which do not exist. An example is given in
my 1979 paper. It will be necessary to check the output to make sure
that this has not occurred.
The polymorphism parsimony method was first used by me, and the results
published (without a clear specification of the method) by Inger
(1967). The method was published by Farris (1978a) and by me (1979).
The method assumes that we can explain the pattern of states by no more
than one origination (0-->1) of state 1, followed by retention of
polymorphism along as many segments of the tree as are necessary,
followed by loss of state 0 or of state 1 where necessary. The program
tries to minimize the total number of polymorphic characters, where
each polymorphism is counted once for each segment of the tree in which
it is retained.
The assumptions of the polymorphism parsimony method are in effect:
1. The ancestral state (state 0) is known in each character.
2. The characters are evolving independently of each other.
3. Different lineages are evolving independently.
4. Forward change (0-->1) is highly improbable over the length of time
involved in the evolution of the group.
5. Retention of polymorphism is also improbable, but far more probable
that forward change, so that we can more easily envisage much
polymorhism than even one additional forward change.
6. Once state 1 is reached, reoccurrence of state 0 is very
improbable, much less probable than multiple retentions of
polymorphism.
7. The lengths of segments in the true tree are not so unequal that we
can more easily envisage retention events occurring in both of two
long segments than one retention in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b,
1988b). For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
Usage
Here is a sample session with fdolpenny
% fdolpenny
Penny algorithm Dollo or polymorphism
Phylip character discrete states file: dolpenny.dat
Phylip dolpenny program output file [dolpenny.fdolpenny]:
How many
trees looked Approximate
at so far Length of How many percentage
(multiples shortest tree trees this long searched
of 100): found so far found so far so far
---------- ------------ ------------ ------------
1 3.00000 1 0.95
Output written to file "dolpenny.fdolpenny"
Trees also written onto file "dolpenny.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
Penny algorithm Dollo or polymorphism
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-outfile] outfile [*.fdolpenny] Phylip dolpenny program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-ancfile properties Ancestral states file
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 0.000 or more)
-howmany integer [1000] How many groups of trees (Any integer
value)
-howoften integer [100] How often to report, in trees (Any
integer value)
-[no]simple boolean [Y] Branch and bound is simple
-method menu [d] Parsimony method (Values: d (Dollo); p
(Polymorphism))
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdolpenny] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-ancseq boolean [N] Print states at all nodes of tree
-stepbox boolean [N] Print out steps in each character
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdolpenny reads discrete character data with "?", "P", "B" states
allowed. .
(0,1) Discrete character data
These programs are intended for the use of morphological systematists
who are dealing with discrete characters, or by molecular evolutionists
dealing with presence-absence data on restriction sites. One of the
programs (PARS) allows multistate characters, with up to 8 states, plus
the unknown state symbol "?". For the others, the characters are
assumed to be coded into a series of (0,1) two-state characters. For
most of the programs there are two other states possible, "P", which
stands for the state of Polymorphism for both states (0 and 1), and
"?", which stands for the state of ignorance: it is the state
"unknown", or "does not apply". The state "P" can also be denoted by
"B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding a
multistate character into a series of two-state (0,1) characters.
Suppose we had a character with four states whose character-state tree
had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We can
represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE, DOLPENNY
and DOLBOOT the multistate recoding does not necessarily work properly,
as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected in
a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for unordered
character states.
Input files for usage example
File: dolpenny.dat
7 6
Alpha1 110110
Alpha2 110110
Beta1 110000
Beta2 110000
Gamma1 100110
Delta 001001
Epsilon 001110
Output file format
fdolpenny output format is standard. It includes a rooted tree and, if
the user selects option 4, a table of the numbers of reversions or
retentions of polymorphism necessary in each character. If any of the
ancestral states has been specified to be unknown, a table of
reconstructed ancestral states is also provided. When reconstructing
the placement of forward changes and reversions under the Dollo method,
keep in mind that each polymorphic state in the input data will require
one "last minute" reversion. This is included in the tabulated counts.
Thus if we have both states 0 and 1 at a tip of the tree the program
will assume that the lineage had state 1 up to the last minute, and
then state 0 arose in that population by reversion, without loss of
state 1.
A table is available to be printed out after each tree, showing for
each branch whether there are known to be changes in the branch, and
what the states are inferred to have been at the top end of the branch.
If the inferred state is a "?" there will be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand.
If the A option is used, then the program will infer, for any character
whose ancestral state is unknown ("?") whether the ancestral state 0 or
1 will give the best tree. If these are tied, then it may not be
possible for the program to infer the state in the internal nodes, and
these will all be printed as ".". If this has happened and you want to
know more about the states at the internal nodes, you will find helpful
to use DOLMOVE to display the tree and examine its interior states, as
the algorithm in DOLMOVE shows all that can be known in this case about
the interior states, including where there is and is not amibiguity.
The algorithm in DOLPENNY gives up more easily on displaying these
states.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is needed
when we use the trees to make a consensus tree of the results of
bootstrapping or jackknifing, to avoid overrepresenting replicates that
find many tied trees.
Output files for usage example
File: dolpenny.fdolpenny
Penny algorithm for Dollo or polymorphism parsimony, version 3.69.650
branch-and-bound to find all most parsimonious trees
requires a total of 3.000
3 trees in all found
+-----------------Delta
!
--2 +--------------Epsilon
! !
+--3 +-----------Gamma1
! !
+--6 +--------Alpha2
! !
+--1 +--Beta2
! +--5
+--4 +--Beta1
!
+-----Alpha1
+-----------------Delta
!
--2 +--------------Epsilon
! !
+--3 +-----------Gamma1
! !
+--6 +--Beta2
! +-----5
! ! +--Beta1
+--4
! +--Alpha2
+-----1
+--Alpha1
+-----------------Delta
!
--2 +--------------Epsilon
! !
+--3 +-----------Gamma1
! !
! ! +--Beta2
+--6 +--5
! +--4 +--Beta1
! ! !
+--1 +-----Alpha2
!
+--------Alpha1
File: dolpenny.treefile
(Delta,(Epsilon,(Gamma1,(Alpha2,((Beta2,Beta1),Alpha1)))))[0.3333];
(Delta,(Epsilon,(Gamma1,((Beta2,Beta1),(Alpha2,Alpha1)))))[0.3333];
(Delta,(Epsilon,(Gamma1,(((Beta2,Beta1),Alpha2),Alpha1))))[0.3333];
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
eclique Largest clique program
edollop Dollo and polymorphism parsimony algorithm
edolpenny Penny algorithm Dollo or polymorphism
efactor Multistate to binary recoding program
emix Mixed parsimony algorithm
epenny Penny algorithm, branch-and-bound
fclique Largest clique program
fdollop Dollo and polymorphism parsimony algorithm
ffactor Multistate to binary recoding program
fmix Mixed parsimony algorithm
fmove Interactive mixed method parsimony
fpars Discrete character parsimony
fpenny Penny algorithm, branch-and-bound
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fgendist.txt 0000664 0001750 0001750 00000044773 12171064331 015750 0000000 0000000 fgendist
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Compute genetic distances from gene frequencies
Description
Computes one of three different genetic distance formulas from gene
frequency data. The formulas are Nei's genetic distance, the
Cavalli-Sforza chord measure, and the genetic distance of Reynolds et.
al. The former is appropriate for data in which new mutations occur in
an infinite isoalleles neutral mutation model, the latter two for a
model without mutation and with pure genetic drift. The distances are
written to a file in a format appropriate for input to the distance
matrix programs.
Algorithm
This program computes any one of three measures of genetic distance
from a set of gene frequencies in different populations (or species).
The three are Nei's genetic distance (Nei, 1972), Cavalli-Sforza's
chord measure (Cavalli- Sforza and Edwards, 1967) and Reynolds, Weir,
and Cockerham's (1983) genetic distance. These are written to an output
file in a format that can be read by the distance matrix phylogeny
programs FITCH and KITSCH.
The three measures have somewhat different assumptions. All assume that
all differences between populations arise from genetic drift. Nei's
distance is formulated for an infinite isoalleles model of mutation, in
which there is a rate of neutral mutation and each mutant is to a
completely new alleles. It is assumed that all loci have the same rate
of neutral mutation, and that the genetic variability initially in the
population is at equilibrium between mutation and genetic drift, with
the effective population size of each population remaining constant.
Nei's distance is:
\ \
/_ /_ p1mi p2mi
m i
D = - ln ( ------------------------------------- ).
\ \ \ \
[ /_ /_ p1mi2]1/2 [ /_ /_ p2mi2]1/2
m i m i
where m is summed over loci, i over alleles at the m-th locus, and
where
p1mi
is the frequency of the i-th allele at the m-th locus in population 1.
Subject to the above assumptions, Nei's genetic distance is expected,
for a sample of sufficiently many equivalent loci, to rise linearly
with time.
The other two genetic distances assume that there is no mutation, and
that all gene frequency changes are by genetic drift alone. However
they do not assume that population sizes have remained constant and
equal in all populations. They cope with changing population size by
having expectations that rise linearly not with time, but with the sum
over time of 1/N, where N is the effective population size. Thus if
population size doubles, genetic drift will be taking place more
slowly, and the genetic distance will be expected to be rising only
half as fast with respect to time. Both genetic distances are different
estimators of the same quantity under the same model.
Cavalli-Sforza's chord distance is given by
\ \ \
D2 = 4 /_ [ 1 - /_ p1mi1/2 p 2mi1/2] / /_ (am - 1)
m i m
where m indexes the loci, where i is summed over the alleles at the
m-th locus, and where a is the number of alleles at the m-th locus. It
can be shown that this distance always satisfies the triangle
inequality. Note that as given here it is divided by the number of
degrees of freedom, the sum of the numbers of alleles minus one. The
quantity which is expected to rise linearly with amount of genetic
drift (sum of 1/N over time) is D squared, the quantity computed above,
and that is what is written out into the distance matrix.
Reynolds, Weir, and Cockerham's (1983) genetic distance is
\ \
/_ /_ [ p1mi - p2mi]2
m i
D2 = --------------------------------------
\ \
2 /_ [ 1 - /_ p1mi p2mi ]
m i
where the notation is as before and D2 is the quantity that is expected
to rise linearly with cumulated genetic drift.
Having computed one of these genetic distances, one which you feel is
appropriate to the biology of the situation, you can use it as the
input to the programs FITCH, KITSCH or NEIGHBOR. Keep in mind that the
statistical model in those programs implicitly assumes that the
distances in the input table have independent errors. For any measure
of genetic distance this will not be true, as bursts of random genetic
drift, or sampling events in drawing the sample of individuals from
each population, cause fluctuations of gene frequency that affect many
distances simultaneously. While this is not expected to bias the
estimate of the phylogeny, it does mean that the weighing of evidence
from all the different distances in the table will not be done with
maximal efficiency. One issue is which value of the P (Power) parameter
should be used. This depends on how the variance of a distance rises
with its expectation. For Cavalli-Sforza's chord distance, and for the
Reynolds et. al. distance it can be shown that the variance of the
distance will be proportional to the square of its expectation; this
suggests a value of 2 for P, which the default value for FITCH and
KITSCH (there is no P option in NEIGHBOR).
If you think that the pure genetic drift model is appropriate, and are
thus tempted to use the Cavalli-Sforza or Reynolds et. al. distances,
you might consider using the maximum likelihood program CONTML instead.
It will correctly weigh the evidence in that case. Like those genetic
distances, it uses approximations that break down as loci start to
drift all the way to fixation. Although Nei's distance will not break
down in that case, it makes other assumptions about equality of
substitution rates at all loci and constancy of population sizes.
qThe most important thing to remember is that genetic distance is not
an abstract, idealized measure of "differentness". It is an estimate of
a parameter (time or cumulated inverse effective population size) of
the model which is thought to have generated the differences we see. As
an estimate, it has statistical properties that can be assessed, and we
should never have to choose between genetic distances based on their
aesthetic properties, or on the personal prestige of their originators.
Considering them as estimates focuses us on the questions which genetic
distances are intended to answer, for if there are none there is no
reason to compute them. For further perspective on genetic distances, I
recommend my own paper evaluating Reynolds, Weir, and Cockerham (1983),
and the material in Nei's book (Nei, 1987).
Usage
Here is a sample session with fgendist
% fgendist
Compute genetic distances from gene frequencies
Phylip gendist program input file: gendist.dat
Phylip gendist program output file [gendist.fgendist]:
Distances calculated for species
European .
African ..
Chinese ...
American ....
Australian .....
Distances written to file "gendist.fgendist"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Compute genetic distances from gene frequencies
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] frequencies File containing one or more sets of data
[-outfile] outfile [*.fgendist] Phylip gendist program output
file
Additional (Optional) qualifiers:
-method menu [n] Which method to use (Values: n (Nei
genetic distance); c (Cavalli-Sforza chord
measure); r (Reynolds genetic distance))
-[no]progress boolean [Y] Print indications of progress of run
-lower boolean [N] Lower triangular distance matrix
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fgendist reads continuous character data
Continuous character data
The programs in this group use gene frequencies and quantitative
character values. One (CONTML) constructs maximum likelihood estimates
of the phylogeny, another (GENDIST) computes genetic distances for use
in the distance matrix programs, and the third (CONTRAST) examines
correlation of traits as they evolve along a given phylogeny.
When the gene frequencies data are used in CONTML or GENDIST, this
involves the following assumptions:
1. Different lineages evolve independently.
2. After two lineages split, their characters change independently.
3. Each gene frequency changes by genetic drift, with or without
mutation (this varies from method to method).
4. Different loci or characters drift independently.
How these assumptions affect the methods will be seen in my papers on
inference of phylogenies from gene frequency and continuous character
data (Felsenstein, 1973b, 1981c, 1985c).
The input formats are fairly similar to the discrete-character
programs, but with one difference. When CONTML is used in the
gene-frequency mode (its usual, default mode), or when GENDIST is used,
the first line contains the number of species (or populations) and the
number of loci and the options information. There then follows a line
which gives the numbers of alleles at each locus, in order. This must
be the full number of alleles, not the number of alleles which will be
input: i. e. for a two-allele locus the number should be 2, not 1.
There then follow the species (population) data, each species beginning
on a new line. The first 10 characters are taken as the name, and
thereafter the values of the individual characters are read
free-format, preceded and separated by blanks. They can go to a new
line if desired, though of course not in the middle of a number.
Missing data is not allowed - an important limitation. In the default
configuration, for each locus, the numbers should be the frequencies of
all but one allele. The menu option A (All) signals that the
frequencies of all alleles are provided in the input data -- the
program will then automatically ignore the last of them. So without the
A option, for a three-allele locus there should be two numbers, the
frequencies of two of the alleles (and of course it must always be the
same two!). Here is a typical data set without the A option:
5 3
2 3 2
Alpha 0.90 0.80 0.10 0.56
Beta 0.72 0.54 0.30 0.20
Gamma 0.38 0.10 0.05 0.98
Delta 0.42 0.40 0.43 0.97
Epsilon 0.10 0.30 0.70 0.62
whereas here is what it would have to look like if the A option were
invoked:
5 3
2 3 2
Alpha 0.90 0.10 0.80 0.10 0.10 0.56 0.44
Beta 0.72 0.28 0.54 0.30 0.16 0.20 0.80
Gamma 0.38 0.62 0.10 0.05 0.85 0.98 0.02
Delta 0.42 0.58 0.40 0.43 0.17 0.97 0.03
Epsilon 0.10 0.90 0.30 0.70 0.00 0.62 0.38
The first line has the number of species (or populations) and the
number of loci. The second line has the number of alleles for each of
the 3 loci. The species lines have names (filled out to 10 characters
with blanks) followed by the gene frequencies of the 2 alleles for the
first locus, the 3 alleles for the second locus, and the 2 alleles for
the third locus. You can start a new line after any of these allele
frequencies, and continue to give the frequencies on that line (without
repeating the species name).
If all alleles of a locus are given, it is important to have them add
up to 1. Roundoff of the frequencies may cause the program to conclude
that the numbers do not sum to 1, and stop with an error message.
While many compilers may be more tolerant, it is probably wise to make
sure that each number, including the first, is preceded by a blank, and
that there are digits both preceding and following any decimal points.
CONTML and CONTRAST also treat quantitative characters (the
continuous-characters mode in CONTML, which is option C). It is assumed
that each character is evolving according to a Brownian motion model,
at the same rate, and independently. In reality it is almost always
impossible to guarantee this. The issue is discussed at length in my
review article in Annual Review of Ecology and Systematics
(Felsenstein, 1988a), where I point out the difficulty of transforming
the characters so that they are not only genetically independent but
have independent selection acting on them. If you are going to use
CONTML to model evolution of continuous characters, then you should at
least make some attempt to remove genetic correlations between the
characters (usually all one can do is remove phenotypic correlations by
transforming the characters so that there is no within-population
covariance and so that the within-population variances of the
characters are equal -- this is equivalent to using Canonical
Variates). However, this will only guarantee that one has removed
phenotypic covariances between characters. Genetic covariances could
only be removed by knowing the coheritabilities of the characters,
which would require genetic experiments, and selective covariances
(covariances due to covariation of selection pressures) would require
knowledge of the sources and extent of selection pressure in all
variables.
CONTRAST is a program designed to infer, for a given phylogeny that is
provided to the program, the covariation between characters in a data
set. Thus we have a program in this set that allow us to take
information about the covariation and rates of evolution of characters
and make an estimate of the phylogeny (CONTML), and a program that
takes an estimate of the phylogeny and infers the variances and
covariances of the character changes. But we have no program that
infers both the phylogenies and the character covariation from the same
data set.
In the quantitative characters mode, a typical small data set would be:
5 6
Alpha 0.345 0.467 1.213 2.2 -1.2 1.0
Beta 0.457 0.444 1.1 1.987 -0.2 2.678
Gamma 0.6 0.12 0.97 2.3 -0.11 1.54
Delta 0.68 0.203 0.888 2.0 1.67
Epsilon 0.297 0.22 0.90 1.9 1.74
Note that in the latter case, there is no line giving the numbers of
alleles at each locus. In this latter case no square-root
transformation of the coordinates is done: each is assumed to give
directly the position on the Brownian motion scale.
For further discussion of options and modifiable constants in CONTML,
GENDIST, and CONTRAST see the documentation files for those programs.
Input files for usage example
File: gendist.dat
5 10
2 2 2 2 2 2 2 2 2 2
European 0.2868 0.5684 0.4422 0.4286 0.3828 0.7285 0.6386 0.0205
0.8055 0.5043
African 0.1356 0.4840 0.0602 0.0397 0.5977 0.9675 0.9511 0.0600
0.7582 0.6207
Chinese 0.1628 0.5958 0.7298 1.0000 0.3811 0.7986 0.7782 0.0726
0.7482 0.7334
American 0.0144 0.6990 0.3280 0.7421 0.6606 0.8603 0.7924 0.0000
0.8086 0.8636
Australian 0.1211 0.2274 0.5821 1.0000 0.2018 0.9000 0.9837 0.0396
0.9097 0.2976
Output file format
fgendist output simply contains on its first line the number of species
(or populations). Each species (or population) starts a new line, with
its name printed out first, and then and there are up to nine genetic
distances printed on each line, in the standard format used as input by
the distance matrix programs. The output, in its default form, is ready
to be used in the distance matrix programs.
Output files for usage example
File: gendist.fgendist
5
European 0.000000 0.078002 0.080749 0.066805 0.103014
African 0.078002 0.000000 0.234698 0.104975 0.227281
Chinese 0.080749 0.234698 0.000000 0.053879 0.063275
American 0.066805 0.104975 0.053879 0.000000 0.134756
Australian 0.103014 0.227281 0.063275 0.134756 0.000000
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
egendist Genetic distance matrix program
fcontml Gene frequency and continuous character maximum likelihood
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdnamlk.txt 0000664 0001750 0001750 00000075525 12171064331 015560 0000000 0000000 fdnamlk
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Estimates nucleotide phylogeny by maximum likelihood
Description
Same as DNAML but assumes a molecular clock. The use of the two
programs together permits a likelihood ratio test of the molecular
clock hypothesis to be made.
Estimates phylogenies from nucleotide sequences by maximum likelihood.
The model employed allows for unequal expected frequencies of the four
nucleotides, for unequal rates of transitions and transversions, and
for different (prespecified) rates of change in different categories of
sites, and also use of a Hidden Markov model of rates, with the program
inferring which sites have which rates. This also allows
gamma-distribution and gamma-plus-invariant sites distributions of
rates across sites.
Algorithm
This program implements the maximum likelihood method for DNA sequences
under the constraint that the trees estimated must be consistent with a
molecular clock. The molecular clock is the assumption that the tips of
the tree are all equidistant, in branch length, from its root. This
program is indirectly related to DNAML. Details of the algorithm are
not yet published, but many aspects of it are similar to DNAML, and
these are published in the paper by Felsenstein and Churchill (1996).
The model of base substitution allows the expected frequencies of the
four bases to be unequal, allows the expected frequencies of
transitions and transversions to be unequal, and has several ways of
allowing different rates of evolution at different sites.
The assumptions of the model are:
1. Each site in the sequence evolves independently.
2. Different lineages evolve independently.
3. There is a molecular clock.
4. Each site undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of
occurrence) which we specify.
5. All relevant sites are included in the sequence, not just those
that have changed or those that are "phylogenetically informative".
6. A substitution consists of one of two sorts of events:
1. The first kind of event consists of the replacement of the
existing base by a base drawn from a pool of purines or a pool
of pyrimidines (depending on whether the base being replaced
was a purine or a pyrimidine). It can lead either to no change
or to a transition.
2. The second kind of event consists of the replacement of the
existing base by a base drawn at random from a pool of bases
at known frequencies, independently of the identity of the
base which is being replaced. This could lead either to a no
change, to a transition or to a transversion. The ratio of the
two purines in the purine replacement pool is the same as
their ratio in the overall pool, and similarly for the
pyrimidines.
The ratios of transitions to transversions can be set by the
user. The substitution process can be diagrammed as follows:
Suppose that you specified A, C, G, and T base frequencies of
0.24, 0.28, 0.27, and 0.21.
o First kind of event:
Determine whether the existing base is a purine or a
pyrimidine. Draw from the proper pool:
Purine pool: Pyrimidine pool:
| | | |
| 0.4706 A | | 0.5714 C |
| 0.5294 G | | 0.4286 T |
| (ratio is | | (ratio is |
| 0.24 : 0.27) | | 0.28 : 0.21) |
|_______________| |_______________|
o Second kind of event:
Draw from the overall pool:
| |
| 0.24 A |
| 0.28 C |
| 0.27 G |
| 0.21 T |
|__________________|
Note that if the existing base is, say, an A, the first kind of event
has a 0.4706 probability of "replacing" it by another A. The second
kind of event has a 0.24 chance of replacing it by another A. This
rather disconcerting model is used because it has nice mathematical
properties that make likelihood calculations far easier. A closely
similar, but not precisely identical model having different rates of
transitions and transversions has been used by Hasegawa et. al.
(1985b). The transition probability formulas for the current model were
given (with my permission) by Kishino and Hasegawa (1989). Another
explanation is available in the paper by Felsenstein and Churchill
(1996).
Note the assumption that we are looking at all sites, including those
that have not changed at all. It is important not to restrict attention
to some sites based on whether or not they have changed; doing that
would bias branch lengths by making them too long, and that in turn
would cause the method to misinterpret the meaning of those sites that
had changed.
This program uses a Hidden Markov Model (HMM) method of inferring
different rates of evolution at different sites. This was described in
a paper by me and Gary Churchill (1996). It allows us to specify to the
program that there will be a number of different possible evolutionary
rates, what the prior probabilities of occurrence of each is, and what
the average length of a patch of sites all having the same rate. The
rates can also be chosen by the program to approximate a Gamma
distribution of rates, or a Gamma distribution plus a class of
invariant sites. The program computes the the likelihood by summing it
over all possible assignments of rates to sites, weighting each by its
prior probability of occurrence.
For example, if we have used the C and A options (described below) to
specify that there are three possible rates of evolution, 1.0, 2.4, and
0.0, that the prior probabilities of a site having these rates are 0.4,
0.3, and 0.3, and that the average patch length (number of consecutive
sites with the same rate) is 2.0, the program will sum the likelihood
over all possibilities, but giving less weight to those that (say)
assign all sites to rate 2.4, or that fail to have consecutive sites
that have the same rate.
The Hidden Markov Model framework for rate variation among sites was
independently developed by Yang (1993, 1994, 1995). We have implemented
a general scheme for a Hidden Markov Model of rates; we allow the rates
and their prior probabilities to be specified arbitrarily by the user,
or by a discrete approximation to a Gamma distribution of rates (Yang,
1995), or by a mixture of a Gamma distribution and a class of invariant
sites.
This feature effectively removes the artificial assumption that all
sites have the same rate, and also means that we need not know in
advance the identities of the sites that have a particular rate of
evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each site (for example, we might want first,
second, and third codon positions in a protein coding sequence to be
three different categories. This is done with the categories input file
and the C option. We then specify (using the menu) the relative rates
of evolution of sites in the different categories. For example, we
might specify that first, second, and third positions evolve at
relative rates of 1.0, 0.8, and 2.7.
If both user-assigned rate categories and Hidden Markov Model rates are
allowed, the program assumes that the actual rate at a site is the
product of the user-assigned category rate and the Hidden Markov Model
regional rate. (This may not always make perfect biological sense: it
would be more natural to assume some upper bound to the rate, as we
have discussed in the Felsenstein and Churchill paper). Nevertheless
you may want to use both types of rate variation.
Usage
Here is a sample session with fdnamlk
% fdnamlk -printdata -ncategories 2 -categories "1111112222222" -rate "1.0 2.0"
-gammatype h -nhmmcategories 5 -hmmrates "0.264 1.413 3.596 7.086 12.641" -hmmpr
obabilities "0.522 0.399 0.076 0.0036 0.000023" -lambda 1.5 -weight "01111111111
10"
Estimates nucleotide phylogeny by maximum likelihood
Input (aligned) nucleotide sequence set(s): dnaml.dat
Phylip tree file (optional):
Phylip dnamlk program output file [dnaml.fdnamlk]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "dnaml.fdnamlk"
Tree also written onto file "dnaml.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Estimates nucleotide phylogeny by maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fdnamlk] Phylip dnamlk program output
file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
-ttratio float [2.0] Transition/transversion ratio (Number
0.001 or more)
-[no]freqsfrom toggle [Y] Use empirical base frequencies from
seqeunce input
* -basefreq array [0.25 0.25 0.25 0.25] Base frequencies for A
C G T/U (use blanks to separate)
-gammatype menu [Constant rate] Rate variation among sites
(Values: g (Gamma distributed rates); i
(Gamma+invariant sites); h (User defined HMM
of rates); n (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ngammacat integer [1] Number of categories (1-9) (Integer from
1 to 9)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ninvarcat integer [1] Number of categories (1-9) including one
for invariant sites (Integer from 1 to 9)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -nhmmcategories integer [1] Number of HMM rate categories (Integer
from 1 to 9)
* -hmmrates array [1.0] HMM category rates
* -hmmprobabilities array [1.0] Probability for each HMM category
* -adjsite boolean [N] Rates at adjacent sites correlated
* -lambda float [1.0] Mean block length of sites having the
same rate (Number 1.000 or more)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
* -lengths boolean [N] Use branch lengths from user trees
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnamlk] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-hypstate boolean [N] Reconstruct hypothetical sequence
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdnamlk reads any normal sequence USAs.
Input files for usage example
File: dnaml.dat
5 13
Alpha AACGTGGCCAAAT
Beta AAGGTCGCCAAAC
Gamma CATTTCGTCACAA
Delta GGTATTTCGGCCT
Epsilon GGGATCTCGGCCC
Output file format
--> fdnamlk output starts by giving the number of species, the number
of sites, and the base frequencies for A, C, G, and T that have been
specified. It then prints out the transition/transversion ratio that
was specified or used by default. It also uses the base frequencies to
compute the actual transition/transversion ratio implied by the
parameter.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of sites is printed, as well as
the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the menu
option to print them out, with the base sequences printed in groups of
ten bases along the lines of the Genbank and EMBL formats. The trees
found are printed as a rooted tree topology. The internal nodes are
numbered arbitrarily for the sake of identification. The number of
trees evaluated so far and the log likelihood of the tree are also
given. The branch lengths in the diagram are roughly proportional to
the estimated branch lengths, except that very short branches are
printed out at least three characters in length so that the connections
can be seen.
A table is printed showing the length of each tree segment, and the
time (in units of expected nucleotide substitutions per site) of each
fork in the tree, measured from the root of the tree. I have not
attempted in include code for approximate confidence limits on branch
points, as I have done for branch lengths in DNAML, both because of the
extreme crudeness of that test, and because the variation of times for
different forks would be highly correlated.
The log likelihood printed out with the final tree can be used to
perform various likelihood ratio tests. One can, for example, compare
runs with different values of the expected transition/transversion
ratio to determine which value is the maximum likelihood estimate, and
what is the allowable range of values (using a likelihood ratio test,
which you will find described in mathematical statistics books). One
could also estimate the base frequencies in the same way. Both of
these, particularly the latter, require multiple runs of the program to
evaluate different possible values, and this might get expensive.
This program makes possible a (reasonably) legitimate statistical test
of the molecular clock. To do such a test, run DNAML and DNAMLK on the
same data. If the trees obtained are of the same topology (when
considered as unrooted), it is legitimate to compare their likelihoods
by the likelihood ratio test. In DNAML the likelihood has been computed
by estimating 2n-3 branch lengths, if their are n tips on the tree. In
DNAMLK it has been computed by estimating n-1 branching times (in
effect, n-1 branch lengths). The difference in the number of parameters
is (2n-3)-(n-1) = n-2. To perform the test take the difference in log
likelihoods between the two runs (DNAML should be the higher of the
two, barring numerical iteration difficulties) and double it. Look this
up on a chi-square distribution with n-2 degrees of freedom. If the
result is significant, the log likelihood has been significantly
increased by allowing all 2n-3 branch lengths to be estimated instead
of just n-1, and molecular clock may be rejected.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the rates
at different sites, the program also performs a statistical test of
each of these trees against the one with highest likelihood. If there
are two user trees, the test done is one which is due to Kishino and
Hasegawa (1989), a version of a test originally introduced by Templeton
(1983). In this implementation it uses the mean and variance of
log-likelihood differences between trees, taken across sites. If the
two trees' means are more than 1.96 standard deviations different then
the trees are declared significantly different. This use of the
empirical variance of log-likelihood differences is more robust and
nonparametric than the classical likelihood ratio test, and may to some
extent compensate for the any lack of realism in the model underlying
this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. In the version used here
the variances and covariances of the sum of log likelihoods across
sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the highest log-likelihood exceeds that
actually observed. Note that this sampling needs random numbers, and so
the program will prompt the user for a random number seed if one has
not already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one. However the
test is not available if we assume that there is autocorrelation of
rates at neighboring sites (option A) and is not done in those cases.
The branch lengths printed out are scaled in terms of expected numbers
of substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate
of change, averaged over all sites analyzed, is set to 1.0 if there are
multiple categories of sites. This means that whether or not there are
multiple categories of sites, the expected fraction of change for very
small branches is equal to the branch length. Of course, when a branch
is twice as long this does not mean that there will be twice as much
net change expected along it, since some of the changes occur in the
same site and overlie or even reverse each other. The branch length
estimates here are in terms of the expected underlying numbers of
changes. That means that a branch of length 0.26 is 26 times as long as
one which would show a 1% difference between the nucleotide sequences
at the beginning and end of the branch. But we would not expect the
sequences at the beginning and end of the branch to be 26% different,
as there would be some overlaying of changes.
Because of limitations of the numerical algorithm, branch length
estimates of zero will often print out as small numbers such as
0.00001. If you see a branch length that small, it is really estimated
to be of zero length.
Another possible source of confusion is the existence of negative
values for the log likelihood. This is not really a problem; the log
likelihood is not a probability but the logarithm of a probability.
When it is negative it simply means that the corresponding probability
is less than one (since we are seeing its logarithm). The log
likelihood is maximized by being made more positive: -30.23 is worse
than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what site categories
contributed the most to the final likelihood. This combination of HMM
rate categories need not have contributed a majority of the likelihood,
just a plurality. Still, it will be helpful as a view of where the
program infers that the higher and lower rates are. Note that the use
in this calculations of the prior probabilities of different rates, and
the average patch length, gives this inference a "smoothed" appearance:
some other combination of rates might make a greater contribution to
the likelihood, but be discounted because it conflicts with this prior
information. See the example output below to see what this printout of
rate categories looks like.
A second list will also be printed out, showing for each site which
rate accounted for the highest fraction of the likelihood. If the
fraction of the likelihood accounted for is less than 95%, a dot is
printed instead.
Option 3 in the menu controls whether the tree is printed out into the
output file. This is on by default, and usually you will want to leave
it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees which
are written onto the output tree file, rather than the trees printed on
the output file. To keep the output file from becoming too large, it
may be wisest to use option 3 to prevent trees being printed onto the
output file.
Option 4 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined trees
are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated at
each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species
which are the input sequences). In that table, if a site has a base
which accounts for more than 95% of the likelihood, it is printed in
capital letters (A rather than a). If the best nucleotide accounts for
less than 50% of the likelihood, the program prints out an ambiguity
code (such as M for "A or C") for the set of nucleotides which, taken
together, account for more half of the likelihood. The ambiguity codes
are listed in the sequence programs documentation file. One limitation
of the current version of the program is that when there are multiple
HMM rates (option R) the reconstructed nucleotides are based on only
the single assignment of rates to sites which accounts for the largest
amount of the likelihood. Thus the assessment of 95% of the likelihood,
in tabulating the ancestral states, refers to 95% of the likelihood
that is accounted for by that particular combination of rates.
Output files for usage example
File: dnaml.fdnamlk
Nucleic acid sequence Maximum Likelihood method, version 3.69.650
5 species, 13 sites
Site categories are:
1111112222 222
Sites are weighted as follows:
01111 11111 110
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
Empirical Base Frequencies:
A 0.23636
C 0.29091
G 0.25455
T(U) 0.21818
Transition/transversion ratio = 2.000000
State in HMM Rate of change Probability
1 0.264 0.522
2 1.413 0.399
3 3.596 0.076
4 7.086 0.0036
5 12.641 0.000023
Site category Rate of change
1 1.000
2 2.000
+-Epsilon
+---------------------------------------------------------4
! +-Delta
--3
! +-------Gamma
+---------------------------------------------------2
! +-Beta
+-----1
+-Alpha
Ln Likelihood = -57.98242
Ancestor Node Node Height Length
-------- ---- ---- ------ ------
root 3
3 4 4.01604 4.01604
4 Epsilon 4.15060 0.13456
4 Delta 4.15060 0.13456
3 2 3.59089 3.59089
2 Gamma 4.15060 0.55971
2 1 3.99329 0.40240
1 Beta 4.15060 0.15731
1 Alpha 4.15060 0.15731
Combination of categories that contributes the most to the likelihood:
1132121111 211
Most probable category at each site if > 0.95 probability ("." otherwise)
.......... ...
File: dnaml.treefile
((Epsilon:0.13456,Delta:0.13456):4.01604,(Gamma:0.55971,
(Beta:0.15731,Alpha:0.15731):0.40240):3.59089);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdnapenny.txt 0000664 0001750 0001750 00000062076 12171064331 016123 0000000 0000000 fdnapenny
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Penny algorithm for DNA
Description
Finds all most parsimonious phylogenies for nucleic acid sequences by
branch-and-bound search. This may not be practical (depending on the
data) for more than 10-11 species or so.
Algorithm
DNAPENNY is a program that will find all of the most parsimonious trees
implied by your data when the nucleic acid sequence parsimony criterion
is employed. It does so not by examining all possible trees, but by
using the more sophisticated "branch and bound" algorithm, a standard
computer science search strategy first applied to phylogenetic
inference by Hendy and Penny (1982). (J. S. Farris [personal
communication, 1975] had also suggested that this strategy, which is
well-known in computer science, might be applied to phylogenies, but he
did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem of
finding these has been shown (Graham and Foulds, 1982; Day, 1983) to be
NP-complete, which is equivalent to saying that there is no fast
algorithm that is guaranteed to solve the problem in all cases (for a
discussion of NP-completeness, see the Scientific American article by
Lewis and Papadimitriou, 1978). The result is that this program,
despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs in
the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of
someone who can let a microcomputer grind all night than for someone
who has the "benefit" of paying for time on the campus mainframe
computer). IT IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE
PROGRAM WILL TAKE ON YOUR DATA. This can be done by running it on
subsets of the species, increasing the number of species in the run
until you either are able to treat the full data set or know that the
program will take unacceptably long on it. (Making a plot of the
logarithm of run time against species number may help to project run
times).
The Algorithm
The search strategy used by DNAPENNY starts by making a tree consisting
of the first two species (the first three if the tree is to be
unrooted). Then it tries to add the next species in all possible places
(there are three of these). For each of the resulting trees it
evaluates the number of base substitutions. It adds the next species to
each of these, again in all possible spaces. If this process would
continue it would simply generate all possible trees, of which there
are a very large number even when the number of species is moderate
(34,459,425 with 10 species). Actually it does not do this, because the
trees are generated in a particular order and some of them are never
generated.
This is because the order in which trees are generated is not quite as
implied above, but is a "depth-first search". This means that first one
adds the third species in the first possible place, then the fourth
species in its first possible place, then the fifth and so on until the
first possible tree has been produced. For each tree the number of
steps is evaluated. Then one "backtracks" by trying the alternative
placements of the last species. When these are exhausted one tries the
next placement of the next-to-last species. The order of placement in a
depth-first search is like this for a four-species case (parentheses
enclose monophyletic groups):
Make tree of first two species: (A,B)
Add C in first place: ((A,B),C)
Add D in first place: (((A,D),B),C)
Add D in second place: ((A,(B,D)),C)
Add D in third place: (((A,B),D),C)
Add D in fourth place: ((A,B),(C,D))
Add D in fifth place: (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place: (((A,D),C),B)
Add D in second place: ((A,(C,D)),B)
Add D in third place: (((A,C),D),B)
Add D in fourth place: ((A,C),(B,D))
Add D in fifth place: (((A,C),B),D)
Add C in third place: (A,(B,C))
Add D in first place: ((A,D),(B,C))
Add D in second place: (A,((B,D),C))
Add D in third place: (A,(B,(C,D)))
Add D in fourth place: (A,((B,C),D))
Add D in fifth place: ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species rooted
trees, each exactly once (the parentheses each enclose a monophyletic
group). As displayed above, the backtracking depth-first search
algorithm is just another way of producing all possible trees one at a
time. The branch and bound algorithm consists of this with one change.
As each tree is constructed, including the partial trees such as
(A,(B,C)), its number of steps is evaluated. In addition a prediction
is made as to how many steps will be added, at a minimum, as further
species are added.
This is done by counting how many sites which are invariant in the data
up the most recent species added will ultimately show variation when
further species are added. Thus if 20 sites vary among species A, B,
and C and their root, and if tree ((A,C),B) requires 24 steps, then if
there are 8 more sites which will be seen to vary when species D is
added, we can immediately say that no matter how we add D, the
resulting tree can have no less than 24 + 8 = 32 steps. The point of
all this is that if a previously-found tree such as ((A,B),(C,D))
required only 30 steps, then we know that there is no point in even
trying to add D to ((A,C),B). We have computed the bound that enables
us to cut off a whole line of inquiry (in this case five trees) and
avoid going down that particular branch any farther.
The branch-and-bound algorithm thus allows us to find all most
parsimonious trees without generating all possible trees. How much of a
saving this is depends strongly on the data. For very clean (nearly
"Hennigian") data, it saves much time, but on very messy data it will
still take a very long time.
The algorithm in the program differs from the one outlined here in some
essential details: it investigates possibilities in the order of their
apparent promise. This applies to the order of addition of species, and
to the places where they are added to the tree. After the first
two-species tree is constructed, the program tries adding each of the
remaining species in turn, each in the best possible place it can find.
Whichever of those species adds (at a minimum) the most additional
steps is taken to be the one to be added next to the tree. When it is
added, it is added in turn to places which cause the fewest additional
steps to be added. This sounds a bit complex, but it is done with the
intention of eliminating regions of the search of all possible trees as
soon as possible, and lowering the bound on tree length as quickly as
possible. This process of evaluating which species to add in which
order goes on the first time the search makes a tree; thereafter it
uses that order.
The program keeps a list of all the most parsimonious trees found so
far. Whenever it finds one that has fewer losses than these, it clears
out the list and restarts it with that tree. In the process the bound
tightens and fewer possibilities need be investigated. At the end the
list contains all the shortest trees. These are then printed out. It
should be mentioned that the program CLIQUE for finding all largest
cliques also works by branch-and-bound. Both problems are NP-complete
but for some reason CLIQUE runs far faster. Although their worst-case
behavior is bad for both programs, those worst cases occur far more
frequently in parsimony problems than in compatibility problems.
Controlling Run Times
Among the quantities available to be set from the menu of DNAPENNY, two
(howoften and howmany) are of particular importance. As DNAPENNY goes
along it will keep count of how many trees it has examined. Suppose
that howoften is 100 and howmany is 1000, the default settings. Every
time 100 trees have been examined, DNAPENNY will print out a line
saying how many multiples of 100 trees have now been examined, how many
steps the most parsimonious tree found so far has, how many trees of
with that number of steps have been found, and a very rough estimate of
what fraction of all trees have been looked at so far. When the number
of these multiples printed out reaches the number howmany (say 1000),
the whole algorithm aborts and prints out that it has not found all
most parsimonious trees, but prints out what is has got so far anyway.
These trees need not be any of the most parsimonious trees: they are
simply the most parsimonious ones found so far. By setting the product
(howoften times howmany) large you can make the algorithm less likely
to abort, but then you risk getting bogged down in a gigantic
computation. You should adjust these constants so that the program
cannot go beyond examining the number of trees you are reasonably
willing to pay for (or wait for). In their initial setting the program
will abort after looking at 100,000 trees. Obviously you may want to
adjust howoften in order to get more or fewer lines of intermediate
notice of how many trees have been looked at so far. Of course, in
small cases you may never even reach the first multiple of howoften,
and nothing will be printed out except some headings and then the final
trees. The indication of the approximate percentage of trees searched
so far will be helpful in judging how much farther you would have to go
to get the full search. Actually, since that fraction is the fraction
of the set of all possible trees searched or ruled out so far, and
since the search becomes progressively more efficient, the approximate
fraction printed out will usually be an underestimate of how far along
the program is, sometimes a serious underestimate.
A constant at the beginning of the program that affects the result is
"maxtrees", which controls the maximum number of trees that can be
stored. Thus if maxtrees is 25, and 32 most parsimonious trees are
found, only the first 25 of these are stored and printed out. If
maxtrees is increased, the program does not run any slower but requires
a little more intermediate storage space. I recommend that maxtrees be
kept as large as you can, provided you are willing to look at an output
with that many trees on it! Initially, maxtrees is set to 100 in the
distribution copy.
Method and Options
The counting of the length of trees is done by an algorithm nearly
identical to the corresponding algorithms in DNAPARS, and thus the
remainder of this document will be nearly identical to the DNAPARS
document.
This program carries out unrooted parsimony (analogous to Wagner trees)
(Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA sequences. The
method of Fitch (1971) is used to count the number of changes of base
needed on a given tree. The assumptions of this method are exactly
analogous to those of DNAPARS:
1. Each site evolves independently.
2. Different lineages evolve independently.
3. The probability of a base substitution at a given site is small
over the lengths of time involved in a branch of the phylogeny.
4. The expected amounts of change in different branches of the
phylogeny do not vary by so much that two changes in a high-rate
branch are more probable than one change in a low-rate branch.
5. The expected amounts of change do not vary enough among sites that
two changes in one site are more probable than one change in
another.
Change from an occupied site to a deletion is counted as one change.
Reversion from a deletion to an occupied site is allowed and is also
counted as one change. That these are the assumptions of parsimony
methods has been documented in a series of papers of mine: (1973a,
1978b, 1979, 1981b, 1983b, 1988b). For an opposing view arguing that
the parsimony methods make no substantive assumptions such as these,
see the papers by Farris (1983) and Sober (1983a, 1983b), but also read
the exchange between Felsenstein and Sober (1986). Change from an
occupied site to a deletion is counted as one change. Reversion from a
deletion to an occupied site is allowed and is also counted as one
change. Note that this in effect assumes that a deletion N bases long
is N separate events.
Usage
Here is a sample session with fdnapenny
% fdnapenny
Penny algorithm for DNA
Input (aligned) nucleotide sequence set(s): dnapenny.dat
Phylip dnapenny program output file [dnapenny.fdnapenny]:
justweights: false
numwts: 0
How many
trees looked Approximate
at so far Length of How many percentage
(multiples shortest tree trees this short searched
of 100): found so far found so far so far
---------- ------------ ------------ ------------
1 9.0 2 0.11
2 8.0 3 6.67
3 8.0 9 20.00
4 8.0 9 86.67
Output written to file "dnapenny.fdnapenny"
Trees also written onto file "dnapenny.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
Penny algorithm for DNA
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-outfile] outfile [*.fdnapenny] Phylip dnapenny program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties (no help text) properties value
-howoften integer [100] How often to report, in trees (Any
integer value)
-howmany integer [1000] How many groups of trees (Any integer
value)
-[no]simple boolean [Y] Branch and bound is simple
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1.0] Threshold value (Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnapenny] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print out steps in each site
-ancseq boolean [N] Print sequences at all nodes of tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdnapenny reads any normal sequence USAs
Input files for usage example
File: dnapenny.dat
8 6
Alpha1 AAGAAG
Alpha2 AAGAAG
Beta1 AAGGGG
Beta2 AAGGGG
Gamma1 AGGAAG
Gamma2 AGGAAG
Delta GGAGGA
Epsilon GGAAAG
Output file format
fdnapenny output is standard: if option 1 is toggled on, the data is
printed out, with the convention that "." means "the same as in the
first species". Then comes a list of equally parsimonious trees, and
(if option 2 is toggled on) a table of the number of changes of state
required in each character. If option 5 is toggled on, a table is
printed out after each tree, showing for each branch whether there are
known to be changes in the branch, and what the states are inferred to
have been at the top end of the branch. If the inferred state is a "?"
or one of the IUB ambiguity symbols, there will be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand. A "?" in the reconstructed states means
that in addition to one or more bases, a deletion may or may not be
present. If option 6 is left in its default state the trees found will
be written to a tree file, so that they are available to be used in
other programs. If the program finds multiple trees tied for best, all
of these are written out onto the output tree file. Each is followed by
a numerical weight in square brackets (such as [0.25000]). This is
needed when we use the trees to make a consensus tree of the results of
bootstrapping or jackknifing, to avoid overrepresenting replicates that
find many tied trees.
Output files for usage example
File: dnapenny.fdnapenny
Penny algorithm for DNA, version 3.69.650
branch-and-bound to find all most parsimonious trees
requires a total of 8.000
9 trees in all found
+--------------------Alpha1
!
! +-----------Alpha2
! !
1 +-----4 +--Epsilon
! ! ! +-----6
! ! ! ! +--Delta
! ! +--5
+--2 ! +--Gamma2
! +-----7
! +--Gamma1
!
! +--Beta2
+--------------3
+--Beta1
remember: this is an unrooted tree!
+--------------------Alpha1
!
! +-----------Alpha2
! !
1 +-----4 +--------Gamma2
! ! ! !
! ! +--7 +--Epsilon
! ! ! +--6
+--2 +--5 +--Delta
! !
! +-----Gamma1
!
! +--Beta2
+--------------3
+--Beta1
[Part of this file has been deleted for brevity]
+--5 +--Delta
!
+-----Gamma1
remember: this is an unrooted tree!
+--------------------Alpha1
!
! +-----Alpha2
1 +-----------2
! ! ! +--Beta2
! ! +--3
! ! +--Beta1
+--4
! +-----Gamma2
! +--7
! ! ! +--Epsilon
+--------5 +--6
! +--Delta
!
+--------Gamma1
remember: this is an unrooted tree!
+--------------------Alpha1
!
! +-----Alpha2
1 +-----------2
! ! ! +--Beta2
! ! +--3
! ! +--Beta1
+--4
! +--Epsilon
! +-----6
! ! +--Delta
+--------5
! +--Gamma2
+-----7
+--Gamma1
remember: this is an unrooted tree!
File: dnapenny.treefile
(Alpha1,((Alpha2,((Epsilon,Delta),(Gamma2,Gamma1))),(Beta2,Beta1)))[0.1111];
(Alpha1,((Alpha2,(Gamma2,((Epsilon,Delta),Gamma1))),(Beta2,Beta1)))[0.1111];
(Alpha1,((Alpha2,((Gamma2,(Epsilon,Delta)),Gamma1)),(Beta2,Beta1)))[0.1111];
(Alpha1,(Alpha2,((Gamma2,((Epsilon,Delta),Gamma1)),(Beta2,Beta1))))[0.1111];
(Alpha1,(Alpha2,(((Epsilon,Delta),(Gamma2,Gamma1)),(Beta2,Beta1))))[0.1111];
(Alpha1,(Alpha2,(((Gamma2,(Epsilon,Delta)),Gamma1),(Beta2,Beta1))))[0.1111];
(Alpha1,((Alpha2,(Beta2,Beta1)),(Gamma2,((Epsilon,Delta),Gamma1))))[0.1111];
(Alpha1,((Alpha2,(Beta2,Beta1)),((Gamma2,(Epsilon,Delta)),Gamma1)))[0.1111];
(Alpha1,((Alpha2,(Beta2,Beta1)),((Epsilon,Delta),(Gamma2,Gamma1))))[0.1111];
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fprotdist.txt 0000664 0001750 0001750 00000056316 12171064331 016157 0000000 0000000 fprotdist
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Protein distance algorithm
Description
Computes a distance measure for protein sequences, using maximum
likelihood estimates based on the Dayhoff PAM matrix, the JTT matrix
model, the PBM model, Kimura's 1983 approximation to these, or a model
based on the genetic code plus a constraint on changing to a different
category of amino acid. The distances can also be corrected for
gamma-distributed and gamma-plus-invariant-sites-distributed rates of
change in different sites. Rates of evolution can vary among sites in a
prespecified way, and also according to a Hidden Markov model. The
program can also make a table of percentage similarity among sequences.
The distances can be used in the distance matrix programs.
Algorithm
This program uses protein sequences to compute a distance matrix, under
four different models of amino acid replacement. It can also compute a
table of similarity between the amino acid sequences. The distance for
each pair of species estimates the total branch length between the two
species, and can be used in the distance matrix programs FITCH, KITSCH
or NEIGHBOR. This is an alternative to use of the sequence data itself
in the parsimony program PROTPARS.
The program reads in protein sequences and writes an output file
containing the distance matrix or similarity table. The five models of
amino acid substitution are one which is based on the Jones, Taylor and
Thornton (1992) model of amino acid change, the PMB model (Veerassamy,
Smith and Tillier, 2004) which is derived from the Blocks database of
conserved protein motifs, one based on the PAM matrixes of Margaret
Dayhoff, one due to Kimura (1983) which approximates it based simply on
the fraction of similar amino acids, and one based on a model in which
the amino acids are divided up into groups, with change occurring based
on the genetic code but with greater difficulty of changing between
groups. The program correctly takes into account a variety of sequence
ambiguities.
The five methods are:
(1) The Dayhoff PAM matrix. This uses Dayhoff's PAM 001 matrix from
Dayhoff (1979), page 348. The PAM model is an empirical one that scales
probabilities of change from one amino acid to another in terms of a
unit which is an expected 1% change between two amino acid sequences.
The PAM 001 matrix is used to make a transition probability matrix
which allows prediction of the probability of changing from any one
amino acid to any other, and also predicts equilibrium amino acid
composition. The program assumes that these probabilities are correct
and bases its computations of distance on them. The distance that is
computed is scaled in units of expected fraction of amino acids
changed. This is a unit such that 1.0 is 100 PAM's.
(2) The Jones-Taylor-Thornton model. This is similar to the Dayhoff PAM
model, except that it is based on a recounting of the number of
observed changes in amino acids by Jones, Taylor, and Thornton (1992).
They used a much larger sample of protein sequences than did Dayhoff.
The distance is scaled in units of the expected fraction of amino acids
changed (100 PAM's). Because its sample is so much larger this model is
to be preferred over the original Dayhoff PAM model. It is the default
model in this program.
(3) The PMB (Probability Matrix from Blocks) model. This is derived
using the Blocks database of conserved protein motifs. It will be
described in a paper by Veerassamy, Smith and Tillier (2004). Elisabeth
Tillier kindly made the matrices available for this model.
(4) Kimura's distance. This is a rough-and-ready distance formula for
approximating PAM distance by simply measuring the fraction of amino
acids, p, that differs between two sequences and computing the distance
as (Kimura, 1983) D = - loge ( 1 - p - 0.2 p2 ). This is very quick to
do but has some obvious limitations. It does not take into account
which amino acids differ or to what amino acids they change, so some
information is lost. The units of the distance measure are fraction of
amino acids differing, as also in the case of the PAM distance. If the
fraction of amino acids differing gets larger than 0.8541 the distance
becomes infinite.
(5) The Categories distance. This is my own concoction. I imagined a
nucleotide sequence changing according to Kimura's 2-parameter model,
with the exception that some changes of amino acids are less likely
than others. The amino acids are grouped into a series of categories.
Any base change that does not change which category the amino acid is
in is allowed, but if an amino acid changes category this is allowed
only a certain fraction of the time. The fraction is called the "ease"
and there is a parameter for it, which is 1.0 when all changes are
allowed and near 0.0 when changes between categories are nearly
impossible.
In this option I have allowed the user to select the
Transition/Transversion ratio, which of several genetic codes to use,
and which categorization of amino acids to use. There are three of
them, a somewhat random sample:
1. The George-Hunt-Barker (1988) classification of amino acids,
2. A classification provided by my colleague Ben Hall when I asked him
for one,
3. One I found in an old "baby biochemistry" book (Conn and Stumpf,
1963), which contains most of the biochemistry I was ever taught,
and all that I ever learned.
Interestingly enough, all of them are consisten with the same linear
ordering of amino acids, which they divide up in different ways. For
the Categories model I have set as default the George/Hunt/Barker
classification with the "ease" parameter set to 0.457 which is
approximately the value implied by the empirical rates in the Dayhoff
PAM matrix.
The method uses, as I have noted, Kimura's (1980) 2-parameter model of
DNA change. The Kimura "2-parameter" model allows for a difference
between transition and transversion rates. Its transition probability
matrix for a short interval of time is:
To: A G C T
---------------------------------
A | 1-a-2b a b b
From: G | a 1-a-2b b b
C | b b 1-a-2b a
T | b b a 1-a-2b
where a is u dt, the product of the rate of transitions per unit time
and dt is the length dt of the time interval, and b is v dt, the
product of half the rate of transversions (i.e., the rate of a specific
transversion) and the length dt of the time interval.
Each distance that is calculated is an estimate, from that particular
pair of species, of the divergence time between those two species. The
Kimura distance is straightforward to compute. The other two are
considerably slower, and they look at all positions, and find that
distance which makes the likelihood highest. This likelihood is in
effect the length of the internal branch in a two-species tree that
connects these two species. Its likelihood is just the product, under
the model, of the probabilities of each position having the (one or)
two amino acids that are actually found. This is fairly slow to
compute.
The computation proceeds from an eigenanalysis (spectral decomposition)
of the transition probability matrix. In the case of the PAM 001 matrix
the eigenvalues and eigenvectors are precomputed and are hard-coded
into the program in over 400 statements. In the case of the Categories
model the program computes the eigenvalues and eigenvectors itself,
which will add a delay. But the delay is independent of the number of
species as the calculation is done only once, at the outset.
The actual algorithm for estimating the distance is in both cases a
bisection algorithm which tries to find the point at which the
derivative os the likelihood is zero. Some of the kinds of ambiguous
amino acids like "glx" are correctly taken into account. However, gaps
are treated as if they are unkown nucleotides, which means those
positions get dropped from that particular comparison. However, they
are not dropped from the whole analysis. You need not eliminate regions
containing gaps, as long as you are reasonably sure of the alignment
there.
Note that there is an assumption that we are looking at all positions,
including those that have not changed at all. It is important not to
restrict attention to some positions based on whether or not they have
changed; doing that would bias the distances by making them too large,
and that in turn would cause the distances to misinterpret the meaning
of those positions that had changed.
The program can now correct distances for unequal rates of change at
different amino acid positions. This correction, which was introduced
for DNA sequences by Jin and Nei (1990), assumes that the distribution
of rates of change among amino acid positions follows a Gamma
distribution. The user is asked for the value of a parameter that
determines the amount of variation of rates among amino acid positions.
Instead of the more widely-known coefficient alpha, PROTDIST uses the
coefficient of variation (ratio of the standard deviation to the mean)
of rates among amino acid positions. . So if there is 20% variation in
rates, the CV is is 0.20. The square of the C.V. is also the reciprocal
of the better-known "shape parameter", alpha, of the Gamma
distribution, so in this case the shape parameter alpha = 1/(0.20*0.20)
= 25. If you want to achieve a particular value of alpha, such as 10,
you will want to use a CV of 1/sqrt(100) = 1/10 = 0.1.
In addition to the five distance calculations, the program can also
compute a table of similarities between amino acid sequences. These
values are the fractions of amino acid positions identical between the
sequences. The diagonal values are 1.0000. No attempt is made to count
similarity of nonidentical amino acids, so that no credit is given for
having (for example) different hydrophobic amino acids at the
corresponding positions in the two sequences. This option has been
requested by many users, who need it for descriptive purposes. It is
not intended that the table be used for inferring the tree.
Usage
Here is a sample session with fprotdist
% fprotdist
Protein distance algorithm
Input (aligned) protein sequence set(s): protdist.dat
Phylip distance matrix output file [protdist.fprotdist]:
Computing distances:
Alpha
Beta .
Gamma ..
Delta ...
Epsilon ....
Output written to file "protdist.fprotdist"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Protein distance algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-outfile] outfile [*.fprotdist] Phylip distance matrix output
file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
-method menu [j] Choose the method to use (Values: j
(Jones-Taylor-Thornton matrix); h
(Henikoff/Tiller PMB matrix); d (Dayhoff PAM
matrix); k (Kimura formula); s (Similarity
table); c (Categories model))
* -gammatype menu [c] Rate variation among sites (Values: g
(Gamma distributed rates); i
(Gamma+invariant sites); c (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -aacateg menu [G] Choose the category to use (Values: G
(George/Hunt/Barker (Cys), (Met Val Leu
Ileu), (Gly Ala Ser Thr Pro)); C (Chemical
(Cys Met), (Val Leu Ileu Gly Ala Ser Thr),
(Pro)); H (Hall (Cys), (Met Val Leu Ileu),
(Gly Ala Ser Thr),(Pro)))
* -whichcode menu [u] Which genetic code (Values: u
(Universal); c (Ciliate); m (Universal
mitochondrial); v (Vertebrate
mitochondrial); f (Fly mitochondrial); y
(Yeast mitochondrial))
* -ease float [0.457] Prob change category (1.0=easy)
(Number from 0.000 to 1.000)
* -ttratio float [2.0] Transition/transversion ratio (Number
0.000 or more)
* -basefreq array [0.25 0.25 0.25 0.25] Base frequencies for A
C G T/U (use blanks to separate)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fprotdist reads any normal sequence USAs.
Input files for usage example
File: protdist.dat
5 13
Alpha AACGTGGCCACAT
Beta AAGGTCGCCACAC
Gamma CAGTTCGCCACAA
Delta GAGATTTCCGCCT
Epsilon GAGATCTCCGCCC
Output file format
fprotdist output contains on its first line the number of species. The
distance matrix is then printed in standard form, with each species
starting on a new line with the species name, followed by the distances
to the species in order. These continue onto a new line after every
nine distances. The distance matrix is square with zero distances on
the diagonal. In general the format of the distance matrix is such that
it can serve as input to any of the distance matrix programs.
If the similarity table is selected, the table that is produced is not
in a format that can be used as input to the distance matrix programs.
it has a heading, and the species names are also put at the tops of the
columns of the table (or rather, the first 8 characters of each species
name is there, the other two characters omitted to save space). There
is not an option to put the table into a format that can be read by the
distance matrix programs, nor is there one to make it into a table of
fractions of difference by subtracting the similarity values from 1.
This is done deliberately to make it more difficult for the use to use
these values to construct trees. The similarity values are not
corrected for multiple changes, and their use to construct trees (even
after converting them to fractions of difference) would be wrong, as it
would lead to severe conflict between the distant pairs of sequences
and the close pairs of sequences.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the menu
selections. The output file begins by giving the number of species and
the number of characters, and the identity of the distance measure that
is being used.
In the Categories model of substitution, the distances printed out are
scaled in terms of expected numbers of substitutions, counting both
transitions and transversions but not replacements of a base by itself,
and scaled so that the average rate of change is set to 1.0. For the
Dayhoff PAM and Kimura models the distance are scaled in terms of the
expected numbers of amino acid substitutions per site. Of course, when
a branch is twice as long this does not mean that there will be twice
as much net change expected along it, since some of the changes may
occur in the same site and overlie or even reverse each other. The
branch lengths estimates here are in terms of the expected underlying
numbers of changes. That means that a branch of length 0.26 is 26 times
as long as one which would show a 1% difference between the protein (or
nucleotide) sequences at the beginning and end of the branch. But we
would not expect the sequences at the beginning and end of the branch
to be 26% different, as there would be some overlaying of changes.
One problem that can arise is that two or more of the species can be so
dissimilar that the distance between them would have to be infinite, as
the likelihood rises indefinitely as the estimated divergence time
increases. For example, with the Kimura model, if the two sequences
differ in 85.41% or more of their positions then the estimate of
divergence time would be infinite. Since there is no way to represent
an infinite distance in the output file, the program regards this as an
error, issues a warning message indicating which pair of species are
causing the problem, and computes a distance of -1.0.
Output files for usage example
File: protdist.fprotdist
5
Alpha 0.000000 0.331834 0.628142 1.036660 1.365098
Beta 0.331834 0.000000 0.377406 1.102689 0.682218
Gamma 0.628142 0.377406 0.000000 0.979550 0.866781
Delta 1.036660 1.102689 0.979550 0.000000 0.227515
Epsilon 1.365098 0.682218 0.866781 0.227515 0.000000
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fseqboot.txt 0000664 0001750 0001750 00000055760 12171064331 015765 0000000 0000000 fseqboot
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped sequences algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of the
package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
SEQBOOT is a general bootstrapping and data set translation tool. It is
intended to allow you to generate multiple data sets that are resampled
versions of the input data set. Since almost all programs in the
package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or permuted.
SEQBOOT can handle molecular sequences, binary characters, restriction
sites, or gene frequencies. It can also convert data sets between
Sequential and Interleaved format, and into the NEXUS format or into a
new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of interest.
For example, if you were using DNAPARS you would first run SEQBOOT and
make a file with 100 bootstrapped data sets. Then you would give this
file the proper name to have it be the input file for DNAPARS. Running
DNAPARS with the M (Multiple Data Sets) menu choice and informing it to
expect 100 data sets, you would generate a big output file as well as a
treefile with the trees from the 100 data sets. This treefile could be
renamed so that it would serve as the input for CONSENSE. When CONSENSE
is run the majority rule consensus tree will result, showing the
outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this package.
The same steps are necessary with all of them. Doing things this way
some of the intermediate files (the tree file from the DNAPARS run, for
example) can be used to summarize the results of the bootstrap in other
ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add one
extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
* The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me
(Felsenstein, 1985b; see also Penny and Hendy, 1985). It involves
creating a new data set by sampling N characters randomly with
replacement, so that the resulting data set has the same size as
the original, but some characters have been left out and others are
duplicated. The random variation of the results from analyzing
these bootstrapped data sets can be shown statistically to be
typical of the variation that you would get from collecting new
data sets. The method assumes that the characters evolve
independently, an assumption that may not be realistic for many
kinds of data.
* The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial
Bootstrap method, and Shimodaira's (2002) AU method, both of which
correct the bias of bootstrap P values.
* Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct
for it by samopling, not individual characters, but blocks of
adjacent characters. This is called a block bootstrap and was
introduced by Kuensch (1989). If the correlations are believed to
extend over some number of characters, you choose a block size, B,
that is larger than this, and choose N/B blocks of size B. In its
implementation here the block bootstrap "wraps around" at the end
of the characters (so that if a block starts in the last B-1
characters, it continues by wrapping around to the first character
after it reaches the last character). Note also that if you have a
DNA sequence data set of an exon of a coding region, you can ensure
that equal numbers of first, second, and third coding positions are
sampled by using the block bootstrap with B = 3.
* Partial block-bootstrapping. Similar to partial bootstrapping
except sampling blocks rather than single characters.
* Delete-half-jackknifing.. This alternative to the bootstrap
involves sampling a random half of the characters, and including
them in the data but dropping the others. The resulting data sets
are half the size of the original, and no characters are
duplicated. The random variation from doing this should be very
similar to that obtained from the bootstrap. The method is
advocated by Wu (1986). It was mentioned by me in my bootstrapping
paper (Felsenstein, 1985b), and has been available for many years
in this program as an option. Note that, for the present,
block-jackknifing is not available, because I cannot figure out how
to do it straightforwardly when the block size is not a divisor of
the number of characters.
* Delete-fraction jackknifing. Jackknifing is advocated by Farris et.
al. (1996) but as deleting a fraction 1/e (1/2.71828). This retains
too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it
is made available here as an option, with the user asked to supply
the fraction of characters that are to be retained.
* Permuting species within characters. This method of resampling
(well, OK, it may not be best to call it resampling) was introduced
by Archie (1989) and Faith (1990; see also Faith and Cranston,
1991). It involves permuting the columns of the data matrix
separately. This produces data matrices that have the same number
and kinds of characters but no taxonomic structure. It is used for
different purposes than the bootstrap, as it tests not the
variation around an estimated tree but the hypothesis that there is
no taxonomic structure in the data: if a statistic such as number
of steps is significantly smaller in the actual data than it is in
replicates that are permuted, then we can argue that there is some
taxonomic structure in the data (though perhaps it might be just
the presence of aa pair of sibling species).
* Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For
many methods of tree inference this will make no difference to the
outcome (unless one has rates of evolution correlated among
adjacent sites). It is included as a possible step in carrying out
a permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
* Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so
as to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
* Rewriting. This is not a resampling or permutation method: it
simply rewrites the data set into a different format. That format
can be the PHYLIP format. For molecular sequences and discrete
morphological character it can also be the NEXUS format. For
molecular sequences one other format is available, a new (and
nonstandard) XML format of our own devising. When the PHYLIP format
is chosen the data set is coverted between Interleaved and
Sequential format. If it was read in as Interleaved sequences, it
will be written out as Sequential format, and vice versa. The NEXUS
format for molecular sequences is always written as interleaved
sequences. The XML format is different from (though similar to) a
number of other XML sequence alignment formats. An example will be
found below. Here is a table to links to those other XML alignment
formats:
Andrew Rambaut's BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html and
http://evolve.zoo.ox.ac.uk/beast/referenindex.html A format for
alignments. There is also a format for phylogenies described there.
MSAML M http://xml.coverpages.org/msaml-desc-dec.html Defined by Paul
Gordon of University of Calgary. See his big list of molecular biology
XML projects.
BSML http://www.bsml.org/resources/default.asp Bioinformatic Sequence
Markup Language includes a multiple sequence alignment XML format
Usage
Here is a sample session with fseqboot
% fseqboot -seed 3
Bootstrapped sequences algorithm
Input (aligned) sequence set: seqboot.dat
Phylip seqboot_seq program output file [seqboot.fseqboot]:
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "seqboot.fseqboot"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Bootstrapped sequences algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqset (Aligned) sequence set filename and optional
format, or reference (input USA)
[-outfile] outfile [*.fseqboot] Phylip seqboot_seq program
output file
Additional (Optional) qualifiers (* if not always prompted):
-categories properties File of input categories
-weights properties Weights file
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -rewriteformat menu [p] Output format (Values: p (PHYLIP); n
(NEXUS); x (XML))
* -seqtype menu [d] Output format (Values: d (dna); p
(protein); r (rna))
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fseqboot data files read by SEQBOOT are the standard ones for the
various kinds of data. For molecular sequences the sequences may be
either interleaved or sequential, and similarly for restriction sites.
Restriction sites data may either have or not have the third argument,
the number of restriction enzymes used. Discrete morphological
characters are always assumed to be in sequential format. Gene
frequencies data start with the number of species and the number of
loci, and then follow that by a line with the number of alleles at each
locus. The data for each locus may either have one entry for each
allele, or omit one allele at each locus. The details of the formats
are given in the main documentation file, and in the documentation
files for the groups of programsreads any normal sequence USAs.
Input files for usage example
File: seqboot.dat
5 6
Alpha AACAAC
Beta AACCCC
Gamma ACCAAC
Delta CCACCA
Epsilon CCAAAC
Output file format
fseqboot output will contain the data sets generated by the resampling
process. Note that, when Gene Frequencies data is used or when Discrete
Morphological characters with the Factors option are used, the number
of characters in each data set may vary. It may also vary if there are
an odd number of characters or sites and the Delete-Half-Jackknife
resampling method is used, for then there will be a 50% chance of
choosing (n+1)/2 characters and a 50% chance of choosing (n-1)/2
characters.
The Factors option causes the characters to be resampled together. If
(say) three adjacent characters all have the same factors characters,
so that they all are understood to be recoding one multistate
character, they will be resampled together as a group.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these
data avoid any result which is sensitive to the input order of species
from showing up repeatedly and thus appearing to have evidence in its
favor.
The numerical options 1 and 2 in the menu also affect the output file.
If 1 is chosen (it is off by default) the program will print the
original input data set on the output file before the resampled data
sets. I cannot actually see why anyone would want to do this. Option 2
toggles the feature (on by default) that prints out up to 20 times
during the resampling process a notification that the program has
completed a certain number of data sets. Thus if 100 resampled data
sets are being produced, every 5 data sets a line is printed saying
which data set has just been completed. This option should be turned
off if the program is running in background and silence is desirable.
At the end of execution the program will always (whatever the setting
of option 2) print a couple of lines saying that output has been
written to the output file.
Output files for usage example
File: seqboot.fseqboot
5 6
Alpha AAACCA
Beta AAACCC
Gamma ACCCCA
Delta CCCAAC
Epsilon CCCAAA
5 6
Alpha AAACAA
Beta AAACCC
Gamma ACCCAA
Delta CCCACC
Epsilon CCCAAA
5 6
Alpha AAAAAC
Beta AAACCC
Gamma AACAAC
Delta CCCCCA
Epsilon CCCAAC
5 6
Alpha CCCCCA
Beta CCCCCC
Gamma CCCCCA
Delta AAAAAC
Epsilon AAAAAA
5 6
Alpha AAAACC
Beta AAACCC
Gamma AACACC
Delta CCCCAA
Epsilon CCCACC
5 6
Alpha AAAACC
Beta ACCCCC
Gamma AAAACC
Delta CCCCAA
Epsilon CAAACC
5 6
Alpha AACCAA
Beta AACCCC
Gamma ACCCAA
Delta CCAACC
Epsilon CCAAAA
5 6
Alpha AAAACC
Beta ACCCCC
Gamma AAAACC
Delta CCCCAA
Epsilon CAAACC
5 6
Alpha AACACC
[Part of this file has been deleted for brevity]
Gamma ACAAAA
Delta CCCCCC
Epsilon CCAAAA
5 6
Alpha AACAAC
Beta AACCCC
Gamma AACAAC
Delta CCACCA
Epsilon CCAAAC
5 6
Alpha AACAAA
Beta AACCCC
Gamma CCCAAA
Delta CCACCC
Epsilon CCAAAA
5 6
Alpha ACAAAA
Beta ACCCCC
Gamma CCAAAA
Delta CACCCC
Epsilon CAAAAA
5 6
Alpha CAAAAA
Beta CCCCCC
Gamma CAAAAA
Delta ACCCCC
Epsilon AAAAAA
5 6
Alpha CAACCC
Beta CCCCCC
Gamma CAACCC
Delta ACCAAA
Epsilon AAACCC
5 6
Alpha ACAACC
Beta ACCCCC
Gamma ACAACC
Delta CACCAA
Epsilon CAAACC
5 6
Alpha AAAAAA
Beta AAAAAC
Gamma ACCCCA
Delta CCCCCC
Epsilon CCCCCA
5 6
Alpha AACAAC
Beta AACCCC
Gamma CCCAAC
Delta CCACCA
Epsilon CCAAAC
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/ftreedistpair.txt 0000664 0001750 0001750 00000041727 12171064331 017006 0000000 0000000 ftreedistpair
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Calculate distance between two sets of trees
Description
Computes the Branch Score distance between trees, which allows for
differences in tree topology and which also makes use of branch
lengths. Also computes the Robinson-Foulds symmetric difference
distance between trees, which allows for differences in tree topology
but does not use branch lengths.
Algorithm
This program computes distances between trees. Two distances are
computed, the Branch Score Distance of Kuhner and Felsenstein (1994),
and the more widely known Symmetric Difference of Robinson and Foulds
(1981). The Branch Score Distance uses branch lengths, and can only be
calculated when the trees have lengths on all branches. The Symmetric
Difference does not use branch length information, only the tree
topologies. It must also be borne in mind that neither distance has any
immediate statistical interpretation -- we cannot say whether a larger
distance is significantly larger than a smaller one.
These distances are computed by considering all possible branches that
could exist on the the two trees. Each branch divides the set of
species into two groups -- the ones connected to one end of the branch
and the ones connected to the other. This makes a partition of the full
set of species. (in Newick notation)
((A,C),(D,(B,E)))
has two internal branches. One induces the partition {A, C | B, D, E}
and the other induces the partition {A, C, D | B, E}. A different tree
with the same set of species,
(((A,D),C),(B,E))
has internal branches that correspond to the two partitions {A, C, D |
B, E} and {A, D | B, C, E}. Note that the other branches, all of which
are external branches, induce partitions that separate one species from
all the others. Thus there are 5 partitions like this: {C | A, B, D, E}
on each of these trees. These are always present on all trees, provided
that each tree has each species at the end of its own branch.
In the case of the Branch Score distance, each partition that does
exist on a tree also has a branch length associated with it. Thus if
the tree is
(((A:0.1,D:0.25):0.05,C:0.01):0.2,(B:0.3,E:0.8):0.2)
The list of partitions and their branch lengths is:
{A | B, C, D, E} 0.1
{D | A, B, C, E} 0.25
{A, D | B, C, E} 0.05
{C | A, B, D, E} 0.01
{A, D, C | B, E} 0.4
{B | A, C, D, E} 0.3
{E | A, B, C, D} 0.8
Note that the tree is being treated as unrooted here, so that the
branch lengths on either side of the rootmost node are summed up to get
a branch length of 0.4.
The Branch Score Distance imagines us as having made a list of all
possible partitions, the ones shown above and also all 7 other possible
partitions, which correspond to branches that are not found in this
tree. These are assigned branch lengths of 0. For two trees, we imagine
constructing these lists, and then summing the squared differences
between the branch lengths. Thus if both trees have branches {A, D | B,
C, E}, the sum contains the square of the difference between the branch
lengths. If one tree has the branch and the other doesn't, it contains
the square of the difference between the branch length and zero (in
other words, the square of that branch length). If both trees do not
have a particular branch, nothing is added to the sum because the
difference is then between 0 and 0.
The Branch Score Distance takes this sum of squared differences and
computes its square root. Note that it has some desirable properties.
When small branches differ in tree topology, it is not very big. When
branches are both present but differ in length, it is affected.
The Symmetric Difference is simply a count of how many partitions there
are, among the two trees, that are on one tree and not on the other. In
the example above there are two partitions, {A, C | B, D, E} and {A, D
| B, C, E}, each of which is present on only one of the two trees. The
Symmetric Difference between the two trees is therefore 2. When the two
trees are fully resolved bifurcating trees, their symmetric distance
must be an even number; it can range from 0 to twice the number of
internal branches, which for n species is 4n-6.
Note the relationship between the two distances. If all trees have all
their branches have length 1.0, the Branch Score Distance is the square
of the Symmetric Difference, as each branch that is present in one but
not in the other results in 1.0 being added to the sum of squared
differences.
We have assumed that nothing is lost if the trees are treated as
unrooted trees. It is easy to define a counterpart to the Branch Score
Distance and one to the Symmetric Difference for these rooted trees.
Each branch then defines a set of species, namely the clade defined by
that branch. Thus if the first of the two trees above were considered
as a rooted tree it would define the three clades {A, C}, {B, D, E},
and {B, E}. The Branch Score Distance is computed from the branch
lengths for all possible sets of species, with 0 put for each set that
does not occur on that tree. The table above will be nearly the same,
but with two entries instead of one for the sets on either side of the
root, {A C D} and {B E}. The Symmetric Difference between two rooted
trees is simply the count of the number of clades that are defined by
one but not by the other. For the second tree the clades would be {A,
D}, {B, C, E}, and {B, E}. The Symmetric Difference between thee two
rooted trees would then be 4.
Although the examples we have discussed have involved fully bifurcating
trees, the input trees can have multifurcations. This does not cause
any complication for the Branch Score Distance. For the Symmetric
Difference, it can lead to distances that are odd numbers.
However, note one strong restriction. The trees should all have the
same list of species. If you use one set of species in the first two
trees, and another in the second two, and choose distances for adjacent
pairs, the distances will be incorrect and will depend on the order of
these pairs in the input tree file, in odd ways.
Usage
Here is a sample session with ftreedistpair
% ftreedistpair -style s
Calculate distance between two sets of trees
Phylip tree file: treedist.dat
Second phylip tree file: treedist.dat
Phylip treedist program output file [treedist.ftreedistpair]:
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Calculate distance between two sets of trees
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-bintreefile] tree Second phylip tree file
[-outfile] outfile [*.ftreedistpair] Phylip treedist program
output file
Additional (Optional) qualifiers:
-dtype menu [b] Distance type (Values: s (Symmetric
difference); b (Branch score distance))
-pairing menu [l] Tree pairing method (Values: c
(Distances between corresponding pairs each
tree file); l (Distances between all
possible pairs in each tree file))
-style menu [v] Distances output option (Values: f
(Full_matrix); v (Verbose, one pair per
line); s (Sparse, one pair per line))
-noroot boolean [N] Trees to be treated as rooted
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-progress boolean [N] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
ftreedistpair reads two input tree files. The tree files may either
have the number of trees on their first line, or not. If the number of
trees is given, it is actually ignored and all trees in the tree file
are considered, even if there are more trees than indicated by the
number. There is no maximum number of trees that can be processed but,
if you feed in too many, there may be an error message about running
out of memory. The problem is particularly acute if you choose the
option to examine all possible pairs of trees one from each of two
input tree files. Thus if there are 1,000 trees in the input tree file,
keep in mind that all possible pairs means 1,000,000 pairs to be
examined!
Input files for usage example
File: treedist.dat
(A:0.1,(B:0.1,(H:0.1,(D:0.1,(J:0.1,(((G:0.1,E:0.1):0.1,(F:0.1,I:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(D:0.1,((J:0.1,H:0.1):0.1,(((G:0.1,E:0.1):0.1,
(F:0.1,I:0.1):0.1):0.1,C:0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(D:0.1,(H:0.1,(J:0.1,(((G:0.1,E:0.1):0.1,(F:0.1,I:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,(G:0.1,((F:0.1,I:0.1):0.1,((J:0.1,(H:0.1,D:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,(G:0.1,((F:0.1,I:0.1):0.1,(((J:0.1,H:0.1):0.1,D:0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((F:0.1,I:0.1):0.1,(G:0.1,((J:0.1,(H:0.1,D:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((F:0.1,I:0.1):0.1,(G:0.1,(((J:0.1,H:0.1):0.1,D:0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((G:0.1,(F:0.1,I:0.1):0.1):0.1,((J:0.1,(H:0.1,
D:0.1):0.1):0.1,C:0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((G:0.1,(F:0.1,I:0.1):0.1):0.1,(((J:0.1,H:0.1):0.1,
D:0.1):0.1,C:0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,(G:0.1,((F:0.1,I:0.1):0.1,((J:0.1,(H:0.1,D:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(D:0.1,(H:0.1,(J:0.1,(((G:0.1,E:0.1):0.1,(F:0.1,I:0.1):0.1):0.1,
C:0.1):0.1):0.1):0.1):0.1):0.1);
(A:0.1,(B:0.1,(E:0.1,((G:0.1,(F:0.1,I:0.1):0.1):0.1,((J:0.1,(H:0.1,
D:0.1):0.1):0.1,C:0.1):0.1):0.1):0.1):0.1);
Output file format
If any of the four types of analysis are selected, the user must
specify how they want the results presented.
The Full matrix (choice F) is a table showing all distances. It is
written onto the output file. The table is presented as groups of 10
columns. Here is the Full matrix for the 12 trees in the input tree
file which is given as an example at the end of this page.
Tree distance program, version 3.6
Symmetric differences between all pairs of trees in tree file:
1 2 3 4 5 6 7 8 9 10
\------------------------------------------------------------
1 | 0 4 2 10 10 10 10 10 10 10
2 | 4 0 2 10 8 10 8 10 8 10
3 | 2 2 0 10 10 10 10 10 10 10
4 | 10 10 10 0 2 2 4 2 4 0
5 | 10 8 10 2 0 4 2 4 2 2
6 | 10 10 10 2 4 0 2 2 4 2
7 | 10 8 10 4 2 2 0 4 2 4
8 | 10 10 10 2 4 2 4 0 2 2
9 | 10 8 10 4 2 4 2 2 0 4
10 | 10 10 10 0 2 2 4 2 4 0
11 | 2 2 0 10 10 10 10 10 10 10
12 | 10 10 10 2 4 2 4 0 2 2
11 12
\------------
1 | 2 10
2 | 2 10
3 | 0 10
4 | 10 2
5 | 10 4
6 | 10 2
7 | 10 4
8 | 10 0
9 | 10 2
10 | 10 2
11 | 0 10
12 | 10 0
The Full matrix is only available for analyses P and L (not for A or
C).
Option V (Verbose) writes one distance per line. The Verbose output is
the default. Here it is for the example data set given below:
Tree distance program, version 3.6
Symmetric differences between adjacent pairs of trees:
Trees 1 and 2: 4
Trees 3 and 4: 10
Trees 5 and 6: 4
Trees 7 and 8: 4
Trees 9 and 10: 4
Trees 11 and 12: 10
Option S (Sparse or terse) is similar except that all that is given on
each line are the numbers of the two trees and the distance, separated
by blanks. This may be a convenient format if you want to write a
program to read these numbers in, and you want to spare yourself the
effort of having the program wade through the words on each line in the
Verbose output. The first four lines of the Sparse output are titles
that your program would want to skip past. Here is the Sparse output
for the example trees.
1 2 4
3 4 10
5 6 4
7 8 4
9 10 4
11 12 10
Output files for usage example
File: treedist.ftreedistpair
1 13 0.000000e+00
1 14 2.000000e-01
1 15 1.414214e-01
1 16 3.162278e-01
1 17 3.162278e-01
1 18 3.162278e-01
1 19 3.162278e-01
1 20 3.162278e-01
1 21 3.162278e-01
1 22 3.162278e-01
1 23 1.414214e-01
1 24 3.162278e-01
2 13 2.000000e-01
2 14 0.000000e+00
2 15 1.414214e-01
2 16 3.162278e-01
2 17 2.828427e-01
2 18 3.162278e-01
2 19 2.828427e-01
2 20 3.162278e-01
2 21 2.828427e-01
2 22 3.162278e-01
2 23 1.414214e-01
2 24 3.162278e-01
3 13 1.414214e-01
3 14 1.414214e-01
3 15 0.000000e+00
3 16 3.162278e-01
3 17 3.162278e-01
3 18 3.162278e-01
3 19 3.162278e-01
3 20 3.162278e-01
3 21 3.162278e-01
3 22 3.162278e-01
3 23 0.000000e+00
3 24 3.162278e-01
4 13 3.162278e-01
4 14 3.162278e-01
4 15 3.162278e-01
4 16 0.000000e+00
4 17 1.414214e-01
4 18 1.414214e-01
4 19 2.000000e-01
4 20 1.414214e-01
4 21 2.000000e-01
4 22 0.000000e+00
4 23 3.162278e-01
4 24 1.414214e-01
5 13 3.162278e-01
5 14 2.828427e-01
[Part of this file has been deleted for brevity]
20 10 1.414214e-01
20 11 3.162278e-01
20 12 0.000000e+00
21 1 3.162278e-01
21 2 2.828427e-01
21 3 3.162278e-01
21 4 2.000000e-01
21 5 1.414214e-01
21 6 2.000000e-01
21 7 1.414214e-01
21 8 1.414214e-01
21 9 0.000000e+00
21 10 2.000000e-01
21 11 3.162278e-01
21 12 1.414214e-01
22 1 3.162278e-01
22 2 3.162278e-01
22 3 3.162278e-01
22 4 0.000000e+00
22 5 1.414214e-01
22 6 1.414214e-01
22 7 2.000000e-01
22 8 1.414214e-01
22 9 2.000000e-01
22 10 0.000000e+00
22 11 3.162278e-01
22 12 1.414214e-01
23 1 1.414214e-01
23 2 1.414214e-01
23 3 0.000000e+00
23 4 3.162278e-01
23 5 3.162278e-01
23 6 3.162278e-01
23 7 3.162278e-01
23 8 3.162278e-01
23 9 3.162278e-01
23 10 3.162278e-01
23 11 0.000000e+00
23 12 3.162278e-01
24 1 3.162278e-01
24 2 3.162278e-01
24 3 3.162278e-01
24 4 1.414214e-01
24 5 2.000000e-01
24 6 1.414214e-01
24 7 2.000000e-01
24 8 0.000000e+00
24 9 1.414214e-01
24 10 1.414214e-01
24 11 3.162278e-01
24 12 0.000000e+00
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
econsense Majority-rule and strict consensus tree
fconsense Majority-rule and strict consensus tree
ftreedist Calculate distances between trees
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fretree.txt 0000664 0001750 0001750 00000027534 12171064331 015575 0000000 0000000 fretree
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Interactive tree rearrangement
Description
Reads in a tree (with branch lengths if necessary) and allows you to
reroot the tree, to flip branches, to change species names and branch
lengths, and then write the result out. Can be used to convert between
rooted and unrooted trees, and to write the tree into a preliminary
version of a new XML tree file format which is under development and
which is described in the RETREE documentation web page.
Algorithm
RETREE is a tree editor. It reads in a tree, or allows the user to
construct one, and displays this tree on the screen. The user then can
specify how the tree is to be rearranged, rerooted or written out to a
file.
The input trees are in one file (with default file name intree), the
output trees are written into another (outtree). The user can reroot,
flip branches, change names of species, change or remove branch
lengths, and move around to look at various parts of the tree if it is
too large to fit on the screen. The trees can be multifurcating at any
level, although the user is warned that many PHYLIP programs still
cannot handle multifurcations above the root, or even at the root.
A major use for this program will be to change rootedness of trees so
that a rooted tree derived from one program can be fed in as an
unrooted tree to another (you are asked about this when you give the
command to write out the tree onto the tree output file). It will also
be useful for specifying the length of a branch in a tree where you
want a program like DNAML, DNAMLK, FITCH, or CONTML to hold that branch
length constant (see the L suboption of the User Tree option in those
programs. It will also be useful for changing the order of species for
purely cosmetic reasons for DRAWGRAM and DRAWTREE, including using the
Midpoint method of rooting the tree. It can also be used to write out a
tree file in the Nexus format used by Paup and MacClade or in our XML
tree file format.
This program uses graphic characters that show the tree to best
advantage on some computer systems. Its graphic characters will work
best on MSDOS systems or MSDOS windows in Windows, and to any system
whose screen or terminals emulate ANSI standard terminals such as old
Digitial VT100 terminals, Telnet programs, or VT100-compatible windows
in the X windowing system. For any other screen types, (such as
Macintosh windows) there is a generic option which does not make use of
screen graphics characters. The program will work well in those cases,
but the tree it displays will look a bit uglier.
Usage
Here is a sample session with fretree
% fretree
Interactive tree rearrangement
Number of species [0]: 10
Phylip tree file: retree.dat
Phylip tree output file [retree.treefile]:
NEXT? (R . U W O T F D B N H J K L C + ? X Q) (? for Help): Q
Do you want to write out the tree to a file? (Y or N): Y
Enter R if the tree is to be rooted, OR enter U if the tree is to be unrooted: U
Tree written to file "retree.treefile"
Reading tree file ...
,>>1:Human
,>22
,>21 `>>2:Chimp
! !
,>20 `>>>>>3:Gorilla
! !
,>>>>>>>>>>19 `>>>>>>>>4:Orang
! !
,>18 `>>>>>>>>>>>5:Gibbon
! !
! ! ,>>>>>>>>6:Barbary Ma
! `>>>>>>>>>>>>>23
! ! ,>>>>>7:Crab-e. Ma
,>>>>>>>17 `>24
! ! ! ,>>8:Rhesus Mac
! ! `>25
! ! `>>9:Jpn Macaq
,>16 !
! ! `>>>>>>>>>>>>>>>>>>>>>>>>>10:Squir. Mon
! !
! ! ,>11:Tarsier
** 7 lines below screen **
Go to the input files for this example
Go to the output files for this example
Command line arguments
Interactive tree rearrangement
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-spp] integer [0] Number of species (Any integer value)
[-intreefile] tree Phylip tree file
[-outtreefile] outfile [*.fretree] Phylip tree output file
Additional (Optional) qualifiers:
-initialtree menu [Arbitary] Initial tree (Values: a
(Arbitary); u (User); s (Specify))
-format menu [p] Format to write trees (Values: p
(PHYLIP); n (NEXUS); x (XML))
-screenwidth integer [80] Width of terminal screen in characters
(Any integer value)
-vscreenwidth integer [80] Width of plotting area in characters
(Any integer value)
-screenlines integer [24] Number of lines on screen (Any integer
value)
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outtreefile" associated qualifiers
-odirectory3 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fretree reads any normal sequence USAs.
Input files for usage example
File: retree.dat
((((((((Human,Chimp),Gorilla),Orang),Gibbon),(Barbary_Ma,(Crab-e._Ma,
(Rhesus_Mac,Jpn_Macaq)))),Squir._Mon),((Tarsier,Lemur),Bovine)),Mouse);
Output file format
The N (output file format) option allows the user to specify that the
tree files that are written by the program will be in one of three
formats:
1. The PHYLIP default file format (the Newick standard) used by the
programs in this package.
2. The Nexus format defined by David Swofford and by Wayne Maddison
and David Maddison for their programs PAUP and MacClade. A tree
file written in Nexus format should be directly readable by those
programs (They also have options to read a regular PHYLIP tree file
as well).
3. An XML tree file format which we have defined.
The XML tree file format is fairly simple. The tree file, which may
have multiple trees, is enclosed in a pair of ...
tags. Each tree is included in tags ...
. Each branch of the tree is enclosed in a pair of tags
... , which enclose the branch and all its descendants.
If the branch has a length, this is given by the LENGTH attribute of
the CLADE tag, so that the pair of tags looks like this: ...
A tip of the tree is at the end of a branch (and hence that branch is
enclosed in a pair of ... tags). Its name is enclosed
by ... tags. Here is an XML tree:
MouseBovineGibbonOrangGorillaChimpHuman
The indentation is for readability but is not part of the XML tree
standard, which ignores that kind of white space.
What programs can read an XML tree? None right now, not even PHYLIP
programs! But soon our lab's LAMARC package will have programs that can
read an XML tree. XML is rapidly becoming the standard for representing
and interchanging complex data -- it is time to have an XML tree
standard. Certain extensions are obvious (to represent the bootstrap
proportion for a branch, use BOOTP=0.83 in the CLADE tag, for example).
There are other proposals for an XML tree standard. They have many
similarities to this one, but are not identical to it. At the moment
there is no mechanism in place for deciding between them other than
seeing which get widely used. Here are links to other proposals:
Taxonomic Markup Language http://www.albany.edu/~gilmr/pubxml/. and
preprint at xml.coverpages.org/gilmour-TML.pdf published in the paper
by Ron Gilmour (2000).
Andrew Rambaut's BEAST XML phylogeny format See page 9 of PDF of BEAST
manual at http://evolve.zoo.ox.ac.uk/beast/ An XML format for
phylogenies is sketchly described there.
treeml http://www.nomencurator.org/InfoVis2003/download/treeml.dtd (see
also example: )
http://www.cs.umd.edu/hcil/iv03contest/datasets/treeml-sample.xml
Jean-Daniel Fekete's DTD for a tree XML file
The W (screen and window Width) option specifies the width in
characters of the area which the trees will be plotted to fit into.
This is by default 80 characters so that they will fit on a normal
width terminal. The actual width of the display on the terminal
(normally 80 characters) will be regarded as a window displaying part
of the tree. Thus you could set the "plotting area" to 132 characters,
and inform the program that the screen width is 80 characters. Then the
program will display only part of the tree at any one time.
Output files for usage example
File: retree.treefile
(((((((Human,Chimp),Gorilla),Orang),Gibbon),(Barbary_Ma,(Crab-e._Ma,
(Rhesus_Mac,Jpn_Macaq)))),Squir._Mon),((Tarsier,Lemur),Bovine),Mouse);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
fdrawgram Plots a cladogram- or phenogram-like rooted tree diagram
fdrawtree Plots an unrooted tree diagram
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fseqbootall.txt 0000664 0001750 0001750 00000057224 12171064331 016453 0000000 0000000 fseqbootall
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped sequences algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of the
package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
SEQBOOT is a general bootstrapping and data set translation tool. It is
intended to allow you to generate multiple data sets that are resampled
versions of the input data set. Since almost all programs in the
package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or permuted.
SEQBOOT can handle molecular sequences, binary characters, restriction
sites, or gene frequencies. It can also convert data sets between
Sequential and Interleaved format, and into the NEXUS format or into a
new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of interest.
For example, if you were using DNAPARS you would first run SEQBOOT and
make a file with 100 bootstrapped data sets. Then you would give this
file the proper name to have it be the input file for DNAPARS. Running
DNAPARS with the M (Multiple Data Sets) menu choice and informing it to
expect 100 data sets, you would generate a big output file as well as a
treefile with the trees from the 100 data sets. This treefile could be
renamed so that it would serve as the input for CONSENSE. When CONSENSE
is run the majority rule consensus tree will result, showing the
outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this package.
The same steps are necessary with all of them. Doing things this way
some of the intermediate files (the tree file from the DNAPARS run, for
example) can be used to summarize the results of the bootstrap in other
ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add one
extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
* The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me
(Felsenstein, 1985b; see also Penny and Hendy, 1985). It involves
creating a new data set by sampling N characters randomly with
replacement, so that the resulting data set has the same size as
the original, but some characters have been left out and others are
duplicated. The random variation of the results from analyzing
these bootstrapped data sets can be shown statistically to be
typical of the variation that you would get from collecting new
data sets. The method assumes that the characters evolve
independently, an assumption that may not be realistic for many
kinds of data.
* The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial
Bootstrap method, and Shimodaira's (2002) AU method, both of which
correct the bias of bootstrap P values.
* Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct
for it by samopling, not individual characters, but blocks of
adjacent characters. This is called a block bootstrap and was
introduced by Kuensch (1989). If the correlations are believed to
extend over some number of characters, you choose a block size, B,
that is larger than this, and choose N/B blocks of size B. In its
implementation here the block bootstrap "wraps around" at the end
of the characters (so that if a block starts in the last B-1
characters, it continues by wrapping around to the first character
after it reaches the last character). Note also that if you have a
DNA sequence data set of an exon of a coding region, you can ensure
that equal numbers of first, second, and third coding positions are
sampled by using the block bootstrap with B = 3.
* Partial block-bootstrapping. Similar to partial bootstrapping
except sampling blocks rather than single characters.
* Delete-half-jackknifing.. This alternative to the bootstrap
involves sampling a random half of the characters, and including
them in the data but dropping the others. The resulting data sets
are half the size of the original, and no characters are
duplicated. The random variation from doing this should be very
similar to that obtained from the bootstrap. The method is
advocated by Wu (1986). It was mentioned by me in my bootstrapping
paper (Felsenstein, 1985b), and has been available for many years
in this program as an option. Note that, for the present,
block-jackknifing is not available, because I cannot figure out how
to do it straightforwardly when the block size is not a divisor of
the number of characters.
* Delete-fraction jackknifing. Jackknifing is advocated by Farris et.
al. (1996) but as deleting a fraction 1/e (1/2.71828). This retains
too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it
is made available here as an option, with the user asked to supply
the fraction of characters that are to be retained.
* Permuting species within characters. This method of resampling
(well, OK, it may not be best to call it resampling) was introduced
by Archie (1989) and Faith (1990; see also Faith and Cranston,
1991). It involves permuting the columns of the data matrix
separately. This produces data matrices that have the same number
and kinds of characters but no taxonomic structure. It is used for
different purposes than the bootstrap, as it tests not the
variation around an estimated tree but the hypothesis that there is
no taxonomic structure in the data: if a statistic such as number
of steps is significantly smaller in the actual data than it is in
replicates that are permuted, then we can argue that there is some
taxonomic structure in the data (though perhaps it might be just
the presence of aa pair of sibling species).
* Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For
many methods of tree inference this will make no difference to the
outcome (unless one has rates of evolution correlated among
adjacent sites). It is included as a possible step in carrying out
a permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
* Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so
as to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
* Rewriting. This is not a resampling or permutation method: it
simply rewrites the data set into a different format. That format
can be the PHYLIP format. For molecular sequences and discrete
morphological character it can also be the NEXUS format. For
molecular sequences one other format is available, a new (and
nonstandard) XML format of our own devising. When the PHYLIP format
is chosen the data set is coverted between Interleaved and
Sequential format. If it was read in as Interleaved sequences, it
will be written out as Sequential format, and vice versa. The NEXUS
format for molecular sequences is always written as interleaved
sequences. The XML format is different from (though similar to) a
number of other XML sequence alignment formats. An example will be
found below. Here is a table to links to those other XML alignment
formats:
Andrew Rambaut's BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html and
http://evolve.zoo.ox.ac.uk/beast/referenindex.html A format for
alignments. There is also a format for phylogenies described there.
MSAML M http://xml.coverpages.org/msaml-desc-dec.html Defined by Paul
Gordon of University of Calgary. See his big list of molecular biology
XML projects.
BSML http://www.bsml.org/resources/default.asp Bioinformatic Sequence
Markup Language includes a multiple sequence alignment XML format
Usage
Here is a sample session with fseqbootall
% fseqbootall -seed 3
Bootstrapped sequences algorithm
Input (aligned) sequence set: seqboot.dat
Phylip seqboot program output file [seqboot.fseqbootall]:
bootstrap: true
jackknife: false
permute: false
lockhart: false
ild: false
justwts: false
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "seqboot.fseqbootall"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Bootstrapped sequences algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infilesequences] seqset (Aligned) sequence set filename and optional
format, or reference (input USA)
[-outfile] outfile [*.fseqbootall] Phylip seqboot program
output file
Additional (Optional) qualifiers (* if not always prompted):
-categories properties File of input categories
-mixfile properties File of mixtures
-ancfile properties File of ancestors
-weights properties Weights file
-factorfile properties Factors file
-datatype menu [s] Choose the datatype (Values: s
(Molecular sequences); m (Discrete
Morphology); r (Restriction Sites); g (Gene
Frequencies))
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -rewriteformat menu [p] Output format (Values: p (PHYLIP); n
(NEXUS); x (XML))
* -seqtype menu [d] Output format (Values: d (dna); p
(protein); r (rna))
* -morphseqtype menu [p] Output format (Values: p (PHYLIP); n
(NEXUS))
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
* -enzymes boolean [N] Is the number of enzymes present in
input file
* -all boolean [N] All alleles present at each locus
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-infilesequences" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fseqbootall data files read by SEQBOOT are the standard ones for the
various kinds of data. For molecular sequences the sequences may be
either interleaved or sequential, and similarly for restriction sites.
Restriction sites data may either have or not have the third argument,
the number of restriction enzymes used. Discrete morphological
characters are always assumed to be in sequential format. Gene
frequencies data start with the number of species and the number of
loci, and then follow that by a line with the number of alleles at each
locus. The data for each locus may either have one entry for each
allele, or omit one allele at each locus. The details of the formats
are given in the main documentation file, and in the documentation
files for the groups of programsreads any normal sequence USAs.
Input files for usage example
File: seqboot.dat
5 6
Alpha AACAAC
Beta AACCCC
Gamma ACCAAC
Delta CCACCA
Epsilon CCAAAC
Output file format
fseqbootall output will contain the data sets generated by the
resampling process. Note that, when Gene Frequencies data is used or
when Discrete Morphological characters with the Factors option are
used, the number of characters in each data set may vary. It may also
vary if there are an odd number of characters or sites and the
Delete-Half-Jackknife resampling method is used, for then there will be
a 50% chance of choosing (n+1)/2 characters and a 50% chance of
choosing (n-1)/2 characters.
The Factors option causes the characters to be resampled together. If
(say) three adjacent characters all have the same factors characters,
so that they all are understood to be recoding one multistate
character, they will be resampled together as a group.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these
data avoid any result which is sensitive to the input order of species
from showing up repeatedly and thus appearing to have evidence in its
favor.
The numerical options 1 and 2 in the menu also affect the output file.
If 1 is chosen (it is off by default) the program will print the
original input data set on the output file before the resampled data
sets. I cannot actually see why anyone would want to do this. Option 2
toggles the feature (on by default) that prints out up to 20 times
during the resampling process a notification that the program has
completed a certain number of data sets. Thus if 100 resampled data
sets are being produced, every 5 data sets a line is printed saying
which data set has just been completed. This option should be turned
off if the program is running in background and silence is desirable.
At the end of execution the program will always (whatever the setting
of option 2) print a couple of lines saying that output has been
written to the output file.
Output files for usage example
File: seqboot.fseqbootall
5 6
Alpha AAACCA
Beta AAACCC
Gamma ACCCCA
Delta CCCAAC
Epsilon CCCAAA
5 6
Alpha AAACAA
Beta AAACCC
Gamma ACCCAA
Delta CCCACC
Epsilon CCCAAA
5 6
Alpha AAAAAC
Beta AAACCC
Gamma AACAAC
Delta CCCCCA
Epsilon CCCAAC
5 6
Alpha CCCCCA
Beta CCCCCC
Gamma CCCCCA
Delta AAAAAC
Epsilon AAAAAA
5 6
Alpha AAAACC
Beta AAACCC
Gamma AACACC
Delta CCCCAA
Epsilon CCCACC
5 6
Alpha AAAACC
Beta ACCCCC
Gamma AAAACC
Delta CCCCAA
Epsilon CAAACC
5 6
Alpha AACCAA
Beta AACCCC
Gamma ACCCAA
Delta CCAACC
Epsilon CCAAAA
5 6
Alpha AAAACC
Beta ACCCCC
Gamma AAAACC
Delta CCCCAA
Epsilon CAAACC
5 6
Alpha AACACC
[Part of this file has been deleted for brevity]
Gamma ACAAAA
Delta CCCCCC
Epsilon CCAAAA
5 6
Alpha AACAAC
Beta AACCCC
Gamma AACAAC
Delta CCACCA
Epsilon CCAAAC
5 6
Alpha AACAAA
Beta AACCCC
Gamma CCCAAA
Delta CCACCC
Epsilon CCAAAA
5 6
Alpha ACAAAA
Beta ACCCCC
Gamma CCAAAA
Delta CACCCC
Epsilon CAAAAA
5 6
Alpha CAAAAA
Beta CCCCCC
Gamma CAAAAA
Delta ACCCCC
Epsilon AAAAAA
5 6
Alpha CAACCC
Beta CCCCCC
Gamma CAACCC
Delta ACCAAA
Epsilon AAACCC
5 6
Alpha ACAACC
Beta ACCCCC
Gamma ACAACC
Delta CACCAA
Epsilon CAAACC
5 6
Alpha AAAAAA
Beta AAAAAC
Gamma ACCCCA
Delta CCCCCC
Epsilon CCCCCA
5 6
Alpha AACAAC
Beta AACCCC
Gamma CCCAAC
Delta CCACCA
Epsilon CCAAAC
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fpromlk.txt 0000664 0001750 0001750 00000065370 12171064331 015613 0000000 0000000 fpromlk
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Protein phylogeny by maximum likelihood
Description
Same as PROML but assumes a molecular clock. The use of the two
programs together permits a likelihood ratio test of the molecular
clock hypothesis to be made.
Estimates phylogenies from protein amino acid sequences by maximum
likelihood. The PAM, JTT, or PMB models can be employed, and also use
of a Hidden Markov model of rates, with the program inferring which
sites have which rates. This also allows gamma-distribution and
gamma-plus-invariant sites distributions of rates across sites. It also
allows different rates of change at known sites.
Algorithm
This program implements the maximum likelihood method for protein amino
acid sequences under the constraint that the trees estimated must be
consistent with a molecular clock. The molecular clock is the
assumption that the tips of the tree are all equidistant, in branch
length, from its root. This program is indirectly related to PROML. It
uses the Dayhoff probability model of change between amino acids. Its
algorithmic details are not yet published, but many of them are similar
to DNAMLK.
The assumptions of the model are:
1. Each position in the sequence evolves independently.
2. Different lineages evolve independently.
3. Each position undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of
occurrence) which we specify.
4. All relevant positions are included in the sequence, not just those
that have changed or those that are "phylogenetically informative".
5. The probabilities of change between amino acids are given by the
model of Jones,
6. Taylor, and Thornton (1992), the PMB model of Veerassamy, Smith and
Tillier (2004), or the PAM model of Dayhoff (Dayhoff and Eck, 1968;
Dayhoff et. al., 1979).
Note the assumption that we are looking at all positions, including
those that have not changed at all. It is important not to restrict
attention to some positions based on whether or not they have changed;
doing that would bias branch lengths by making them too long, and that
in turn would cause the method to misinterpret the meaning of those
positions that had changed.
This program uses a Hidden Markov Model (HMM) method of inferring
different rates of evolution at different amino acid positions. This
was described in a paper by me and Gary Churchill (1996). It allows us
to specify to the program that there will be a number of different
possible evolutionary rates, what the prior probabilities of occurrence
of each is, and what the average length of a patch of positions all
having the same rate. The rates can also be chosen by the program to
approximate a Gamma distribution of rates, or a Gamma distribution plus
a class of invariant positions. The program computes the likelihood by
summing it over all possible assignments of rates to positions,
weighting each by its prior probability of occurrence.
For example, if we have used the C and A options (described below) to
specify that there are three possible rates of evolution, 1.0, 2.4, and
0.0, that the prior probabilities of a position having these rates are
0.4, 0.3, and 0.3, and that the average patch length (number of
consecutive positions with the same rate) is 2.0, the program will sum
the likelihood over all possibilities, but giving less weight to those
that (say) assign all positions to rate 2.4, or that fail to have
consecutive positions that have the same rate.
The Hidden Markov Model framework for rate variation among positions
was independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of rates; we
allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant positions.
This feature effectively removes the artificial assumption that all
positions have the same rate, and also means that we need not know in
advance the identities of the positions that have a particular rate of
evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each positions (for example, we might want amino
acid positions in the active site of a protein to change more slowly
than other positions. This is done with the categories input file and
the C option. We then specify (using the menu) the relative rates of
evolution of amino acid positions in the different categories. For
example, we might specify that positions in the active site evolve at
relative rates of 0.2 compared to 1.0 at other positions. If we are
assuming that a particular position maintains a cysteine bridge to
another, we may want to put it in a category of positions (including
perhaps the initial position of the protein sequence which maintains
methionine) which changes at a rate of 0.0.
If both user-assigned rate categories and Hidden Markov Model rates are
allowed, the program assumes that the actual rate at a position is the
product of the user-assigned category rate and the Hidden Markov Model
regional rate. (This may not always make perfect biological sense: it
would be more natural to assume some upper bound to the rate, as we
have discussed in the Felsenstein and Churchill paper). Nevertheless
you may want to use both types of rate variation.
Usage
Here is a sample session with fpromlk
% fpromlk
Protein phylogeny by maximum likelihood
Input (aligned) protein sequence set(s): promlk.dat
Phylip tree file (optional):
Phylip promlk program output file [promlk.fpromlk]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "promlk.fpromlk"
Tree also written onto file "promlk.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Protein phylogeny by maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fpromlk] Phylip promlk program output
file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
* -lengths boolean [N] Use branch lengths from user trees
-model menu [Jones-Taylor-Thornton] Probability model
for amino acid change (Values: j
(Jones-Taylor-Thornton); h (Henikoff/Tillier
PMBs); d (Dayhoff PAM))
-gammatype menu [n] Rate variation among sites (Values: g
(Gamma distributed rates); i
(Gamma+invariant sites); h (User defined HMM
of rates); n (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ngammacat integer [1] Number of categories (1-9) (Integer from
1 to 9)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ninvarcat integer [1] Number of categories (1-9) including one
for invariant sites (Integer from 1 to 9)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -nhmmcategories integer [1] Number of HMM rate categories (Integer
from 1 to 9)
* -hmmrates array [1.0] HMM category rates
* -hmmprobabilities array [1.0] Probability for each HMM category
* -adjsite boolean [N] Rates at adjacent sites correlated
* -lambda float [1.0] Mean block length of sites having the
same rate (Number 1.000 or more)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fpromlk] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-hypstate boolean [N] Reconstruct hypothetical sequence
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fpromlk reads any normal sequence USAs.
Input files for usage example
File: promlk.dat
5 13
Alpha AACGTGGCCAAAT
Beta AAGGTCGCCAAAC
Gamma CATTTCGTCACAA
Delta GGTATTTCGGCCT
Epsilon GGGATCTCGGCCC
Output file format
fpromlk output starts by giving the number of species, the number of
amino acid positions.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of positions is printed, as well
as the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the menu
option to print them out, with the base sequences printed in groups of
ten amino acids. The trees found are printed as a rooted tree topology.
The internal nodes are numbered arbitrarily for the sake of
identification. The number of trees evaluated so far and the log
likelihood of the tree are also given. The branch lengths in the
diagram are roughly proportional to the estimated branch lengths,
except that very short branches are printed out at least three
characters in length so that the connections can be seen. The unit of
branch length is the expected fraction of amino acids changed (so that
1.0 is 100 PAMs).
A table is printed showing the length of each tree segment, and the
time (in units of expected amino acid substitutions per position) of
each fork in the tree, measured from the root of the tree. I have not
attempted in include code for approximate confidence limits on branch
points, as I have done for branch lengths in PROML, both because of the
extreme crudeness of that test, and because the variation of times for
different forks would be highly correlated.
The log likelihood printed out with the final tree can be used to
perform various likelihood ratio tests. One can, for example, compare
runs with different values of the relative rate of change in the active
site and in the rest of the protein to determine which value is the
maximum likelihood estimate, and what is the allowable range of values
(using a likelihood ratio test, which you will find described in
mathematical statistics books). One could also estimate the base
frequencies in the same way. Both of these, particularly the latter,
require multiple runs of the program to evaluate different possibl
values, and this might get expensive.
This program makes possible a (reasonably) legitimate statistical test
of the molecular clock. To do such a test, run PROML and PROMLK on the
same data. If the trees obtained are of the same topology (when
considered as unrooted), it is legitimate to compare their likelihoods
by the likelihood ratio test. In PROML the likelihood has been computed
by estimating 2n-3 branch lengths, if their are n tips on the tree. In
PROMLK it has been computed by estimating n-1 branching times (in
effect, n-1 branch lengths). The difference in the number of parameters
is (2n-3)-(n-1) = n-2. To perform the test take the difference in log
likelihoods between the two runs (PROML should be the higher of the
two, barring numerical iteration difficulties) and double it. Look this
up on a chi-square distribution with n-2 degrees of freedom. If the
result is significant, the log likelihood has been significantly
increased by allowing all 2n-3 branch lengths to be estimated instead
of just n-1, and molecular clock may be rejected.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the rates
at different amino acid positions, the program also performs a
statistical test of each of these trees against the one with highest
likelihood. If there are two user trees, the test done is one which is
due to Kishino and Hasegawa (1989), a version of a test originally
introduced by Templeton (1983). In this implementation it uses the mean
and variance of log-likelihood differences between trees, taken across
amino acid positions. If the two trees' means are more than 1.96
standard deviations different then the trees are declared significantly
different. This use of the empirical variance of log-likelihood
differences is more robust and nonparametric than the classical
likelihood ratio test, and may to some extent compensate for the any
lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. In the version used here
the variances and covariances of the sum of log likelihoods across
amino acid positions are computed for all pairs of trees. To test
whether the difference between each tree and the best one is larger
than could have been expected if they all had the same expected
log-likelihood, log-likelihoods for all trees are sampled with these
covariances and equal means (Shimodaira and Hasegawa's "least favorable
hypothesis"), and a P value is computed from the fraction of times the
difference between the tree's value and the highest log-likelihood
exceeds that actually observed. Note that this sampling needs random
numbers, and so the program will prompt the user for a random number
seed if one has not already been supplied. With the two-tree KHT test
no random numbers are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one. However the
test is not available if we assume that there is autocorrelation of
rates at neighboring positions (option A) and is not done in those
cases.
The branch lengths printed out are scaled in terms of 100 times the
expected numbers of amino acid substitutions, scaled so that the
average rate of change, averaged over all the positions analyzed, is
set to 100.0, if there are multiple categories of positions. This means
that whether or not there are multiple categories of positions, the
expected percentage of change for very small branches is equal to the
branch length. Of course, when a branch is twice as long this does not
mean that there will be twice as much net change expected along it,
since some of the changes occur in the same position and overlie or
even reverse each other. underlying numbers of changes. That means that
a branch of length 26 is 26 times as long as one which would show a 1%
difference between the amino acid sequences at the beginning and end of
the branch, but we would not expect the sequences at the beginning and
end of the branch to be 26% different, as there would be some
overlaying of changes.
Because of limitations of the numerical algorithm, branch length
estimates of zero will often print out as small numbers such as
0.00001. If you see a branch length that small, it is really estimated
to be of zero length.
Another possible source of confusion is the existence of negative
values for the log likelihood. This is not really a problem; the log
likelihood is not a probability but the logarithm of a probability.
When it is negative it simply means that the corresponding probability
is less than one (since we are seeing its logarithm). The log
likelihood is maximized by being made more positive: -30.23 is worse
than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what amino acid position
categories contributed the most to the final likelihood. This
combination of HMM rate categories need not have contributed a majority
of the likelihood, just a plurality. Still, it will be helpful as a
view of where the program infers that the higher and lower rates are.
Note that the use in this calculations of the prior probabilities of
different rates, and the average patch length, gives this inference a
"smoothed" appearance: some other combination of rates might make a
greater contribution to the likelihood, but be discounted because it
conflicts with this prior information. See the example output below to
see what this printout of rate categories looks like. A second list
will also be printed out, showing for each position which rate
accounted for the highest fraction of the likelihood. If the fraction
of the likelihood accounted for is less than 95%, a dot is printed
instead.
Option 3 in the menu controls whether the tree is printed out into the
output file. This is on by default, and usually you will want to leave
it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees which
are written onto the output tree file, rather than the trees printed on
the output file. To keep the output file from becoming too large, it
may be wisest to use option 3 to prevent trees being printed onto the
output file.
Option 4 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined trees
are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated at
each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species
which are the input sequences). The symbol printed out is for the amino
acid which accounts for the largest fraction of the likelihood at that
position. In that table, if a position has an amino acid which accounts
for more than 95% of the likelihood, its symbol printed in capital
letters (W rather than w). One limitation of the current version of the
program is that when there are multiple HMM rates (option R) the
reconstructed amino acids are based on only the single assignment of
rates to positions which accounts for the largest amount of the
likelihood. Thus the assessment of 95% of the likelihood, in tabulating
the ancestral states, refers to 95% of the likelihood that is accounted
for by that particular combination of rates.
Output files for usage example
File: promlk.fpromlk
Amino acid sequence
Maximum Likelihood method with molecular clock, version 3.69.650
Jones-Taylor-Thornton model of amino acid change
+-----------Epsilon
+---------------------------------------4
! +-----------Delta
--3
! +----------------------------Gamma
+----------------------2
! +--------Beta
+-------------------1
+--------Alpha
Ln Likelihood = -134.70332
Ancestor Node Node Height Length
-------- ---- ---- ------ ------
root 3
3 4 0.66464 0.66464
4 Epsilon 0.85971 0.19507
4 Delta 0.85971 0.19507
3 2 0.37420 0.37420
2 Gamma 0.85971 0.48551
2 1 0.70208 0.32788
1 Beta 0.85971 0.15763
1 Alpha 0.85971 0.15763
File: promlk.treefile
((Epsilon:0.19507,Delta:0.19507):0.66464,(Gamma:0.48551,
(Beta:0.15763,Alpha:0.15763):0.32788):0.37420);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/ffreqboot.txt 0000664 0001750 0001750 00000064734 12171064331 016133 0000000 0000000 ffreqboot
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped genetic frequencies algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of the
package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
FFREQBOOT is a gene frequency specific version of SEQBOOT.
SEQBOOT is a general bootstrapping and data set translation tool. It is
intended to allow you to generate multiple data sets that are resampled
versions of the input data set. Since almost all programs in the
package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or permuted.
SEQBOOT can handle molecular sequences, binary characters, restriction
sites, or gene frequencies. It can also convert data sets between
Sequential and Interleaved format, and into the NEXUS format or into a
new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of interest.
For example, if you were using DNAPARS you would first run SEQBOOT and
make a file with 100 bootstrapped data sets. Then you would give this
file the proper name to have it be the input file for DNAPARS. Running
DNAPARS with the M (Multiple Data Sets) menu choice and informing it to
expect 100 data sets, you would generate a big output file as well as a
treefile with the trees from the 100 data sets. This treefile could be
renamed so that it would serve as the input for CONSENSE. When CONSENSE
is run the majority rule consensus tree will result, showing the
outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this package.
The same steps are necessary with all of them. Doing things this way
some of the intermediate files (the tree file from the DNAPARS run, for
example) can be used to summarize the results of the bootstrap in other
ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add one
extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
* The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me
(Felsenstein, 1985b; see also Penny and Hendy, 1985). It involves
creating a new data set by sampling N characters randomly with
replacement, so that the resulting data set has the same size as
the original, but some characters have been left out and others are
duplicated. The random variation of the results from analyzing
these bootstrapped data sets can be shown statistically to be
typical of the variation that you would get from collecting new
data sets. The method assumes that the characters evolve
independently, an assumption that may not be realistic for many
kinds of data.
* The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial
Bootstrap method, and Shimodaira's (2002) AU method, both of which
correct the bias of bootstrap P values.
* Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct
for it by samopling, not individual characters, but blocks of
adjacent characters. This is called a block bootstrap and was
introduced by Kuensch (1989). If the correlations are believed to
extend over some number of characters, you choose a block size, B,
that is larger than this, and choose N/B blocks of size B. In its
implementation here the block bootstrap "wraps around" at the end
of the characters (so that if a block starts in the last B-1
characters, it continues by wrapping around to the first character
after it reaches the last character). Note also that if you have a
DNA sequence data set of an exon of a coding region, you can ensure
that equal numbers of first, second, and third coding positions are
sampled by using the block bootstrap with B = 3.
* Partial block-bootstrapping. Similar to partial bootstrapping
except sampling blocks rather than single characters.
* Delete-half-jackknifing.. This alternative to the bootstrap
involves sampling a random half of the characters, and including
them in the data but dropping the others. The resulting data sets
are half the size of the original, and no characters are
duplicated. The random variation from doing this should be very
similar to that obtained from the bootstrap. The method is
advocated by Wu (1986). It was mentioned by me in my bootstrapping
paper (Felsenstein, 1985b), and has been available for many years
in this program as an option. Note that, for the present,
block-jackknifing is not available, because I cannot figure out how
to do it straightforwardly when the block size is not a divisor of
the number of characters.
* Delete-fraction jackknifing. Jackknifing is advocated by Farris et.
al. (1996) but as deleting a fraction 1/e (1/2.71828). This retains
too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it
is made available here as an option, with the user asked to supply
the fraction of characters that are to be retained.
* Permuting species within characters. This method of resampling
(well, OK, it may not be best to call it resampling) was introduced
by Archie (1989) and Faith (1990; see also Faith and Cranston,
1991). It involves permuting the columns of the data matrix
separately. This produces data matrices that have the same number
and kinds of characters but no taxonomic structure. It is used for
different purposes than the bootstrap, as it tests not the
variation around an estimated tree but the hypothesis that there is
no taxonomic structure in the data: if a statistic such as number
of steps is significantly smaller in the actual data than it is in
replicates that are permuted, then we can argue that there is some
taxonomic structure in the data (though perhaps it might be just
the presence of aa pair of sibling species).
* Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For
many methods of tree inference this will make no difference to the
outcome (unless one has rates of evolution correlated among
adjacent sites). It is included as a possible step in carrying out
a permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
* Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so
as to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
* Rewriting. This is not a resampling or permutation method: it
simply rewrites the data set into a different format. That format
can be the PHYLIP format. For molecular sequences and discrete
morphological character it can also be the NEXUS format. For
molecular sequences one other format is available, a new (and
nonstandard) XML format of our own devising. When the PHYLIP format
is chosen the data set is coverted between Interleaved and
Sequential format. If it was read in as Interleaved sequences, it
will be written out as Sequential format, and vice versa. The NEXUS
format for molecular sequences is always written as interleaved
sequences. The XML format is different from (though similar to) a
number of other XML sequence alignment formats. An example will be
found below. Here is a table to links to those other XML alignment
formats:
Andrew Rambaut's BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html and
http://evolve.zoo.ox.ac.uk/beast/referenindex.html A format for
alignments. There is also a format for phylogenies described there.
MSAML M http://xml.coverpages.org/msaml-desc-dec.html Defined by Paul
Gordon of University of Calgary. See his big list of molecular biology
XML projects.
BSML http://www.bsml.org/resources/default.asp Bioinformatic Sequence
Markup Language includes a multiple sequence alignment XML format
Usage
Here is a sample session with ffreqboot
% ffreqboot -seed 3
Bootstrapped genetic frequencies algorithm
Input file: freqboot.dat
Phylip seqboot_freq program output file [freqboot.ffreqboot]:
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "freqboot.ffreqboot"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Bootstrapped genetic frequencies algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] frequencies (no help text) frequencies value
[-outfile] outfile [*.ffreqboot] Phylip seqboot_freq program
output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
ffreqboot data files read by SEQBOOT are the standard ones for the
various kinds of data. For molecular sequences the sequences may be
either interleaved or sequential, and similarly for restriction sites.
Restriction sites data may either have or not have the third argument,
the number of restriction enzymes used. Discrete morphological
characters are always assumed to be in sequential format. Gene
frequencies data start with the number of species and the number of
loci, and then follow that by a line with the number of alleles at each
locus. The data for each locus may either have one entry for each
allele, or omit one allele at each locus. The details of the formats
are given in the main documentation file, and in the documentation
files for the groups of programsreads any normal sequence USAs.
Input files for usage example
File: freqboot.dat
5 10
2 2 2 2 2 2 2 2 2 2
European 0.2868 0.5684 0.4422 0.4286 0.3828 0.7285 0.6386 0.0205
0.8055 0.5043
African 0.1356 0.4840 0.0602 0.0397 0.5977 0.9675 0.9511 0.0600
0.7582 0.6207
Chinese 0.1628 0.5958 0.7298 1.0000 0.3811 0.7986 0.7782 0.0726
0.7482 0.7334
American 0.0144 0.6990 0.3280 0.7421 0.6606 0.8603 0.7924 0.0000
0.8086 0.8636
Australian 0.1211 0.2274 0.5821 1.0000 0.2018 0.9000 0.9837 0.0396
0.9097 0.2976
Output file format
ffreqboot output will contain the data sets generated by the resampling
process. Note that, when Gene Frequencies data is used or when Discrete
Morphological characters with the Factors option are used, the number
of characters in each data set may vary. It may also vary if there are
an odd number of characters or sites and the Delete-Half-Jackknife
resampling method is used, for then there will be a 50% chance of
choosing (n+1)/2 characters and a 50% chance of choosing (n-1)/2
characters.
The Factors option causes the characters to be resampled together. If
(say) three adjacent characters all have the same factors characters,
so that they all are understood to be recoding one multistate
character, they will be resampled together as a group.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these
data avoid any result which is sensitive to the input order of species
from showing up repeatedly and thus appearing to have evidence in its
favor.
The numerical options 1 and 2 in the menu also affect the output file.
If 1 is chosen (it is off by default) the program will print the
original input data set on the output file before the resampled data
sets. I cannot actually see why anyone would want to do this. Option 2
toggles the feature (on by default) that prints out up to 20 times
during the resampling process a notification that the program has
completed a certain number of data sets. Thus if 100 resampled data
sets are being produced, every 5 data sets a line is printed saying
which data set has just been completed. This option should be turned
off if the program is running in background and silence is desirable.
At the end of execution the program will always (whatever the setting
of option 2) print a couple of lines saying that output has been
written to the output file.
Output files for usage example
File: freqboot.ffreqboot
5 10
2 2 2 2 2 2 2 2 2 2
European 0.28680 0.71320 0.56840 0.43160 0.56840 0.43160 0.44220 0.55780
0.42860 0.57140 0.38280 0.61720 0.38280 0.61720 0.72850 0.27150
0.72850 0.27150 0.02050 0.97950
African 0.13560 0.86440 0.48400 0.51600 0.48400 0.51600 0.06020 0.93980
0.03970 0.96030 0.59770 0.40230 0.59770 0.40230 0.96750 0.03250
0.96750 0.03250 0.06000 0.94000
Chinese 0.16280 0.83720 0.59580 0.40420 0.59580 0.40420 0.72980 0.27020
1.00000 0.00000 0.38110 0.61890 0.38110 0.61890 0.79860 0.20140
0.79860 0.20140 0.07260 0.92740
American 0.01440 0.98560 0.69900 0.30100 0.69900 0.30100 0.32800 0.67200
0.74210 0.25790 0.66060 0.33940 0.66060 0.33940 0.86030 0.13970
0.86030 0.13970 0.00000 1.00000
Australian 0.12110 0.87890 0.22740 0.77260 0.22740 0.77260 0.58210 0.41790
1.00000 0.00000 0.20180 0.79820 0.20180 0.79820 0.90000 0.10000
0.90000 0.10000 0.03960 0.96040
5 10
2 2 2 2 2 2 2 2 2 2
European 0.28680 0.71320 0.56840 0.43160 0.44220 0.55780 0.42860 0.57140
0.38280 0.61720 0.38280 0.61720 0.38280 0.61720 0.02050 0.97950
0.02050 0.97950 0.80550 0.19450
African 0.13560 0.86440 0.48400 0.51600 0.06020 0.93980 0.03970 0.96030
0.59770 0.40230 0.59770 0.40230 0.59770 0.40230 0.06000 0.94000
0.06000 0.94000 0.75820 0.24180
Chinese 0.16280 0.83720 0.59580 0.40420 0.72980 0.27020 1.00000 0.00000
0.38110 0.61890 0.38110 0.61890 0.38110 0.61890 0.07260 0.92740
0.07260 0.92740 0.74820 0.25180
American 0.01440 0.98560 0.69900 0.30100 0.32800 0.67200 0.74210 0.25790
0.66060 0.33940 0.66060 0.33940 0.66060 0.33940 0.00000 1.00000
0.00000 1.00000 0.80860 0.19140
Australian 0.12110 0.87890 0.22740 0.77260 0.58210 0.41790 1.00000 0.00000
0.20180 0.79820 0.20180 0.79820 0.20180 0.79820 0.03960 0.96040
0.03960 0.96040 0.90970 0.09030
5 10
2 2 2 2 2 2 2 2 2 2
European 0.28680 0.71320 0.28680 0.71320 0.44220 0.55780 0.42860 0.57140
0.42860 0.57140 0.38280 0.61720 0.72850 0.27150 0.80550 0.19450
0.80550 0.19450 0.50430 0.49570
African 0.13560 0.86440 0.13560 0.86440 0.06020 0.93980 0.03970 0.96030
0.03970 0.96030 0.59770 0.40230 0.96750 0.03250 0.75820 0.24180
0.75820 0.24180 0.62070 0.37930
Chinese 0.16280 0.83720 0.16280 0.83720 0.72980 0.27020 1.00000 0.00000
1.00000 0.00000 0.38110 0.61890 0.79860 0.20140 0.74820 0.25180
0.74820 0.25180 0.73340 0.26660
American 0.01440 0.98560 0.01440 0.98560 0.32800 0.67200 0.74210 0.25790
0.74210 0.25790 0.66060 0.33940 0.86030 0.13970 0.80860 0.19140
0.80860 0.19140 0.86360 0.13640
Australian 0.12110 0.87890 0.12110 0.87890 0.58210 0.41790 1.00000 0.00000
1.00000 0.00000 0.20180 0.79820 0.90000 0.10000 0.90970 0.09030
[Part of this file has been deleted for brevity]
5 10
2 2 2 2 2 2 2 2 2 2
European 0.28680 0.71320 0.56840 0.43160 0.56840 0.43160 0.56840 0.43160
0.42860 0.57140 0.38280 0.61720 0.38280 0.61720 0.80550 0.19450
0.50430 0.49570 0.50430 0.49570
African 0.13560 0.86440 0.48400 0.51600 0.48400 0.51600 0.48400 0.51600
0.03970 0.96030 0.59770 0.40230 0.59770 0.40230 0.75820 0.24180
0.62070 0.37930 0.62070 0.37930
Chinese 0.16280 0.83720 0.59580 0.40420 0.59580 0.40420 0.59580 0.40420
1.00000 0.00000 0.38110 0.61890 0.38110 0.61890 0.74820 0.25180
0.73340 0.26660 0.73340 0.26660
American 0.01440 0.98560 0.69900 0.30100 0.69900 0.30100 0.69900 0.30100
0.74210 0.25790 0.66060 0.33940 0.66060 0.33940 0.80860 0.19140
0.86360 0.13640 0.86360 0.13640
Australian 0.12110 0.87890 0.22740 0.77260 0.22740 0.77260 0.22740 0.77260
1.00000 0.00000 0.20180 0.79820 0.20180 0.79820 0.90970 0.09030
0.29760 0.70240 0.29760 0.70240
5 10
2 2 2 2 2 2 2 2 2 2
European 0.28680 0.71320 0.28680 0.71320 0.56840 0.43160 0.56840 0.43160
0.44220 0.55780 0.42860 0.57140 0.42860 0.57140 0.72850 0.27150
0.63860 0.36140 0.02050 0.97950
African 0.13560 0.86440 0.13560 0.86440 0.48400 0.51600 0.48400 0.51600
0.06020 0.93980 0.03970 0.96030 0.03970 0.96030 0.96750 0.03250
0.95110 0.04890 0.06000 0.94000
Chinese 0.16280 0.83720 0.16280 0.83720 0.59580 0.40420 0.59580 0.40420
0.72980 0.27020 1.00000 0.00000 1.00000 0.00000 0.79860 0.20140
0.77820 0.22180 0.07260 0.92740
American 0.01440 0.98560 0.01440 0.98560 0.69900 0.30100 0.69900 0.30100
0.32800 0.67200 0.74210 0.25790 0.74210 0.25790 0.86030 0.13970
0.79240 0.20760 0.00000 1.00000
Australian 0.12110 0.87890 0.12110 0.87890 0.22740 0.77260 0.22740 0.77260
0.58210 0.41790 1.00000 0.00000 1.00000 0.00000 0.90000 0.10000
0.98370 0.01630 0.03960 0.96040
5 10
2 2 2 2 2 2 2 2 2 2
European 0.56840 0.43160 0.56840 0.43160 0.44220 0.55780 0.44220 0.55780
0.42860 0.57140 0.38280 0.61720 0.38280 0.61720 0.72850 0.27150
0.63860 0.36140 0.80550 0.19450
African 0.48400 0.51600 0.48400 0.51600 0.06020 0.93980 0.06020 0.93980
0.03970 0.96030 0.59770 0.40230 0.59770 0.40230 0.96750 0.03250
0.95110 0.04890 0.75820 0.24180
Chinese 0.59580 0.40420 0.59580 0.40420 0.72980 0.27020 0.72980 0.27020
1.00000 0.00000 0.38110 0.61890 0.38110 0.61890 0.79860 0.20140
0.77820 0.22180 0.74820 0.25180
American 0.69900 0.30100 0.69900 0.30100 0.32800 0.67200 0.32800 0.67200
0.74210 0.25790 0.66060 0.33940 0.66060 0.33940 0.86030 0.13970
0.79240 0.20760 0.80860 0.19140
Australian 0.22740 0.77260 0.22740 0.77260 0.58210 0.41790 0.58210 0.41790
1.00000 0.00000 0.20180 0.79820 0.20180 0.79820 0.90000 0.10000
0.98370 0.01630 0.90970 0.09030
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdnadist.txt 0000664 0001750 0001750 00000057330 12171064331 015732 0000000 0000000 fdnadist
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Nucleic acid sequence distance matrix program
Description
Computes four different distances between species from nucleic acid
sequences. The distances can then be used in the distance matrix
programs. The distances are the Jukes-Cantor formula, one based on
Kimura's 2- parameter method, the F84 model used in DNAML, and the
LogDet distance. The distances can also be corrected for
gamma-distributed and gamma-plus-invariant-sites-distributed rates of
change in different sites. Rates of evolution can vary among sites in a
prespecified way, and also according to a Hidden Markov model. The
program can also make a table of percentage similarity among sequences.
Algorithm
This program uses nucleotide sequences to compute a distance matrix,
under four different models of nucleotide substitution. It can also
compute a table of similarity between the nucleotide sequences. The
distance for each pair of species estimates the total branch length
between the two species, and can be used in the distance matrix
programs FITCH, KITSCH or NEIGHBOR. This is an alternative to use of
the sequence data itself in the maximum likelihood program DNAML or the
parsimony program DNAPARS.
The program reads in nucleotide sequences and writes an output file
containing the distance matrix, or else a table of similarity between
sequences. The four models of nucleotide substitution are those of
Jukes and Cantor (1969), Kimura (1980), the F84 model (Kishino and
Hasegawa, 1989; Felsenstein and Churchill, 1996), and the model
underlying the LogDet distance (Barry and Hartigan, 1987; Lake, 1994;
Steel, 1994; Lockhart et. al., 1994). All except the LogDet distance
can be made to allow for for unequal rates of substitution at different
sites, as Jin and Nei (1990) did for the Jukes-Cantor model. The
program correctly takes into account a variety of sequence ambiguities,
although in cases where they exist it can be slow.
Jukes and Cantor's (1969) model assumes that there is independent
change at all sites, with equal probability. Whether a base changes is
independent of its identity, and when it changes there is an equal
probability of ending up with each of the other three bases. Thus the
transition probability matrix (this is a technical term from
probability theory and has nothing to do with transitions as opposed to
transversions) for a short period of time dt is:
To: A G C T
---------------------------------
A | 1-3a a a a
From: G | a 1-3a a a
C | a a 1-3a a
T | a a a 1-3a
where a is u dt, the product of the rate of substitution per unit time
(u) and the length dt of the time interval. For longer periods of time
this implies that the probability that two sequences will differ at a
given site is:
p = 3/4 ( 1 - e- 4/3 u t)
and hence that if we observe p, we can compute an estimate of the
branch length ut by inverting this to get
ut = - 3/4 loge ( 1 - 4/3 p )
The Kimura "2-parameter" model is almost as symmetric as this, but
allows for a difference between transition and transversion rates. Its
transition probability matrix for a short interval of time is:
To: A G C T
---------------------------------
A | 1-a-2b a b b
From: G | a 1-a-2b b b
C | b b 1-a-2b a
T | b b a 1-a-2b
where a is u dt, the product of the rate of transitions per unit time
and dt is the length dt of the time interval, and b is v dt, the
product of half the rate of transversions (i.e., the rate of a specific
transversion) and the length dt of the time interval.
The F84 model incorporates different rates of transition and
transversion, but also allowing for different frequencies of the four
nucleotides. It is the model which is used in DNAML, the maximum
likelihood nucelotide sequence phylogenies program in this package. You
will find the model described in the document for that program. The
transition probabilities for this model are given by Kishino and
Hasegawa (1989), and further explained in a paper by me and Gary
Churchill (1996).
The LogDet distance allows a fairly general model of substitution. It
computes the distance from the determinant of the empirically observed
matrix of joint probabilities of nucleotides in the two species. An
explanation of it is available in the chapter by Swofford et, al.
(1996).
The first three models are closely related. The DNAML model reduces to
Kimura's two-parameter model if we assume that the equilibrium
frequencies of the four bases are equal. The Jukes-Cantor model in turn
is a special case of the Kimura 2-parameter model where a = b. Thus
each model is a special case of the ones that follow it, Jukes-Cantor
being a special case of both of the others.
The Jin and Nei (1990) correction for variation in rate of evolution
from site to site can be adapted to all of the first three models. It
assumes that the rate of substitution varies from site to site
according to a gamma distribution, with a coefficient of variation that
is specified by the user. The user is asked for it when choosing this
option in the menu.
Each distance that is calculated is an estimate, from that particular
pair of species, of the divergence time between those two species. For
the Jukes- Cantor model, the estimate is computed using the formula for
ut given above, as long as the nucleotide symbols in the two sequences
are all either A, C, G, T, U, N, X, ?, or - (the latter four indicate a
deletion or an unknown nucleotide. This estimate is a maximum
likelihood estimate for that model. For the Kimura 2-parameter model,
with only these nucleotide symbols, formulas special to that estimate
are also computed. These are also, in effect, computing the maximum
likelihood estimate for that model. In the Kimura case it depends on
the observed sequences only through the sequence length and the
observed number of transition and transversion differences between
those two sequences. The calculation in that case is a maximum
likelihood estimate and will differ somewhat from the estimate obtained
from the formulas in Kimura's original paper. That formula was also a
maximum likelihood estimate, but with the transition/transversion ratio
estimated empirically, separately for each pair of sequences. In the
present case, one overall preset transition/transversion ratio is used
which makes the computations harder but achieves greater consistency
between different comparisons.
For the F84 model, or for any of the models where one or both sequences
contain at least one of the other ambiguity codons such as Y, R, etc.,
a maximum likelihood calculation is also done using code which was
originally written for DNAML. Its disadvantage is that it is slow. The
resulting distance is in effect a maximum likelihood estimate of the
divergence time (total branch length between) the two sequences.
However the present program will be much faster than versions earlier
than 3.5, because I have speeded up the iterations.
The LogDet model computes the distance from the determinant of the
matrix of co-occurrence of nucleotides in the two species, according to
the formula
D = - 1/4(loge(|F|) - 1/2loge(fA1fC1fG1fT1fA2fC2fG2fT2))
Where F is a matrix whose (i,j) element is the fraction of sites at
which base i occurs in one species and base j occurs in the other. fji
is the fraction of sites at which species i has base j. The LogDet
distance cannot cope with ambiguity codes. It must have completely
defined sequences. One limitation of the LogDet distance is that it may
be infinite sometimes, if there are too many changes between certain
pairs of nucleotides. This can be particularly noticeable with
distances computed from bootstrapped sequences. Note that there is an
assumption that we are looking at all sites, including those that have
not changed at all. It is important not to restrict attention to some
sites based on whether or not they have changed; doing that would bias
the distances by making them too large, and that in turn would cause
the distances to misinterpret the meaning of those sites that had
changed.
For all of these distance methods, the program allows us to specify
that "third position" bases have a different rate of substitution than
first and second positions, that introns have a different rate than
exons, and so on. The Categories option which does this allows us to
make up to 9 categories of sites and specify different rates of change
for them.
In addition to the four distance calculations, the program can also
compute a table of similarities between nucleotide sequences. These
values are the fractions of sites identical between the sequences. The
diagonal values are 1.0000. No attempt is made to count similarity of
nonidentical nucleotides, so that no credit is given for having (for
example) different purines at corresponding sites in the two sequences.
This option has been requested by many users, who need it for
descriptive purposes. It is not intended that the table be used for
inferring the tree.
Usage
Here is a sample session with fdnadist
% fdnadist
Nucleic acid sequence distance matrix program
Input (aligned) nucleotide sequence set(s): dnadist.dat
Distance methods
f : F84 distance model
k : Kimura 2-parameter distance
j : Jukes-Cantor distance
l : LogDet distance
s : Similarity table
Choose the method to use [F84 distance model]:
Phylip distance matrix output file [dnadist.fdnadist]:
Distances calculated for species
Alpha ....
Beta ...
Gamma ..
Delta .
Epsilon
Distances written to file "dnadist.fdnadist"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Nucleic acid sequence distance matrix program
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
-method menu [F84 distance model] Choose the method to
use (Values: f (F84 distance model); k
(Kimura 2-parameter distance); j
(Jukes-Cantor distance); l (LogDet
distance); s (Similarity table))
[-outfile] outfile [*.fdnadist] Phylip distance matrix output
file
Additional (Optional) qualifiers (* if not always prompted):
* -gammatype menu [No distribution parameters used] Gamma
distribution (Values: g (Gamma distributed
rates); i (Gamma+invariant sites); n (No
distribution parameters used))
* -ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array [1.0] Category rates
* -categories properties File of substitution rate categories
-weights properties Weights file
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -ttratio float [2.0] Transition/transversion ratio (Number
0.001 or more)
* -[no]freqsfrom toggle [Y] Use empirical base frequencies from
seqeunce input
* -basefreq array [0.25 0.25 0.25 0.25] Base frequencies for A
C G T/U (use blanks to separate)
-lower boolean [N] Output as a lower triangular distance
matrix
-humanreadable boolean [@($(method)==s?Y:N)] Output as a
human-readable distance matrix
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdnadist reads any normal sequence USAs.
Input files for usage example
File: dnadist.dat
5 13
Alpha AACGTGGCCACAT
Beta AAGGTCGCCACAC
Gamma CAGTTCGCCACAA
Delta GAGATTTCCGCCT
Epsilon GAGATCTCCGCCC
Output file format
fdnadist output contains on its first line the number of species. The
distance matrix is then printed in standard form, with each species
starting on a new line with the species name, followed by the distances
to the species in order. These continue onto a new line after every
nine distances. If the L option is used, the matrix or distances is in
lower triangular form, so that only the distances to the other species
that precede each species are printed. Otherwise the distance matrix is
square with zero distances on the diagonal. In general the format of
the distance matrix is such that it can serve as input to any of the
distance matrix programs.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the menu
selections. The output file begins by giving the number of species and
the number of characters, and the identity of the distance measure that
is being used.
If the C (Categories) option is used a table of the relative rates of
expected substitution at each category of sites is printed, and a
listing of the categories each site is in.
There will then follow the equilibrium frequencies of the four bases.
If the Jukes-Cantor or Kimura distances are used, these will
necessarily be 0.25 : 0.25 : 0.25 : 0.25. The output then shows the
transition/transversion ratio that was specified or used by default. In
the case of the Jukes-Cantor distance this will always be 0.5. The
transition-transversion parameter (as opposed to the ratio) is also
printed out: this is used within the program and can be ignored. There
then follow the data sequences, with the base sequences printed in
groups of ten bases along the lines of the Genbank and EMBL formats.
The distances printed out are scaled in terms of expected numbers of
substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate
of change, averaged over all sites analyzed, is set to 1.0 if there are
multiple categories of sites. This means that whether or not there are
multiple categories of sites, the expected fraction of change for very
small branches is equal to the branch length. Of course, when a branch
is twice as long this does not mean that there will be twice as much
net change expected along it, since some of the changes may occur in
the same site and overlie or even reverse each other. The branch
lengths estimates here are in terms of the expected underlying numbers
of changes. That means that a branch of length 0.26 is 26 times as long
as one which would show a 1% difference between the nucleotide
sequences at the beginning and end of the branch. But we would not
expect the sequences at the beginning and end of the branch to be 26%
different, as there would be some overlaying of changes.
One problem that can arise is that two or more of the species can be so
dissimilar that the distance between them would have to be infinite, as
the likelihood rises indefinitely as the estimated divergence time
increases. For example, with the Jukes-Cantor model, if the two
sequences differ in 75% or more of their positions then the estimate of
dovergence time would be infinite. Since there is no way to represent
an infinite distance in the output file, the program regards this as an
error, issues an error message indicating which pair of species are
causing the problem, and stops. It might be that, had it continued
running, it would have also run into the same problem with other pairs
of species. If the Kimura distance is being used there may be no error
message; the program may simply give a large distance value (it is
iterating towards infinity and the value is just where the iteration
stopped). Likewise some maximum likelihood estimates may also become
large for the same reason (the sequences showing more divergence than
is expected even with infinite branch length). I hope in the future to
add more warning messages that would alert the user the this.
If the similarity table is selected, the table that is produced is not
in a format that can be used as input to the distance matrix programs.
it has a heading, and the species names are also put at the tops of the
columns of the table (or rather, the first 8 characters of each species
name is there, the other two characters omitted to save space). There
is not an option to put the table into a format that can be read by the
distance matrix programs, nor is there one to make it into a table of
fractions of difference by subtracting the similarity values from 1.
This is done deliberately to make it more difficult for the use to use
these values to construct trees. The similarity values are not
corrected for multiple changes, and their use to construct trees (even
after converting them to fractions of difference) would be wrong, as it
would lead to severe conflict between the distant pairs of sequences
and the close pairs of sequences.
Output files for usage example
File: dnadist.fdnadist
5
Alpha 0.000000 0.303900 0.857544 1.158927 1.542899
Beta 0.303900 0.000000 0.339727 0.913522 0.619671
Gamma 0.857544 0.339727 0.000000 1.631729 1.293713
Delta 1.158927 0.913522 1.631729 0.000000 0.165882
Epsilon 1.542899 0.619671 1.293713 0.165882 0.000000
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fmix.txt 0000664 0001750 0001750 00000046254 12171064331 015104 0000000 0000000 fmix
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Mixed parsimony algorithm
Description
Estimates phylogenies by some parsimony methods for discrete character
data with two states (0 and 1). Allows use of the Wagner parsimony
method, the Camin-Sokal parsimony method, or arbitrary mixtures of
these. Also reconstructs ancestral states and allows weighting of
characters (does not infer branch lengths).
Algorithm
MIX is a general parsimony program which carries out the Wagner and
Camin-Sokal parsimony methods in mixture, where each character can have
its method specified separately. The program defaults to carrying out
Wagner parsimony.
The Camin-Sokal parsimony method explains the data by assuming that
changes 0 --> 1 are allowed but not changes 1 --> 0. Wagner parsimony
allows both kinds of changes. (This under the assumption that 0 is the
ancestral state, though the program allows reassignment of the
ancestral state, in which case we must reverse the state numbers 0 and
1 throughout this discussion). The criterion is to find the tree which
requires the minimum number of changes. The Camin-Sokal method is due
to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
(1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
1. Ancestral states are known (Camin-Sokal) or unknown (Wagner).
2. Different characters evolve independently.
3. Different lineages evolve independently.
4. Changes 0 --> 1 are much more probable than changes 1 --> 0
(Camin-Sokal) or equally probable (Wagner).
5. Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the
group in question.
6. Other kinds of evolutionary event such as retention of polymorphism
are far less probable than 0 --> 1 changes.
7. Rates of evolution in different lineages are sufficiently low that
two changes in a long segment of the tree are far less probable
than one change in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b,
1988b). For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
Usage
Here is a sample session with fmix
% fmix
Mixed parsimony algorithm
Phylip character discrete states file: mix.dat
Phylip tree file (optional):
Phylip mix program output file [mix.fmix]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
Output written to file "mix.fmix"
Trees also written onto file "mix.treefile"
Go to the input files for this example
Go to the output files for this example
Example 2
% fmix -printdata -ancfile mixancfile.dat
Mixed parsimony algorithm
Phylip character discrete states file: mix.dat
Phylip tree file (optional):
Phylip mix program output file [mix.fmix]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
Output written to file "mix.fmix"
Trees also written onto file "mix.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
Mixed parsimony algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fmix] Phylip mix program output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-ancfile properties Ancestral states file
-mixfile properties Mixture file
-method menu [Wagner] Choose the method to use (Values: w
(Wagner); c (Camin-Sokal); m (Mixed))
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-threshold float [$(infile.discretesize)] Threshold value
(Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fmix] Phylip tree output file (optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-ancseq boolean [N] Print states at all nodes of tree
-stepbox boolean [N] Print out steps in each character
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fmix reads discrete character data. States "?", "P", and "B" are
allowed.
(0,1) Discrete character data
These programs are intended for the use of morphological systematists
who are dealing with discrete characters, or by molecular evolutionists
dealing with presence-absence data on restriction sites. One of the
programs (PARS) allows multistate characters, with up to 8 states, plus
the unknown state symbol "?". For the others, the characters are
assumed to be coded into a series of (0,1) two-state characters. For
most of the programs there are two other states possible, "P", which
stands for the state of Polymorphism for both states (0 and 1), and
"?", which stands for the state of ignorance: it is the state
"unknown", or "does not apply". The state "P" can also be denoted by
"B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding a
multistate character into a series of two-state (0,1) characters.
Suppose we had a character with four states whose character-state tree
had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We can
represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE, DOLPENNY
and DOLBOOT the multistate recoding does not necessarily work properly,
as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected in
a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for unordered
character states.
Input files for usage example
File: mix.dat
5 6
Alpha 110110
Beta 110000
Gamma 100110
Delta 001001
Epsilon 001110
Input files for usage example 2
File: mixancfile.dat
001??1
Output file format
fmix output is standard: a list of equally parsimonious trees, which
will be printed as rooted or unrooted depending on which is
appropriate, and, if the user chooses, a table of the number of changes
of state required in each character. If the Wagner option is in force
for a character, it may not be possible to unambiguously locate the
places on the tree where the changes occur, as there may be multiple
possibilities. If the user selects menu option 5, a table is printed
out after each tree, showing for each branch whether there are known to
be changes in the branch, and what the states are inferred to have been
at the top end of the branch. If the inferred state is a "?" there will
be multiple equally-parsimonious assignments of states; the user must
work these out for themselves by hand.
If the Camin-Sokal parsimony method is invoked and the Ancestors option
is also used, then the program will infer, for any character whose
ancestral state is unknown ("?") whether the ancestral state 0 or 1
will give the fewest state changes. If these are tied, then it may not
be possible for the program to infer the state in the internal nodes,
and these will all be printed as ".". If this has happened and you want
to know more about the states at the internal nodes, you will find
helpful to use MOVE to display the tree and examine its interior
states, as the algorithm in MOVE shows all that can be known in this
case about the interior states, including where there is and is not
amibiguity. The algorithm in MIX gives up more easily on displaying
these states.
If the A option is not used, then the program will assume 0 as the
ancestral state for those characters following the Camin-Sokal method,
and will assume that the ancestral state is unknown for those
characters following Wagner parsimony. If any characters have unknown
ancestral states, and if the resulting tree is rooted (even by
outgroup), a table will also be printed out showing the best guesses of
which are the ancestral states in each character. You will find it
useful to understand the difference between the Camin-Sokal parsimony
criterion with unknown ancestral state and the Wagner parsimony
criterion.
If the U (User Tree) option is used and more than one tree is supplied,
the program also performs a statistical test of each of these trees
against the best tree. This test, which is a version of the test
proposed by Alan Templeton (1983) and evaluated in a test case by me
(1985a). It is closely parallel to a test using log likelihood
differences invented by Kishino and Hasegawa (1989), and uses the mean
and variance of step differences between trees, taken across
characters. If the mean is more than 1.96 standard deviations different
then the trees are declared significantly different. The program prints
out a table of the steps for each tree, the differences of each from
the highest one, the variance of that quantity as determined by the
step differences at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
It is important to understand that the test assumes that all the binary
characters are evolving independently, which is unlikely to be true for
many suites of morphological characters.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. In the version used here
the variances and covariances of the sums of steps across characters
are computed for all pairs of trees. To test whether the difference
between each tree and the best one is larger than could have been
expected if they all had the same expected number of steps, numbers of
steps for all trees are sampled with these covariances and equal means
(Shimodaira and Hasegawa's "least favorable hypothesis"), and a P value
is computed from the fraction of times the difference between the
tree's value and the lowest number of steps exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers are
used.
In either the KHT or the SH test the program prints out a table of the
number of steps for each tree, the differences of each from the lowest
one, the variance of that quantity as determined by the differences of
the numbers of steps at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is needed
when we use the trees to make a consensus tree of the results of
bootstrapping or jackknifing, to avoid overrepresenting replicates that
find many tied trees.
Output files for usage example
File: mix.fmix
Mixed parsimony algorithm, version 3.69.650
Wagner parsimony method
4 trees in all found
+--Epsilon
+-----4
! +--Gamma
+--2
! ! +--Delta
--1 +-----3
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 9.000
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
--1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 9.000
+--------Epsilon
+--4
! ! +-----Gamma
! +--2
--1 ! +--Delta
! +--3
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 9.000
+--------Gamma
+--2
! ! +-----Epsilon
! +--4
--1 ! +--Delta
! +--3
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 9.000
File: mix.treefile
(((Epsilon,Gamma),(Delta,Beta)),Alpha)[0.2500];
((Gamma,((Epsilon,Delta),Beta)),Alpha)[0.2500];
((Epsilon,(Gamma,(Delta,Beta))),Alpha)[0.2500];
((Gamma,(Epsilon,(Delta,Beta))),Alpha)[0.2500];
Output files for usage example 2
File: mix.fmix
Mixed parsimony algorithm, version 3.69.650
5 species, 6 characters
Wagner parsimony method
Name Characters
---- ----------
Alpha 11011 0
Beta 11000 0
Gamma 10011 0
Delta 00100 1
Epsilon 00111 0
Ancestral states:
001?? 1
One most parsimonious tree found:
+-----------Delta
--3
! +--------Epsilon
+--4
! +-----Gamma
+--2
! +--Beta
+--1
+--Alpha
requires a total of 8.000
best guesses of ancestral states:
0 1 2 3 4 5 6 7 8 9
*--------------------
0! 0 0 1 ? ? 1
File: mix.treefile
(Delta,(Epsilon,(Gamma,(Beta,Alpha))));
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
eclique Largest clique program
edollop Dollo and polymorphism parsimony algorithm
edolpenny Penny algorithm Dollo or polymorphism
efactor Multistate to binary recoding program
emix Mixed parsimony algorithm
epenny Penny algorithm, branch-and-bound
fclique Largest clique program
fdollop Dollo and polymorphism parsimony algorithm
fdolpenny Penny algorithm Dollo or polymorphism
ffactor Multistate to binary recoding program
fmove Interactive mixed method parsimony
fpars Discrete character parsimony
fpenny Penny algorithm, branch-and-bound
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fpenny.txt 0000664 0001750 0001750 00000065063 12171064331 015437 0000000 0000000 fpenny
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Penny algorithm, branch-and-bound
Description
Finds all most parsimonious phylogenies for discrete-character data
with two states, for the Wagner, Camin-Sokal, and mixed parsimony
criteria using the branch-and-bound method of exact search. May be
impractical (depending on the data) for more than 10-11 species.
Algorithm
PENNY is a program that will find all of the most parsimonious trees
implied by your data. It does so not by examining all possible trees,
but by using the more sophisticated "branch and bound" algorithm, a
standard computer science search strategy first applied to phylogenetic
inference by Hendy and Penny (1982). (J. S. Farris [personal
communication, 1975] had also suggested that this strategy, which is
well-known in computer science, might be applied to phylogenies, but he
did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem of
finding these has been shown (Graham and Foulds, 1982; Day, 1983) to be
NP-complete, which is equivalent to saying that there is no fast
algorithm that is guaranteed to solve the problem in all cases (for a
discussion of NP-completeness, see the Scientific American article by
Lewis and Papadimitriou, 1978). The result is that this program,
despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs in
the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of
someone who can let a microcomputer grind all night than for someone
who has the "benefit" of paying for time on the campus mainframe
computer). IT IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE
PROGRAM WILL TAKE ON YOUR DATA. This can be done by running it on
subsets of the species, increasing the number of species in the run
until you either are able to treat the full data set or know that the
program will take unacceptably long on it. (Making a plot of the
logarithm of run time against species number may help to project run
times).
The Algorithm
The search strategy used by PENNY starts by making a tree consisting of
the first two species (the first three if the tree is to be unrooted).
Then it tries to add the next species in all possible places (there are
three of these). For each of the resulting trees it evaluates the
number of steps. It adds the next species to each of these, again in
all possible spaces. If this process would continue it would simply
generate all possible trees, of which there are a very large number
even when the number of species is moderate (34,459,425 with 10
species). Actually it does not do this, because the trees are generated
in a particular order and some of them are never generated.
Actually the order in which trees are generated is not quite as implied
above, but is a "depth-first search". This means that first one adds
the third species in the first possible place, then the fourth species
in its first possible place, then the fifth and so on until the first
possible tree has been produced. Its number of steps is evaluated. Then
one "backtracks" by trying the alternative placements of the last
species. When these are exhausted one tries the next placement of the
next-to-last species. The order of placement in a depth-first search is
like this for a four-species case (parentheses enclose monophyletic
groups):
Make tree of first two species (A,B)
Add C in first place ((A,B),C)
Add D in first place (((A,D),B),C)
Add D in second place ((A,(B,D)),C)
Add D in third place (((A,B),D),C)
Add D in fourth place ((A,B),(C,D))
Add D in fifth place (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place (((A,D),C),B)
Add D in second place ((A,(C,D)),B)
Add D in third place (((A,C),D),B)
Add D in fourth place ((A,C),(B,D))
Add D in fifth place (((A,C),B),D)
Add C in third place (A,(B,C))
Add D in first place ((A,D),(B,C))
Add D in second place (A,((B,D),C))
Add D in third place (A,(B,(C,D)))
Add D in fourth place (A,((B,C),D))
Add D in fifth place ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species rooted
bifurcating trees, each exactly once (the parentheses each enclose a
monophyletic group). As displayed above, the backtracking depth-first
search algorithm is just another way of producing all possible trees
one at a time. The branch and bound algorithm consists of this with one
change. As each tree is constructed, including the partial trees such
as (A,(B,C)), its number of steps is evaluated. In addition a
prediction is made as to how many steps will be added, at a minimum, as
further species are added.
This is done by counting how many binary characters which are invariant
in the data up the species most recently added will ultimately show
variation when further species are added. Thus if 20 characters vary
among species A, B, and C and their root, and if tree ((A,C),B)
requires 24 steps, then if there are 8 more characters which will be
seen to vary when species D is added, we can immediately say that no
matter how we add D, the resulting tree can have no less than 24 + 8 =
32 steps. The point of all this is that if a previously-found tree such
as ((A,B),(C,D)) required only 30 steps, then we know that there is no
point in even trying to add D to ((A,C),B). We have computed the bound
that enables us to cut off a whole line of inquiry (in this case five
trees) and avoid going down that particular branch any farther.
The branch-and-bound algorithm thus allows us to find all most
parsimonious trees without generating all possible trees. How much of a
saving this is depends strongly on the data. For very clean (nearly
"Hennigian") data, it saves much time, but on very messy data it will
still take a very long time.
The algorithm in the program differs from the one outlined here in some
essential details: it investigates possibilities in the order of their
apparent promise. This applies to the order of addition of species, and
to the places where they are added to the tree. After the first
two-species tree is constructed, the program tries adding each of the
remaining species in turn, each in the best possible place it can find.
Whichever of those species adds (at a minimum) the most additional
steps is taken to be the one to be added next to the tree. When it is
added, it is added in turn to places which cause the fewest additional
steps to be added. This sounds a bit complex, but it is done with the
intention of eliminating regions of the search of all possible trees as
soon as possible, and lowering the bound on tree length as quickly as
possible.
The program keeps a list of all the most parsimonious trees found so
far. Whenever it finds one that has fewer steps than these, it clears
out the list and restarts the list with that tree. In the process the
bound tightens and fewer possibilities need be investigated. At the end
the list contains all the shortest trees. These are then printed out.
It should be mentioned that the program CLIQUE for finding all largest
cliques also works by branch-and-bound. Both problems are NP-complete
but for some reason CLIQUE runs far faster. Although their worst-case
behavior is bad for both programs, those worst cases occur far more
frequently in parsimony problems than in compatibility problems.
Controlling Run Times
Among the quantities available to be set at the beginning of a run of
PENNY, two (howoften and howmany) are of particular importance. As
PENNY goes along it will keep count of how many trees it has examined.
Suppose that howoften is 100 and howmany is 1000, the default settings.
Every time 100 trees have been examined, PENNY will print out a line
saying how many multiples of 100 trees have now been examined, how many
steps the most parsimonious tree found so far has, how many trees of
with that number of steps have been found, and a very rough estimate of
what fraction of all trees have been looked at so far.
When the number of these multiples printed out reaches the number
howmany (say 1000), the whole algorithm aborts and prints out that it
has not found all most parsimonious trees, but prints out what is has
got so far anyway. These trees need not be any of the most parsimonious
trees: they are simply the most parsimonious ones found so far. By
setting the product (howoften times howmany) large you can make the
algorithm less likely to abort, but then you risk getting bogged down
in a gigantic computation. You should adjust these constants so that
the program cannot go beyond examining the number of trees you are
reasonably willing to wait for. In their initial setting the program
will abort after looking at 100,000 trees. Obviously you may want to
adjust howoften in order to get more or fewer lines of intermediate
notice of how many trees have been looked at so far. Of course, in
small cases you may never even reach the first multiple of howoften and
nothing will be printed out except some headings and then the final
trees.
The indication of the approximate percentage of trees searched so far
will be helpful in judging how much farther you would have to go to get
the full search. Actually, since that fraction is the fraction of the
set of all possible trees searched or ruled out so far, and since the
search becomes progressively more efficient, the approximate fraction
printed out will usually be an underestimate of how far along the
program is, sometimes a serious underestimate.
A constant that affects the result is "maxtrees", which controls the
maximum number of trees that can be stored. Thus if "maxtrees" is 25,
and 32 most parsimonious trees are found, only the first 25 of these
are stored and printed out. If "maxtrees" is increased, the program
does not run any slower but requires a little more intermediate storage
space. I recommend that "maxtrees" be kept as large as you can,
provided you are willing to look at an output with that many trees on
it! Initially, "maxtrees" is set to 100 in the distribution copy.
Methods and Options
The counting of the length of trees is done by an algorithm nearly
identical to the corresponding algorithms in MIX, and thus the
remainder of this document will be nearly identical to the MIX
document. MIX is a general parsimony program which carries out the
Wagner and Camin-Sokal parsimony methods in mixture, where each
character can have its method specified. The program defaults to
carrying out Wagner parsimony.
The Camin-Sokal parsimony method explains the data by assuming that
changes 0 --> 1 are allowed but not changes 1 --> 0. Wagner parsimony
allows both kinds of changes. (This under the assumption that 0 is the
ancestral state, though the program allows reassignment of the
ancestral state, in which case we must reverse the state numbers 0 and
1 throughout this discussion). The criterion is to find the tree which
requires the minimum number of changes. The Camin-Sokal method is due
to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
(1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
1. Ancestral states are known (Camin-Sokal) or unknown (Wagner).
2. Different characters evolve independently.
3. Different lineages evolve independently.
4. Changes 0 --> 1 are much more probable than changes 1 --> 0
(Camin-Sokal) or equally probable (Wagner).
5. Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the
group in question.
6. Other kinds of evolutionary event such as retention of polymorphism
are far less probable than 0 --> 1 changes.
7. Rates of evolution in different lineages are sufficiently low that
two changes in a long segment of the tree are far less probable
than one change in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b,
1988b). For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
Usage
Here is a sample session with fpenny
% fpenny
Penny algorithm, branch-and-bound
Phylip character discrete states file: penny.dat
Phylip penny program output file [penny.fpenny]:
How many
trees looked Approximate
at so far Length of How many percentage
(multiples shortest tree trees this long searched
of 100): found so far found so far so far
---------- ------------ ------------ ------------
1 8.00000 1 6.67
2 8.00000 3 20.00
3 8.00000 3 53.33
4 8.00000 3 93.33
Output written to file "penny.fpenny"
Trees also written onto file "penny.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
Penny algorithm, branch-and-bound
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-outfile] outfile [*.fpenny] Phylip penny program output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Phylip weights file (optional)
-ancfile properties Phylip ancestral states file (optional)
-mixfile properties Phylip mix output file (optional)
-method menu [Wagner] Choose the method to use (Values:
Wag (Wagner); Cam (Camin-Sokal); Mix
(Mixed))
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-howmany integer [1000] How many groups of trees (Any integer
value)
-howoften integer [100] How often to report, in trees (Any
integer value)
-simple boolean Branch and bound is simple
-threshold float [$(infile.discretesize)] Threshold value
(Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fpenny] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print out steps in each site
-ancseq boolean [N] Print states at all nodes of tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fpenny reads discrste character data.
(0,1) Discrete character data
These programs are intended for the use of morphological systematists
who are dealing with discrete characters, or by molecular evolutionists
dealing with presence-absence data on restriction sites. One of the
programs (PARS) allows multistate characters, with up to 8 states, plus
the unknown state symbol "?". For the others, the characters are
assumed to be coded into a series of (0,1) two-state characters. For
most of the programs there are two other states possible, "P", which
stands for the state of Polymorphism for both states (0 and 1), and
"?", which stands for the state of ignorance: it is the state
"unknown", or "does not apply". The state "P" can also be denoted by
"B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding a
multistate character into a series of two-state (0,1) characters.
Suppose we had a character with four states whose character-state tree
had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We can
represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE, DOLPENNY
and DOLBOOT the multistate recoding does not necessarily work properly,
as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected in
a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for unordered
character states.
Input files for usage example
File: penny.dat
7 6
Alpha1 110110
Alpha2 110110
Beta1 110000
Beta2 110000
Gamma1 100110
Delta 001001
Epsilon 001110
Output file format
fpenny output is standard: a set of trees, which will be printed as
rooted or unrooted depending on which is appropriate, and if the user
elects to see them, tables of the number of changes of state required
in each character. If the Wagner option is in force for a character, it
may not be possible to unambiguously locate the places on the tree
where the changes occur, as there may be multiple possibilities. A
table is available to be printed out after each tree, showing for each
branch whether there are known to be changes in the branch, and what
the states are inferred to have been at the top end of the branch. If
the inferred state is a "?" there will be multiple equally-parsimonious
assignments of states; the user must work these out for themselves by
hand.
If the Camin-Sokal parsimony method (option C or S) is invoked and the
A option is also used, then the program will infer, for any character
whose ancestral state is unknown ("?") whether the ancestral state 0 or
1 will give the fewest state changes. If these are tied, then it may
not be possible for the program to infer the state in the internal
nodes, and these will all be printed as ".". If this has happened and
you want to know more about the states at the internal nodes, you will
find helpful to use MOVE to display the tree and examine its interior
states, as the algorithm in MOVE shows all that can be known in this
case about the interior states, including where there is and is not
amibiguity. The algorithm in PENNY gives up more easily on displaying
these states.
If the A option is not used, then the program will assume 0 as the
ancestral state for those characters following the Camin-Sokal method,
and will assume that the ancestral state is unknown for those
characters following Wagner parsimony. If any characters have unknown
ancestral states, and if the resulting tree is rooted (even by
outgroup), a table will be printed out showing the best guesses of
which are the ancestral states in each character. You will find it
useful to understand the difference between the Camin-Sokal parsimony
criterion with unknown ancestral state and the Wagner parsimony
criterion.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is needed
when we use the trees to make a consensus tree of the results of
bootstrapping or jackknifing, to avoid overrepresenting replicates that
find many tied trees.
Output files for usage example
File: penny.fpenny
Penny algorithm, version 3.69.650
branch-and-bound to find all most parsimonious trees
Wagner parsimony method
requires a total of 8.000
3 trees in all found
+-----------------Alpha1
!
! +--------Alpha2
--1 !
! +-----4 +--Epsilon
! ! ! +--6
! ! +--5 +--Delta
+--2 !
! +-----Gamma1
!
! +--Beta2
+-----------3
+--Beta1
remember: this is an unrooted tree!
+-----------------Alpha1
!
--1 +--------------Alpha2
! !
! ! +--Epsilon
+--2 +--6
! +-----5 +--Delta
! ! !
+--4 +-----Gamma1
!
! +--Beta2
+--------3
+--Beta1
remember: this is an unrooted tree!
+-----------------Alpha1
!
! +-----Alpha2
--1 +--------2
! ! ! +--Beta2
! ! +--3
+--4 +--Beta1
!
! +--Epsilon
! +--6
+--------5 +--Delta
!
+-----Gamma1
remember: this is an unrooted tree!
File: penny.treefile
(Alpha1,((Alpha2,((Epsilon,Delta),Gamma1)),(Beta2,Beta1)))[0.3333];
(Alpha1,(Alpha2,(((Epsilon,Delta),Gamma1),(Beta2,Beta1))))[0.3333];
(Alpha1,((Alpha2,(Beta2,Beta1)),((Epsilon,Delta),Gamma1)))[0.3333];
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
eclique Largest clique program
edollop Dollo and polymorphism parsimony algorithm
edolpenny Penny algorithm Dollo or polymorphism
efactor Multistate to binary recoding program
emix Mixed parsimony algorithm
epenny Penny algorithm, branch-and-bound
fclique Largest clique program
fdollop Dollo and polymorphism parsimony algorithm
fdolpenny Penny algorithm Dollo or polymorphism
ffactor Multistate to binary recoding program
fmix Mixed parsimony algorithm
fmove Interactive mixed method parsimony
fpars Discrete character parsimony
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/ffactor.txt 0000664 0001750 0001750 00000032521 12171064331 015555 0000000 0000000 ffactor
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Multistate to binary recoding program
Description
Takes discrete multistate data with character state trees and produces
the corresponding data set with two states (0 and 1). Written by
Christopher Meacham. This program was formerly used to accomodate
multistate characters in MIX, but this is less necessary now that PARS
is available.
Algorithm
This program factors a data set that contains multistate characters,
creating a data set consisting entirely of binary (0,1) characters
that, in turn, can be used as input to any of the other discrete
character programs in this package, except for PARS. Besides this
primary function, FACTOR also provides an easy way of deleting
characters from a data set. The input format for FACTOR is very similar
to the input format for the other discrete character programs except
for the addition of character-state tree descriptions.
Note that this program has no way of converting an unordered multistate
character into binary characters. Fortunately, PARS has joined the
package, and it enables unordered multistate characters, in which any
state can change to any other in one step, to be analyzed with
parsimony.
FACTOR is really for a different case, that in which there are multiple
states related on a "character state tree", which specifies for each
state which other states it can change to. That graph of states is
assumed to be a tree, with no loops in it.
Usage
Here is a sample session with ffactor
% ffactor
Multistate to binary recoding program
Phylip factor program input file: factor.dat
Phylip factor program output file [factor.ffactor]:
Data matrix written on file "factor.ffactor"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Multistate to binary recoding program
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] infile Phylip factor program input file
[-outfile] outfile [*.ffactor] Phylip factor program output
file
Additional (Optional) qualifiers:
-anc boolean [N] Put ancestral states in output file
-factors boolean [N] Put factors information in output file
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers:
-outfactorfile outfile [*.ffactor] Phylip factor data output file
(optional)
-outancfile outfile [*.ffactor] Phylip ancestor data output file
(optional)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outfactorfile" associated qualifiers
-odirectory string Output directory
"-outancfile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
ffactor reads character state tree data.
This program factors a data set that contains multistate characters,
creating a data set consisting entirely of binary (0,1) characters
that, in turn, can be used as input to any of the other discrete
character programs in this package, except for PARS. Besides this
primary function, FACTOR also provides an easy way of deleting
characters from a data set. The input format for FACTOR is very similar
to the input format for the other discrete character programs except
for the addition of character-state tree descriptions.
Note that this program has no way of converting an unordered multistate
character into binary characters. Fortunately, PARS has joined the
package, and it enables unordered multistate characters, in which any
state can change to any other in one step, to be analyzed with
parsimony.
FACTOR is really for a different case, that in which there are multiple
states related on a "character state tree", which specifies for each
state which other states it can change to. That graph of states is
assumed to be a tree, with no loops in it.
First line
The first line of the input file should contain the number of species
and the number of multistate characters. This first line is followed by
the lines describing the character-state trees, one description per
line. The species information constitutes the last part of the file.
Any number of lines may be used for a single species.
The first line is free format with the number of species first,
separated by at least one blank (space) from the number of multistate
characters, which in turn is separated by at least one blank from the
options, if present.
Character-state tree descriptions
The character-state trees are described in free format. The character
number of the multistate character is given first followed by the
description of the tree itself. Each description must be completed on a
single line. Each character that is to be factored must have a
description, and the characters must be described in the order that
they occur in the input, that is, in numerical order.
The tree is described by listing the pairs of character states that are
adjacent to each other in the character-state tree. The two character
states in each adjacent pair are separated by a colon (":"). If
character fifteen has this character state tree for possible states
"A", "B", "C", and "D":
A ---- B ---- C
|
|
|
D
then the character-state tree description would be
15 A:B B:C D:B
Note that either symbol may appear first. The ancestral state is
identified, if desired, by putting it "adjacent" to a period. If we
wanted to root character fifteen at state C:
A <--- B <--- C
|
|
V
D
we could write
15 B:D A:B C:B .:C
Both the order in which the pairs are listed and the order of the
symbols in each pair are arbitrary. However, each pair may only appear
once in the list. Any symbols may be used for a character state in the
input except the character that signals the connection between two
states (in the distribution copy this is set to ":"), ".", and, of
course, a blank. Blanks are ignored completely in the tree description
so that even B:DA:BC:B.:C or B : DA : BC : B. : C would be equivalent
to the above example. However, at least one blank must separate the
character number from the tree description.
Deleting characters from a data set
If no description line appears in the input for a particular character,
then that character will be omitted from the output. If the character
number is given on the line, but no character-state tree is provided,
then the symbol for the character in the input will be copied directly
to the output without change. This is useful for characters that are
already coded "0" and "1". Characters can be deleted from a data set
simply by listing only those that are to appear in the output.
Terminating the list of tree descriptions
The last character-state tree description should be followed by a line
containing the number "999". This terminates processing of the trees
and indicates the beginning of the species information.
Species information
The format for the species information is basically identical to the
other discrete character programs. The first ten character positions
are allotted to the species name (this value may be changed by altering
the value of the constant nmlngth at the beginning of the program). The
character states follow and may be continued to as many lines as
desired. There is no current method for indicating polymorphisms. It is
possible to either put blanks between characters or not.
There is a method for indicating uncertainty about states. There is one
character value that stands for "unknown". If this appears in the input
data then "?" is written out in all the corresponding positions in the
output file. The character value that designates "unknown" is given in
the constant unkchar at the beginning of the program, and can be
changed by changing that constant. It is set to "?" in the distribution
copy.
Input files for usage example
File: factor.dat
4 6
1 A:B B:C
2 A:B B:.
4
5 0:1 1:2 .:0
6 .:# #:$ #:%
999
Alpha CAW00#
Beta BBX01%
Gamma ABY12#
Epsilon CAZ01$
Output file format
The first line of ffactor output will contain the number of species and
the number of binary characters in the factored data set followed by
the letter "A" if the A option was specified in the input. If option F
was specified, the next line will begin "FACTORS". If option A was
specified, the line describing the ancestor will follow next. Finally,
the factored characters will be written for each species in the format
required for input by the other discrete programs in the package. The
maximum length of the output lines is 80 characters, but this maximum
length can be changed prior to compilation.
In fact, the format of the output file for the A and F options is not
correct for the current release of PHYLIP. We need to change their
output to write a factors file and an ancestors file instead of putting
the Factors and Ancestors information into the data file.
Output files for usage example
File: factor.ffactor
4 5
Alpha CA00#
Beta BB01%
Gamma AB12#
Epsilon CA01$
File: factor.factor
File: factor.ancestor
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
The output should be checked for error messages. Errors will occur in
the character-state tree descriptions if the format is incorrect
(colons in the wrong place, etc.), if more than one root is specified,
if the tree contains loops (and hence is not a tree), and if the tree
is not connected, e.g.
A:B B:C D:E
describes
A ---- B ---- C D ---- E
This "tree" is in two unconnected pieces. An error will also occur if a
symbol appears in the data set that is not in the tree description for
that character. Blanks at the end of lines when the species information
is continued to a new line will cause this kind of error.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
eclique Largest clique program
edollop Dollo and polymorphism parsimony algorithm
edolpenny Penny algorithm Dollo or polymorphism
efactor Multistate to binary recoding program
emix Mixed parsimony algorithm
epenny Penny algorithm, branch-and-bound
fclique Largest clique program
fdollop Dollo and polymorphism parsimony algorithm
fdolpenny Penny algorithm Dollo or polymorphism
fmix Mixed parsimony algorithm
fmove Interactive mixed method parsimony
fpars Discrete character parsimony
fpenny Penny algorithm, branch-and-bound
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fmove.txt 0000664 0001750 0001750 00000022764 12171064331 015255 0000000 0000000 fmove
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Interactive mixed method parsimony
Description
Interactive construction of phylogenies from discrete character data
with two states (0 and 1). Evaluates parsimony and compatibility
criteria for those phylogenies and displays reconstructed states
throughout the tree. This can be used to find parsimony or
compatibility estimates by hand.
Algorithm
MOVE is an interactive parsimony program, inspired by Wayne Maddison
and David Maddison's marvellous program MacClade, which is written for
Apple Macintosh computers. MOVE reads in a data set which is prepared
in almost the same format as one for the mixed method parsimony program
MIX. It allows the user to choose an initial tree, and displays this
tree on the screen. The user can look at different characters and the
way their states are distributed on that tree, given the most
parsimonious reconstruction of state changes for that particular tree.
The user then can specify how the tree is to be rearraranged, rerooted
or written out to a file. By looking at different rearrangements of the
tree the user can manually search for the most parsimonious tree, and
can get a feel for how different characters are affected by changes in
the tree topology.
This program is compatible with fewer computer systems than the other
programs in PHYLIP. It can be adapted to MSDOS systems or to any system
whose screen or terminals emulate DEC VT100 terminals (such as Telnet
programs for logging in to remote computers over a TCP/IP network,
VT100-compatible windows in the X windowing system, and any terminal
compatible with ANSI standard terminals). For any other screen types,
there is a generic option which does not make use of screen graphics
characters to display the character states. This will be less
effective, as the states will be less easy to see when displayed.
MOVE uses as its numerical criterion the Wagner and Camin-Sokal
parsimony methods in mixture, where each character can have its method
specified separately. The program defaults to carrying out Wagner
parsimony.
The Camin-Sokal parsimony method explains the data by assuming that
changes 0 --> 1 are allowed but not changes 1 --> 0. Wagner parsimony
allows both kinds of changes. (This under the assumption that 0 is the
ancestral state, though the program allows reassignment of the
ancestral state, in which case we must reverse the state numbers 0 and
1 throughout this discussion). The criterion is to find the tree which
requires the minimum number of changes. The Camin- Sokal method is due
to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
(1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
1. Ancestral states are known (Camin-Sokal) or unknown (Wagner).
2. Different characters evolve independently.
3. Different lineages evolve independently.
4. Changes 0 --> 1 are much more probable than changes 1 --> 0
(Camin-Sokal) or equally probable (Wagner).
5. Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the
group in question.
6. Other kinds of evolutionary event such as retention of polymorphism
are far less probable than 0 --> 1 changes.
7. Rates of evolution in different lineages are sufficiently low that
two changes in a long segment of the tree are far less probable
than one change in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b,
1988b). For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
Usage
Here is a sample session with fmove
% fmove
Interactive mixed method parsimony
Phylip character discrete states file: move.dat
Phylip tree file (optional):
NEXT? (R # + - S . T U W O F H J K L C ? X Q) (? for Help): Q
Do you want to write out the tree to a file? (Y or N): Y
5 species, 6 characters
Wagner parsimony method
Computing steps needed for compatibility in characters...
(unrooted) 8.0 Steps 4 chars compatible
,-----------5:Epsilon
--9
! ,--------4:Delta
`--8
! ,-----3:Gamma
`--7
! ,--2:Beta
`--6
`--1:Alpha
Tree written to file "move.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
Interactive mixed method parsimony
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing data set
[-intreefile] tree Phylip tree file (optional)
Additional (Optional) qualifiers:
-weights properties Weights file
-ancfile properties Ancestral states file
-factorfile properties Factors file
-method menu [Wagner] Choose the method to use (Values: w
(Wagner); c (Camin-Sokal); m (Mixed))
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-threshold float [$(infile.discretesize)] Threshold value
(Number 0.000 or more)
-initialtree menu [Arbitary] Initial tree (Values: a
(Arbitary); u (User); s (Specify))
-screenwidth integer [80] Width of terminal screen in characters
(Any integer value)
-screenlines integer [24] Number of lines on screen (Any integer
value)
-outtreefile outfile [*.fmove] Phylip tree output file (optional)
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
The fmove input data file is set up almost identically to the data
files for MIX.
Input files for usage example
File: move.dat
5 6
Alpha 110110
Beta 110000
Gamma 100110
Delta 001001
Epsilon 001110
Output file format
fmove outputs a graph to the specified graphics device. outputs a
report format file. The default format is ...
Output files for usage example
File: move.treefile
(Epsilon,(Delta,(Gamma,(Beta,Alpha))));
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
eclique Largest clique program
edollop Dollo and polymorphism parsimony algorithm
edolpenny Penny algorithm Dollo or polymorphism
efactor Multistate to binary recoding program
emix Mixed parsimony algorithm
epenny Penny algorithm, branch-and-bound
fclique Largest clique program
fdollop Dollo and polymorphism parsimony algorithm
fdolpenny Penny algorithm Dollo or polymorphism
ffactor Multistate to binary recoding program
fmix Mixed parsimony algorithm
fpars Discrete character parsimony
fpenny Penny algorithm, branch-and-bound
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fcontml.txt 0000664 0001750 0001750 00000060313 12171064331 015573 0000000 0000000 fcontml
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Gene frequency and continuous character maximum likelihood
Description
Estimates phylogenies from gene frequency data by maximum likelihood
under a model in which all divergence is due to genetic drift in the
absence of new mutations. Does not assume a molecular clock. An
alternative method of analyzing this data is to compute Nei's genetic
distance and use one of the distance matrix programs. This program can
also do maximum likelihood analysis of continuous characters that
evolve by a Brownian Motion model, but it assumes that the characters
evolve at equal rates and in an uncorrelated fashion, so that it does
not take into account the usual correlations of characters.
Algorithm
This program estimates phylogenies by the restricted maximum likelihood
method based on the Brownian motion model. It is based on the model of
Edwards and Cavalli-Sforza (1964; Cavalli-Sforza and Edwards, 1967).
Gomberg (1966), Felsenstein (1973b, 1981c) and Thompson (1975) have
done extensive further work leading to efficient algorithms. CONTML
uses restricted maximum likelihood estimation (REML), which is the
criterion used by Felsenstein (1973b). The actual algorithm is an
iterative EM Algorithm (Dempster, Laird, and Rubin, 1977) which is
guaranteed to always give increasing likelihoods. The algorithm is
described in detail in a paper of mine (Felsenstein, 1981c), which you
should definitely consult if you are going to use this program. Some
simulation tests of it are given by Rohlf and Wooten (1988) and Kim and
Burgman (1988).
The default (gene frequency) mode treats the input as gene frequencies
at a series of loci, and square-root-transforms the allele frequencies
(constructing the frequency of the missing allele at each locus first).
This enables us to use the Brownian motion model on the resulting
coordinates, in an approximation equivalent to using Cavalli-Sforza and
Edwards's (1967) chord measure of genetic distance and taking that to
give distance between particles undergoing pure Brownian motion. It
assumes that each locus evolves independently by pure genetic drift.
The alternative continuous characters mode (menu option C) treats the
input as a series of coordinates of each species in N dimensions. It
assumes that we have transformed the characters to remove correlations
and to standardize their variances.
A word about microsatellite data
Many current users of CONTML use it to analyze microsatellite data.
There are three ways to do this:
* Coding each copy number as an allele, and feeding in the
frequencies of these alleles. As CONTML's gene frequency mode
assumes that all change is by genetic drift, this means that no
copy number arises by mutation during the divergence of the
populations. Since microsatellite loci have very high mutation
rates, this is questionable.
* Use some other program, one not in the PHYLIP package, to compute
distances among the populations. Some of the programs that can do
this are RSTCalc, poptrfdos, Microsat, and Populations. Links to
them can be found at my Phylogeny Programs web site at
http://evolution.gs.washington.edu/phylip/software.html.
Those distance measures allow for mutation during the divergence of
the populations. But even they are not perfect -- they do not allow
us to use all the information contained in the gene frequency
differences of within a copy number allele. There is a need for a
more complete statistical treatment of inference of phylogenies
from microsatellite models, ones that take both mutation and
genetic drift fully into account.
* Alternatively, there is the Brownian motion approximation to mean
population copy number. This is described in my book (Felsenstein,
2004, Chapter 15, pp. 242-245), and it is implicit also in the
microsatellite distances. Each locus is coded as a single
continuous character, the mean of the copy number in at that
microsatellite locus in that species. Thus if the species (or
population) has frequencies 0.10, 0.24, 0.60, and 0.06 of alleles
that have 18, 19, 20, and 21 copies, it is coded as having
0.10 X 18 + 0.24 X 19 + 0.60 X 20 + 0.06 X 21 = 19.62
copies. These values can, I believe, be calculated by a spreadsheet
program. Each microsatellite is represented by one character, and
the continuous character mode of CONTML is used (not the gene
frequencies mode). This coding allows for mutation that changes
copy number. It does not make complete use of all data, but neither
does the treatment of microsatellite gene frequencies as changing
only genetic drift. frequency
Usage
Here is a sample session with fcontml
% fcontml -printdata
Gene frequency and continuous character maximum likelihood
Input file: contml.dat
Phylip tree file (optional):
Phylip contml program output file [contml.fcontml]:
Adding species:
1. European
2. African
3. Chinese
4. American
5. Australian
Output written to file "contml.fcontml"
Tree also written onto file "contml.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Gene frequency and continuous character maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] frequencies File containing one or more sets of data
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fcontml] Phylip contml program output
file
Additional (Optional) qualifiers (* if not always prompted):
-datatype menu [g] Input type in infile (Values: g (Gene
frequencies); i (Continuous characters))
* -lengths boolean [N] Use branch lengths from user trees
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fcontml] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fcontml reads continuous character data.
Continuous character data
The programs in this group use gene frequencies and quantitative
character values. One (CONTML) constructs maximum likelihood estimates
of the phylogeny, another (GENDIST) computes genetic distances for use
in the distance matrix programs, and the third (CONTRAST) examines
correlation of traits as they evolve along a given phylogeny.
When the gene frequencies data are used in CONTML or GENDIST, this
involves the following assumptions:
1. Different lineages evolve independently.
2. After two lineages split, their characters change independently.
3. Each gene frequency changes by genetic drift, with or without
mutation (this varies from method to method).
4. Different loci or characters drift independently.
How these assumptions affect the methods will be seen in my papers on
inference of phylogenies from gene frequency and continuous character
data (Felsenstein, 1973b, 1981c, 1985c).
The input formats are fairly similar to the discrete-character
programs, but with one difference. When CONTML is used in the
gene-frequency mode (its usual, default mode), or when GENDIST is used,
the first line contains the number of species (or populations) and the
number of loci and the options information. There then follows a line
which gives the numbers of alleles at each locus, in order. This must
be the full number of alleles, not the number of alleles which will be
input: i. e. for a two-allele locus the number should be 2, not 1.
There then follow the species (population) data, each species beginning
on a new line. The first 10 characters are taken as the name, and
thereafter the values of the individual characters are read
free-format, preceded and separated by blanks. They can go to a new
line if desired, though of course not in the middle of a number.
Missing data is not allowed - an important limitation. In the default
configuration, for each locus, the numbers should be the frequencies of
all but one allele. The menu option A (All) signals that the
frequencies of all alleles are provided in the input data -- the
program will then automatically ignore the last of them. So without the
A option, for a three-allele locus there should be two numbers, the
frequencies of two of the alleles (and of course it must always be the
same two!). Here is a typical data set without the A option:
5 3
2 3 2
Alpha 0.90 0.80 0.10 0.56
Beta 0.72 0.54 0.30 0.20
Gamma 0.38 0.10 0.05 0.98
Delta 0.42 0.40 0.43 0.97
Epsilon 0.10 0.30 0.70 0.62
whereas here is what it would have to look like if the A option were
invoked:
5 3
2 3 2
Alpha 0.90 0.10 0.80 0.10 0.10 0.56 0.44
Beta 0.72 0.28 0.54 0.30 0.16 0.20 0.80
Gamma 0.38 0.62 0.10 0.05 0.85 0.98 0.02
Delta 0.42 0.58 0.40 0.43 0.17 0.97 0.03
Epsilon 0.10 0.90 0.30 0.70 0.00 0.62 0.38
The first line has the number of species (or populations) and the
number of loci. The second line has the number of alleles for each of
the 3 loci. The species lines have names (filled out to 10 characters
with blanks) followed by the gene frequencies of the 2 alleles for the
first locus, the 3 alleles for the second locus, and the 2 alleles for
the third locus. You can start a new line after any of these allele
frequencies, and continue to give the frequencies on that line (without
repeating the species name).
If all alleles of a locus are given, it is important to have them add
up to 1. Roundoff of the frequencies may cause the program to conclude
that the numbers do not sum to 1, and stop with an error message.
While many compilers may be more tolerant, it is probably wise to make
sure that each number, including the first, is preceded by a blank, and
that there are digits both preceding and following any decimal points.
CONTML and CONTRAST also treat quantitative characters (the
continuous-characters mode in CONTML, which is option C). It is assumed
that each character is evolving according to a Brownian motion model,
at the same rate, and independently. In reality it is almost always
impossible to guarantee this. The issue is discussed at length in my
review article in Annual Review of Ecology and Systematics
(Felsenstein, 1988a), where I point out the difficulty of transforming
the characters so that they are not only genetically independent but
have independent selection acting on them. If you are going to use
CONTML to model evolution of continuous characters, then you should at
least make some attempt to remove genetic correlations between the
characters (usually all one can do is remove phenotypic correlations by
transforming the characters so that there is no within-population
covariance and so that the within-population variances of the
characters are equal -- this is equivalent to using Canonical
Variates). However, this will only guarantee that one has removed
phenotypic covariances between characters. Genetic covariances could
only be removed by knowing the coheritabilities of the characters,
which would require genetic experiments, and selective covariances
(covariances due to covariation of selection pressures) would require
knowledge of the sources and extent of selection pressure in all
variables.
CONTRAST is a program designed to infer, for a given phylogeny that is
provided to the program, the covariation between characters in a data
set. Thus we have a program in this set that allow us to take
information about the covariation and rates of evolution of characters
and make an estimate of the phylogeny (CONTML), and a program that
takes an estimate of the phylogeny and infers the variances and
covariances of the character changes. But we have no program that
infers both the phylogenies and the character covariation from the same
data set.
In the quantitative characters mode, a typical small data set would be:
5 6
Alpha 0.345 0.467 1.213 2.2 -1.2 1.0
Beta 0.457 0.444 1.1 1.987 -0.2 2.678
Gamma 0.6 0.12 0.97 2.3 -0.11 1.54
Delta 0.68 0.203 0.888 2.0 1.67
Epsilon 0.297 0.22 0.90 1.9 1.74
Note that in the latter case, there is no line giving the numbers of
alleles at each locus. In this latter case no square-root
transformation of the coordinates is done: each is assumed to give
directly the position on the Brownian motion scale.
For further discussion of options and modifiable constants in CONTML,
GENDIST, and CONTRAST see the documentation files for those programs.
Input files for usage example
File: contml.dat
5 10
2 2 2 2 2 2 2 2 2 2
European 0.2868 0.5684 0.4422 0.4286 0.3828 0.7285 0.6386 0.0205
0.8055 0.5043
African 0.1356 0.4840 0.0602 0.0397 0.5977 0.9675 0.9511 0.0600
0.7582 0.6207
Chinese 0.1628 0.5958 0.7298 1.0000 0.3811 0.7986 0.7782 0.0726
0.7482 0.7334
American 0.0144 0.6990 0.3280 0.7421 0.6606 0.8603 0.7924 0.0000
0.8086 0.8636
Australian 0.1211 0.2274 0.5821 1.0000 0.2018 0.9000 0.9837 0.0396
0.9097 0.2976
Output file format
fcontml output has a standard appearance. The topology of the tree is
given by an unrooted tree diagram. The lengths (in time or in expected
amounts of variance) are given in a table below the topology, and a
rough confidence interval given for each length. Negative lower bounds
on length indicate that rearrangements may be acceptable.
The units of length are amounts of expected accumulated variance (not
time). The log likelihood (natural log) of each tree is also given, and
it is indicated how many topologies have been tried. The tree does not
necessarily have all tips contemporary, and the log likelihood may be
either positive or negative (this simply corresponds to whether the
density function does or does not exceed 1) and a negative log
likelihood does not indicate any error. The log likelihood allows
various formal likelihood ratio hypothesis tests. The description of
the tree includes approximate standard errors on the lengths of
segments of the tree. These are calculated by considering only the
curvature of the likelihood surface as the length of the segment is
varied, holding all other lengths constant. As such they are most
probably underestimates of the variance, and hence may give too much
confidence in the given tree.
One should use caution in interpreting the likelihoods that are printed
out. If the model is wrong, it will not be possible to use the
likelihoods to make formal statistical statements. Thus, if gene
frequencies are being analyzed, but the gene frequencies change not
only by genetic drift, but also by mutation, the model is not correct.
It would be as well-justified in this case to use GENDIST to compute
the Nei (1972) genetic distance and then use FITCH, KITSCH or NEIGHBOR
to make a tree. If continuous characters are being analyzed, but if the
characters have not been transformed to new coordinates that evolve
independently and at equal rates, then the model is also violated and
no statistical analysis is possible. Doing such a transformation is not
easy, and usually not even possible.
If the U (User Tree) option is used and more than one tree is supplied,
the program also performs a statistical test of each of these trees
against the one with highest likelihood. If there are two user trees,
the test done is one which is due to Kishino and Hasegawa (1989), a
version of a test originally introduced by Templeton (1983). In this
implementation it uses the mean and variance of log-likelihood
differences between trees, taken across loci. If the two trees means
are more than 1.96 standard deviations different then the trees are
declared significantly different. This use of the empirical variance of
log-likelihood differences is more robust and nonparametric than the
classical likelihood ratio test, and may to some extent compensate for
the any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. The version used here is a
multivariate normal approximation to their test; it is due to
Shimodaira (1998). The variances and covariances of the sum of log
likelihoods across loci are computed for all pairs of trees. To test
whether the difference between each tree and the best one is larger
than could have been expected if they all had the same expected
log-likelihood, log-likelihoods for all trees are sampled with these
covariances and equal means (Shimodaira and Hasegawa's "least favorable
hypothesis"), and a P value is computed from the fraction of times the
difference between the tree's value and the highest log-likelihood
exceeds that actually observed. Note that this sampling needs random
numbers, and so the program will prompt the user for a random number
seed if one has not already been supplied. With the two-tree KHT test
no random numbers are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one.
One problem which sometimes arises is that the program is fed two
species (or populations) with identical transformed gene frequencies:
this can happen if sample sizes are small and/or many loci are
monomorphic. In this case the program "gets its knickers in a twist"
and can divide by zero, usually causing a crash. If you suspect that
this has happened, check for two species with identical coordinates. If
you find them, eliminate one from the problem: the two must always show
up as being at the same point on the tree anyway.
Output files for usage example
File: contml.fcontml
Continuous character Maximum Likelihood method version 3.69.650
5 Populations, 10 Loci
Numbers of alleles at the loci:
------- -- ------- -- --- -----
2 2 2 2 2 2 2 2 2 2
Name Gene Frequencies
---- ---- -----------
locus: 1 1 2 2 3 3
4 4 5 5 6 6
7 7 8 8 9 9
10 10
European 0.28680 0.71320 0.56840 0.43160 0.44220 0.55780
0.42860 0.57140 0.38280 0.61720 0.72850 0.27150
0.63860 0.36140 0.02050 0.97950 0.80550 0.19450
0.50430 0.49570
African 0.13560 0.86440 0.48400 0.51600 0.06020 0.93980
0.03970 0.96030 0.59770 0.40230 0.96750 0.03250
0.95110 0.04890 0.06000 0.94000 0.75820 0.24180
0.62070 0.37930
Chinese 0.16280 0.83720 0.59580 0.40420 0.72980 0.27020
1.00000 0.00000 0.38110 0.61890 0.79860 0.20140
0.77820 0.22180 0.07260 0.92740 0.74820 0.25180
0.73340 0.26660
American 0.01440 0.98560 0.69900 0.30100 0.32800 0.67200
0.74210 0.25790 0.66060 0.33940 0.86030 0.13970
0.79240 0.20760 0.00000 1.00000 0.80860 0.19140
0.86360 0.13640
Australian 0.12110 0.87890 0.22740 0.77260 0.58210 0.41790
1.00000 0.00000 0.20180 0.79820 0.90000 0.10000
0.98370 0.01630 0.03960 0.96040 0.90970 0.09030
0.29760 0.70240
+-----------------------------------------------------------African
!
! +-------------------------------Australian
1-------------3
! ! +-----------------------American
! +-----2
! +Chinese
!
+European
remember: this is an unrooted tree!
Ln Likelihood = 38.71914
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
1 African 0.09693444 ( 0.03123910, 0.19853604)
1 3 0.02252816 ( 0.00089799, 0.05598045)
3 Australian 0.05247405 ( 0.01177094, 0.11542374)
3 2 0.00945315 ( -0.00897717, 0.03795670)
2 American 0.03806240 ( 0.01095938, 0.07997877)
2 Chinese 0.00208822 ( -0.00960622, 0.02017433)
1 European 0.00000000 ( -0.01627246, 0.02516630)
File: contml.treefile
(African:0.09693444,(Australian:0.05247405,(American:0.03806240,Chinese:0.002088
22):0.00945315):0.02252816,
European:0.00000000);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
egendist Genetic distance matrix program
fgendist Compute genetic distances from gene frequencies
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdollop.txt 0000664 0001750 0001750 00000045150 12171064331 015572 0000000 0000000 fdollop
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Dollo and polymorphism parsimony algorithm
Description
Estimates phylogenies by the Dollo or polymorphism parsimony criteria
for discrete character data with two states (0 and 1). Also
reconstructs ancestral states and allows weighting of characters. Dollo
parsimony is particularly appropriate for restriction sites data; with
ancestor states specified as unknown it may be appropriate for
restriction fragments data.
Algorithm
This program carries out the Dollo and polymorphism parsimony methods.
The Dollo parsimony method was first suggested in print in verbal form
by Le Quesne (1974) and was first well-specified by Farris (1977). The
method is named after Louis Dollo since he was one of the first to
assert that in evolution it is harder to gain a complex feature than to
lose it. The algorithm explains the presence of the state 1 by allowing
up to one forward change 0-->1 and as many reversions 1-->0 as are
necessary to explain the pattern of states seen. The program attempts
to minimize the number of 1-->0 reversions necessary. The assumptions
of this method are in effect:
1. We know which state is the ancestral one (state 0).
2. The characters are evolving independently.
3. Different lineages evolve independently.
4. The probability of a forward change (0-->1) is small over the
evolutionary times involved.
5. The probability of a reversion (1-->0) is also small, but still far
larger than the probability of a forward change, so that many
reversions are easier to envisage than even one extra forward
change.
6. Retention of polymorphism for both states (0 and 1) is highly
improbable.
7. The lengths of the segments of the true tree are not so unequal
that two changes in a long segment are as probable as one in a
short segment.
One problem can arise when using additive binary recoding to represent
a multistate character as a series of two-state characters. Unlike the
Camin-Sokal, Wagner, and Polymorphism methods, the Dollo method can
reconstruct ancestral states which do not exist. An example is given in
my 1979 paper. It will be necessary to check the output to make sure
that this has not occurred.
The polymorphism parsimony method was first used by me, and the results
published (without a clear specification of the method) by Inger
(1967). The method was independently published by Farris (1978a) and by
me (1979). The method assumes that we can explain the pattern of states
by no more than one origination (0-->1) of state 1, followed by
retention of polymorphism along as many segments of the tree as are
necessary, followed by loss of state 0 or of state 1 where necessary.
The program tries to minimize the total number of polymorphic
characters, where each polymorphism is counted once for each segment of
the tree in which it is retained.
The assumptions of the polymorphism parsimony method are in effect:
1. The ancestral state (state 0) is known in each character.
2. The characters are evolving independently of each other.
3. Different lineages are evolving independently.
4. Forward change (0-->1) is highly improbable over the length of time
involved in the evolution of the group.
5. Retention of polymorphism is also improbable, but far more probable
that forward change, so that we can more easily envisage much
polymorhism than even one additional forward change.
6. Once state 1 is reached, reoccurrence of state 0 is very
improbable, much less probable than multiple retentions of
polymorphism.
7. The lengths of segments in the true tree are not so unequal that we
can more easily envisage retention events occurring in both of two
long segments than one retention in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b,
1988b). For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
Usage
Here is a sample session with fdollop
% fdollop
Dollo and polymorphism parsimony algorithm
Phylip character discrete states file: dollop.dat
Phylip tree file (optional):
Phylip dollop program output file [dollop.fdollop]:
Dollo and polymorphism parsimony algorithm, version 3.69.650
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
.........
Output written to file "dollop.fdollop"
Trees also written onto file "dollop.treefile"
Go to the input files for this example
Go to the output files for this example
Command line arguments
Dollo and polymorphism parsimony algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fdollop] Phylip dollop program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Phylip weights file (optional)
-ancfile properties Ancestral states file
-method menu [d] Parsimony method (Values: d (Dollo); p
(Polymorphism))
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-threshold float [$(infile.discretesize)] Threshold value
(Number 0.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdollop] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-ancseq boolean [N] Print states at all nodes of tree
-stepbox boolean [N] Print out steps in each character
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdollop reads discrete character data with "?", "P", "B" states
allowed. .
(0,1) Discrete character data
These programs are intended for the use of morphological systematists
who are dealing with discrete characters, or by molecular evolutionists
dealing with presence-absence data on restriction sites. One of the
programs (PARS) allows multistate characters, with up to 8 states, plus
the unknown state symbol "?". For the others, the characters are
assumed to be coded into a series of (0,1) two-state characters. For
most of the programs there are two other states possible, "P", which
stands for the state of Polymorphism for both states (0 and 1), and
"?", which stands for the state of ignorance: it is the state
"unknown", or "does not apply". The state "P" can also be denoted by
"B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding a
multistate character into a series of two-state (0,1) characters.
Suppose we had a character with four states whose character-state tree
had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We can
represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE, DOLPENNY
and DOLBOOT the multistate recoding does not necessarily work properly,
as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected in
a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for unordered
character states.
Input files for usage example
File: dollop.dat
5 6
Alpha 110110
Beta 110000
Gamma 100110
Delta 001001
Epsilon 001110
Output file format
fdollop output is standard: a list of equally parsimonious trees, and,
if the user selects menu option 4, a table of the numbers of reversions
or retentions of polymorphism necessary in each character. If any of
the ancestral states has been specified to be unknown, a table of
reconstructed ancestral states is also provided. When reconstructing
the placement of forward changes and reversions under the Dollo method,
keep in mind that each polymorphic state in the input data will require
one "last minute" reversion. This is included in the tabulated counts.
Thus if we have both states 0 and 1 at a tip of the tree the program
will assume that the lineage had state 1 up to the last minute, and
then state 0 arose in that population by reversion, without loss of
state 1.
If the user selects menu option 5, a table is printed out after each
tree, showing for each branch whether there are known to be changes in
the branch, and what the states are inferred to have been at the top
end of the branch. If the inferred state is a "?" there may be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand.
If the A option is used, then the program will infer, for any character
whose ancestral state is unknown ("?") whether the ancestral state 0 or
1 will give the best tree. If these are tied, then it may not be
possible for the program to infer the state in the internal nodes, and
these will all be printed as ".". If this has happened and you want to
know more about the states at the internal nodes, you will find helpful
to use DOLMOVE to display the tree and examine its interior states, as
the algorithm in DOLMOVE shows all that can be known in this case about
the interior states, including where there is and is not amibiguity.
The algorithm in DOLLOP gives up more easily on displaying these
states.
If the U (User Tree) option is used and more than one tree is supplied,
the program also performs a statistical test of each of these trees
against the best tree. This test, which is a version of the test
proposed by Alan Templeton (1983) and evaluated in a test case by me
(1985a). It is closely parallel to a test using log likelihood
differences invented by Kishino and Hasegawa (1989), and uses the mean
and variance of step differences between trees, taken across
characters. If the mean is more than 1.96 standard deviations different
then the trees are declared significantly different. The program prints
out a table of the steps for each tree, the differences of each from
the highest one, the variance of that quantity as determined by the
step differences at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
It is important to understand that the test assumes that all the binary
characters are evolving independently, which is unlikely to be true for
many suites of morphological characters.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. In the version used here
the variances and covariances of the sums of steps across characters
are computed for all pairs of trees. To test whether the difference
between each tree and the best one is larger than could have been
expected if they all had the same expected number of steps, numbers of
steps for all trees are sampled with these covariances and equal means
(Shimodaira and Hasegawa's "least favorable hypothesis"), and a P value
is computed from the fraction of times the difference between the
tree's value and the lowest number of steps exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers are
used.
In either the KHT or the SH test the program prints out a table of the
number of steps for each tree, the differences of each from the lowest
one, the variance of that quantity as determined by the differences of
the numbers of steps at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is needed
when we use the trees to make a consensus tree of the results of
bootstrapping or jackknifing, to avoid overrepresenting replicates that
find many tied trees.
Output files for usage example
File: dollop.fdollop
Dollo and polymorphism parsimony algorithm, version 3.69.650
Dollo parsimony method
One most parsimonious tree found:
+-----------Delta
--3
! +--------Epsilon
+--4
! +-----Gamma
+--2
! +--Beta
+--1
+--Alpha
requires a total of 3.000
File: dollop.treefile
(Delta,(Epsilon,(Gamma,(Beta,Alpha))));
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
eclique Largest clique program
edollop Dollo and polymorphism parsimony algorithm
edolpenny Penny algorithm Dollo or polymorphism
efactor Multistate to binary recoding program
emix Mixed parsimony algorithm
epenny Penny algorithm, branch-and-bound
fclique Largest clique program
fdolpenny Penny algorithm Dollo or polymorphism
ffactor Multistate to binary recoding program
fmix Mixed parsimony algorithm
fmove Interactive mixed method parsimony
fpars Discrete character parsimony
fpenny Penny algorithm, branch-and-bound
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fconsense.txt 0000664 0001750 0001750 00000033360 12171064331 016116 0000000 0000000 fconsense
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Majority-rule and strict consensus tree
Description
Computes consensus trees by the majority-rule consensus tree method,
which also allows one to easily find the strict consensus tree. Is not
able to compute the Adams consensus tree. Trees are input in a tree
file in standard nested-parenthesis notation, which is produced by many
of the tree estimation programs in the package. This program can be
used as the final step in doing bootstrap analyses for many of the
methods in the package.
Algorithm
fconsense reads a file of computer-readable trees and prints out (and
may also write out onto a file) a consensus tree. At the moment it
carries out a family of consensus tree methods called the Ml methods
(Margush and McMorris, 1981). These include strict consensus and
majority rule consensus. Basically the consensus tree consists of
monophyletic groups that occur as often as possible in the data. If a
group occurs in more than a fraction l of all the input trees it will
definitely appear in the consensus tree.
The tree printed out has at each fork a number indicating how many
times the group which consists of the species to the right of
(descended from) the fork occurred. Thus if we read in 15 trees and
find that a fork has the number 15, that group occurred in all of the
trees. The strict consensus tree consists of all groups that occurred
100% of the time, the rest of the resolution being ignored. The tree
printed out here includes groups down to 50%, and below it until the
tree is fully resolved.
The majority rule consensus tree consists of all groups that occur more
than 50% of the time. Any other percentage level between 50% and 100%
can also be used, and that is why the program in effect carries out a
family of methods. You have to decide on the percentage level, figure
out for yourself what number of occurrences that would be (e.g. 15 in
the above case for 100%), and resolutely ignore any group below that
number. Do not use numbers at or below 50%, because some groups
occurring (say) 35% of the time will not be shown on the tree. The
collection of all groups that occur 35% or more of the time may include
two groups that are mutually self contradictory and cannot appear in
the same tree. In this program, as the default method I have included
groups that occur less than 50% of the time, working downwards in their
frequency of occurrence, as long as they continue to resolve the tree
and do not contradict more frequent groups. In this respect the method
is similar to the Nelson consensus method (Nelson, 1979) as explicated
by Page (1989) although it is not identical to it.
The program can also carry out Strict consensus, Majority Rule
consensus without the extension which adds groups until the tree is
fully resolved, and other members of the Ml family, where the user
supplied the fraction of times the group must appear in the input trees
to be included in the consensus tree. For the moment the program cannot
carry out any other consensus tree method, such as Adams consensus
(Adams, 1972, 1986) or methods based on quadruples of species
(Estabrook, McMorris, and Meacham, 1985).
Usage
Here is a sample session with fconsense
% fconsense
Majority-rule and strict consensus tree
Phylip tree file: consense.dat
Phylip consense program output file [consense.fconsense]:
Consensus tree written to file "consense.treefile"
Output written to file "consense.fconsense"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Majority-rule and strict consensus tree
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-outfile] outfile [*.fconsense] Phylip consense program output
file
Additional (Optional) qualifiers (* if not always prompted):
-method menu [mre] Consensus method (Values: s (strict
consensus tree); mr (Majority Rule); mre
(Majority Rule (extended)); ml (Minimum
fraction (0.5 to 1.0)))
* -mlfrac float [0.5] Fraction (l) of times a branch must
appear (Number from 0.500 to 1.000)
-root toggle [N] Trees to be treated as Rooted
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fconsense] Phylip tree output file
(optional)
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-[no]prntsets boolean [Y] Print out the sets of species
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fconsense reads any normal sequence USAs.
Input files for usage example
File: consense.dat
(A,(B,(H,(D,(J,(((G,E),(F,I)),C))))));
(A,(B,(D,((J,H),(((G,E),(F,I)),C)))));
(A,(B,(D,(H,(J,(((G,E),(F,I)),C))))));
(A,(B,(E,(G,((F,I),((J,(H,D)),C))))));
(A,(B,(E,(G,((F,I),(((J,H),D),C))))));
(A,(B,(E,((F,I),(G,((J,(H,D)),C))))));
(A,(B,(E,((F,I),(G,(((J,H),D),C))))));
(A,(B,(E,((G,(F,I)),((J,(H,D)),C)))));
(A,(B,(E,((G,(F,I)),(((J,H),D),C)))));
Output file format
fconsense output is a list of the species (in the order in which they
appear in the first tree, which is the numerical order used in the
program), a list of the subsets that appear in the consensus tree, a
list of those that appeared in one or another of the individual trees
but did not occur frequently enough to get into the consensus tree,
followed by a diagram showing the consensus tree. The lists of subsets
consists of a row of symbols, each either "." or "*". The species that
are in the set are marked by "*". Every ten species there is a blank,
to help you keep track of the alignment of columns. The order of
symbols corresponds to the order of species in the species list. Thus a
set that consisted of the second, seventh, and eighth out of 13 species
would be represented by:
.*....**.. ...
Note that if the trees are unrooted the final tree will have one group,
consisting of every species except the Outgroup (which by default is
the first species encountered on the first tree), which always appears.
It will not be listed in either of the lists of sets, but it will be
shown in the final tree as occurring all of the time. This is hardly
surprising: in telling the program that this species is the outgroup we
have specified that the set consisting of all of the others is always a
monophyletic set. So this is not to be taken as interesting
information, despite its dramatic appearance.
Output files for usage example
File: consense.fconsense
Consensus tree program, version 3.69.650
Species in order:
1. A
2. B
3. H
4. D
5. J
6. G
7. E
8. F
9. I
10. C
Sets included in the consensus tree
Set (species in order) How many times out of 9.00
.......**. 9.00
..******** 9.00
..****.*** 6.00
..***..... 6.00
..***....* 6.00
..*.*..... 4.00
..***..*** 2.00
Sets NOT included in consensus tree:
Set (species in order) How many times out of 9.00
.....**... 3.00
.....***** 3.00
..**...... 3.00
.....****. 3.00
..****...* 2.00
.....*.**. 2.00
..*.****** 2.00
....****** 2.00
...******* 1.00
Extended majority rule consensus tree
CONSENSUS TREE:
the numbers on the branches indicate the number
of times the partition of the species into the two sets
which are separated by that branch occurred
among the trees, out of 9.00 trees
+-----------------------C
|
+--6.00-| +-------H
| | +--4.00-|
| +--6.00-| +-------J
+--2.00-| |
| | +---------------D
| |
+--6.00-| | +-------F
| | +------------------9.00-|
| | +-------I
+--9.00-| |
| | +---------------------------------------G
+-------| |
| | +-----------------------------------------------E
| |
| +-------------------------------------------------------B
|
+---------------------------------------------------------------A
remember: this is an unrooted tree!
File: consense.treefile
((((((C:9.00,((H:9.00,J:9.00):4.00,D:9.00):6.00):6.00,(F:9.00,I:9.00):9.00):2.00
,G:9.00):6.00,
E:9.00):9.00,B:9.00):9.00,A:9.00);
Branch Lengths on the Consensus Tree?
Note that the lengths on the tree on the output tree file are not
branch lengths but the number of times that each group appeared in the
input trees. This number is the sum of the weights of the trees in
which it appeared, so that if there are 11 trees, ten of them having
weight 0.1 and one weight 1.0, a group that appeared in the last tree
and in 6 others would be shown as appearing 1.6 times and its branch
length will be 1.6. This means that if you take the consensus tree from
the output tree file and try to draw it, the branch lengths will be
strange. I am often asked how to put the correct branch lengths on
these (this is one of our Frequently Asked Questions). There is no
simple answer to this. It depends on what "correct" means. For example,
if you have a group of species that shows up in 80% of the trees, and
the branch leading to that group has average length 0.1 among that 80%,
is the "correct" length 0.1? Or is it (0.80 x 0.1)? There is no simple
answer. However, if you want to take the consensus tree as an estimate
of the true tree (rather than as an indicator of the conflicts among
trees) you may be able to use the User Tree (option U) mode of the
phylogeny program that you used, and use it to put branch lengths on
that tree. Thus, if you used DNAML, you can take the consensus tree,
make sure it is an unrooted tree, and feed that to DNAML using the
original data set (before bootstrapping) and DNAML's option U. As DNAML
wants an unrooted tree, you may have to use RETREE to make the tree
unrooted (using the W option of RETREE and choosing the unrooted option
within it). Of course you will also want to change the tree file name
from "outree" to "intree". If you used a phylogeny program that does
not infer branch lengths, you might want to use a different one (such
as FITCH or DNAML) to infer the branch lengths, again making sure the
tree is unrooted, if the program needs that.
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
econsense Majority-rule and strict consensus tree
ftreedist Calculate distances between trees
ftreedistpair Calculate distance between two sets of trees
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
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PHYLIPNEW-3.69.650/emboss_doc/text/fclique.txt 0000664 0001750 0001750 00000023103 12171064331 015555 0000000 0000000 fclique
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Largest clique program
Description
Finds the largest clique of mutually compatible characters, and the
phylogeny which they recommend, for discrete character data with two
states. The largest clique (or all cliques within a given size range of
the largest one) are found by a very fast branch and bound search
method. The method does not allow for missing data. For such cases the
T (Threshold) option of PARS or MIX may be a useful alternative.
Compatibility methods are particular useful when some characters are of
poor quality and the rest of good quality, but when it is not known in
advance which ones are which.
Algorithm
This program uses the compatibility method for unrooted two-state
characters to obtain the largest cliques of characters and the trees
which they suggest. This approach originated in the work of Le Quesne
(1969), though the algorithms were not precisely specified until the
later work of Estabrook, Johnson, and McMorris (1976a, 1976b). These
authors proved the theorem that a group of two-state characters which
were pairwise compatible would be jointly compatible. This program uses
an algorithm inspired by the Kent Fiala - George Estabrook program
CLINCH, though closer in detail to the algorithm of Bron and Kerbosch
(1973). I am indebted to Kent Fiala for pointing out that paper to me,
and to David Penny for decribing to me his branch-and-bound approach to
finding largest cliques, from which I have also borrowed. I am
particularly grateful to Kent Fiala for catching a bug in versions 2.0
and 2.1 which resulted in those versions failing to find all of the
cliques which they should. The program computes a compatibility matrix
for the characters, then uses a recursive procedure to examine all
possible cliques of characters.
After one pass through all possible cliques, the program knows the size
of the largest clique, and during a second pass it prints out the
cliques of the right size. It also, along with each clique, prints out
the tree suggested by that clique.
ASSUMPTIONS
Basically the following assumptions are made:
1. Each character evolves independently.
2. Different lineages evolve independently.
3. The ancestral state is not known.
4. Each character has a small chance of being one which evolves so
rapidly, or is so thoroughly misinterpreted, that it provides no
information on the tree.
5. The probability of a single change in a character (other than in
the high rate characters) is low but not as low as the probability
of being one of these "bad" characters.
6. The probability of two changes in a low-rate character is much less
than the probability that it is a high-rate character.
7. The true tree has segments which are not so unequal in length that
two changes in a long are as easy to envisage as one change in a
short segment.
The assumptions of compatibility methods have been treated in several
of my papers (1978b, 1979, 1981b, 1988b), especially the 1981 paper.
For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
A constant available for alteration at the beginning of the program is
the form width, "FormWide", which you may want to change to make it as
large as possible consistent with the page width available on your
output device, so as to avoid the output of cliques and of trees
getting wrapped around unnecessarily.
Usage
Here is a sample session with fclique
% fclique
Largest clique program
Phylip discrete states file: clique.dat
Phylip clique program output file [clique.fclique]:
Output written to file "clique.fclique"
Tree written on file "clique.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Largest clique program
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates Phylip discrete states file
[-outfile] outfile [*.fclique] Phylip clique program output
file
Additional (Optional) qualifiers (* if not always prompted):
-ancfile properties Phylip ancestral states file (optional)
-factorfile properties Phylip multistate factors file (optional)
-weights properties Phylip weights file (optional)
-cliqmin integer [0] Minimum clique size (Integer 0 or more)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fclique] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-printcomp boolean [N] Print out compatibility matrix
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
Input to the algorithm is standard, but the "?", "P", and "B" states
are not allowed. This is a serious limitation of this program. If you
want to find large cliques in data that have "?" states, I recommend
that you use fmix instead with the -Threshold option and the value of
the threshold set to 2.0. The theory underlying this is given in my
paper on character weighting (Felsenstein, 1981b).
fclique reads discrete character data with 2 states.
Input files for usage example
File: clique.dat
5 6
Alpha 110110
Beta 110000
Gamma 100110
Delta 001001
Epsilon 001110
Output file format
fclique writes the cliques to the text output file and a tree to a
separate output file
Output files for usage example
File: clique.fclique
Largest clique program, version 3.69.650
Largest Cliques
------- -------
Characters: ( 1 2 3 6)
Tree and characters:
2 1 3 6
0 0 1 1
+1-Delta
+0--1-+
+--0-+ +--Epsilon
! !
! +--------Gamma
!
+-------------Alpha
!
+-------------Beta
remember: this is an unrooted tree!
File: clique.treefile
(((Delta,Epsilon),Gamma),Alpha,Beta);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
eclique Largest clique program
edollop Dollo and polymorphism parsimony algorithm
edolpenny Penny algorithm Dollo or polymorphism
efactor Multistate to binary recoding program
emix Mixed parsimony algorithm
epenny Penny algorithm, branch-and-bound
fdollop Dollo and polymorphism parsimony algorithm
fdolpenny Penny algorithm Dollo or polymorphism
ffactor Multistate to binary recoding program
fmix Mixed parsimony algorithm
fmove Interactive mixed method parsimony
fpars Discrete character parsimony
fpenny Penny algorithm, branch-and-bound
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fneighbor.txt 0000664 0001750 0001750 00000031774 12171064331 016105 0000000 0000000 fneighbor
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Phylogenies from distance matrix by N-J or UPGMA method
Description
An implementation by Mary Kuhner and John Yamato of Saitou and Nei's
"Neighbor Joining Method," and of the UPGMA (Average Linkage
clustering) method. Neighbor Joining is a distance matrix method
producing an unrooted tree without the assumption of a clock. UPGMA
does assume a clock. The branch lengths are not optimized by the least
squares criterion but the methods are very fast and thus can handle
much larger data sets.
Algorithm
This program implements the Neighbor-Joining method of Saitou and Nei
(1987) and the UPGMA method of clustering. The program was written by
Mary Kuhner and Jon Yamato, using some code from program FITCH. An
important part of the code was translated from FORTRAN code from the
neighbor-joining program written by Naruya Saitou and by Li Jin, and is
used with the kind permission of Drs. Saitou and Jin.
NEIGHBOR constructs a tree by successive clustering of lineages,
setting branch lengths as the lineages join. The tree is not rearranged
thereafter. The tree does not assume an evolutionary clock, so that it
is in effect an unrooted tree. It should be somewhat similar to the
tree obtained by FITCH. The program cannot evaluate a User tree, nor
can it prevent branch lengths from becoming negative. However the
algorithm is far faster than FITCH or KITSCH. This will make it
particularly effective in their place for large studies or for
bootstrap or jackknife resampling studies which require runs on
multiple data sets.
The UPGMA option constructs a tree by successive (agglomerative)
clustering using an average-linkage method of clustering. It has some
relationship to KITSCH, in that when the tree topology turns out the
same, the branch lengths with UPGMA will turn out to be the same as
with the P = 0 option of KITSCH.
The programs FITCH, KITSCH, and NEIGHBOR are for dealing with data
which comes in the form of a matrix of pairwise distances between all
pairs of taxa, such as distances based on molecular sequence data, gene
frequency genetic distances, amounts of DNA hybridization, or
immunological distances. In analyzing these data, distance matrix
programs implicitly assume that:
* Each distance is measured independently from the others: no item of
data contributes to more than one distance.
* The distance between each pair of taxa is drawn from a distribution
with an expectation which is the sum of values (in effect amounts
of evolution) along the tree from one tip to the other. The
variance of the distribution is proportional to a power p of the
expectation.
These assumptions can be traced in the least squares methods of
programs FITCH and KITSCH but it is not quite so easy to see them in
operation in the Neighbor-Joining method of NEIGHBOR, where the
independence assumptions is less obvious.
THESE TWO ASSUMPTIONS ARE DUBIOUS IN MOST CASES: independence will not
be expected to be true in most kinds of data, such as genetic distances
from gene frequency data. For genetic distance data in which pure
genetic drift without mutation can be assumed to be the mechanism of
change CONTML may be more appropriate. However, FITCH, KITSCH, and
NEIGHBOR will not give positively misleading results (they will not
make a statistically inconsistent estimate) provided that additivity
holds, which it will if the distance is computed from the original data
by a method which corrects for reversals and parallelisms in evolution.
If additivity is not expected to hold, problems are more severe. A
short discussion of these matters will be found in a review article of
mine (1984a). For detailed, if sometimes irrelevant, controversy see
the papers by Farris (1981, 1985, 1986) and myself (1986, 1988b).
For genetic distances from gene frequencies, FITCH, KITSCH, and
NEIGHBOR may be appropriate if a neutral mutation model can be assumed
and Nei's genetic distance is used, or if pure drift can be assumed and
either Cavalli-Sforza's chord measure or Reynolds, Weir, and
Cockerham's (1983) genetic distance is used. However, in the latter
case (pure drift) CONTML should be better.
Restriction site and restriction fragment data can be treated by
distance matrix methods if a distance such as that of Nei and Li (1979)
is used. Distances of this sort can be computed in PHYLIp by the
program RESTDIST.
For nucleic acid sequences, the distances computed in DNADIST allow
correction for multiple hits (in different ways) and should allow one
to analyse the data under the presumption of additivity. In all of
these cases independence will not be expected to hold. DNA
hybridization and immunological distances may be additive and
independent if transformed properly and if (and only if) the standards
against which each value is measured are independent. (This is rarely
exactly true).
FITCH and the Neighbor-Joining option of NEIGHBOR fit a tree which has
the branch lengths unconstrained. KITSCH and the UPGMA option of
NEIGHBOR, by contrast, assume that an "evolutionary clock" is valid,
according to which the true branch lengths from the root of the tree to
each tip are the same: the expected amount of evolution in any lineage
is proportional to elapsed time.
Usage
Here is a sample session with fneighbor
% fneighbor
Phylogenies from distance matrix by N-J or UPGMA method
Phylip distance matrix file: neighbor.dat
Phylip neighbor program output file [neighbor.fneighbor]:
Cycle 4: species 1 ( 0.91769) joins species 2 ( 0.76891)
Cycle 3: node 1 ( 0.42027) joins species 3 ( 0.35793)
Cycle 2: species 6 ( 0.15168) joins species 7 ( 0.11752)
Cycle 1: node 1 ( 0.04648) joins species 4 ( 0.28469)
last cycle:
node 1 ( 0.02696) joins species 5 ( 0.15393) joins node 6 ( 0.03982)
Output written on file "neighbor.fneighbor"
Tree written on file "neighbor.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Phylogenies from distance matrix by N-J or UPGMA method
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-datafile] distances Phylip distance matrix file
[-outfile] outfile [*.fneighbor] Phylip neighbor program output
file
Additional (Optional) qualifiers (* if not always prompted):
-matrixtype menu [s] Type of data matrix (Values: s (Square);
u (Upper triangular); l (Lower triangular))
-treetype menu [n] Neighbor-joining or UPGMA tree (Values:
n (Neighbor-joining); u (UPGMA))
* -outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-jumble toggle [N] Randomise input order of species
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-replicates boolean [N] Subreplicates
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fneighbor] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fneighbor reads any normal sequence USAs.
Input files for usage example
File: neighbor.dat
7
Bovine 0.0000 1.6866 1.7198 1.6606 1.5243 1.6043 1.5905
Mouse 1.6866 0.0000 1.5232 1.4841 1.4465 1.4389 1.4629
Gibbon 1.7198 1.5232 0.0000 0.7115 0.5958 0.6179 0.5583
Orang 1.6606 1.4841 0.7115 0.0000 0.4631 0.5061 0.4710
Gorilla 1.5243 1.4465 0.5958 0.4631 0.0000 0.3484 0.3083
Chimp 1.6043 1.4389 0.6179 0.5061 0.3484 0.0000 0.2692
Human 1.5905 1.4629 0.5583 0.4710 0.3083 0.2692 0.0000
Output file format
fneighbor output consists of an tree (rooted if UPGMA, unrooted if
Neighbor-Joining) and the lengths of the interior segments. The Average
Percent Standard Deviation is not computed or printed out. If the tree
found by Neighbor is fed into FITCH as a User Tree, it will compute
this quantity if one also selects the N option of FITCH to ensure that
none of the branch lengths is re-estimated.
As NEIGHBOR runs it prints out an account of the successive clustering
levels, if you allow it to. This is mostly for reassurance and can be
suppressed using menu option 2. In this printout of cluster levels the
word "OTU" refers to a tip species, and the word "NODE" to an interior
node of the resulting tree.
Output files for usage example
File: neighbor.fneighbor
Neighbor-Joining/UPGMA method version 3.69.650
7 Populations
Neighbor-joining method
Negative branch lengths allowed
+---------------------------------------------Mouse
!
! +---------------------Gibbon
1------------------------2
! ! +----------------Orang
! +--4
! ! +--------Gorilla
! +-5
! ! +--------Chimp
! +-3
! +------Human
!
+------------------------------------------------------Bovine
remember: this is an unrooted tree!
Between And Length
------- --- ------
1 Mouse 0.76891
1 2 0.42027
2 Gibbon 0.35793
2 4 0.04648
4 Orang 0.28469
4 5 0.02696
5 Gorilla 0.15393
5 3 0.03982
3 Chimp 0.15168
3 Human 0.11752
1 Bovine 0.91769
File: neighbor.treefile
(Mouse:0.76891,(Gibbon:0.35793,(Orang:0.28469,(Gorilla:0.15393,
(Chimp:0.15168,Human:0.11752):0.03982):0.02696):0.04648):0.42027,Bovine:0.91769)
;
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
efitch Fitch-Margoliash and least-squares distance methods
ekitsch Fitch-Margoliash method with contemporary tips
eneighbor Phylogenies from distance matrix by N-J or UPGMA method
ffitch Fitch-Margoliash and least-squares distance methods
fkitsch Fitch-Margoliash method with contemporary tips
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fpars.txt 0000664 0001750 0001750 00000044241 12171064331 015246 0000000 0000000 fpars
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Discrete character parsimony
Description
Multistate discrete-characters parsimony method. Up to 8 states (as
well as "?") are allowed. Cannot do Camin-Sokal or Dollo Parsimony. Can
cope with multifurcations, reconstruct ancestral states, use character
weights, and infer branch lengths.
Algorithm
PARS is a general parsimony program which carries out the Wagner
parsimony method with multiple states. Wagner parsimony allows changes
among all states. The criterion is to find the tree which requires the
minimum number of changes. The Wagner method was originated by Eck and
Dayhoff (1966) and by Kluge and Farris (1969). Here are its
assumptions:
1. Ancestral states are unknown unknown.
2. Different characters evolve independently.
3. Different lineages evolve independently.
4. Changes to all other states are equally probable (Wagner).
5. These changes are a priori improbable over the evolutionary time
spans involved in the differentiation of the group in question.
6. Other kinds of evolutionary event such as retention of polymorphism
are far less probable than these state changes.
7. Rates of evolution in different lineages are sufficiently low that
two changes in a long segment of the tree are far less probable
than one change in a short segment.
That these are the assumptions of parsimony methods has been documented
in a series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b,
1988b). For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
Usage
Here is a sample session with fpars
% fpars
Discrete character parsimony
Input file: pars.dat
Phylip tree file (optional):
Phylip pars program output file [pars.fpars]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements on the first of the trees tied for best
!---------!
.........
.........
Collapsing best trees
.
Output written to file "pars.fpars"
Tree also written onto file "pars.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Discrete character parsimony
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fpars] Phylip pars program output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-method menu [Wagner] Choose the parsimony method to use
(Values: w (Wagner); c (Camin-Sokal))
-maxtrees integer [100] Number of trees to save (Integer from
1 to 1000000)
* -[no]thorough toggle [Y] More thorough search
* -[no]rearrange boolean [Y] Rearrange on just one best tree
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fpars] Phylip tree output file (optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print steps at each site
-ancseq boolean [N] Print states at all nodes of tree
* -[no]dotdiff boolean [Y] Use dot differencing to display results
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fpars reads discrete characters input, except that multiple states (up
to 9 of them) are allowed. Any characters other than "?" are allowed as
states, up to a maximum of 9 states. In fact, one can use different
symbols in different columns of the data matrix, although it is rather
unlikely that you would want to do that. The symbols you can use are:
* The digits 0-9,
* The letters A-Z and a-z,
* The symbols "!\"#$%&'()*+,-./:;<=>?@\[\\]^_`\{|}~
(of these, probably only + and - will be of interest to most
users).
But note that these do not include blank (" "). Blanks in the input
data are simply skipped by the program, so that they can be used to
make characters into groups for ease of viewing. The "?" (question
mark) symbol has special meaning. It is allowed in the input but is not
available as the symbol of a state. Rather, it means that the state is
unknown.
PARS can handle both bifurcating and multifurcating trees. In doing its
search for most parsimonious trees, it adds species not only by
creating new forks in the middle of existing branches, but it also
tries putting them at the end of new branches which are added to
existing forks. Thus it searches among both bifurcating and
multifurcating trees. If a branch in a tree does not have any
characters which might change in that branch in the most parsimonious
tree, it does not save that tree. Thus in any tree that results, a
branch exists only if some character has a most parsimonious
reconstruction that would involve change in that branch.
It also saves a number of trees tied for best (you can alter the number
it saves using the V option in the menu). When rearranging trees, it
tries rearrangements of all of the saved trees. This makes the
algorithm slower than earlier programs such as MIX.
(0,1) Discrete character data
These programs are intended for the use of morphological systematists
who are dealing with discrete characters, or by molecular evolutionists
dealing with presence-absence data on restriction sites. One of the
programs (PARS) allows multistate characters, with up to 8 states, plus
the unknown state symbol "?". For the others, the characters are
assumed to be coded into a series of (0,1) two-state characters. For
most of the programs there are two other states possible, "P", which
stands for the state of Polymorphism for both states (0 and 1), and
"?", which stands for the state of ignorance: it is the state
"unknown", or "does not apply". The state "P" can also be denoted by
"B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding a
multistate character into a series of two-state (0,1) characters.
Suppose we had a character with four states whose character-state tree
had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We can
represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE, DOLPENNY
and DOLBOOT the multistate recoding does not necessarily work properly,
as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected in
a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for unordered
character states.
Input files for usage example
File: pars.dat
5 6
Alpha 110110
Beta 110000
Gamma 100110
Delta 001001
Epsilon 001110
Output file format
fpars output is standard: if option 1 is toggled on, the data is
printed out, with the convention that "." means "the same as in the
first species". Then comes a list of equally parsimonious trees. Each
tree has branch lengths. These are computed using an algorithm
published by Hochbaum and Pathria (1997) which I first heard of from
Wayne Maddison who invented it independently of them. This algorithm
averages the number of reconstructed changes of state over all sites a
over all possible most parsimonious placements of the changes of state
among branches. Note that it does not correct in any way for multiple
changes that overlay each other.
If option 2 is toggled on a table of the number of changes of state
required in each character is also printed. If option 5 is toggled on,
a table is printed out after each tree, showing for each branch whether
there are known to be changes in the branch, and what the states are
inferred to have been at the top end of the branch. This is a
reconstruction of the ancestral sequences in the tree. If you choose
option 5, a menu item D appears which gives you the opportunity to turn
off dot-differencing so that complete ancestral sequences are shown. If
the inferred state is a "?", there will be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand. If option 6 is left in its default state
the trees found will be written to a tree file, so that they are
available to be used in other programs. If the program finds multiple
trees tied for best, all of these are written out onto the output tree
file. Each is followed by a numerical weight in square brackets (such
as [0.25000]). This is needed when we use the trees to make a consensus
tree of the results of bootstrapping or jackknifing, to avoid
overrepresenting replicates that find many tied trees.
If the U (User Tree) option is used and more than one tree is supplied,
the program also performs a statistical test of each of these trees
against the best tree. This test, which is a version of the test
proposed by Alan Templeton (1983) and evaluated in a test case by me
(1985a). It is closely parallel to a test using log likelihood
differences due to Kishino and Hasegawa (1989), and uses the mean and
variance of step differences between trees, taken across sites. If the
mean is more than 1.96 standard deviations different then the trees are
declared significantly different. The program prints out a table of the
steps for each tree, the differences of each from the best one, the
variance of that quantity as determined by the step differences at
individual sites, and a conclusion as to whether that tree is or is not
significantly worse than the best one. It is important to understand
that the test assumes that all the discrete characters are evolving
independently, which is unlikely to be true for
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. In the version used here
the variances and covariances of the sums of steps across characters
are computed for all pairs of trees. To test whether the difference
between each tree and the best one is larger than could have been
expected if they all had the same expected number of steps, numbers of
steps for all trees are sampled with these covariances and equal means
(Shimodaira and Hasegawa's "least favorable hypothesis"), and a P value
is computed from the fraction of times the difference between the
tree's value and the lowest number of steps exceeds that actually
observed. Note that this sampling needs random numbers, and so the
program will prompt the user for a random number seed if one has not
already been supplied. With the two-tree KHT test no random numbers are
used.
In either the KHT or the SH test the program prints out a table of the
number of steps for each tree, the differences of each from the lowest
one, the variance of that quantity as determined by the differences of
the numbers of steps at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
Option 6 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined trees
are written to the output tree file.
Output files for usage example
File: pars.fpars
Discrete character parsimony algorithm, version 3.69.650
One most parsimonious tree found:
+Epsilon
+----------------3
+--------2 +-------------------------Delta
| |
| +Gamma
|
1----------------Beta
|
+Alpha
requires a total of 8.000
between and length
------- --- ------
1 2 1.00
2 3 2.00
3 Epsilon 0.00
3 Delta 3.00
2 Gamma 0.00
1 Beta 2.00
1 Alpha 0.00
File: pars.treefile
(((Epsilon:0.00,Delta:3.00):2.00,Gamma:0.00):1.00,Beta:2.00,Alpha:0.00);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
eclique Largest clique program
edollop Dollo and polymorphism parsimony algorithm
edolpenny Penny algorithm Dollo or polymorphism
efactor Multistate to binary recoding program
emix Mixed parsimony algorithm
epenny Penny algorithm, branch-and-bound
fclique Largest clique program
fdollop Dollo and polymorphism parsimony algorithm
fdolpenny Penny algorithm Dollo or polymorphism
ffactor Multistate to binary recoding program
fmix Mixed parsimony algorithm
fmove Interactive mixed method parsimony
fpenny Penny algorithm, branch-and-bound
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/ffitch.txt 0000664 0001750 0001750 00000031007 12171064331 015372 0000000 0000000 ffitch
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Fitch-Margoliash and least-squares distance methods
Description
Estimates phylogenies from distance matrix data under the "additive
tree model" according to which the distances are expected to equal the
sums of branch lengths between the species. Uses the Fitch-Margoliash
criterion and some related least squares criteria, or the Minimum
Evolution distance matrix method. Does not assume an evolutionary
clock. This program will be useful with distances computed from
molecular sequences, restriction sites or fragments distances, with DNA
hybridization measurements, and with genetic distances computed from
gene frequencies.
Algorithm
The programs FITCH, KITSCH, and NEIGHBOR are for dealing with data
which comes in the form of a matrix of pairwise distances between all
pairs of taxa, such as distances based on molecular sequence data, gene
frequency genetic distances, amounts of DNA hybridization, or
immunological distances. In analyzing these data, distance matrix
programs implicitly assume that:
* Each distance is measured independently from the others: no item of
data contributes to more than one distance.
* The distance between each pair of taxa is drawn from a distribution
with an expectation which is the sum of values (in effect amounts
of evolution) along the tree from one tip to the other. The
variance of the distribution is proportional to a power p of the
expectation.
These assumptions can be traced in the least squares methods of
programs FITCH and KITSCH but it is not quite so easy to see them in
operation in the Neighbor-Joining method of NEIGHBOR, where the
independence assumptions is less obvious.
THESE TWO ASSUMPTIONS ARE DUBIOUS IN MOST CASES: independence will not
be expected to be true in most kinds of data, such as genetic distances
from gene frequency data. For genetic distance data in which pure
genetic drift without mutation can be assumed to be the mechanism of
change CONTML may be more appropriate. However, FITCH, KITSCH, and
NEIGHBOR will not give positively misleading results (they will not
make a statistically inconsistent estimate) provided that additivity
holds, which it will if the distance is computed from the original data
by a method which corrects for reversals and parallelisms in evolution.
If additivity is not expected to hold, problems are more severe. A
short discussion of these matters will be found in a review article of
mine (1984a). For detailed, if sometimes irrelevant, controversy see
the papers by Farris (1981, 1985, 1986) and myself (1986, 1988b).
For genetic distances from gene frequencies, FITCH, KITSCH, and
NEIGHBOR may be appropriate if a neutral mutation model can be assumed
and Nei's genetic distance is used, or if pure drift can be assumed and
either Cavalli-Sforza's chord measure or Reynolds, Weir, and
Cockerham's (1983) genetic distance is used. However, in the latter
case (pure drift) CONTML should be better.
Restriction site and restriction fragment data can be treated by
distance matrix methods if a distance such as that of Nei and Li (1979)
is used. Distances of this sort can be computed in PHYLIp by the
program RESTDIST.
For nucleic acid sequences, the distances computed in DNADIST allow
correction for multiple hits (in different ways) and should allow one
to analyse the data under the presumption of additivity. In all of
these cases independence will not be expected to hold. DNA
hybridization and immunological distances may be additive and
independent if transformed properly and if (and only if) the standards
against which each value is measured are independent. (This is rarely
exactly true).
FITCH and the Neighbor-Joining option of NEIGHBOR fit a tree which has
the branch lengths unconstrained. KITSCH and the UPGMA option of
NEIGHBOR, by contrast, assume that an "evolutionary clock" is valid,
according to which the true branch lengths from the root of the tree to
each tip are the same: the expected amount of evolution in any lineage
is proportional to elapsed time.
Usage
Here is a sample session with ffitch
% ffitch
Fitch-Margoliash and least-squares distance methods
Phylip distance matrix file: fitch.dat
Phylip tree file (optional):
Phylip fitch program output file [fitch.ffitch]:
Adding species:
1. Bovine
2. Mouse
3. Gibbon
4. Orang
5. Gorilla
6. Chimp
7. Human
Output written to file "fitch.ffitch"
Tree also written onto file "fitch.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Fitch-Margoliash and least-squares distance methods
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-datafile] distances File containing one or more distance
matrices
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.ffitch] Phylip fitch program output file
Additional (Optional) qualifiers (* if not always prompted):
-matrixtype menu [s] Type of input data matrix (Values: s
(Square); u (Upper triangular); l (Lower
triangular))
-minev boolean [N] Minimum evolution
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-power float [2.0] Power (Any numeric value)
* -lengths boolean [N] Use branch lengths from user trees
* -negallowed boolean [N] Negative branch lengths allowed
* -global boolean [N] Global rearrangements
-replicates boolean [N] Subreplicates
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.ffitch] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
ffitch reads any normal sequence USAs.
Input files for usage example
File: fitch.dat
7
Bovine 0.0000 1.6866 1.7198 1.6606 1.5243 1.6043 1.5905
Mouse 1.6866 0.0000 1.5232 1.4841 1.4465 1.4389 1.4629
Gibbon 1.7198 1.5232 0.0000 0.7115 0.5958 0.6179 0.5583
Orang 1.6606 1.4841 0.7115 0.0000 0.4631 0.5061 0.4710
Gorilla 1.5243 1.4465 0.5958 0.4631 0.0000 0.3484 0.3083
Chimp 1.6043 1.4389 0.6179 0.5061 0.3484 0.0000 0.2692
Human 1.5905 1.4629 0.5583 0.4710 0.3083 0.2692 0.0000
Output file format
ffitch output consists of an unrooted tree and the lengths of the
interior segments. The sum of squares is printed out, and if P = 2.0
Fitch and Margoliash's "average percent standard deviation" is also
computed and printed out. This is the sum of squares, divided by N-2,
and then square-rooted and then multiplied by 100 (n is the number of
species on the tree):
APSD = ( SSQ / (N-2) )1/2 x 100.
where N is the total number of off-diagonal distance measurements that
are in the (square) distance matrix. If the S (subreplication) option
is in force it is instead the sum of the numbers of replicates in all
the non-diagonal cells of the distance matrix. But if the L or R option
is also in effect, so that the distance matrix read in is lower- or
upper-triangular, then the sum of replicates is only over those cells
actually read in. If S is not in force, the number of replicates in
each cell is assumed to be 1, so that N is n(n-1), where n is the
number of species. The APSD gives an indication of the average
percentage error. The number of trees examined is also printed out.
Output files for usage example
File: fitch.ffitch
7 Populations
Fitch-Margoliash method version 3.69.650
__ __ 2
\ \ (Obs - Exp)
Sum of squares = /_ /_ ------------
2
i j Obs
Negative branch lengths not allowed
+---------------------------------------------Mouse
!
! +------Human
! +--5
! +-4 +--------Chimp
! ! !
! +--3 +---------Gorilla
! ! !
1------------------------2 +-----------------Orang
! !
! +---------------------Gibbon
!
+------------------------------------------------------Bovine
remember: this is an unrooted tree!
Sum of squares = 0.01375
Average percent standard deviation = 1.85418
Between And Length
------- --- ------
1 Mouse 0.76985
1 2 0.41983
2 3 0.04986
3 4 0.02121
4 5 0.03695
5 Human 0.11449
5 Chimp 0.15471
4 Gorilla 0.15680
3 Orang 0.29209
2 Gibbon 0.35537
1 Bovine 0.91675
File: fitch.treefile
(Mouse:0.76985,((((Human:0.11449,Chimp:0.15471):0.03695,
Gorilla:0.15680):0.02121,Orang:0.29209):0.04986,Gibbon:0.35537):0.41983,Bovine:0
.91675);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
efitch Fitch-Margoliash and least-squares distance methods
ekitsch Fitch-Margoliash method with contemporary tips
eneighbor Phylogenies from distance matrix by N-J or UPGMA method
fkitsch Fitch-Margoliash method with contemporary tips
fneighbor Phylogenies from distance matrix by N-J or UPGMA method
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdnainvar.txt 0000664 0001750 0001750 00000046325 12171064331 016110 0000000 0000000 fdnainvar
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Nucleic acid sequence invariants method
Description
For nucleic acid sequence data on four species, computes Lake's and
Cavender's phylogenetic invariants, which test alternative tree
topologies. The program also tabulates the frequencies of occurrence of
the different nucleotide patterns. Lake's invariants are the method
which he calls "evolutionary parsimony".
Algorithm
This program reads in nucleotide sequences for four species and
computes the phylogenetic invariants discovered by James Cavender
(Cavender and Felsenstein, 1987) and James Lake (1987). Lake's method
is also called by him "evolutionary parsimony". I prefer Cavender's
more mathematically precise term "invariants", as the method bears
somewhat more relationship to likelihood methods than to parsimony. The
invariants are mathematical formulas (in the present case linear or
quadratic) in the EXPECTED frequencies of site patterns which are zero
for all trees of a given tree topology, irrespective of branch lengths.
We can consider at a given site that if there are no ambiguities, we
could have for four species the nucleotide patterns (considering the
same site across all four species) AAAA, AAAC, AAAG, ... through TTTT,
256 patterns in all.
The invariants are formulas in the expected pattern frequencies, not
the observed pattern frequencies. When they are computed using the
observed pattern frequencies, we will usually find that they are not
precisely zero even when the model is correct and we have the correct
tree topology. Only as the number of nucleotides scored becomes
infinite will the observed pattern frequencies approach their
expectations; otherwise, we must do a statistical test of the
invariants.
Some explanation of invariants will be found in the above papers, and
also in my recent review article on statistical aspects of inferring
phylogenies (Felsenstein, 1988b). Although invariants have some
important advantages, their validity also depends on symmetry
assumptions that may not be satisfied. In the discussion below suppose
that the possible unrooted phylogenies are I: ((A,B),(C,D)), II:
((A,C),(B,D)), and III: ((A,D),(B,C)).
Lake's Invariants, Their Testing and Assumptions
Lake's invariants are fairly simple to describe: the patterns involved
are only those in which there are two purines and two pyrimidines at a
site. Thus a site with AACT would affect the invariants, but a site
with AAGG would not. Let us use (as Lake does) the symbols 1, 2, 3, and
4, with the proviso that 1 and 2 are either both of the purines or both
of the pyrimidines; 3 and 4 are the other two nucleotides. Thus 1 and 2
always differ by a transition; so do 3 and 4. Lake's invariants,
expressed in terms of expected frequencies, are the three quantities:
(1) P(1133) + P(1234) - P(1134) - P(1233),
(2) P(1313) + P(1324) - P(1314) - P(1323),
(3) P(1331) + P(1342) - P(1341) - P(1332),
He showed that invariants (2) and (3) are zero under Topology I, (1)
and (3) are zero under topology II, and (1) and (2) are zero under
Topology III. If, for example, we see a site with pattern ACGC, we can
start by setting 1=A. Then 2 must be G. We can then set 3=C (so that 4
is T). Thus its pattern type, making those substitutions, is 1323.
P(1323) is the expected probability of the type of pattern which
includes ACGC, TGAG, GTAT, etc.
Lake's invariants are easily tested with observed frequencies. For
example, the first of them is a test of whether there are as many sites
of types 1133 and 1234 as there are of types 1134 and 1233; this is
easily tested with a chi-square test or, as in this program, with an
exact binomial test. Note that with several invariants to test, we risk
overestimating the significance of results if we simply accept the
nominal 95% levels of significance (Li and Guoy, 1990).
Lake's invariants assume that each site is evolving independently, and
that starting from any base a transversion is equally likely to end up
at each of the two possible bases (thus, an A undergoing a transversion
is equally likely to end up as a C or a T, and similarly for the other
four bases from which one could start. Interestingly, Lake's results do
not assume that rates of evolution are the same at all sites. The
result that the total of 1133 and 1234 is expected to be the same as
the total of 1134 and 1233 is unaffected by the fact that we may have
aggregated the counts over classes of sites evolving at different
rates.
Cavender's Invariants, Their Testing and Assumptions
Cavender's invariants (Cavender and Felsenstein, 1987) are for the case
of a character with two states. In the nucleic acid case we can
classify nucleotides into two states, R and Y (Purine and Pyrimidine)
and then use the two-state results. Cavender starts, as before, with
the pattern frequencies. Coding purines as R and pyrimidines as Y, the
patterns types are RRRR, RRRY, and so on until YYYY, a total of 16
types. Cavender found quadratic functions of the expected frequencies
of these 16 types that were expected to be zero under a given
phylogeny, irrespective of branch lengths. Two invariants (called K and
L) were found for each tree topology. The L invariants are particularly
easy to understand. If we have the tree topology ((A,B),(C,D)), then in
the case of two symmetric states, the event that A and B have the same
state should be independent of whether C and D have the same state, as
the events determining these happen in different parts of the tree. We
can set up a contingency table:
C = D C =/= D
------------------------------
|
A = B | YYYY, YYRR, YYYR, YYRY,
| RRRR, RRYY RRYR, RRRY
|
A =/= B | YRYY, YRRR, YRYR, YRRY,
| RYYY, RYRR RYYR, RYRY
and we expect that the events C = D and A = B will be independent.
Cavender's L invariant for this tree topology is simply the negative of
the crossproduct difference,
P(A=/=B and C=D) P(A=B and C=/=D) - P(A=B and C=D) P(A=/=B and C=/=D).
One of these L invariants is defined for each of the three tree
topologies. They can obviously be tested simply by doing a chi-square
test on the contingency table. The one corresponding to the correct
topology should be statistically indistinguishable from zero. Again,
there is a possible multiple tests problem if all three are tested at a
nominal value of 95%.
The K invariants are differences between the L invariants. When one of
the tables is expected to have crossproduct difference zero, the other
two are expected to be nonzero, and also to be equal. So the difference
of their crossproduct differences can be taken; this is the K
invariant. It is not so easily tested.
The assumptions of Cavender's invariants are different from those of
Lake's. One obviously need not assume anything about the frequencies
of, or transitions among, the two different purines or the two
different pyrimidines. However one does need to assume independent
events at each site, and one needs to assume that the Y and R states
are symmetric, that the probability per unit time that a Y changes into
an R is the same as the probability that an R changes into a Y, so that
we expect equal frequencies of the two states. There is also an
assumption that all sites are changing between these two states at the
same expected rate. This assumption is not needed for Lake's
invariants, since expectations of sums are equal to sums of
expectations, but for Cavender's it is, since products of expectations
are not equal to expectations of products.
It is helpful to have both sorts of invariants available; with further
work we may appreciate what other invaraints there are for various
models of nucleic acid change.
Usage
Here is a sample session with fdnainvar
% fdnainvar -printdata
Nucleic acid sequence invariants method
Input (aligned) nucleotide sequence set(s): dnainvar.dat
Phylip weights file (optional):
Phylip dnainvar program output file [dnainvar.fdnainvar]:
Output written to output file "dnainvar.fdnainvar"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Nucleic acid sequence invariants method
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
-weights properties Phylip weights file (optional)
[-outfile] outfile [*.fdnainvar] Phylip dnainvar program output
file
Additional (Optional) qualifiers (* if not always prompted):
-printdata boolean [N] Print data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing to display results
-[no]printpattern boolean [Y] Print counts of patterns
-[no]printinvariant boolean [Y] Print invariants
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdnainvar reads any normal sequence USAs.
Input files for usage example
File: dnainvar.dat
4 13
Alpha AACGTGGCCAAAT
Beta AAGGTCGCCAAAC
Gamma CATTTCGTCACAA
Delta GGTATTTCGGCCT
Output file format
fdnainvar output consists first (if option 1 is selected) of a
reprinting of the input data, then (if option 2 is on) tables of
observed pattern frequencies and pattern type frequencies. A table will
be printed out, in alphabetic order AAAA through TTTT of all the
patterns that appear among the sites and the number of times each
appears. This table will be invaluable for computation of any other
invariants. There follows another table, of pattern types, using the
1234 notation, in numerical order 1111 through 1234, of the number of
times each type of pattern appears. In this computation all sites at
which there are any ambiguities or deletions are omitted. Cavender's
invariants could actually be computed from sites that have only Y or R
ambiguities; this will be done in the next release of this program.
If option 3 is on the invariants are then printed out, together with
their statistical tests. For Lake's invariants the two sums which are
expected to be equal are printed out, and then the result of an
one-tailed exact binomial test which tests whether the difference is
expected to be this positive or more. The P level is given (but
remember the multiple-tests problem!).
For Cavender's L invariants the contingency tables are given. Each is
tested with a one-tailed chi-square test. It is possible that the
expected numbers in some categories could be too small for valid use of
this test; the program does not check for this. It is also possible
that the chi-square could be significant but in the wrong direction;
this is not tested in the current version of the program. To check it
beware of a chi-square greater than 3.841 but with a positive
invariant. The invariants themselves are computed, as the difference of
cross-products. Their absolute magnitudes are not important, but which
one is closest to zero may be indicative. Significantly nonzero
invariants should be negative if the model is valid. The K invariants,
which are simply differences among the L invariants, are also printed
out without any test on them being conducted. Note that it is possible
to use the bootstrap utility SEQBOOT to create multiple data sets, and
from the output from sunning all of these get the empirical variability
of these quadratic invariants.
Output files for usage example
File: dnainvar.fdnainvar
Nucleic acid sequence Invariants method, version 3.69.650
4 species, 13 sites
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta ..G..C.... ..C
Gamma C.TT.C.T.. C.A
Delta GGTA.TT.GG CC.
Pattern Number of times
AAAC 1
AAAG 2
AACC 1
AACG 1
CCCG 1
CCTC 1
CGTT 1
GCCT 1
GGGT 1
GGTA 1
TCAT 1
TTTT 1
Symmetrized patterns (1, 2 = the two purines and 3, 4 = the two pyrimidines
or 1, 2 = the two pyrimidines and 3, 4 = the two purines)
1111 1
1112 2
1113 3
1121 1
1132 2
1133 1
1231 1
1322 1
1334 1
Tree topologies (unrooted):
I: ((Alpha,Beta),(Gamma,Delta))
II: ((Alpha,Gamma),(Beta,Delta))
III: ((Alpha,Delta),(Beta,Gamma))
[Part of this file has been deleted for brevity]
different purine:pyrimidine ratios from 1:1.
Tree I:
Contingency Table
2 8
1 2
Quadratic invariant = 4.0
Chi-square = 0.23111 (not significant)
Tree II:
Contingency Table
1 5
1 6
Quadratic invariant = -1.0
Chi-square = 0.01407 (not significant)
Tree III:
Contingency Table
1 2
6 4
Quadratic invariant = 8.0
Chi-square = 0.66032 (not significant)
Cavender's quadratic invariants (type K) using purines vs. pyrimidines
(these are expected to be zero for the correct tree topology)
They will be misled if there are substantially
different evolutionary rate between sites, or
different purine:pyrimidine ratios from 1:1.
No statistical test is done on them here.
Tree I: -9.0
Tree II: 4.0
Tree III: 5.0
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fprotpars.txt 0000664 0001750 0001750 00000073314 12171064331 016156 0000000 0000000 fprotpars
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Protein parsimony algorithm
Description
Estimates phylogenies from protein sequences (input using the standard
one-letter code for amino acids) using the parsimony method, in a
variant which counts only those nucleotide changes that change the
amino acid, on the assumption that silent changes are more easily
accomplished.
Algorithm
This program infers an unrooted phylogeny from protein sequences, using
a new method intermediate between the approaches of Eck and Dayhoff
(1966) and Fitch (1971). Eck and Dayhoff (1966) allowed any amino acid
to change to any other, and counted the number of such changes needed
to evolve the protein sequences on each given phylogeny. This has the
problem that it allows replacements which are not consistent with the
genetic code, counting them equally with replacements that are
consistent. Fitch, on the other hand, counted the minimum number of
nucleotide substitutions that would be needed to achieve the given
protein sequences. This counts silent changes equally with those that
change the amino acid.
The present method insists that any changes of amino acid be consistent
with the genetic code so that, for example, lysine is allowed to change
to methionine but not to proline. However, changes between two amino
acids via a third are allowed and counted as two changes if each of the
two replacements is individually allowed. This sometimes allows changes
that at first sight you would think should be outlawed. Thus we can
change from phenylalanine to glutamine via leucine in two steps total.
Consulting the genetic code, you will find that there is a leucine
codon one step away from a phenylalanine codon, and a leucine codon one
step away from glutamine. But they are not the same leucine codon. It
actually takes three base substitutions to get from either of the
phenylalanine codons TTT and TTC to either of the glutamine codons CAA
or CAG. Why then does this program count only two? The answer is that
recent DNA sequence comparisons seem to show that synonymous changes
are considerably faster and easier than ones that change the amino
acid. We are assuming that, in effect, synonymous changes occur so much
more readily that they need not be counted. Thus, in the chain of
changes TTT (Phe) --> CTT (Leu) --> CTA (Leu) --> CAA (Glu), the middle
one is not counted because it does not change the amino acid (leucine).
To maintain consistency with the genetic code, it is necessary for the
program internally to treat serine as two separate states (ser1 and
ser2) since the two groups of serine codons are not adjacent in the
code. Changes to the state "deletion" are counted as three steps to
prevent the algorithm from assuming unnecessary deletions. The state
"unknown" is simply taken to mean that the amino acid, which has not
been determined, will in each part of a tree that is evaluated be
assumed be whichever one causes the fewest steps.
The assumptions of this method (which has not been described in the
literature), are thus something like this:
Change in different sites is independent. Change in different lineages
is independent. The probability of a base substitution that changes the
amino acid sequence is small over the lengths of time involved in a
branch of the phylogeny. The expected amounts of change in different
branches of the phylogeny do not vary by so much that two changes in a
high-rate branch are more probable than one change in a low-rate
branch. The expected amounts of change do not vary enough among sites
that two changes in one site are more probable than one change in
another. The probability of a base change that is synonymous is much
higher than the probability of a change that is not synonymous. That
these are the assumptions of parsimony methods has been documented in a
series of papers of mine: (1973a, 1978b, 1979, 1981b, 1983b, 1988b).
For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the works by Farris (1983)
and Sober (1983a, 1983b, 1988), but also read the exchange between
Felsenstein and Sober (1986).
The input for the program is fairly standard. The first line contains
the number of species and the number of amino acid positions (counting
any stop codons that you want to include).
Next come the species data. Each sequence starts on a new line, has a
ten-character species name that must be blank-filled to be of that
length, followed immediately by the species data in the one-letter
code. The sequences must either be in the "interleaved" or "sequential"
formats described in the Molecular Sequence Programs document. The I
option selects between them. The sequences can have internal blanks in
the sequence but there must be no extra blanks at the end of the
terminated line. Note that a blank is not a valid symbol for a
deletion.
The protein sequences are given by the one-letter code used by
described in the Molecular Sequence Programs documentation file. Note
that if two polypeptide chains are being used that are of different
length owing to one terminating before the other, they should be coded
as (say)
HIINMA*????
HIPNMGVWABT
since after the stop codon we do not definitely know that there has
been a deletion, and do not know what amino acid would have been there.
If DNA studies tell us that there is DNA sequence in that region, then
we could use "X" rather than "?". Note that "X" means an unknown amino
acid, but definitely an amino acid, while "?" could mean either that or
a deletion. The distinction is often significant in regions where there
are deletions: one may want to encode a six-base deletion as "-?????"
since that way the program will only count one deletion, not six
deletion events, when the deletion arises. However, if there are
overlapping deletions it may not be so easy to know what coding is
correct.
One will usually want to use "?" after a stop codon, if one does not
know what amino acid is there. If the DNA sequence has been observed
there, one probably ought to resist putting in the amino acids that
this DNA would code for, and one should use "X" instead, because under
the assumptions implicit in this parsimony method, changes to any
noncoding sequence are much easier than changes in a coding region that
change the amino acid, so that they shouldn't be counted anyway!
The form of this information is the standard one described in the main
documentation file. For the U option the tree provided must be a rooted
bifurcating tree, with the root placed anywhere you want, since that
root placement does not affect anything.
Usage
Here is a sample session with fprotpars
% fprotpars
Protein parsimony algorithm
Input (aligned) protein sequence set(s): protpars.dat
Phylip tree file (optional):
Phylip protpars program output file [protpars.fprotpars]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
.........
Output written to file "protpars.fprotpars"
Trees also written onto file "protpars.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Example 2
% fprotpars -njumble 3 -seed 3 -printdata -ancseq -whichcode m -stepbox -outgrno
2 -dothreshold -threshold 3
Protein parsimony algorithm
Input (aligned) protein sequence set(s): protpars.dat
Phylip tree file (optional):
Phylip protpars program output file [protpars.fprotpars]:
Adding species:
1. Delta
2. Epsilon
3. Alpha
4. Beta
5. Gamma
Doing global rearrangements
!---------!
.........
.........
Adding species:
1. Beta
2. Epsilon
3. Delta
4. Alpha
5. Gamma
Doing global rearrangements
!---------!
.........
Adding species:
1. Epsilon
2. Alpha
3. Gamma
4. Delta
5. Beta
Doing global rearrangements
!---------!
.........
Output written to file "protpars.fprotpars"
Trees also written onto file "protpars.treefile"
Done.
Go to the output files for this example
Example 3
% fprotpars -njumble 3 -seed 3
Protein parsimony algorithm
Input (aligned) protein sequence set(s): protpars2.dat
Phylip tree file (optional):
Phylip protpars program output file [protpars2.fprotpars]:
Data set # 1:
Adding species:
1. Delta
2. Epsilon
3. Alpha
4. Beta
5. Gamma
Doing global rearrangements
!---------!
.........
.........
Adding species:
1. Beta
2. Epsilon
3. Delta
4. Alpha
5. Gamma
Doing global rearrangements
!---------!
.........
Adding species:
1. Epsilon
2. Alpha
3. Gamma
4. Delta
5. Beta
Doing global rearrangements
!---------!
.........
Output written to file "protpars2.fprotpars"
Trees also written onto file "protpars2.treefile"
Data set # 2:
Adding species:
1. Gamma
2. Delta
3. Epsilon
4. Beta
5. Alpha
Doing global rearrangements
!---------!
.........
.........
Adding species:
1. Alpha
2. Delta
3. Epsilon
4. Gamma
5. Beta
Doing global rearrangements
!---------!
.........
Adding species:
1. Epsilon
2. Beta
3. Gamma
4. Alpha
5. Delta
Doing global rearrangements
!---------!
.........
Output written to file "protpars2.fprotpars"
Trees also written onto file "protpars2.treefile"
Data set # 3:
Adding species:
1. Delta
2. Beta
3. Gamma
4. Alpha
5. Epsilon
Doing global rearrangements
!---------!
.........
.........
Adding species:
1. Gamma
2. Delta
3. Beta
4. Epsilon
5. Alpha
Doing global rearrangements
!---------!
.........
Adding species:
1. Epsilon
2. Alpha
3. Gamma
4. Delta
5. Beta
Doing global rearrangements
!---------!
.........
Output written to file "protpars2.fprotpars"
Trees also written onto file "protpars2.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Example 4
% fprotpars -option
Protein parsimony algorithm
Input (aligned) protein sequence set(s): protpars.dat
Phylip tree file (optional):
Phylip weights file (optional): protparswts.dat
Number of times to randomise [0]:
Species number to use as outgroup [0]:
Use threshold parsimony [N]:
Genetic codes
U : Universal
M : Mitochondrial
V : Vertebrate mitochondrial
F : Fly mitochondrial
Y : Yeast mitochondrial
Use which genetic code [Universal]:
Phylip protpars program output file [protpars.fprotpars]:
Write out trees to tree file [Y]:
Phylip tree output file (optional) [protpars.treefile]:
Print data at start of run [N]:
Print indications of progress of run [Y]:
Print out tree [Y]:
Print steps at each site [N]:
Print sequences at all nodes of tree [N]:
Weights set # 1:
Adding species:
1. Delta
2. Alpha
3. Gamma
4. Epsilon
5. Beta
Doing global rearrangements
!---------!
.........
.........
Output written to file "protpars.fprotpars"
Trees also written onto file "protpars.treefile"
Weights set # 2:
Adding species:
1. Epsilon
2. Alpha
3. Delta
4. Gamma
5. Beta
Doing global rearrangements
!---------!
.........
.........
Output written to file "protpars.fprotpars"
Trees also written onto file "protpars.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Protein parsimony algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fprotpars] Phylip protpars program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Phylip weights file (optional)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 1.000 or more)
-whichcode menu [Universal] Use which genetic code (Values:
U (Universal); M (Mitochondrial); V
(Vertebrate mitochondrial); F (Fly
mitochondrial); Y (Yeast mitochondrial))
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fprotpars] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print steps at each site
-ancseq boolean [N] Print sequences at all nodes of tree
* -[no]dotdiff boolean [Y] Use dot differencing to display results
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fprotpars reads any normal sequence USAs.
Input files for usage example
File: protpars.dat
5 10
Alpha ABCDEFGHIK
Beta AB--EFGHIK
Gamma ?BCDSFG*??
Delta CIKDEFGHIK
Epsilon DIKDEFGHIK
Input files for usage example 3
File: protpars2.dat
5 10
Alpha AABBCCCFHK
Beta AABB---FHK
Gamma ??BBCCCF*?
Delta CCIIKKKFHK
Epsilon DDIIKKKFHK
5 10
Alpha AADDEGGIIK
Beta AA--EGGIIK
Gamma ??DDSGG???
Delta CCDDEGGIIK
Epsilon DDDDEGGIIK
5 10
Alpha AACDDDEGHI
Beta AA----EGHI
Gamma ??CDDDSG*?
Delta CCKDDDEGHI
Epsilon DDKDDDEGHI
Input files for usage example 4
File: protparswts.dat
1111100000
0000011111
Output file format
fprotpars output is standard: if option 1 is toggled on, the data is
printed out, with the convention that "." means "the same as in the
first species". Then comes a list of equally parsimonious trees, and
(if option 2 is toggled on) a table of the number of changes of state
required in each position. If option 5 is toggled on, a table is
printed out after each tree, showing for each branch whether there are
known to be changes in the branch, and what the states are inferred to
have been at the top end of the branch. This is a reconstruction of the
ancestral sequences in the tree. If you choose option 5, a menu item
"." appears which gives you the opportunity to turn off
dot-differencing so that complete ancestral sequences are shown. If the
inferred state is a "?" there will be multiple equally-parsimonious
assignments of states; the user must work these out for themselves by
hand. If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is needed
when we use the trees to make a consensus tree of the results of
bootstrapping or jackknifing, to avoid overrepresenting replicates that
find many tied trees. If the U (User Tree) option is used and more than
one tree is supplied, the program also performs a statistical test of
each of these trees against the best tree. This test, which is a
version of the test proposed by Alan Templeton (1983) and evaluated in
a test case by me (1985a). It is closely parallel to a test using log
likelihood differences due to Kishino and Hasegawa (1989), and uses the
mean and variance of step differences between trees, taken across
positions. If the mean is more than 1.96 standard deviations different
then the trees are declared significantly different. The program prints
out a table of the steps for each tree, the differences of each from
the best one, the variance of that quantity as determined by the step
differences at individual positions, and a conclusion as to whether
that tree is or is not significantly worse than the best one.
Output files for usage example
File: protpars.fprotpars
Protein parsimony algorithm, version 3.69.650
3 trees in all found
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
+--Epsilon
+-----4
! +--Delta
+--3
! ! +--Gamma
1 +-----2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
File: protpars.treefile
((Gamma,((Epsilon,Delta),Beta)),Alpha)[0.3333];
((((Epsilon,Delta),Gamma),Beta),Alpha)[0.3333];
(((Epsilon,Delta),(Gamma,Beta)),Alpha)[0.3333];
Output files for usage example 2
File: protpars.fprotpars
Protein parsimony algorithm, version 3.69.650
5 species, 10 sites
Name Sequences
---- ---------
Alpha ABCDEFGHIK
Beta ..--......
Gamma ?...S..*??
Delta CIK.......
Epsilon DIK.......
3 trees in all found
+-----------Beta
!
1 +--------Gamma
! !
+--2 +--Epsilon
! +--4
+--3 +--Delta
!
+-----Alpha
remember: (although rooted by outgroup) this is an unrooted tree!
requires a total of 14.000
steps in each position:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0! 3 1 5 3 2 0 0 2 0
10! 0
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
root 1 AN??EFGHIK
1 Beta maybe .B--......
[Part of this file has been deleted for brevity]
root 1 AN??EFGHIK
1 Beta maybe .B--......
1 2 maybe ..CD......
2 3 maybe ?.........
3 4 yes .IK.......
4 Epsilon maybe D.........
4 Delta yes C.........
3 Gamma yes ?B..S..*??
2 Alpha maybe .B........
+-----------Beta
!
1 +--Epsilon
! +-----4
! ! +--Delta
+--3
! +--Gamma
+-----2
+--Alpha
remember: (although rooted by outgroup) this is an unrooted tree!
requires a total of 14.000
steps in each position:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0! 3 1 5 3 2 0 0 2 0
10! 0
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
root 1 AN??EFGHIK
1 Beta maybe .B--......
1 3 yes ..?D......
3 4 yes ?IK.......
4 Epsilon maybe D.........
4 Delta yes C.........
3 2 yes ..C.......
2 Gamma yes ?B..S..*??
2 Alpha maybe .B........
File: protpars.treefile
(Beta,(Gamma,((Epsilon,Delta),Alpha)))[0.3333];
(Beta,(((Epsilon,Delta),Gamma),Alpha))[0.3333];
(Beta,((Epsilon,Delta),(Gamma,Alpha)))[0.3333];
Output files for usage example 3
File: protpars2.fprotpars
Protein parsimony algorithm, version 3.69.650
Data set # 1:
3 trees in all found
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 25.000
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 25.000
+--Epsilon
+-----4
[Part of this file has been deleted for brevity]
+--------Gamma
+--2
! ! +-----Epsilon
! +--4
1 ! +--Delta
! +--3
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 24.000
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 24.000
+--Epsilon
+-----4
! +--Delta
+--3
! ! +--Gamma
1 +-----2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 24.000
File: protpars2.treefile
((Gamma,((Epsilon,Delta),Beta)),Alpha)[0.3333];
((((Epsilon,Delta),Gamma),Beta),Alpha)[0.3333];
(((Epsilon,Delta),(Gamma,Beta)),Alpha)[0.3333];
((Gamma,(Delta,(Epsilon,Beta))),Alpha)[0.0667];
(((Epsilon,Gamma),(Delta,Beta)),Alpha)[0.0667];
((Gamma,((Epsilon,Delta),Beta)),Alpha)[0.0667];
((Epsilon,(Gamma,(Delta,Beta))),Alpha)[0.0667];
((Gamma,(Epsilon,(Delta,Beta))),Alpha)[0.0667];
(((Delta,Gamma),(Epsilon,Beta)),Alpha)[0.0667];
(((Delta,(Epsilon,Gamma)),Beta),Alpha)[0.0667];
((((Epsilon,Delta),Gamma),Beta),Alpha)[0.0667];
((Epsilon,((Delta,Gamma),Beta)),Alpha)[0.0667];
(((Epsilon,(Delta,Gamma)),Beta),Alpha)[0.0667];
((Delta,(Gamma,(Epsilon,Beta))),Alpha)[0.0667];
((Delta,((Epsilon,Gamma),Beta)),Alpha)[0.0667];
(((Epsilon,Delta),(Gamma,Beta)),Alpha)[0.0667];
((Delta,(Epsilon,(Gamma,Beta))),Alpha)[0.0667];
((Epsilon,(Delta,(Gamma,Beta))),Alpha)[0.0667];
((Gamma,(Delta,(Epsilon,Beta))),Alpha)[0.2000];
((Gamma,((Epsilon,Delta),Beta)),Alpha)[0.2000];
((Gamma,(Epsilon,(Delta,Beta))),Alpha)[0.2000];
((((Epsilon,Delta),Gamma),Beta),Alpha)[0.2000];
(((Epsilon,Delta),(Gamma,Beta)),Alpha)[0.2000];
Output files for usage example 4
File: protpars.fprotpars
Protein parsimony algorithm, version 3.69.650
Weights set # 1:
3 trees in all found
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 14.000
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 14.000
[Part of this file has been deleted for brevity]
+--Epsilon
+-----4
! +--Delta
+--3
! ! +--Gamma
1 +-----2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 2.000
+--------Delta
+--3
! ! +-----Epsilon
! +--4
1 ! +--Gamma
! +--2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 2.000
+--------Epsilon
+--4
! ! +-----Delta
! +--3
1 ! +--Gamma
! +--2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 2.000
File: protpars.treefile
((Gamma,((Epsilon,Delta),Beta)),Alpha)[0.3333];
((((Epsilon,Delta),Gamma),Beta),Alpha)[0.3333];
(((Epsilon,Delta),(Gamma,Beta)),Alpha)[0.3333];
((Gamma,(Delta,(Epsilon,Beta))),Alpha)[0.0667];
(((Epsilon,Gamma),(Delta,Beta)),Alpha)[0.0667];
((Gamma,((Epsilon,Delta),Beta)),Alpha)[0.0667];
((Epsilon,(Gamma,(Delta,Beta))),Alpha)[0.0667];
((Gamma,(Epsilon,(Delta,Beta))),Alpha)[0.0667];
(((Delta,Gamma),(Epsilon,Beta)),Alpha)[0.0667];
(((Delta,(Epsilon,Gamma)),Beta),Alpha)[0.0667];
((((Epsilon,Delta),Gamma),Beta),Alpha)[0.0667];
((Epsilon,((Delta,Gamma),Beta)),Alpha)[0.0667];
(((Epsilon,(Delta,Gamma)),Beta),Alpha)[0.0667];
((Delta,(Gamma,(Epsilon,Beta))),Alpha)[0.0667];
((Delta,((Epsilon,Gamma),Beta)),Alpha)[0.0667];
(((Epsilon,Delta),(Gamma,Beta)),Alpha)[0.0667];
((Delta,(Epsilon,(Gamma,Beta))),Alpha)[0.0667];
((Epsilon,(Delta,(Gamma,Beta))),Alpha)[0.0667];
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fcontrast.txt 0000664 0001750 0001750 00000043457 12171064331 016146 0000000 0000000 fcontrast
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Continuous character contrasts
Description
Reads a tree from a tree file, and a data set with continuous
characters data, and produces the independent contrasts for those
characters, for use in any multivariate statistics package. Will also
produce covariances, regressions and correlations between characters
for those contrasts. Can also correct for within-species sampling
variation when individual phenotypes are available within a population.
Algorithm
This program implements the contrasts calculation described in my 1985
paper on the comparative method (Felsenstein, 1985d). It reads in a
data set of the standard quantitative characters sort, and also a tree
from the treefile. It then forms the contrasts between species that,
according to that tree, are statistically independent. This is done for
each character. The contrasts are all standardized by branch lengths
(actually, square roots of branch lengths).
The method is explained in the 1985 paper. It assumes a Brownian motion
model. This model was introduced by Edwards and Cavalli-Sforza (1964;
Cavalli-Sforza and Edwards, 1967) as an approximation to the evolution
of gene frequencies. I have discussed (Felsenstein, 1973b, 1981c,
1985d, 1988b) the difficulties inherent in using it as a model for the
evolution of quantitative characters. Chief among these is that the
characters do not necessarily evolve independently or at equal rates.
This program allows one to evaluate this, if there is independent
information on the phylogeny. You can compute the variance of the
contrasts for each character, as a measure of the variance accumulating
per unit branch length. You can also test covariances of characters.
The statistics that are printed out include the covariances between all
pairs of characters, the regressions of each character on each other
(column j is regressed on row i), and the correlations between all
pairs of characters. In assessing degress of freedom it is important to
realize that each contrast was taken to have expectation zero, which is
known because each contrast could as easily have been computed xi-xj
instead of xj-xi. Thus there is no loss of a degree of freedom for
estimation of a mean. The degrees of freedom is thus the same as the
number of contrasts, namely one less than the number of species (tips).
If you feed these contrasts into a multivariate statistics program make
sure that it knows that each variable has expectation exactly zero.
Within-species variation
With the W option selected, CONTRAST analyzes data sets with variation
within species, using a model like that proposed by Michael Lynch
(1990). The method is described in vague terms in my book (Felsenstein,
2004, pp. 441). If you select the W option for within-species
variation, the data set should have this structure (on the left are the
data, on the right my comments:
10 5 number of species, number of characters
Alpha 2 name of 1st species, # of individuals
2.01 5.3 1.5 -3.41 0.3 data for individual #1
1.98 4.3 2.1 -2.98 0.45 data for individual #2
Gammarus 3 name of 2nd species, # of individuals
6.57 3.1 2.0 -1.89 0.6 data for individual #1
7.62 3.4 1.9 -2.01 0.7 data for individual #2
6.02 3.0 1.9 -2.03 0.6 data for individual #3
... (and so on)
The covariances, correlations, and regressions for the "additive"
(between-species evolutionary variation) and "environmental"
(within-species phenotypic variation) are printed out (the maximum
likelihood estimates of each). The program also estimates the
within-species phenotypic variation in the case where the
between-species evolutionary covariances are forced to be zero. The
log-likelihoods of these two cases are compared and a likelihood ratio
test (LRT) is carried out. The program prints the result of this test
as a chi-square variate, and gives the number of degrees of freedom of
the LRT. You have to look up the chi-square variable on a table of the
chi-square distribution. The A option is available (if the W option is
invoked) to allow you to turn off the doing of this test if you want
to.
The log-likelihood of the data under the models with and without
between-species For the moment the program cannot handle the case where
within-species variation is to be taken into account but where only
species means are available. (It can handle cases where some species
have only one member in their sample).
We hope to fix this soon. We are also on our way to incorporating
full-sib, half-sib, or clonal groups within species, so as to do one
analysis for within-species genetic and between-species phylogenetic
variation.
The data set used as an example below is the example from a paper by
Michael Lynch (1990), his characters having been log-transformed. In
the case where there is only one specimen per species, Lynch's model is
identical to our model of within-species variation (for multiple
individuals per species it is not a subcase of his model).
Usage
Here is a sample session with fcontrast
% fcontrast
Continuous character contrasts
Input file: contrast.dat
Phylip tree file (optional): contrast.tree
Phylip contrast program output file [contrast.fcontrast]:
Output written to file "contrast.fcontrast"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Continuous character contrasts
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] frequencies File containing one or more sets of data
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fcontrast] Phylip contrast program output
file
Additional (Optional) qualifiers (* if not always prompted):
-varywithin boolean [N] Within-population variation in data
* -[no]reg boolean [Y] Print out correlations and regressions
* -writecont boolean [N] Print out contrasts
* -[no]nophylo boolean [Y] LRT test of no phylogenetic component,
with and without VarA
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fcontrast reads continuous character data.
Continuous character data
The programs in this group use gene frequencies and quantitative
character values. One (CONTML) constructs maximum likelihood estimates
of the phylogeny, another (GENDIST) computes genetic distances for use
in the distance matrix programs, and the third (CONTRAST) examines
correlation of traits as they evolve along a given phylogeny.
When the gene frequencies data are used in CONTML or GENDIST, this
involves the following assumptions:
1. Different lineages evolve independently.
2. After two lineages split, their characters change independently.
3. Each gene frequency changes by genetic drift, with or without
mutation (this varies from method to method).
4. Different loci or characters drift independently.
How these assumptions affect the methods will be seen in my papers on
inference of phylogenies from gene frequency and continuous character
data (Felsenstein, 1973b, 1981c, 1985c).
The input formats are fairly similar to the discrete-character
programs, but with one difference. When CONTML is used in the
gene-frequency mode (its usual, default mode), or when GENDIST is used,
the first line contains the number of species (or populations) and the
number of loci and the options information. There then follows a line
which gives the numbers of alleles at each locus, in order. This must
be the full number of alleles, not the number of alleles which will be
input: i. e. for a two-allele locus the number should be 2, not 1.
There then follow the species (population) data, each species beginning
on a new line. The first 10 characters are taken as the name, and
thereafter the values of the individual characters are read
free-format, preceded and separated by blanks. They can go to a new
line if desired, though of course not in the middle of a number.
Missing data is not allowed - an important limitation. In the default
configuration, for each locus, the numbers should be the frequencies of
all but one allele. The menu option A (All) signals that the
frequencies of all alleles are provided in the input data -- the
program will then automatically ignore the last of them. So without the
A option, for a three-allele locus there should be two numbers, the
frequencies of two of the alleles (and of course it must always be the
same two!). Here is a typical data set without the A option:
5 3
2 3 2
Alpha 0.90 0.80 0.10 0.56
Beta 0.72 0.54 0.30 0.20
Gamma 0.38 0.10 0.05 0.98
Delta 0.42 0.40 0.43 0.97
Epsilon 0.10 0.30 0.70 0.62
whereas here is what it would have to look like if the A option were
invoked:
5 3
2 3 2
Alpha 0.90 0.10 0.80 0.10 0.10 0.56 0.44
Beta 0.72 0.28 0.54 0.30 0.16 0.20 0.80
Gamma 0.38 0.62 0.10 0.05 0.85 0.98 0.02
Delta 0.42 0.58 0.40 0.43 0.17 0.97 0.03
Epsilon 0.10 0.90 0.30 0.70 0.00 0.62 0.38
The first line has the number of species (or populations) and the
number of loci. The second line has the number of alleles for each of
the 3 loci. The species lines have names (filled out to 10 characters
with blanks) followed by the gene frequencies of the 2 alleles for the
first locus, the 3 alleles for the second locus, and the 2 alleles for
the third locus. You can start a new line after any of these allele
frequencies, and continue to give the frequencies on that line (without
repeating the species name).
If all alleles of a locus are given, it is important to have them add
up to 1. Roundoff of the frequencies may cause the program to conclude
that the numbers do not sum to 1, and stop with an error message.
While many compilers may be more tolerant, it is probably wise to make
sure that each number, including the first, is preceded by a blank, and
that there are digits both preceding and following any decimal points.
CONTML and CONTRAST also treat quantitative characters (the
continuous-characters mode in CONTML, which is option C). It is assumed
that each character is evolving according to a Brownian motion model,
at the same rate, and independently. In reality it is almost always
impossible to guarantee this. The issue is discussed at length in my
review article in Annual Review of Ecology and Systematics
(Felsenstein, 1988a), where I point out the difficulty of transforming
the characters so that they are not only genetically independent but
have independent selection acting on them. If you are going to use
CONTML to model evolution of continuous characters, then you should at
least make some attempt to remove genetic correlations between the
characters (usually all one can do is remove phenotypic correlations by
transforming the characters so that there is no within-population
covariance and so that the within-population variances of the
characters are equal -- this is equivalent to using Canonical
Variates). However, this will only guarantee that one has removed
phenotypic covariances between characters. Genetic covariances could
only be removed by knowing the coheritabilities of the characters,
which would require genetic experiments, and selective covariances
(covariances due to covariation of selection pressures) would require
knowledge of the sources and extent of selection pressure in all
variables.
CONTRAST is a program designed to infer, for a given phylogeny that is
provided to the program, the covariation between characters in a data
set. Thus we have a program in this set that allow us to take
information about the covariation and rates of evolution of characters
and make an estimate of the phylogeny (CONTML), and a program that
takes an estimate of the phylogeny and infers the variances and
covariances of the character changes. But we have no program that
infers both the phylogenies and the character covariation from the same
data set.
In the quantitative characters mode, a typical small data set would be:
5 6
Alpha 0.345 0.467 1.213 2.2 -1.2 1.0
Beta 0.457 0.444 1.1 1.987 -0.2 2.678
Gamma 0.6 0.12 0.97 2.3 -0.11 1.54
Delta 0.68 0.203 0.888 2.0 1.67
Epsilon 0.297 0.22 0.90 1.9 1.74
Note that in the latter case, there is no line giving the numbers of
alleles at each locus. In this latter case no square-root
transformation of the coordinates is done: each is assumed to give
directly the position on the Brownian motion scale.
For further discussion of options and modifiable constants in CONTML,
GENDIST, and CONTRAST see the documentation files for those programs.
Input files for usage example
File: contrast.dat
5 2
Homo 4.09434 4.74493
Pongo 3.61092 3.33220
Macaca 2.37024 3.36730
Ateles 2.02815 2.89037
Galago -1.46968 2.30259
File: contrast.tree
((((Homo:0.21,Pongo:0.21):0.28,Macaca:0.49):0.13,Ateles:0.62):0.38,Galago:1.00);
Output file format
fcontrast statistics that are printed out include the covariances
between all pairs of characters, the regressions of each character on
each other (column j is regressed on row i), and the correlations
between all pairs of characters. In assessing degress of freedom it is
important to realize that each contrast was taken to have expectation
zero, which is known because each contrast could as easily have been
computed xi-xj instead of xj-xi. Thus there is no loss of a degree of
freedom for estimation of a mean. The degrees of freedom is thus the
same as the number of contrasts, namely one less than the number of
species (tips). If you feed these contrasts into a multivariate
statistics program make sure that it knows that each variable has
expectation exactly zero. With the W option selected, the covariances,
correlations, and regressions for the "additive" (between-species
evolutionary variation) and "environmental" (within-species phenotypic
variation) are printed out (the maximum likelihood estimates of each).
The program also estimates the within-species phenotypic variation in
the case where the between-species evolutionary covariances are forced
to be zero. The log-likelihoods of these two cases are compared and a
likelihood ratio test (LRT) is carried out. The program prints the
result of this test as a chi-square variate, and gives the number of
degrees of freedom of the LRT. You have to look up the chi-square
variable on a table of the chi-square distribution. The A option is
available (if the W option is invoked) to allow you to turn off the
doing of this test if you want to.
Output files for usage example
File: contrast.fcontrast
Covariance matrix
---------- ------
3.9423 1.7028
1.7028 1.7062
Regressions (columns on rows)
----------- -------- -- -----
1.0000 0.4319
0.9980 1.0000
Correlations
------------
1.0000 0.6566
0.6566 1.0000
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
econtml Continuous character maximum likelihood method
econtrast Continuous character contrasts
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/Makefile.am 0000664 0001750 0001750 00000001160 11137346163 015426 0000000 0000000 pkgdata_DATA = fclique.txt \
fconsense.txt fcontml.txt fcontrast.txt \
fdiscboot.txt fdnacomp.txt fdnadist.txt fdnainvar.txt \
fdnaml.txt fdnamlk.txt fdnamove.txt fdnapars.txt fdnapenny.txt \
fdollop.txt fdolmove.txt fdolpenny.txt \
fdrawgram.txt fdrawtree.txt \
ffactor.txt ffitch.txt ffreqboot.txt \
fgendist.txt fkitsch.txt \
fmix.txt fmove.txt fneighbor.txt \
fpars.txt fpenny.txt fproml.txt fpromlk.txt \
fprotdist.txt fprotpars.txt \
frestboot.txt frestdist.txt frestml.txt fretree.txt \
fseqboot.txt fseqbootall.txt \
ftreedist.txt ftreedistpair.txt
pkgdatadir=$(prefix)/share/EMBOSS/doc/programs/text
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PHYLIPNEW-3.69.650/emboss_doc/text/fdnaml.txt 0000664 0001750 0001750 00000106414 12171064331 015375 0000000 0000000 fdnaml
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Estimate nucleotide phylogeny by maximum likelihood
Description
Estimates phylogenies from nucleotide sequences by maximum likelihood.
The model employed allows for unequal expected frequencies of the four
nucleotides, for unequal rates of transitions and transversions, and
for different (prespecified) rates of change in different categories of
sites, and also use of a Hidden Markov model of rates, with the program
inferring which sites have which rates. This also allows
gamma-distribution and gamma-plus-invariant sites distributions of
rates across sites.
Algorithm
This program implements the maximum likelihood method for DNA
sequences. The present version is faster than earlier versions of
DNAML. Details of the algorithm are published in the paper by
Felsenstein and Churchill (1996). The model of base substitution allows
the expected frequencies of the four bases to be unequal, allows the
expected frequencies of transitions and transversions to be unequal,
and has several ways of allowing different rates of evolution at
different sites.
The assumptions of the present model are:
1. Each site in the sequence evolves independently.
2. Different lineages evolve independently.
3. Each site undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of
occurrence) which we specify.
4. All relevant sites are included in the sequence, not just those
that have changed or those that are "phylogenetically informative".
5. A substitution consists of one of two sorts of events:
1. The first kind of event consists of the replacement of the
existing base by a base drawn from a pool of purines or a pool
of pyrimidines (depending on whether the base being replaced
was a purine or a pyrimidine). It can lead either to no change
or to a transition.
2. The second kind of event consists of the replacement of the
existing base by a base drawn at random from a pool of bases
at known frequencies, independently of the identity of the
base which is being replaced. This could lead either to a no
change, to a transition or to a transversion.
The ratio of the two purines in the purine replacement pool is
the same as their ratio in the overall pool, and similarly for
the pyrimidines.
The ratios of transitions to transversions can be set by the
user. The substitution process can be diagrammed as follows:
Suppose that you specified A, C, G, and T base frequencies of
0.24, 0.28, 0.27, and 0.21.
o First kind of event:
Determine whether the existing base is a purine or a
pyrimidine. Draw from the proper pool:
Purine pool: Pyrimidine pool:
| | | |
| 0.4706 A | | 0.5714 C |
| 0.5294 G | | 0.4286 T |
| (ratio is | | (ratio is |
| 0.24 : 0.27) | | 0.28 : 0.21) |
|_______________| |_______________|
o Second kind of event:
Draw from the overall pool:
| |
| 0.24 A |
| 0.28 C |
| 0.27 G |
| 0.21 T |
|__________________|
Note that if the existing base is, say, an A, the first kind of event
has a 0.4706 probability of "replacing" it by another A. The second
kind of event has a 0.24 chance of replacing it by another A. This
rather disconcerting model is used because it has nice mathematical
properties that make likelihood calculations far easier. A closely
similar, but not precisely identical model having different rates of
transitions and transversions has been used by Hasegawa et. al.
(1985b). The transition probability formulas for the current model were
given (with my permission) by Kishino and Hasegawa (1989). Another
explanation is available in the paper by Felsenstein and Churchill
(1996).
Note the assumption that we are looking at all sites, including those
that have not changed at all. It is important not to restrict attention
to some sites based on whether or not they have changed; doing that
would bias branch lengths by making them too long, and that in turn
would cause the method to misinterpret the meaning of those sites that
had changed.
This program uses a Hidden Markov Model (HMM) method of inferring
different rates of evolution at different sites. This was described in
a paper by me and Gary Churchill (1996). It allows us to specify to the
program that there will be a number of different possible evolutionary
rates, what the prior probabilities of occurrence of each is, and what
the average length of a patch of sites all having the same rate. The
rates can also be chosen by the program to approximate a Gamma
distribution of rates, or a Gamma distribution plus a class of
invariant sites. The program computes the the likelihood by summing it
over all possible assignments of rates to sites, weighting each by its
prior probability of occurrence.
For example, if we have used the C and A options (described below) to
specify that there are three possible rates of evolution, 1.0, 2.4, and
0.0, that the prior probabilities of a site having these rates are 0.4,
0.3, and 0.3, and that the average patch length (number of consecutive
sites with the same rate) is 2.0, the program will sum the likelihood
over all possibilities, but giving less weight to those that (say)
assign all sites to rate 2.4, or that fail to have consecutive sites
that have the same rate.
The Hidden Markov Model framework for rate variation among sites was
independently developed by Yang (1993, 1994, 1995). We have implemented
a general scheme for a Hidden Markov Model of rates; we allow the rates
and their prior probabilities to be specified arbitrarily by the user,
or by a discrete approximation to a Gamma distribution of rates (Yang,
1995), or by a mixture of a Gamma distribution and a class of invariant
sites.
This feature effectively removes the artificial assumption that all
sites have the same rate, and also means that we need not know in
advance the identities of the sites that have a particular rate of
evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each site (for example, we might want first,
second, and third codon positions in a protein coding sequence to be
three different categories. This is done with the categories input file
and the C option. We then specify (using the menu) the relative rates
of evolution of sites in the different categories. For example, we
might specify that first, second, and third positions evolve at
relative rates of 1.0, 0.8, and 2.7.
If both user-assigned rate categories and Hidden Markov Model rates are
allowed, the program assumes that the actual rate at a site is the
product of the user-assigned category rate and the Hidden Markov Model
regional rate. (This may not always make perfect biological sense: it
would be more natural to assume some upper bound to the rate, as we
have discussed in the Felsenstein and Churchill paper). Nevertheless
you may want to use both types of rate variation.
Usage
Here is a sample session with fdnaml
% fdnaml -printdata -ncategories 2 -categories "1111112222222" -rate "1.0 2.0" -
gammatype h -nhmmcategories 5 -hmmrates "0.264 1.413 3.596 7.086 12.641" -hmmpro
babilities "0.522 0.399 0.076 0.0036 0.000023" -lambda 1.5 -weight "011111111111
0"
Estimate nucleotide phylogeny by maximum likelihood
Input (aligned) nucleotide sequence set(s): dnaml.dat
Phylip tree file (optional):
Phylip dnaml program output file [dnaml.fdnaml]:
mulsets: false
datasets : 1
rctgry : true
gama : false
invar : false
numwts : 1
numseqs : 1
ctgry: true
categs : 2
rcategs : 5
auto_: false
freqsfrom : true
global : false
hypstate : false
improve : false
invar : false
jumble : false
njumble : 1
lngths : false
lambda : 1.000000
cv : 1.000000
freqa : 0.000000
freqc : 0.000000
freqg : 0.000000
freqt : 0.000000
outgrno : 1
outgropt: false
trout : true
ttratio : 2.000000
ttr : false
usertree : false
weights: true
printdata : true
progress : true
treeprint: true
interleaved : false
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "dnaml.fdnaml"
Tree also written onto file "dnaml.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Example 2
% fdnaml -printdata -njumble 3 -seed 3
Estimate nucleotide phylogeny by maximum likelihood
Input (aligned) nucleotide sequence set(s): dnaml.dat
Phylip tree file (optional):
Phylip dnaml program output file [dnaml.fdnaml]:
mulsets: false
datasets : 1
rctgry : false
gama : false
invar : false
numwts : 0
numseqs : 1
ctgry: false
categs : 1
rcategs : 1
auto_: false
freqsfrom : true
global : false
hypstate : false
improve : false
invar : false
jumble : true
njumble : 3
lngths : false
lambda : 1.000000
cv : 1.000000
freqa : 0.000000
freqc : 0.000000
freqg : 0.000000
freqt : 0.000000
outgrno : 1
outgropt: false
trout : true
ttratio : 2.000000
ttr : false
usertree : false
weights: false
printdata : true
progress : true
treeprint: true
interleaved : false
Adding species:
1. Delta
2. Epsilon
3. Alpha
4. Beta
5. Gamma
Adding species:
1. Beta
2. Epsilon
3. Delta
4. Alpha
5. Gamma
Adding species:
1. Epsilon
2. Alpha
3. Gamma
4. Delta
5. Beta
Output written to file "dnaml.fdnaml"
Tree also written onto file "dnaml.treefile"
Done.
Go to the output files for this example
Command line arguments
Estimate nucleotide phylogeny by maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fdnaml] Phylip dnaml program output file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
* -lengths boolean [N] Use branch lengths from user trees
-ttratio float [2.0] Transition/transversion ratio (Number
0.001 or more)
-[no]freqsfrom toggle [Y] Use empirical base frequencies from
seqeunce input
* -basefreq array [0.25 0.25 0.25 0.25] Base frequencies for A
C G T/U (use blanks to separate)
-gammatype menu [Constant rate] Rate variation among sites
(Values: g (Gamma distributed rates); i
(Gamma+invariant sites); h (User defined HMM
of rates); n (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ngammacat integer [1] Number of categories (1-9) (Integer from
1 to 9)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ninvarcat integer [1] Number of categories (1-9) including one
for invariant sites (Integer from 1 to 9)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -nhmmcategories integer [1] Number of HMM rate categories (Integer
from 1 to 9)
* -hmmrates array [1.0] HMM category rates
* -hmmprobabilities array [1.0] Probability for each HMM category
* -adjsite boolean [N] Rates at adjacent sites correlated
* -lambda float [1.0] Mean block length of sites having the
same rate (Number 1.000 or more)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]rough boolean [Y] Speedier but rougher analysis
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnaml] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-hypstate boolean [N] Reconstruct hypothetical sequence
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdnaml reads any normal sequence USAs.
Input files for usage example
File: dnaml.dat
5 13
Alpha AACGTGGCCAAAT
Beta AAGGTCGCCAAAC
Gamma CATTTCGTCACAA
Delta GGTATTTCGGCCT
Epsilon GGGATCTCGGCCC
Output file format
fdnaml output starts by giving the number of species, the number of
sites, and the base frequencies for A, C, G, and T that have been
specified. It then prints out the transition/transversion ratio that
was specified or used by default. It also uses the base frequencies to
compute the actual transition/transversion ratio implied by the
parameter.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of sites is printed, as well as
the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the menu
option to print them out, with the base sequences printed in groups of
ten bases along the lines of the Genbank and EMBL formats. The trees
found are printed as an unrooted tree topology (possibly rooted by
outgroup if so requested). The internal nodes are numbered arbitrarily
for the sake of identification. The number of trees evaluated so far
and the log likelihood of the tree are also given. Note that the trees
printed out have a trifurcation at the base. The branch lengths in the
diagram are roughly proportional to the estimated branch lengths,
except that very short branches are printed out at least three
characters in length so that the connections can be seen.
A table is printed showing the length of each tree segment (in units of
expected nucleotide substitutions per site), as well as (very) rough
confidence limits on their lengths. If a confidence limit is negative,
this indicates that rearrangement of the tree in that region is not
excluded, while if both limits are positive, rearrangement is still not
necessarily excluded because the variance calculation on which the
confidence limits are based results in an underestimate, which makes
the confidence limits too narrow.
In addition to the confidence limits, the program performs a crude
Likelihood Ratio Test (LRT) for each branch of the tree. The program
computes the ratio of likelihoods with and without this branch length
forced to zero length. This done by comparing the likelihoods changing
only that branch length. A truly correct LRT would force that branch
length to zero and also allow the other branch lengths to adjust to
that. The result would be a likelihood ratio closer to 1. Therefore the
present LRT will err on the side of being too significant. YOU ARE
WARNED AGAINST TAKING IT TOO SERIOUSLY. If you want to get a better
likelihood curve for a branch length you can do multiple runs with
different prespecified lengths for that branch, as discussed above in
the discussion of the L option.
One should also realize that if you are looking not at a
previously-chosen branch but at all branches, that you are seeing the
results of multiple tests. With 20 tests, one is expected to reach
significance at the P = .05 level purely by chance. You should
therefore use a much more conservative significance level, such as .05
divided by the number of tests. The significance of these tests is
shown by printing asterisks next to the confidence interval on each
branch length. It is important to keep in mind that both the confidence
limits and the tests are very rough and approximate, and probably
indicate more significance than they should. Nevertheless, maximum
likelihood is one of the few methods that can give you any indication
of its own error; most other methods simply fail to warn the user that
there is any error! (In fact, whole philosophical schools of
taxonomists exist whose main point seems to be that there isn't any
error, that the "most parsimonious" tree is the best tree by definition
and that's that).
The log likelihood printed out with the final tree can be used to
perform various likelihood ratio tests. One can, for example, compare
runs with different values of the expected transition/transversion
ratio to determine which value is the maximum likelihood estimate, and
what is the allowable range of values (using a likelihood ratio test,
which you will find described in mathematical statistics books). One
could also estimate the base frequencies in the same way. Both of
these, particularly the latter, require multiple runs of the program to
evaluate different possible values, and this might get expensive.
If the U (User Tree) option is used and more than one tree is supplied,
and the program is not told to assume autocorrelation between the rates
at different sites, the program also performs a statistical test of
each of these trees against the one with highest likelihood. If there
are two user trees, the test done is one which is due to Kishino and
Hasegawa (1989), a version of a test originally introduced by Templeton
(1983). In this implementation it uses the mean and variance of
log-likelihood differences between trees, taken across sites. If the
two trees' means are more than 1.96 standard deviations different then
the trees are declared significantly different. This use of the
empirical variance of log-likelihood differences is more robust and
nonparametric than the classical likelihood ratio test, and may to some
extent compensate for the any lack of realism in the model underlying
this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they introduced
a resampling method to make this correction. In the version used here
the variances and covariances of the sum of log likelihoods across
sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could have
been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the highest log-likelihood exceeds that
actually observed. Note that this sampling needs random numbers, and so
the program will prompt the user for a random number seed if one has
not already been supplied. With the two-tree KHT test no random numbers
are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one. However the
test is not available if we assume that there is autocorrelation of
rates at neighboring sites (option A) and is not done in those cases.
The branch lengths printed out are scaled in terms of expected numbers
of substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate
of change, averaged over all sites analyzed, is set to 1.0 if there are
multiple categories of sites. This means that whether or not there are
multiple categories of sites, the expected fraction of change for very
small branches is equal to the branch length. Of course, when a branch
is twice as long this does not mean that there will be twice as much
net change expected along it, since some of the changes occur in the
same site and overlie or even reverse each other. The branch length
estimates here are in terms of the expected underlying numbers of
changes. That means that a branch of length 0.26 is 26 times as long as
one which would show a 1% difference between the nucleotide sequences
at the beginning and end of the branch. But we would not expect the
sequences at the beginning and end of the branch to be 26% different,
as there would be some overlaying of changes.
Confidence limits on the branch lengths are also given. Of course a
negative value of the branch length is meaningless, and a confidence
limit overlapping zero simply means that the branch length is not
necessarily significantly different from zero. Because of limitations
of the numerical algorithm, branch length estimates of zero will often
print out as small numbers such as 0.00001. If you see a branch length
that small, it is really estimated to be of zero length. Note that
versions 2.7 and earlier of this program printed out the branch lengths
in terms of expected probability of change, so that they were scaled
differently.
Another possible source of confusion is the existence of negative
values for the log likelihood. This is not really a problem; the log
likelihood is not a probability but the logarithm of a probability.
When it is negative it simply means that the corresponding probability
is less than one (since we are seeing its logarithm). The log
likelihood is maximized by being made more positive: -30.23 is worse
than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what site categories
contributed the most to the final likelihood. This combination of HMM
rate categories need not have contributed a majority of the likelihood,
just a plurality. Still, it will be helpful as a view of where the
program infers that the higher and lower rates are. Note that the use
in this calculations of the prior probabilities of different rates, and
the average patch length, gives this inference a "smoothed" appearance:
some other combination of rates might make a greater contribution to
the likelihood, but be discounted because it conflicts with this prior
information. See the example output below to see what this printout of
rate categories looks like. A second list will also be printed out,
showing for each site which rate accounted for the highest fraction of
the likelihood. If the fraction of the likelihood accounted for is less
than 95%, a dot is printed instead.
Option 3 in the menu controls whether the tree is printed out into the
output file. This is on by default, and usually you will want to leave
it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees which
are written onto the output tree file, rather than the trees printed on
the output file. To keep the output file from becoming too large, it
may be wisest to use option 3 to prevent trees being printed onto the
output file.
Option 4 in the menu controls whether the tree estimated by the program
is written onto a tree file. The default name of this output tree file
is "outtree". If the U option is in effect, all the user-defined trees
are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated at
each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species
which are the input sequences). In that table, if a site has a base
which accounts for more than 95% of the likelihood, it is printed in
capital letters (A rather than a). If the best nucleotide accounts for
less than 50% of the likelihood, the program prints out an ambiguity
code (such as M for "A or C") for the set of nucleotides which, taken
together, account for more half of the likelihood. The ambiguity codes
are listed in the sequence programs documentation file. One limitation
of the current version of the program is that when there are multiple
HMM rates (option R) the reconstructed nucleotides are based on only
the single assignment of rates to sites which accounts for the largest
amount of the likelihood. Thus the assessment of 95% of the likelihood,
in tabulating the ancestral states, refers to 95% of the likelihood
that is accounted for by that particular combination of rates.
Output files for usage example
File: dnaml.fdnaml
Nucleic acid sequence Maximum Likelihood method, version 3.69.650
5 species, 13 sites
Site categories are:
1111112222 222
Sites are weighted as follows:
01111 11111 110
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
Empirical Base Frequencies:
A 0.23636
C 0.29091
G 0.25455
T(U) 0.21818
Transition/transversion ratio = 2.000000
State in HMM Rate of change Probability
1 0.264 0.522
2 1.413 0.399
3 3.596 0.076
4 7.086 0.0036
5 12.641 0.000023
Site category Rate of change
1 1.000
2 2.000
+Epsilon
+--------------------------------------------------------3
+--2 +-Delta
| |
| +Beta
|
1------Gamma
|
+-Alpha
remember: this is an unrooted tree!
Ln Likelihood = -57.87892
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
1 Alpha 0.26766 ( zero, 0.80513) *
1 2 0.04687 ( zero, 0.48388)
2 3 7.59821 ( zero, 22.01485) **
3 Epsilon 0.00006 ( zero, 0.46205)
3 Delta 0.27319 ( zero, 0.73380) **
2 Beta 0.00006 ( zero, 0.44052)
1 Gamma 0.95677 ( zero, 2.46186) **
* = significantly positive, P < 0.05
** = significantly positive, P < 0.01
Combination of categories that contributes the most to the likelihood:
1132121111 211
Most probable category at each site if > 0.95 probability ("." otherwise)
.......... ...
File: dnaml.treefile
(((Epsilon:0.00006,Delta:0.27319):7.59821,Beta:0.00006):0.04687,
Gamma:0.95677,Alpha:0.26766);
Output files for usage example 2
File: dnaml.fdnaml
Nucleic acid sequence Maximum Likelihood method, version 3.69.650
5 species, 13 sites
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
Empirical Base Frequencies:
A 0.24615
C 0.29231
G 0.24615
T(U) 0.21538
Transition/transversion ratio = 2.000000
+Epsilon
+--------------------------------------------1
+--2 +--------Delta
| |
| +Beta
|
3------------------------------Gamma
|
+-----Alpha
remember: this is an unrooted tree!
Ln Likelihood = -72.25088
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
3 Alpha 0.20745 ( zero, 0.56578)
3 2 0.09408 ( zero, 0.40912)
2 1 1.51296 ( zero, 3.31130) **
1 Epsilon 0.00006 ( zero, 0.34299)
1 Delta 0.28137 ( zero, 0.62654) **
2 Beta 0.00006 ( zero, 0.32900)
3 Gamma 1.01651 ( zero, 2.33178) **
* = significantly positive, P < 0.05
** = significantly positive, P < 0.01
File: dnaml.treefile
(((Epsilon:0.00006,Delta:0.28137):1.51296,Beta:0.00006):0.09408,
Gamma:1.01651,Alpha:0.20745);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
frestml Restriction site maximum likelihood method
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/fdrawgram.txt 0000664 0001750 0001750 00000026333 12171064331 016107 0000000 0000000 fdrawgram
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Plots a cladogram- or phenogram-like rooted tree diagram
Description
Plots rooted phylogenies, cladograms, circular trees and phenograms in
a wide variety of user-controllable formats. The program is interactive
and allows previewing of the tree on PC, Macintosh, or X Windows
screens, or on Tektronix or Digital graphics terminals. Final output
can be to a file formatted for one of the drawing programs, for a
ray-tracing or VRML browser, or one at can be sent to a laser printer
(such as Postscript or PCL-compatible printers), on graphics screens or
terminals, on pen plotters or on dot matrix printers capable of
graphics.
Similar to DRAWTREE but plots rooted phylogenies.
Algorithm
DRAWGRAM interactively plots a cladogram- or phenogram-like rooted tree
diagram, with many options including orientation of tree and branches,
style of tree, label sizes and angles, tree depth, margin sizes, stem
lengths, and placement of nodes in the tree. Particularly if you can
use your computer to preview the plot, you can very effectively adjust
the details of the plotting to get just the kind of plot you want.
To understand the working of DRAWGRAM and DRAWTREE, you should first
read the Tree Drawing Programs web page in this documentation.
As with DRAWTREE, to run DRAWGRAM you need a compiled copy of the
program, a font file, and a tree file. The tree file has a default name
of intree. The font file has a default name of "fontfile". If there is
no file of that name, the program will ask you for the name of a font
file (we provide ones that have the names font1 through font6). Once
you decide on a favorite one of these, you could make a copy of it and
call it fontfile, and it will then be used by default. Note that the
program will get confused if the input tree file has the number of
trees on the first line of the file, so that numbr may have to be
removed.
Usage
Here is a sample session with fdrawgram
% fdrawgram -previewer n
Plots a cladogram- or phenogram-like rooted tree diagram
Phylip tree file: drawgram.tree
Phylip drawgram output file [drawgram.fdrawgram]:
DRAWGRAM from PHYLIP version 3.69.650
Reading tree ...
Tree has been read.
Loading the font ....
Font loaded.
Writing plot file ...
Plot written to file "drawgram.fdrawgram"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Plots a cladogram- or phenogram-like rooted tree diagram
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-plotfile] outfile [*.fdrawgram] Phylip drawgram output file
Additional (Optional) qualifiers (* if not always prompted):
-[no]grows boolean [Y] Tree grows horizontally
-style menu [c] Tree style output (Values: c (cladogram
(v-shaped)); p (phenogram (branches are
square)); v (curvogram (branches are 1/4 out
of an ellipse)); e (eurogram (branches
angle outward, then up)); s (swooporam
(branches curve outward then reverse)); o
(circular tree))
-plotter menu [l] Plotter or printer the tree will be
drawn on (Values: l (Postscript printer file
format); m (PICT format (for drawing
programs)); j (HP 75 DPI Laserjet PCL file
format); s (HP 150 DPI Laserjet PCL file
format); y (HP 300 DPI Laserjet PCL file
format); w (MS-Windows Bitmap); f (FIG 2.0
drawing program format); a (Idraw drawing
program format); z (VRML Virtual Reality
Markup Language file); n (PCX 640x350 file
format (for drawing programs)); p (PCX
800x600 file format (for drawing programs));
q (PCX 1024x768 file format (for drawing
programs)); k (TeKtronix 4010 graphics
terminal); x (X Bitmap format); v (POVRAY 3D
rendering program file); r (Rayshade 3D
rendering program file); h (Hewlett-Packard
pen plotter (HPGL file format)); d (DEC
ReGIS graphics (VT240 terminal)); e (Epson
MX-80 dot-matrix printer); c
(Prowriter/Imagewriter dot-matrix printer);
t (Toshiba 24-pin dot-matrix printer); o
(Okidata dot-matrix printer); b (Houston
Instruments plotter); u (other (one you have
inserted code for)))
-previewer menu [x] Previewing device (Values: n (Will not
be previewed); I i (MSDOS graphics screen
m:Macintosh screens); x (X Windows display);
w (MS Windows display); k (TeKtronix 4010
graphics terminal); d (DEC ReGIS graphics
(VT240 terminal)); o (Other (one you have
inserted code for)))
-lengths boolean [N] Use branch lengths from user trees
* -labelrotation float [90.0] Angle of labels (0 degrees is
horizontal for a tree growing vertically)
(Number from 0.000 to 360.000)
-[no]rescaled toggle [Y] Automatically rescale branch lengths
* -bscale float [1.0] Centimeters per unit branch length
(Any numeric value)
-treedepth float [0.53] Depth of tree as fraction of its
breadth (Number from 0.100 to 100.000)
-stemlength float [0.05] Stem length as fraction of tree depth
(Number from 0.010 to 100.000)
-nodespace float [0.3333] Character height as fraction of tip
spacing (Number from 0.100 to 100.000)
-nodeposition menu [c] Position of interior nodes (Values: i
(Intermediate between their immediate
descendants); w (Weighted average of tip
positions); c (Centered among their ultimate
descendants); n (Innermost of immediate
descendants); v (So tree is v shaped))
* -xmargin float [1.65] Horizontal margin (cm) (Number 0.100
or more)
* -ymargin float [2.16] Vertical margin (cm) (Number 0.100 or
more)
* -xrayshade float [1.65] Horizontal margin (pixels) for
Rayshade output (Number 0.100 or more)
* -yrayshade float [2.16] Vertical margin (pixels) for Rayshade
output (Number 0.100 or more)
-paperx float [20.63750] Paper width (Any numeric value)
-papery float [26.98750] Paper height (Number 0.100 or
more)
-pagesheight float [1] Number of trees across height of page
(Number 1.000 or more)
-pageswidth float [1] Number of trees across width of page
(Number 1.000 or more)
-hpmargin float [0.41275] Horizontal overlap (cm) (Number
0.001 or more)
-vpmargin float [0.53975] Vertical overlap (cm) (Number
0.001 or more)
Advanced (Unprompted) qualifiers:
-fontfile string [font1] Fontfile name (Any string)
Associated qualifiers:
"-plotfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
fdrawgram reads ...
Input files for usage example
File: drawgram.tree
(Delta,(Epsilon,(Gamma,(Beta,Alpha))));
Output file format
fdrawgram output ...
Output files for usage example
Graphics File: drawgram.fdrawgram
[fdrawgram results]
Data files
The font file has a default name of "fontfile". If there is no file of
that name, the program will ask you for the name of a font file (we
provide ones that have the names font1 through font6). Once you decide
on a favorite one of these, you could make a copy of it and call it
fontfile, and it will then be used by default.
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
fdrawtree Plots an unrooted tree diagram
fretree Interactive tree rearrangement
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
PHYLIPNEW-3.69.650/emboss_doc/text/frestml.txt 0000664 0001750 0001750 00000031744 12171064331 015613 0000000 0000000 frestml
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Restriction site maximum likelihood method
Description
Estimation of phylogenies by maximum likelihood using restriction sites
data (not restriction fragments but presence/absence of individual
sites). It employs the Jukes-Cantor symmetrical model of nucleotide
change, which does not allow for differences of rate between
transitions and transversions. This program is very slow.
Algorithm
This program implements a maximum likelihood method for restriction
sites data (not restriction fragment data). This program is one of the
slowest programs in this package, and can be very tedious to run. It is
possible to have the program search for the maximum likelihood tree. It
will be more practical for some users (those that do not have fast
machines) to use the U (User Tree) option, which takes less run time,
optimizing branch lengths and computing likelihoods for particular tree
topologies suggested by the user. The model used here is essentially
identical to that used by Smouse and Li (1987) who give explicit
expressions for computing the likelihood for three-species trees. It
does not place prior probabilities on trees as they do. The present
program extends their approach to multiple species by a technique
which, while it does not give explicit expressions for likelihoods,
does enable their computation and the iterative improvement of branch
lengths. It also allows for multiple restriction enzymes. The algorithm
has been described in a paper (Felsenstein, 1992). Another relevant
paper is that of DeBry and Slade (1985).
The assumptions of the present model are:
1. Each restriction site evolves independently.
2. Different lineages evolve independently.
3. Each site undergoes substitution at an expected rate which we
specify.
4. Substitutions consist of replacement of a nucleotide by one of the
other three nucleotides, chosen at random.
Note that if the existing base is, say, an A, the chance of it being
replaced by a G is 1/3, and so is the chance that it is replaced by a
T. This means that there can be no difference in the (expected) rate of
transitions and transversions. Users who are upset at this might ponder
the fact that a version allowing different rates of transitions and
transversions would run an estimated 16 times slower. If it also
allowed for unequal frequencies of the four bases, it would run about
300,000 times slower! For the moment, until a better method is
available, I guess I'll stick with this one!
Subject to these assumptions, the program is an approximately correct
maximum likelihood method.
Usage
Here is a sample session with frestml
% frestml
Restriction site maximum likelihood method
Input file: restml.dat
Phylip tree file (optional):
Phylip restml program output file [restml.frestml]:
numseqs: 1
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "restml.frestml"
Tree also written onto file "restml.treefile"
Done.
Go to the input files for this example
Go to the output files for this example
Command line arguments
Restriction site maximum likelihood method
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-data] discretestates File containing one or more sets of
restriction data
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.frestml] Phylip restml program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]allsites boolean [Y] All sites detected
* -lengths boolean [N] Use lengths from user trees
-sitelength integer [6] Site length (Integer from 1 to 8)
* -global boolean [N] Global rearrangements
* -[no]rough boolean [Y] Speedier but rougher analysis
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.frestml] Phylip tree output file
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Input file format
frestml input is fairly standard, with one addition. As usual the first
line of the file gives the number of species and the number of sites,
but there is also a third number, which is the number of different
restriction enzymes that were used to detect the restriction sites.
Thus a data set with 10 species and 35 different sites, representing
digestion with 4 different enzymes, would have the first line of the
data file look like this:
10 35 4
The first line of the data file will also contain a letter W following
these numbers (and separated from them by a space) if the Weights
option is being used. As with all programs using the weights option, a
line or lines must then follow, before the data, with the weights for
each site.
The site data are in standard form. Each species starts with a species
name whose maximum length is given by the constant "nmlngth" (whose
value in the program as distributed is 10 characters). The name should,
as usual, be padded out to that length with blanks if necessary. The
sites data then follows, one character per site (any blanks will be
skipped and ignored). Like the DNA and protein sequence data, the
restriction sites data may be either in the "interleaved" form or the
"sequential" form. Note that if you are analyzing restriction sites
data with the programs DOLLOP or MIX or other discrete character
programs, at the moment those programs do not use the "aligned" or
"interleaved" data format. Therefore you may want to avoid that format
when you have restriction sites data that you will want to feed into
those programs.
The presence of a site is indicated by a "+" and the absence by a "-".
I have also allowed the use of "1" and "0" as synonyms for "+" and "-",
for compatibility with MIX and DOLLOP which do not allow "+" and "-".
If the presence of the site is unknown (for example, if the DNA
containing it has been deleted so that one does not know whether it
would have contained the site) then the state "?" can be used to
indicate that the state of this site is unknown.
User-defined trees may follow the data in the usual way. The trees must
be unrooted, which means that at their base they must have a
trifurcation.
Input files for usage example
File: restml.dat
5 13 2
Alpha ++-+-++--+++-
Beta ++++--+--+++-
Gamma -+--+-++-+-++
Delta ++-+----++---
Epsilon ++++----++---
Output file format
frestml outputs a graph to the specified graphics device. outputs a
report format file. The default format is ...
Output files for usage example
File: restml.frestml
Restriction site Maximum Likelihood method, version 3.69.650
Recognition sequences all 6 bases long
Sites absent from all species are assumed to have been omitted
+----Gamma
|
| +Beta
1--2
| | +Epsilon
| +--3
| +Delta
|
+Alpha
remember: this is an unrooted tree!
Ln Likelihood = -40.47082
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
1 Gamma 0.10794 ( 0.01144, 0.21872) **
1 2 0.01244 ( zero, 0.04712)
2 Beta 0.00100 ( zero, infinity)
2 3 0.05878 ( zero, 0.12675) **
3 Epsilon 0.00022 ( zero, infinity)
3 Delta 0.01451 ( zero, 0.04459) **
1 Alpha 0.01244 ( zero, 0.04717)
* = significantly positive, P < 0.05
** = significantly positive, P < 0.01
File: restml.treefile
(Gamma:0.10794,(Beta:0.00100,(Epsilon:0.00022,
Delta:0.01451):0.05878):0.01244,Alpha:0.01244);
Data files
None
Notes
None.
References
None.
Warnings
None.
Diagnostic Error Messages
None.
Exit status
It always exits with status 0.
Known bugs
None.
See also
Program name Description
distmat Create a distance matrix from a multiple sequence alignment
ednacomp DNA compatibility algorithm
ednadist Nucleic acid sequence distance matrix program
ednainvar Nucleic acid sequence invariants method
ednaml Phylogenies from nucleic acid maximum likelihood
ednamlk Phylogenies from nucleic acid maximum likelihood with clock
ednapars DNA parsimony algorithm
ednapenny Penny algorithm for DNA
eprotdist Protein distance algorithm
eprotpars Protein parsimony algorithm
erestml Restriction site maximum likelihood method
eseqboot Bootstrapped sequences algorithm
fdiscboot Bootstrapped discrete sites algorithm
fdnacomp DNA compatibility algorithm
fdnadist Nucleic acid sequence distance matrix program
fdnainvar Nucleic acid sequence invariants method
fdnaml Estimate nucleotide phylogeny by maximum likelihood
fdnamlk Estimates nucleotide phylogeny by maximum likelihood
fdnamove Interactive DNA parsimony
fdnapars DNA parsimony algorithm
fdnapenny Penny algorithm for DNA
fdolmove Interactive Dollo or polymorphism parsimony
ffreqboot Bootstrapped genetic frequencies algorithm
fproml Protein phylogeny by maximum likelihood
fpromlk Protein phylogeny by maximum likelihood
fprotdist Protein distance algorithm
fprotpars Protein parsimony algorithm
frestboot Bootstrapped restriction sites algorithm
frestdist Calculate distance matrix from restriction sites or fragments
fseqboot Bootstrapped sequences algorithm
fseqbootall Bootstrapped sequences algorithm
Author(s)
This program is an EMBOSS conversion of a program written by Joe
Felsenstein as part of his PHYLIP package.
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
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PHYLIPNEW-3.69.650/emboss_doc/html/ffitch.html 0000664 0001750 0001750 00000053203 12171064331 015501 0000000 0000000
EMBOSS: ffitch
Please help by correcting and extending the Wiki pages.
Function
Fitch-Margoliash and least-squares distance methods
Description
Estimates phylogenies from distance matrix data under the "additive
tree model" according to which the distances are expected to equal the
sums of branch lengths between the species. Uses the Fitch-Margoliash
criterion and some related least squares criteria, or the Minimum
Evolution distance matrix method. Does not assume an evolutionary
clock. This program will be useful with distances computed from
molecular sequences, restriction sites or fragments distances, with
DNA hybridization measurements, and with genetic distances computed
from gene frequencies.
Algorithm
The programs FITCH, KITSCH, and NEIGHBOR are for dealing with data
which comes in the form of a matrix of pairwise distances between all
pairs of taxa, such as distances based on molecular sequence data,
gene frequency genetic distances, amounts of DNA hybridization, or
immunological distances. In analyzing these data, distance matrix
programs implicitly assume that:
Each distance is measured independently from the others: no item of
data contributes to more than one distance.
The distance between each pair of taxa is drawn from a distribution
with an expectation which is the sum of values (in effect amounts of
evolution) along the tree from one tip to the other. The variance of
the distribution is proportional to a power p of the expectation.
These assumptions can be traced in the least squares methods of
programs FITCH and KITSCH but it is not quite so easy to see them in
operation in the Neighbor-Joining method of NEIGHBOR, where the
independence assumptions is less obvious.
THESE TWO ASSUMPTIONS ARE DUBIOUS IN MOST CASES: independence will not
be expected to be true in most kinds of data, such as genetic
distances from gene frequency data. For genetic distance data in which
pure genetic drift without mutation can be assumed to be the mechanism
of change CONTML may be more appropriate. However, FITCH, KITSCH, and
NEIGHBOR will not give positively misleading results (they will not
make a statistically inconsistent estimate) provided that additivity
holds, which it will if the distance is computed from the original
data by a method which corrects for reversals and parallelisms in
evolution. If additivity is not expected to hold, problems are more
severe. A short discussion of these matters will be found in a review
article of mine (1984a). For detailed, if sometimes irrelevant,
controversy see the papers by Farris (1981, 1985, 1986) and myself
(1986, 1988b).
For genetic distances from gene frequencies, FITCH, KITSCH, and
NEIGHBOR may be appropriate if a neutral mutation model can be assumed
and Nei's genetic distance is used, or if pure drift can be assumed
and either Cavalli-Sforza's chord measure or Reynolds, Weir, and
Cockerham's (1983) genetic distance is used. However, in the latter
case (pure drift) CONTML should be better.
Restriction site and restriction fragment data can be treated by
distance matrix methods if a distance such as that of Nei and Li
(1979) is used. Distances of this sort can be computed in PHYLIp by
the program RESTDIST.
For nucleic acid sequences, the distances computed in DNADIST allow
correction for multiple hits (in different ways) and should allow one
to analyse the data under the presumption of additivity. In all of
these cases independence will not be expected to hold. DNA
hybridization and immunological distances may be additive and
independent if transformed properly and if (and only if) the standards
against which each value is measured are independent. (This is rarely
exactly true).
FITCH and the Neighbor-Joining option of NEIGHBOR fit a tree which has
the branch lengths unconstrained. KITSCH and the UPGMA option of
NEIGHBOR, by contrast, assume that an "evolutionary clock" is valid,
according to which the true branch lengths from the root of the tree
to each tip are the same: the expected amount of evolution in any
lineage is proportional to elapsed time.
Usage
Here is a sample session with ffitch
% ffitch
Fitch-Margoliash and least-squares distance methods
Phylip distance matrix file: fitch.dat
Phylip tree file (optional):
Phylip fitch program output file [fitch.ffitch]:
Adding species:
1. Bovine
2. Mouse
3. Gibbon
4. Orang
5. Gorilla
6. Chimp
7. Human
Output written to file "fitch.ffitch"
Tree also written onto file "fitch.treefile"
Done.
Fitch-Margoliash and least-squares distance methods
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-datafile] distances File containing one or more distance
matrices
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.ffitch] Phylip fitch program output file
Additional (Optional) qualifiers (* if not always prompted):
-matrixtype menu [s] Type of input data matrix (Values: s
(Square); u (Upper triangular); l (Lower
triangular))
-minev boolean [N] Minimum evolution
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-power float [2.0] Power (Any numeric value)
* -lengths boolean [N] Use branch lengths from user trees
* -negallowed boolean [N] Negative branch lengths allowed
* -global boolean [N] Global rearrangements
-replicates boolean [N] Subreplicates
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.ffitch] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-datafile] (Parameter 1)
distances
File containing one or more distance matrices
Distance matrix
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip fitch program output file
Output file
<*>.ffitch
Additional (Optional) qualifiers
-matrixtype
list
Type of input data matrix
s
(Square)
u
(Upper triangular)
l
(Lower triangular)
s
-minev
boolean
Minimum evolution
Boolean value Yes/No
No
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-power
float
Power
Any numeric value
2.0
-lengths
boolean
Use branch lengths from user trees
Boolean value Yes/No
No
-negallowed
boolean
Negative branch lengths allowed
Boolean value Yes/No
No
-global
boolean
Global rearrangements
Boolean value Yes/No
No
-replicates
boolean
Subreplicates
Boolean value Yes/No
No
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.ffitch
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
ffitch output consists of an unrooted tree and the lengths of
the interior segments. The sum of squares is printed out, and if P =
2.0 Fitch and Margoliash's "average percent standard deviation" is
also computed and printed out. This is the sum of squares, divided by
N-2, and then square-rooted and then multiplied by 100 (n is the
number of species on the tree):
APSD = ( SSQ / (N-2) )1/2 x 100.
where N is the total number of off-diagonal distance measurements that
are in the (square) distance matrix. If the S (subreplication) option
is in force it is instead the sum of the numbers of replicates in all
the non-diagonal cells of the distance matrix. But if the L or R
option is also in effect, so that the distance matrix read in is
lower- or upper-triangular, then the sum of replicates is only over
those cells actually read in. If S is not in force, the number of
replicates in each cell is assumed to be 1, so that N is n(n-1), where
n is the number of species. The APSD gives an indication of the
average percentage error. The number of trees examined is also printed
out.
Output files for usage example
File: fitch.ffitch
7 Populations
Fitch-Margoliash method version 3.69.650
__ __ 2
\ \ (Obs - Exp)
Sum of squares = /_ /_ ------------
2
i j Obs
Negative branch lengths not allowed
+---------------------------------------------Mouse
!
! +------Human
! +--5
! +-4 +--------Chimp
! ! !
! +--3 +---------Gorilla
! ! !
1------------------------2 +-----------------Orang
! !
! +---------------------Gibbon
!
+------------------------------------------------------Bovine
remember: this is an unrooted tree!
Sum of squares = 0.01375
Average percent standard deviation = 1.85418
Between And Length
------- --- ------
1 Mouse 0.76985
1 2 0.41983
2 3 0.04986
3 4 0.02121
4 5 0.03695
5 Human 0.11449
5 Chimp 0.15471
4 Gorilla 0.15680
3 Orang 0.29209
2 Gibbon 0.35537
1 Bovine 0.91675
Please help by correcting and extending the Wiki pages.
Function
Penny algorithm, branch-and-bound
Description
Finds all most parsimonious phylogenies for discrete-character data
with two states, for the Wagner, Camin-Sokal, and mixed parsimony
criteria using the branch-and-bound method of exact search. May be
impractical (depending on the data) for more than 10-11 species.
Algorithm
PENNY is a program that will find all of the most parsimonious trees
implied by your data. It does so not by examining all possible trees,
but by using the more sophisticated "branch and bound" algorithm, a
standard computer science search strategy first applied to
phylogenetic inference by Hendy and Penny (1982). (J. S. Farris
[personal communication, 1975] had also suggested that this strategy,
which is well-known in computer science, might be applied to
phylogenies, but he did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem
of finding these has been shown (Graham and Foulds, 1982; Day, 1983)
to be NP-complete, which is equivalent to saying that there is no fast
algorithm that is guaranteed to solve the problem in all cases (for a
discussion of NP-completeness, see the Scientific American article by
Lewis and Papadimitriou, 1978). The result is that this program,
despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs in
the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of
someone who can let a microcomputer grind all night than for someone
who has the "benefit" of paying for time on the campus mainframe
computer). IT IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE
PROGRAM WILL TAKE ON YOUR DATA. This can be done by running it on
subsets of the species, increasing the number of species in the run
until you either are able to treat the full data set or know that the
program will take unacceptably long on it. (Making a plot of the
logarithm of run time against species number may help to project run
times).
The Algorithm
The search strategy used by PENNY starts by making a tree consisting
of the first two species (the first three if the tree is to be
unrooted). Then it tries to add the next species in all possible
places (there are three of these). For each of the resulting trees it
evaluates the number of steps. It adds the next species to each of
these, again in all possible spaces. If this process would continue it
would simply generate all possible trees, of which there are a very
large number even when the number of species is moderate (34,459,425
with 10 species). Actually it does not do this, because the trees are
generated in a particular order and some of them are never generated.
Actually the order in which trees are generated is not quite as
implied above, but is a "depth-first search". This means that first
one adds the third species in the first possible place, then the
fourth species in its first possible place, then the fifth and so on
until the first possible tree has been produced. Its number of steps
is evaluated. Then one "backtracks" by trying the alternative
placements of the last species. When these are exhausted one tries the
next placement of the next-to-last species. The order of placement in
a depth-first search is like this for a four-species case (parentheses
enclose monophyletic groups):
Make tree of first two species (A,B)
Add C in first place ((A,B),C)
Add D in first place (((A,D),B),C)
Add D in second place ((A,(B,D)),C)
Add D in third place (((A,B),D),C)
Add D in fourth place ((A,B),(C,D))
Add D in fifth place (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place (((A,D),C),B)
Add D in second place ((A,(C,D)),B)
Add D in third place (((A,C),D),B)
Add D in fourth place ((A,C),(B,D))
Add D in fifth place (((A,C),B),D)
Add C in third place (A,(B,C))
Add D in first place ((A,D),(B,C))
Add D in second place (A,((B,D),C))
Add D in third place (A,(B,(C,D)))
Add D in fourth place (A,((B,C),D))
Add D in fifth place ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species rooted
bifurcating trees, each exactly once (the parentheses each enclose a
monophyletic group). As displayed above, the backtracking depth-first
search algorithm is just another way of producing all possible trees
one at a time. The branch and bound algorithm consists of this with
one change. As each tree is constructed, including the partial trees
such as (A,(B,C)), its number of steps is evaluated. In addition a
prediction is made as to how many steps will be added, at a minimum,
as further species are added.
This is done by counting how many binary characters which are
invariant in the data up the species most recently added will
ultimately show variation when further species are added. Thus if 20
characters vary among species A, B, and C and their root, and if tree
((A,C),B) requires 24 steps, then if there are 8 more characters which
will be seen to vary when species D is added, we can immediately say
that no matter how we add D, the resulting tree can have no less than
24 + 8 = 32 steps. The point of all this is that if a previously-found
tree such as ((A,B),(C,D)) required only 30 steps, then we know that
there is no point in even trying to add D to ((A,C),B). We have
computed the bound that enables us to cut off a whole line of inquiry
(in this case five trees) and avoid going down that particular branch
any farther.
The branch-and-bound algorithm thus allows us to find all most
parsimonious trees without generating all possible trees. How much of
a saving this is depends strongly on the data. For very clean (nearly
"Hennigian") data, it saves much time, but on very messy data it will
still take a very long time.
The algorithm in the program differs from the one outlined here in
some essential details: it investigates possibilities in the order of
their apparent promise. This applies to the order of addition of
species, and to the places where they are added to the tree. After the
first two-species tree is constructed, the program tries adding each
of the remaining species in turn, each in the best possible place it
can find. Whichever of those species adds (at a minimum) the most
additional steps is taken to be the one to be added next to the
tree. When it is added, it is added in turn to places which cause the
fewest additional steps to be added. This sounds a bit complex, but it
is done with the intention of eliminating regions of the search of all
possible trees as soon as possible, and lowering the bound on tree
length as quickly as possible.
The program keeps a list of all the most parsimonious trees found so
far. Whenever it finds one that has fewer steps than these, it clears
out the list and restarts the list with that tree. In the process the
bound tightens and fewer possibilities need be investigated. At the
end the list contains all the shortest trees. These are then printed
out. It should be mentioned that the program CLIQUE for finding all
largest cliques also works by branch-and-bound. Both problems are
NP-complete but for some reason CLIQUE runs far faster. Although their
worst-case behavior is bad for both programs, those worst cases occur
far more frequently in parsimony problems than in compatibility
problems.
Controlling Run Times
Among the quantities available to be set at the beginning of a run of
PENNY, two (howoften and howmany) are of particular importance. As
PENNY goes along it will keep count of how many trees it has
examined. Suppose that howoften is 100 and howmany is 1000, the
default settings. Every time 100 trees have been examined, PENNY will
print out a line saying how many multiples of 100 trees have now been
examined, how many steps the most parsimonious tree found so far has,
how many trees of with that number of steps have been found, and a
very rough estimate of what fraction of all trees have been looked at
so far.
When the number of these multiples printed out reaches the number
howmany (say 1000), the whole algorithm aborts and prints out that it
has not found all most parsimonious trees, but prints out what is has
got so far anyway. These trees need not be any of the most
parsimonious trees: they are simply the most parsimonious ones found
so far. By setting the product (howoften times howmany) large you can
make the algorithm less likely to abort, but then you risk getting
bogged down in a gigantic computation. You should adjust these
constants so that the program cannot go beyond examining the number of
trees you are reasonably willing to wait for. In their initial setting
the program will abort after looking at 100,000 trees. Obviously you
may want to adjust howoften in order to get more or fewer lines of
intermediate notice of how many trees have been looked at so far. Of
course, in small cases you may never even reach the first multiple of
howoften and nothing will be printed out except some headings and then
the final trees.
The indication of the approximate percentage of trees searched so far
will be helpful in judging how much farther you would have to go to
get the full search. Actually, since that fraction is the fraction of
the set of all possible trees searched or ruled out so far, and since
the search becomes progressively more efficient, the approximate
fraction printed out will usually be an underestimate of how far along
the program is, sometimes a serious underestimate.
A constant that affects the result is "maxtrees", which controls the
maximum number of trees that can be stored. Thus if "maxtrees" is 25,
and 32 most parsimonious trees are found, only the first 25 of these
are stored and printed out. If "maxtrees" is increased, the program
does not run any slower but requires a little more intermediate
storage space. I recommend that "maxtrees" be kept as large as you
can, provided you are willing to look at an output with that many
trees on it! Initially, "maxtrees" is set to 100 in the distribution
copy.
Methods and Options
The counting of the length of trees is done by an algorithm nearly
identical to the corresponding algorithms in MIX, and thus the
remainder of this document will be nearly identical to the MIX
document. MIX is a general parsimony program which carries out the
Wagner and Camin-Sokal parsimony methods in mixture, where each
character can have its method specified. The program defaults to
carrying out Wagner parsimony.
The Camin-Sokal parsimony method explains the data by assuming that
changes 0 --> 1 are allowed but not changes 1 --> 0. Wagner parsimony
allows both kinds of changes. (This under the assumption that 0 is the
ancestral state, though the program allows reassignment of the
ancestral state, in which case we must reverse the state numbers 0 and
1 throughout this discussion). The criterion is to find the tree which
requires the minimum number of changes. The Camin-Sokal method is due
to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
(1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
Ancestral states are known (Camin-Sokal) or unknown (Wagner).
Different characters evolve independently.
Different lineages evolve independently.
Changes 0 --> 1 are much more probable than changes 1 --> 0
(Camin-Sokal) or equally probable (Wagner).
Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the group
in question.
Other kinds of evolutionary event such as retention of polymorphism
are far less probable than 0 --> 1 changes.
Rates of evolution in different lineages are sufficiently low that two
changes in a long segment of the tree are far less probable than one
change in a short segment.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b), but also read the exchange
between Felsenstein and Sober (1986).
Usage
Here is a sample session with fpenny
% fpenny
Penny algorithm, branch-and-bound
Phylip character discrete states file: penny.dat
Phylip penny program output file [penny.fpenny]:
How many
trees looked Approximate
at so far Length of How many percentage
(multiples shortest tree trees this long searched
of 100): found so far found so far so far
---------- ------------ ------------ ------------
1 8.00000 1 6.67
2 8.00000 3 20.00
3 8.00000 3 53.33
4 8.00000 3 93.33
Output written to file "penny.fpenny"
Trees also written onto file "penny.treefile"
Penny algorithm, branch-and-bound
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-outfile] outfile [*.fpenny] Phylip penny program output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Phylip weights file (optional)
-ancfile properties Phylip ancestral states file (optional)
-mixfile properties Phylip mix output file (optional)
-method menu [Wagner] Choose the method to use (Values:
Wag (Wagner); Cam (Camin-Sokal); Mix
(Mixed))
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-howmany integer [1000] How many groups of trees (Any integer
value)
-howoften integer [100] How often to report, in trees (Any
integer value)
-simple boolean Branch and bound is simple
-threshold float [$(infile.discretesize)] Threshold value
(Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fpenny] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print out steps in each site
-ancseq boolean [N] Print states at all nodes of tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
File containing one or more data sets
Discrete states file
[-outfile] (Parameter 2)
outfile
Phylip penny program output file
Output file
<*>.fpenny
Additional (Optional) qualifiers
-weights
properties
Phylip weights file (optional)
Property value(s)
-ancfile
properties
Phylip ancestral states file (optional)
Property value(s)
-mixfile
properties
Phylip mix output file (optional)
Property value(s)
-method
list
Choose the method to use
Wag
(Wagner)
Cam
(Camin-Sokal)
Mix
(Mixed)
Wagner
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-howmany
integer
How many groups of trees
Any integer value
1000
-howoften
integer
How often to report, in trees
Any integer value
100
-simple
boolean
Branch and bound is simple
Boolean value Yes/No
No
-threshold
float
Threshold value
Number 1.000 or more
$(infile.discretesize)
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fpenny
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-stepbox
boolean
Print out steps in each site
Boolean value Yes/No
No
-ancseq
boolean
Print states at all nodes of tree
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fpenny reads discrste character data.
(0,1) Discrete character data
These programs are intended for the use of morphological
systematists who are dealing with discrete characters, or by molecular
evolutionists dealing with presence-absence data on restriction
sites. One of the programs (PARS) allows multistate characters, with
up to 8 states, plus the unknown state symbol "?". For the others, the
characters are assumed to be coded into a series of (0,1) two-state
characters. For most of the programs there are two other states
possible, "P", which stands for the state of Polymorphism for both
states (0 and 1), and "?", which stands for the state of ignorance: it
is the state "unknown", or "does not apply". The state "P" can also be
denoted by "B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding
a multistate character into a series of two-state (0,1)
characters. Suppose we had a character with four states whose
character-state tree had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We
can represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE,
DOLPENNY and DOLBOOT the multistate recoding does not necessarily work
properly, as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected
in a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for
unordered character states.
fpenny output is standard: a set of trees, which will be
printed as rooted or unrooted depending on which is appropriate, and
if the user elects to see them, tables of the number of changes of
state required in each character. If the Wagner option is in force for
a character, it may not be possible to unambiguously locate the places
on the tree where the changes occur, as there may be multiple
possibilities. A table is available to be printed out after each tree,
showing for each branch whether there are known to be changes in the
branch, and what the states are inferred to have been at the top end
of the branch. If the inferred state is a "?" there will be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand.
If the Camin-Sokal parsimony method (option C or S) is invoked and the
A option is also used, then the program will infer, for any character
whose ancestral state is unknown ("?") whether the ancestral state 0
or 1 will give the fewest state changes. If these are tied, then it
may not be possible for the program to infer the state in the internal
nodes, and these will all be printed as ".". If this has happened and
you want to know more about the states at the internal nodes, you will
find helpful to use MOVE to display the tree and examine its interior
states, as the algorithm in MOVE shows all that can be known in this
case about the interior states, including where there is and is not
amibiguity. The algorithm in PENNY gives up more easily on displaying
these states.
If the A option is not used, then the program will assume 0 as the
ancestral state for those characters following the Camin-Sokal method,
and will assume that the ancestral state is unknown for those
characters following Wagner parsimony. If any characters have unknown
ancestral states, and if the resulting tree is rooted (even by
outgroup), a table will be printed out showing the best guesses of
which are the ancestral states in each character. You will find it
useful to understand the difference between the Camin-Sokal parsimony
criterion with unknown ancestral state and the Wagner parsimony
criterion.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is
needed when we use the trees to make a consensus tree of the results
of bootstrapping or jackknifing, to avoid overrepresenting replicates
that find many tied trees.
Output files for usage example
File: penny.fpenny
Penny algorithm, version 3.69.650
branch-and-bound to find all most parsimonious trees
Wagner parsimony method
requires a total of 8.000
3 trees in all found
+-----------------Alpha1
!
! +--------Alpha2
--1 !
! +-----4 +--Epsilon
! ! ! +--6
! ! +--5 +--Delta
+--2 !
! +-----Gamma1
!
! +--Beta2
+-----------3
+--Beta1
remember: this is an unrooted tree!
+-----------------Alpha1
!
--1 +--------------Alpha2
! !
! ! +--Epsilon
+--2 +--6
! +-----5 +--Delta
! ! !
+--4 +-----Gamma1
!
! +--Beta2
+--------3
+--Beta1
remember: this is an unrooted tree!
+-----------------Alpha1
!
! +-----Alpha2
--1 +--------2
! ! ! +--Beta2
! ! +--3
+--4 +--Beta1
!
! +--Epsilon
! +--6
+--------5 +--Delta
!
+-----Gamma1
remember: this is an unrooted tree!
Please help by correcting and extending the Wiki pages.
Function
Plots an unrooted tree diagram
Description
Plots unrooted phylogenies, cladograms, circular trees and phenograms in
a wide variety of user-controllable formats. The program is
interactive and allows previewing of the tree on PC, Macintosh, or X
Windows screens, or on Tektronix or Digital graphics terminals. Final
output can be to a file formatted for one of the drawing programs, for
a ray-tracing or VRML browser, or one at can be sent to a laser
printer (such as Postscript or PCL-compatible printers), on graphics
screens or terminals, on pen plotters or on dot matrix printers
capable of graphics.
Similar to DRAWGRAM but plots unrooted phylogenies.
Algorithm
DRAWTREE interactively plots an unrooted tree diagram, with many
options including orientation of tree and branches, label sizes and
angles, margin sizes. Particularly if you can use your computer screen
to preview the plot, you can very effectively adjust the details of
the plotting to get just the kind of plot you want.
To understand the working of DRAWGRAM and DRAWTREE, you should first
read the Tree Drawing Programs web page in this documentation.
As with DRAWGRAM, to run DRAWTREE you need a compiled copy of the
program, a font file, and a tree file. The tree file has a default
name of intree. The font file has a default name of "fontfile". If
there is no file of that name, the program will ask you for the name
of a font file (we provide ones that have the names font1 through
font6). Once you decide on a favorite one of these, you could make a
copy of it and call it fontfile, and it will then be used by
default. Note that the program will get confused if the input tree
file has the number of trees on the first line of the file, so that
number may have to be removed.
Usage
Here is a sample session with fdrawtree
% fdrawtree -previewer n
Plots an unrooted tree diagram
Phylip tree file: drawgram.tree
Phylip drawtree output file [drawgram.fdrawtree]:
DRAWTREE from PHYLIP version 3.69.650
Reading tree ...
Tree has been read.
Loading the font ...
Font loaded.
Writing plot file ...
Plot written to file "drawgram.fdrawtree"
Done.
Plots an unrooted tree diagram
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-plotfile] outfile [*.fdrawtree] Phylip drawtree output file
Additional (Optional) qualifiers (* if not always prompted):
-plotter menu [l] Plotter or printer the tree will be
drawn on (Values: l (Postscript printer file
format); m (PICT format (for drawing
programs)); j (HP Laserjet 75 dpi PCL file
format); s (HP Laserjet 150 dpi PCL file
format); y (HP Laserjet 300 dpi PCL file
format); w (MS-Windows Bitmap); f (FIG 2.0
drawing program format); a (Idraw drawing
program format); z (VRML Virtual Reality
Markup Language file); n (PCX 640x350 file
format (for drawing programs)); p (PCX
800x600 file format (for drawing programs));
q (PCX 1024x768 file format (for drawing
programs)); k (TeKtronix 4010 graphics
terminal); x (X Bitmap format); v (POVRAY 3D
rendering program file); r (Rayshade 3D
rendering program file); h (Hewlett-Packard
pen plotter (HPGL file format)); d (DEC
ReGIS graphics (VT240 terminal)); e (Epson
MX-80 dot-matrix printer); c
(Prowriter/Imagewriter dot-matrix printer);
t (Toshiba 24-pin dot-matrix printer); o
(Okidata dot-matrix printer); b (Houston
Instruments plotter); u (other (one you have
inserted code for)))
-previewer menu [x] Previewing device (Values: n (Will not
be previewed); I i (MSDOS graphics screen
m:Macintosh screens); x (X Windows display);
w (MS Windows display); k (TeKtronix 4010
graphics terminal); d (DEC ReGIS graphics
(VT240 terminal)); o (Other (one you have
inserted code for)))
-iterate menu [e] Iterate to improve tree (Values: n (No);
e (Equal-Daylight algorithm); b (n-Body
algorithm))
-lengths boolean [N] Use branch lengths from user trees
-labeldirection menu [m] Label direction (Values: a (along); f
(fixed); r (radial); m (middle))
-treeangle float [90.0] Angle the tree is to be plotted
(Number from -360.000 to 360.000)
-arc float [360] Degrees the arc should occupy (Number
from 0.000 to 360.000)
* -labelrotation float [90.0] Angle of labels (0 degrees is
horizontal for a tree growing vertically)
(Number from 0.000 to 360.000)
-[no]rescaled toggle [Y] Automatically rescale branch lengths
* -bscale float [1.0] Centimeters per unit branch length
(Any numeric value)
-treedepth float [0.53] Depth of tree as fraction of its
breadth (Number from 0.100 to 100.000)
* -xmargin float [1.65] Horizontal margin (cm) (Number 0.100
or more)
* -ymargin float [2.16] Vertical margin (cm) (Number 0.100 or
more)
* -xrayshade float [1.65] Horizontal margin (pixels) (Number
0.100 or more)
* -yrayshade float [2.16] Vertical margin (pixels) (Number
0.100 or more)
-paperx float [20.63750] Paper width (Any numeric value)
-papery float [26.98750] Paper height (Number 0.100 or
more)
-pagesheight float [1] Number of trees across height of page
(Number 1.000 or more)
-pageswidth float [1] Number of trees across width of page
(Number 1.000 or more)
-hpmargin float [0.41275] Horizontal overlap (cm) (Number
0.001 or more)
-vpmargin float [0.53975] Vertical overlap (cm) (Number
0.001 or more)
Advanced (Unprompted) qualifiers:
-fontfile string [font1] Fontfile name (Any string)
Associated qualifiers:
"-plotfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-intreefile] (Parameter 1)
tree
Phylip tree file
Phylogenetic tree
[-plotfile] (Parameter 2)
outfile
Phylip drawtree output file
Output file
<*>.fdrawtree
Additional (Optional) qualifiers
-plotter
list
Plotter or printer the tree will be drawn on
l
(Postscript printer file format)
m
(PICT format (for drawing programs))
j
(HP Laserjet 75 dpi PCL file format)
s
(HP Laserjet 150 dpi PCL file format)
y
(HP Laserjet 300 dpi PCL file format)
w
(MS-Windows Bitmap)
f
(FIG 2.0 drawing program format)
a
(Idraw drawing program format)
z
(VRML Virtual Reality Markup Language file)
n
(PCX 640x350 file format (for drawing programs))
p
(PCX 800x600 file format (for drawing programs))
q
(PCX 1024x768 file format (for drawing programs))
k
(TeKtronix 4010 graphics terminal)
x
(X Bitmap format)
v
(POVRAY 3D rendering program file)
r
(Rayshade 3D rendering program file)
h
(Hewlett-Packard pen plotter (HPGL file format))
d
(DEC ReGIS graphics (VT240 terminal))
e
(Epson MX-80 dot-matrix printer)
c
(Prowriter/Imagewriter dot-matrix printer)
t
(Toshiba 24-pin dot-matrix printer)
o
(Okidata dot-matrix printer)
b
(Houston Instruments plotter)
u
(other (one you have inserted code for))
l
-previewer
list
Previewing device
n
(Will not be previewed)
I i
(MSDOS graphics screen m:Macintosh screens)
x
(X Windows display)
w
(MS Windows display)
k
(TeKtronix 4010 graphics terminal)
d
(DEC ReGIS graphics (VT240 terminal))
o
(Other (one you have inserted code for))
x
-iterate
list
Iterate to improve tree
n
(No)
e
(Equal-Daylight algorithm)
b
(n-Body algorithm)
e
-lengths
boolean
Use branch lengths from user trees
Boolean value Yes/No
No
-labeldirection
list
Label direction
a
(along)
f
(fixed)
r
(radial)
m
(middle)
m
-treeangle
float
Angle the tree is to be plotted
Number from -360.000 to 360.000
90.0
-arc
float
Degrees the arc should occupy
Number from 0.000 to 360.000
360
-labelrotation
float
Angle of labels (0 degrees is horizontal for a tree growing vertically)
Number from 0.000 to 360.000
90.0
-[no]rescaled
toggle
Automatically rescale branch lengths
Toggle value Yes/No
Yes
-bscale
float
Centimeters per unit branch length
Any numeric value
1.0
-treedepth
float
Depth of tree as fraction of its breadth
Number from 0.100 to 100.000
0.53
-xmargin
float
Horizontal margin (cm)
Number 0.100 or more
1.65
-ymargin
float
Vertical margin (cm)
Number 0.100 or more
2.16
-xrayshade
float
Horizontal margin (pixels)
Number 0.100 or more
1.65
-yrayshade
float
Vertical margin (pixels)
Number 0.100 or more
2.16
-paperx
float
Paper width
Any numeric value
20.63750
-papery
float
Paper height
Number 0.100 or more
26.98750
-pagesheight
float
Number of trees across height of page
Number 1.000 or more
1
-pageswidth
float
Number of trees across width of page
Number 1.000 or more
1
-hpmargin
float
Horizontal overlap (cm)
Number 0.001 or more
0.41275
-vpmargin
float
Vertical overlap (cm)
Number 0.001 or more
0.53975
Advanced (Unprompted) qualifiers
-fontfile
string
Fontfile name
Any string
font1
Associated qualifiers
"-plotfile" associated outfile qualifiers
-odirectory2 -odirectory_plotfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fdrawtree input ...
Input files for usage example
File: drawgram.tree
(Delta,(Epsilon,(Gamma,(Beta,Alpha))));
Output file format
fdrawtree
outputs ...
Output files for usage example
Graphics File: drawgram.fdrawtree
Data files
The font file has a default name of "fontfile". If there is no file of
that name, the program will ask you for the name of a font file (we
provide ones that have the names font1 through font6). Once you decide
on a favorite one of these, you could make a copy of it and call it
fontfile, and it will then be used by default.
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped discrete sites algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of
the package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
SEQBOOT is a general bootstrapping and data set translation tool. It
is intended to allow you to generate multiple data sets that are
resampled versions of the input data set. Since almost all programs in
the package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or
permuted. SEQBOOT can handle molecular sequences, binary characters,
restriction sites, or gene frequencies. It can also convert data sets
between Sequential and Interleaved format, and into the NEXUS format
or into a new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of
interest. For example, if you were using DNAPARS you would first run
SEQBOOT and make a file with 100 bootstrapped data sets. Then you
would give this file the proper name to have it be the input file for
DNAPARS. Running DNAPARS with the M (Multiple Data Sets) menu choice
and informing it to expect 100 data sets, you would generate a big
output file as well as a treefile with the trees from the 100 data
sets. This treefile could be renamed so that it would serve as the
input for CONSENSE. When CONSENSE is run the majority rule consensus
tree will result, showing the outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this
package. The same steps are necessary with all of them. Doing things
this way some of the intermediate files (the tree file from the
DNAPARS run, for example) can be used to summarize the results of the
bootstrap in other ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add
one extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me (Felsenstein,
1985b; see also Penny and Hendy, 1985). It involves creating a new
data set by sampling N characters randomly with replacement, so that
the resulting data set has the same size as the original, but some
characters have been left out and others are duplicated. The random
variation of the results from analyzing these bootstrapped data sets
can be shown statistically to be typical of the variation that you
would get from collecting new data sets. The method assumes that the
characters evolve independently, an assumption that may not be
realistic for many kinds of data.
The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial Bootstrap
method, and Shimodaira's (2002) AU method, both of which correct the
bias of bootstrap P values.
Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct for
it by samopling, not individual characters, but blocks of adjacent
characters. This is called a block bootstrap and was introduced by
Künsch (1989). If the correlations are believed to extend over some
number of characters, you choose a block size, B, that is larger than
this, and choose N/B blocks of size B. In its implementation here the
block bootstrap "wraps around" at the end of the characters (so that
if a block starts in the last B-1 characters, it continues by wrapping
around to the first character after it reaches the last
character). Note also that if you have a DNA sequence data set of an
exon of a coding region, you can ensure that equal numbers of first,
second, and third coding positions are sampled by using the block
bootstrap with B = 3.
Partial block-bootstrapping. Similar to partial bootstrapping except
sampling blocks rather than single characters.
Delete-half-jackknifing.. This alternative to the bootstrap involves
sampling a random half of the characters, and including them in the
data but dropping the others. The resulting data sets are half the
size of the original, and no characters are duplicated. The random
variation from doing this should be very similar to that obtained from
the bootstrap. The method is advocated by Wu (1986). It was mentioned
by me in my bootstrapping paper (Felsenstein, 1985b), and has been
available for many years in this program as an option. Note that, for
the present, block-jackknifing is not available, because I cannot
figure out how to do it straightforwardly when the block size is not a
divisor of the number of characters.
Delete-fraction jackknifing. Jackknifing is advocated by Farris
et. al. (1996) but as deleting a fraction 1/e (1/2.71828). This
retains too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it is
made available here as an option, with the user asked to supply the
fraction of characters that are to be retained.
Permuting species within characters. This method of resampling (well,
OK, it may not be best to call it resampling) was introduced by Archie
(1989) and Faith (1990; see also Faith and Cranston, 1991). It
involves permuting the columns of the data matrix separately. This
produces data matrices that have the same number and kinds of
characters but no taxonomic structure. It is used for different
purposes than the bootstrap, as it tests not the variation around an
estimated tree but the hypothesis that there is no taxonomic structure
in the data: if a statistic such as number of steps is significantly
smaller in the actual data than it is in replicates that are permuted,
then we can argue that there is some taxonomic structure in the data
(though perhaps it might be just the presence of aa pair of sibling
species).
Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For many
methods of tree inference this will make no difference to the outcome
(unless one has rates of evolution correlated among adjacent
sites). It is included as a possible step in carrying out a
permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so as
to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
Rewriting. This is not a resampling or permutation method: it simply
rewrites the data set into a different format. That format can be the
PHYLIP format. For molecular sequences and discrete morphological
character it can also be the NEXUS format. For molecular sequences one
other format is available, a new (and nonstandard) XML format of our
own devising. When the PHYLIP format is chosen the data set is
coverted between Interleaved and Sequential format. If it was read in
as Interleaved sequences, it will be written out as Sequential format,
and vice versa. The NEXUS format for molecular sequences is always
written as interleaved sequences. The XML format is different from
(though similar to) a number of other XML sequence alignment
formats. An example will be found below. Here is a table to links to
those other XML alignment formats:
Andrew Rambaut's
BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html
and http://evolve.zoo.ox.ac.uk/beast/referenindex.html
A format for alignments. There
is also a format for phylogenies
described there.
MSAML M
http://xml.coverpages.org/msaml-desc-dec.html
Defined by Paul Gordon of
University of Calgary. See his
big list of molecular biology
XML projects.
BSML
http://www.bsml.org/resources/default.asp
Bioinformatic Sequence
Markup Language
includes a multiple sequence
alignment XML format
Usage
Here is a sample session with fdiscboot
% fdiscboot -seed 3
Bootstrapped discrete sites algorithm
Input file: discboot.dat
Phylip seqboot_disc program output file [discboot.fdiscboot]:
Phylip ancestor data output file (optional) [discboot.ancfile]:
Phylip mix data output file (optional) [discboot.mixfile]:
Phylip factor data output file (optional) [discboot.factfile]:
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "discboot.fdiscboot"
Done.
Bootstrapped discrete sites algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates (no help text) discretestates value
[-outfile] outfile [*.fdiscboot] Phylip seqboot_disc program
output file
[-outancfile] outfile [*.fdiscboot] Phylip ancestor data output
file (optional)
[-outmixfile] outfile [*.fdiscboot] Phylip mix data output file
(optional)
[-outfactfile] outfile [*.fdiscboot] Phylip factor data output file
(optional)
Additional (Optional) qualifiers (* if not always prompted):
-mixfile properties File of mixtures
-ancfile properties File of ancestors
-weights properties Weights file
-factorfile properties Factors file
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -morphseqtype menu [p] Output format (Values: p (PHYLIP); n
(NEXUS))
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outancfile" associated qualifiers
-odirectory3 string Output directory
"-outmixfile" associated qualifiers
-odirectory4 string Output directory
"-outfactfile" associated qualifiers
-odirectory5 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
(no help text) discretestates value
Discrete states file
[-outfile] (Parameter 2)
outfile
Phylip seqboot_disc program output file
Output file
<*>.fdiscboot
[-outancfile] (Parameter 3)
outfile
Phylip ancestor data output file (optional)
Output file
<*>.fdiscboot
[-outmixfile] (Parameter 4)
outfile
Phylip mix data output file (optional)
Output file
<*>.fdiscboot
[-outfactfile] (Parameter 5)
outfile
Phylip factor data output file (optional)
Output file
<*>.fdiscboot
Additional (Optional) qualifiers
-mixfile
properties
File of mixtures
Property value(s)
-ancfile
properties
File of ancestors
Property value(s)
-weights
properties
Weights file
Property value(s)
-factorfile
properties
Factors file
Property value(s)
-test
list
Choose test
b
(Bootstrap)
j
(Jackknife)
c
(Permute species for each character)
o
(Permute character order)
s
(Permute within species)
r
(Rewrite data)
b
-regular
toggle
Altered sampling fraction
Toggle value Yes/No
No
-fracsample
float
Samples as percentage of sites
Number from 0.100 to 100.000
100.0
-morphseqtype
list
Output format
p
(PHYLIP)
n
(NEXUS)
p
-blocksize
integer
Block size for bootstraping
Integer 1 or more
1
-reps
integer
How many replicates
Integer 1 or more
100
-justweights
list
Write out datasets or just weights
d
(Datasets)
w
(Weights)
d
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-printdata
boolean
Print out the data at start of run
Boolean value Yes/No
No
-[no]dotdiff
boolean
Use dot-differencing
Boolean value Yes/No
Yes
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
"-outancfile" associated outfile qualifiers
-odirectory3 -odirectory_outancfile
string
Output directory
Any string
"-outmixfile" associated outfile qualifiers
-odirectory4 -odirectory_outmixfile
string
Output directory
Any string
"-outfactfile" associated outfile qualifiers
-odirectory5 -odirectory_outfactfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped sequences algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of
the package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
SEQBOOT is a general bootstrapping and data set translation tool. It
is intended to allow you to generate multiple data sets that are
resampled versions of the input data set. Since almost all programs in
the package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or
permuted. SEQBOOT can handle molecular sequences, binary characters,
restriction sites, or gene frequencies. It can also convert data sets
between Sequential and Interleaved format, and into the NEXUS format
or into a new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of
interest. For example, if you were using DNAPARS you would first run
SEQBOOT and make a file with 100 bootstrapped data sets. Then you
would give this file the proper name to have it be the input file for
DNAPARS. Running DNAPARS with the M (Multiple Data Sets) menu choice
and informing it to expect 100 data sets, you would generate a big
output file as well as a treefile with the trees from the 100 data
sets. This treefile could be renamed so that it would serve as the
input for CONSENSE. When CONSENSE is run the majority rule consensus
tree will result, showing the outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this
package. The same steps are necessary with all of them. Doing things
this way some of the intermediate files (the tree file from the
DNAPARS run, for example) can be used to summarize the results of the
bootstrap in other ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add
one extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me (Felsenstein,
1985b; see also Penny and Hendy, 1985). It involves creating a new
data set by sampling N characters randomly with replacement, so that
the resulting data set has the same size as the original, but some
characters have been left out and others are duplicated. The random
variation of the results from analyzing these bootstrapped data sets
can be shown statistically to be typical of the variation that you
would get from collecting new data sets. The method assumes that the
characters evolve independently, an assumption that may not be
realistic for many kinds of data.
The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial Bootstrap
method, and Shimodaira's (2002) AU method, both of which correct the
bias of bootstrap P values.
Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct for
it by samopling, not individual characters, but blocks of adjacent
characters. This is called a block bootstrap and was introduced by
Künsch (1989). If the correlations are believed to extend over some
number of characters, you choose a block size, B, that is larger than
this, and choose N/B blocks of size B. In its implementation here the
block bootstrap "wraps around" at the end of the characters (so that
if a block starts in the last B-1 characters, it continues by wrapping
around to the first character after it reaches the last
character). Note also that if you have a DNA sequence data set of an
exon of a coding region, you can ensure that equal numbers of first,
second, and third coding positions are sampled by using the block
bootstrap with B = 3.
Partial block-bootstrapping. Similar to partial bootstrapping except
sampling blocks rather than single characters.
Delete-half-jackknifing.. This alternative to the bootstrap involves
sampling a random half of the characters, and including them in the
data but dropping the others. The resulting data sets are half the
size of the original, and no characters are duplicated. The random
variation from doing this should be very similar to that obtained from
the bootstrap. The method is advocated by Wu (1986). It was mentioned
by me in my bootstrapping paper (Felsenstein, 1985b), and has been
available for many years in this program as an option. Note that, for
the present, block-jackknifing is not available, because I cannot
figure out how to do it straightforwardly when the block size is not a
divisor of the number of characters.
Delete-fraction jackknifing. Jackknifing is advocated by Farris
et. al. (1996) but as deleting a fraction 1/e (1/2.71828). This
retains too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it is
made available here as an option, with the user asked to supply the
fraction of characters that are to be retained.
Permuting species within characters. This method of resampling (well,
OK, it may not be best to call it resampling) was introduced by Archie
(1989) and Faith (1990; see also Faith and Cranston, 1991). It
involves permuting the columns of the data matrix separately. This
produces data matrices that have the same number and kinds of
characters but no taxonomic structure. It is used for different
purposes than the bootstrap, as it tests not the variation around an
estimated tree but the hypothesis that there is no taxonomic structure
in the data: if a statistic such as number of steps is significantly
smaller in the actual data than it is in replicates that are permuted,
then we can argue that there is some taxonomic structure in the data
(though perhaps it might be just the presence of aa pair of sibling
species).
Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For many
methods of tree inference this will make no difference to the outcome
(unless one has rates of evolution correlated among adjacent
sites). It is included as a possible step in carrying out a
permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so as
to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
Rewriting. This is not a resampling or permutation method: it simply
rewrites the data set into a different format. That format can be the
PHYLIP format. For molecular sequences and discrete morphological
character it can also be the NEXUS format. For molecular sequences one
other format is available, a new (and nonstandard) XML format of our
own devising. When the PHYLIP format is chosen the data set is
coverted between Interleaved and Sequential format. If it was read in
as Interleaved sequences, it will be written out as Sequential format,
and vice versa. The NEXUS format for molecular sequences is always
written as interleaved sequences. The XML format is different from
(though similar to) a number of other XML sequence alignment
formats. An example will be found below. Here is a table to links to
those other XML alignment formats:
Andrew Rambaut's
BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html
and http://evolve.zoo.ox.ac.uk/beast/referenindex.html
A format for alignments. There
is also a format for phylogenies
described there.
MSAML M
http://xml.coverpages.org/msaml-desc-dec.html
Defined by Paul Gordon of
University of Calgary. See his
big list of molecular biology
XML projects.
BSML
http://www.bsml.org/resources/default.asp
Bioinformatic Sequence
Markup Language
includes a multiple sequence
alignment XML format
Usage
Here is a sample session with fseqbootall
% fseqbootall -seed 3
Bootstrapped sequences algorithm
Input (aligned) sequence set: seqboot.dat
Phylip seqboot program output file [seqboot.fseqbootall]:
bootstrap: true
jackknife: false
permute: false
lockhart: false
ild: false
justwts: false
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "seqboot.fseqbootall"
Done.
Bootstrapped sequences algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infilesequences] seqset (Aligned) sequence set filename and optional
format, or reference (input USA)
[-outfile] outfile [*.fseqbootall] Phylip seqboot program
output file
Additional (Optional) qualifiers (* if not always prompted):
-categories properties File of input categories
-mixfile properties File of mixtures
-ancfile properties File of ancestors
-weights properties Weights file
-factorfile properties Factors file
-datatype menu [s] Choose the datatype (Values: s
(Molecular sequences); m (Discrete
Morphology); r (Restriction Sites); g (Gene
Frequencies))
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -rewriteformat menu [p] Output format (Values: p (PHYLIP); n
(NEXUS); x (XML))
* -seqtype menu [d] Output format (Values: d (dna); p
(protein); r (rna))
* -morphseqtype menu [p] Output format (Values: p (PHYLIP); n
(NEXUS))
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
* -enzymes boolean [N] Is the number of enzymes present in
input file
* -all boolean [N] All alleles present at each locus
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-infilesequences" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infilesequences] (Parameter 1)
seqset
(Aligned) sequence set filename and optional format, or reference (input USA)
Readable set of sequences
Required
[-outfile] (Parameter 2)
outfile
Phylip seqboot program output file
Output file
<*>.fseqbootall
Additional (Optional) qualifiers
-categories
properties
File of input categories
Property value(s)
-mixfile
properties
File of mixtures
Property value(s)
-ancfile
properties
File of ancestors
Property value(s)
-weights
properties
Weights file
Property value(s)
-factorfile
properties
Factors file
Property value(s)
-datatype
list
Choose the datatype
s
(Molecular sequences)
m
(Discrete Morphology)
r
(Restriction Sites)
g
(Gene Frequencies)
s
-test
list
Choose test
b
(Bootstrap)
j
(Jackknife)
c
(Permute species for each character)
o
(Permute character order)
s
(Permute within species)
r
(Rewrite data)
b
-regular
toggle
Altered sampling fraction
Toggle value Yes/No
No
-fracsample
float
Samples as percentage of sites
Number from 0.100 to 100.000
100.0
-rewriteformat
list
Output format
p
(PHYLIP)
n
(NEXUS)
x
(XML)
p
-seqtype
list
Output format
d
(dna)
p
(protein)
r
(rna)
d
-morphseqtype
list
Output format
p
(PHYLIP)
n
(NEXUS)
p
-blocksize
integer
Block size for bootstraping
Integer 1 or more
1
-reps
integer
How many replicates
Integer 1 or more
100
-justweights
list
Write out datasets or just weights
d
(Datasets)
w
(Weights)
d
-enzymes
boolean
Is the number of enzymes present in input file
Boolean value Yes/No
No
-all
boolean
All alleles present at each locus
Boolean value Yes/No
No
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-printdata
boolean
Print out the data at start of run
Boolean value Yes/No
No
-[no]dotdiff
boolean
Use dot-differencing
Boolean value Yes/No
Yes
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-infilesequences" associated seqset qualifiers
-sbegin1 -sbegin_infilesequences
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_infilesequences
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_infilesequences
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_infilesequences
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_infilesequences
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_infilesequences
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_infilesequences
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_infilesequences
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_infilesequences
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_infilesequences
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_infilesequences
string
Input sequence format
Any string
-iquery1 -iquery_infilesequences
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_infilesequences
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_infilesequences
string
Database name
Any string
-sid1 -sid_infilesequences
string
Entryname
Any string
-ufo1 -ufo_infilesequences
string
UFO features
Any string
-fformat1 -fformat_infilesequences
string
Features format
Any string
-fopenfile1 -fopenfile_infilesequences
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fseqbootall data files read by SEQBOOT are the standard ones for
the various kinds of data. For molecular sequences the sequences may
be either interleaved or sequential, and similarly for restriction
sites. Restriction sites data may either have or not have the third
argument, the number of restriction enzymes used. Discrete
morphological characters are always assumed to be in sequential
format. Gene frequencies data start with the number of species and the
number of loci, and then follow that by a line with the number of
alleles at each locus. The data for each locus may either have one
entry for each allele, or omit one allele at each locus. The details
of the formats are given in the main documentation file, and in the
documentation files for the groups of programsreads any normal
sequence USAs.
fseqbootall output will contain the data sets generated by the
resampling process. Note that, when Gene Frequencies data is used or
when Discrete Morphological characters with the Factors option are
used, the number of characters in each data set may vary. It may also
vary if there are an odd number of characters or sites and the
Delete-Half-Jackknife resampling method is used, for then there will
be a 50% chance of choosing (n+1)/2 characters and a 50% chance of
choosing (n-1)/2 characters.
The Factors option causes the characters to be resampled together. If
(say) three adjacent characters all have the same factors characters,
so that they all are understood to be recoding one multistate
character, they will be resampled together as a group.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these
data avoid any result which is sensitive to the input order of species
from showing up repeatedly and thus appearing to have evidence in its
favor.
The numerical options 1 and 2 in the menu also affect the output
file. If 1 is chosen (it is off by default) the program will print the
original input data set on the output file before the resampled data
sets. I cannot actually see why anyone would want to do this. Option 2
toggles the feature (on by default) that prints out up to 20 times
during the resampling process a notification that the program has
completed a certain number of data sets. Thus if 100 resampled data
sets are being produced, every 5 data sets a line is printed saying
which data set has just been completed. This option should be turned
off if the program is running in background and silence is
desirable. At the end of execution the program will always (whatever
the setting of option 2) print a couple of lines saying that output
has been written to the output file.
Please help by correcting and extending the Wiki pages.
Function
Restriction site maximum likelihood method
Description
Estimation of phylogenies by maximum likelihood using restriction
sites data (not restriction fragments but presence/absence of
individual sites). It employs the Jukes-Cantor symmetrical model of
nucleotide change, which does not allow for differences of rate
between transitions and transversions. This program is very slow.
Algorithm
This program implements a maximum likelihood method for restriction
sites data (not restriction fragment data). This program is one of the
slowest programs in this package, and can be very tedious to run. It
is possible to have the program search for the maximum likelihood
tree. It will be more practical for some users (those that do not have
fast machines) to use the U (User Tree) option, which takes less run
time, optimizing branch lengths and computing likelihoods for
particular tree topologies suggested by the user. The model used here
is essentially identical to that used by Smouse and Li (1987) who give
explicit expressions for computing the likelihood for three-species
trees. It does not place prior probabilities on trees as they do. The
present program extends their approach to multiple species by a
technique which, while it does not give explicit expressions for
likelihoods, does enable their computation and the iterative
improvement of branch lengths. It also allows for multiple restriction
enzymes. The algorithm has been described in a paper (Felsenstein,
1992). Another relevant paper is that of DeBry and Slade (1985).
The assumptions of the present model are:
Each restriction site evolves independently.
Different lineages evolve independently.
Each site undergoes substitution at an expected rate which we specify.
Substitutions consist of replacement of a nucleotide by one of the
other three nucleotides, chosen at random.
Note that if the existing base is, say, an A, the chance of it being
replaced by a G is 1/3, and so is the chance that it is replaced by a
T. This means that there can be no difference in the (expected) rate
of transitions and transversions. Users who are upset at this might
ponder the fact that a version allowing different rates of transitions
and transversions would run an estimated 16 times slower. If it also
allowed for unequal frequencies of the four bases, it would run about
300,000 times slower! For the moment, until a better method is
available, I guess I'll stick with this one!
Subject to these assumptions, the program is an approximately correct
maximum likelihood method.
Usage
Here is a sample session with frestml
% frestml
Restriction site maximum likelihood method
Input file: restml.dat
Phylip tree file (optional):
Phylip restml program output file [restml.frestml]:
numseqs: 1
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "restml.frestml"
Tree also written onto file "restml.treefile"
Done.
Restriction site maximum likelihood method
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-data] discretestates File containing one or more sets of
restriction data
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.frestml] Phylip restml program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]allsites boolean [Y] All sites detected
* -lengths boolean [N] Use lengths from user trees
-sitelength integer [6] Site length (Integer from 1 to 8)
* -global boolean [N] Global rearrangements
* -[no]rough boolean [Y] Speedier but rougher analysis
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.frestml] Phylip tree output file
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-data] (Parameter 1)
discretestates
File containing one or more sets of restriction data
Discrete states file
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip restml program output file
Output file
<*>.frestml
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-[no]allsites
boolean
All sites detected
Boolean value Yes/No
Yes
-lengths
boolean
Use lengths from user trees
Boolean value Yes/No
No
-sitelength
integer
Site length
Integer from 1 to 8
6
-global
boolean
Global rearrangements
Boolean value Yes/No
No
-[no]rough
boolean
Speedier but rougher analysis
Boolean value Yes/No
Yes
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file
Output file
<*>.frestml
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
frestml input is fairly standard, with one addition. As usual
the first line of the file gives the number of species and the number
of sites, but there is also a third number, which is the number of
different restriction enzymes that were used to detect the restriction
sites. Thus a data set with 10 species and 35 different sites,
representing digestion with 4 different enzymes, would have the first
line of the data file look like this:
10 35 4
The first line of the data file will also contain a letter W following
these numbers (and separated from them by a space) if the Weights
option is being used. As with all programs using the weights option, a
line or lines must then follow, before the data, with the weights for
each site.
The site data are in standard form. Each species starts with a species
name whose maximum length is given by the constant "nmlngth" (whose
value in the program as distributed is 10 characters). The name
should, as usual, be padded out to that length with blanks if
necessary. The sites data then follows, one character per site (any
blanks will be skipped and ignored). Like the DNA and protein sequence
data, the restriction sites data may be either in the "interleaved"
form or the "sequential" form. Note that if you are analyzing
restriction sites data with the programs DOLLOP or MIX or other
discrete character programs, at the moment those programs do not use
the "aligned" or "interleaved" data format. Therefore you may want to
avoid that format when you have restriction sites data that you will
want to feed into those programs.
The presence of a site is indicated by a "+" and the absence by a
"-". I have also allowed the use of "1" and "0" as synonyms for "+"
and "-", for compatibility with MIX and DOLLOP which do not allow "+"
and "-". If the presence of the site is unknown (for example, if the
DNA containing it has been deleted so that one does not know whether
it would have contained the site) then the state "?" can be used to
indicate that the state of this site is unknown.
User-defined trees may follow the data in the usual way. The trees
must be unrooted, which means that at their base they must have a
trifurcation.
Please help by correcting and extending the Wiki pages.
Function
Penny algorithm Dollo or polymorphism
Description
Finds all most parsimonious phylogenies for discrete-character data
with two states, for the Dollo or polymorphism parsimony criteria
using the branch-and-bound method of exact search. May be impractical
(depending on the data) for more than 10-11 species.
Algorithm
DOLPENNY is a program that will find all of the most parsimonious
trees implied by your data when the Dollo or polymorphism parsimony
criteria are employed. It does so not by examining all possible trees,
but by using the more sophisticated "branch and bound" algorithm, a
standard computer science search strategy first applied to
phylogenetic inference by Hendy and Penny (1982). (J. S. Farris
[personal communication, 1975] had also suggested that this strategy,
which is well-known in computer science, might be applied to
phylogenies, but he did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem
of finding these has been shown (Graham and Foulds, 1982; Day, 1983)
to be NP-complete, which is equivalent to saying that there is no fast
algorithm that is guaranteed to solve the problem in all cases (for a
discussion of NP-completeness, see the Scientific American article by
Lewis and Papadimitriou, 1978). The result is that this program,
despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs in
the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of
someone who can let a microcomputer grind all night than for someone
who has the "benefit" of paying for time on the campus mainframe
computer). IT IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE
PROGRAM WILL TAKE ON YOUR DATA. This can be done by running it on
subsets of the species, increasing the number of species in the run
until you either are able to treat the full data set or know that the
program will take unacceptably long on it. (Making a plot of the
logarithm of run time against species number may help to project run
times).
The Algorithm
The search strategy used by DOLPENNY starts by making a tree
consisting of the first two species (the first three if the tree is to
be unrooted). Then it tries to add the next species in all possible
places (there are three of these). For each of the resulting trees it
evaluates the number of losses. It adds the next species to each of
these, again in all possible spaces. If this process would continue it
would simply generate all possible trees, of which there are a very
large number even when the number of species is moderate (34,459,425
with 10 species). Actually it does not do this, because the trees are
generated in a particular order and some of them are never generated.
Actually the order in which trees are generated is not quite as
implied above, but is a "depth-first search". This means that first
one adds the third species in the first possible place, then the
fourth species in its first possible place, then the fifth and so on
until the first possible tree has been produced. Its number of steps
is evaluated. Then one "backtracks" by trying the alternative
placements of the last species. When these are exhausted one tries the
next placement of the next-to-last species. The order of placement in
a depth-first search is like this for a four-species case (parentheses
enclose monophyletic groups):
Make tree of first two species (A,B)
Add C in first place ((A,B),C)
Add D in first place (((A,D),B),C)
Add D in second place ((A,(B,D)),C)
Add D in third place (((A,B),D),C)
Add D in fourth place ((A,B),(C,D))
Add D in fifth place (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place (((A,D),C),B)
Add D in second place ((A,(C,D)),B)
Add D in third place (((A,C),D),B)
Add D in fourth place ((A,C),(B,D))
Add D in fifth place (((A,C),B),D)
Add C in third place (A,(B,C))
Add D in first place ((A,D),(B,C))
Add D in second place (A,((B,D),C))
Add D in third place (A,(B,(C,D)))
Add D in fourth place (A,((B,C),D))
Add D in fifth place ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species rooted
bifurcating trees, each exactly once (the parentheses each enclose a
monophyletic group). As displayed above, the backtracking depth-first
search algorithm is just another way of producing all possible trees
one at a time. The branch and bound algorithm consists of this with
one change. As each tree is constructed, including the partial trees
such as (A,(B,C)), its number of losses (or retentions of
polymorphism) is evaluated.
The point of this is that if a previously-found tree such as
((A,B),(C,D)) required fewer losses, then we know that there is no
point in even trying to add D to ((A,C),B). We have computed the bound
that enables us to cut off a whole line of inquiry (in this case five
trees) and avoid going down that particular branch any farther.
The branch-and-bound algorithm thus allows us to find all most
parsimonious trees without generating all possible trees. How much of
a saving this is depends strongly on the data. For very clean (nearly
"Hennigian") data, it saves much time, but on very messy data it will
still take a very long time.
The algorithm in the program differs from the one outlined here in
some essential details: it investigates possibilities in the order of
their apparent promise. This applies to the order of addition of
species, and to the places where they are added to the tree. After the
first two-species tree is constructed, the program tries adding each
of the remaining species in turn, each in the best possible place it
can find. Whichever of those species adds (at a minimum) the most
additional steps is taken to be the one to be added next to the
tree. When it is added, it is added in turn to places which cause the
fewest additional steps to be added. This sounds a bit complex, but it
is done with the intention of eliminating regions of the search of all
possible trees as soon as possible, and lowering the bound on tree
length as quickly as possible.
The program keeps a list of all the most parsimonious trees found so
far. Whenever it finds one that has fewer losses than these, it clears
out the list and restarts the list with that tree. In the process the
bound tightens and fewer possibilities need be investigated. At the
end the list contains all the shortest trees. These are then printed
out. It should be mentioned that the program CLIQUE for finding all
largest cliques also works by branch-and-bound. Both problems are
NP-complete but for some reason CLIQUE runs far faster. Although their
worst-case behavior is bad for both programs, those worst cases occur
far more frequently in parsimony problems than in compatibility
problems.
Controlling Run Times
Among the quantities available to be set at the beginning of a run of
DOLPENNY, two (howoften and howmany) are of particular importance. As
DOLPENNY goes along it will keep count of how many trees it has
examined. Suppose that howoften is 100 and howmany is 300, the default
settings. Every time 100 trees have been examined, DOLPENNY will print
out a line saying how many multiples of 100 trees have now been
examined, how many steps the most parsimonious tree found so far has,
how many trees of with that number of steps have been found, and a
very rough estimate of what fraction of all trees have been looked at
so far.
When the number of these multiples printed out reaches the number
howmany (say 1000), the whole algorithm aborts and prints out that it
has not found all most parsimonious trees, but prints out what is has
got so far anyway. These trees need not be any of the most
parsimonious trees: they are simply the most parsimonious ones found
so far. By setting the product (howoften X howmany) large you can make
the algorithm less likely to abort, but then you risk getting bogged
down in a gigantic computation. You should adjust these constants so
that the program cannot go beyond examining the number of trees you
are reasonably willing to pay for (or wait for). In their initial
setting the program will abort after looking at 100,000
trees. Obviously you may want to adjust howoften in order to get more
or fewer lines of intermediate notice of how many trees have been
looked at so far. Of course, in small cases you may never even reach
the first multiple of howoften and nothing will be printed out except
some headings and then the final trees.
The indication of the approximate percentage of trees searched so far
will be helpful in judging how much farther you would have to go to
get the full search. Actually, since that fraction is the fraction of
the set of all possible trees searched or ruled out so far, and since
the search becomes progressively more efficient, the approximate
fraction printed out will usually be an underestimate of how far along
the program is, sometimes a serious underestimate.
A constant that affects the result is "maxtrees", which controls the
maximum number of trees that can be stored. Thus if "maxtrees" is 25,
and 32 most parsimonious trees are found, only the first 25 of these
are stored and printed out. If "maxtrees" is increased, the program
does not run any slower but requires a little more intermediate
storage space. I recommend that "maxtrees" be kept as large as you
can, provided you are willing to look at an output with that many
trees on it! Initially, "maxtrees" is set to 100 in the distribution
copy.
Methods and Options
The counting of the length of trees is done by an algorithm nearly
identical to the corresponding algorithms in DOLLOP, and thus the
remainder of this document will be nearly identical to the DOLLOP
document. The Dollo parsimony method was first suggested in print in
verbal form by Le Quesne (1974) and was first well-specified by Farris
(1977). The method is named after Louis Dollo since he was one of the
first to assert that in evolution it is harder to gain a complex
feature than to lose it. The algorithm explains the presence of the
state 1 by allowing up to one forward change 0-->1 and as many
reversions 1-->0 as are necessary to explain the pattern of states
seen. The program attempts to minimize the number of 1-->0 reversions
necessary.
The assumptions of this method are in effect:
We know which state is the ancestral one (state 0).
The characters are evolving independently.
Different lineages evolve independently.
The probability of a forward change (0-->1) is small over the
evolutionary times involved.
The probability of a reversion (1-->0) is also small, but still far
larger than the probability of a forward change, so that many
reversions are easier to envisage than even one extra forward change.
Retention of polymorphism for both states (0 and 1) is highly improbable.
The lengths of the segments of the true tree are not so unequal that
two changes in a long segment are as probable as one in a short
segment.
That these are the assumptions is established in several of my papers
(1973a, 1978b, 1979, 1981b, 1983). For an opposing view arguing that
the parsimony methods make no substantive assumptions such as these,
see the papers by Farris (1983) and Sober (1983a, 1983b), but also
read the exchange between Felsenstein and Sober (1986).
One problem can arise when using additive binary recoding to represent
a multistate character as a series of two-state characters. Unlike the
Camin-Sokal, Wagner, and Polymorphism methods, the Dollo method can
reconstruct ancestral states which do not exist. An example is given
in my 1979 paper. It will be necessary to check the output to make
sure that this has not occurred.
The polymorphism parsimony method was first used by me, and the
results published (without a clear specification of the method) by
Inger (1967). The method was published by Farris (1978a) and by me
(1979). The method assumes that we can explain the pattern of states
by no more than one origination (0-->1) of state 1, followed by
retention of polymorphism along as many segments of the tree as are
necessary, followed by loss of state 0 or of state 1 where
necessary. The program tries to minimize the total number of
polymorphic characters, where each polymorphism is counted once for
each segment of the tree in which it is retained.
The assumptions of the polymorphism parsimony method are in effect:
The ancestral state (state 0) is known in each character.
The characters are evolving independently of each other.
Different lineages are evolving independently.
Forward change (0-->1) is highly improbable over the length of time
involved in the evolution of the group.
Retention of polymorphism is also improbable, but far more probable
that forward change, so that we can more easily envisage much
polymorhism than even one additional forward change.
Once state 1 is reached, reoccurrence of state 0 is very improbable,
much less probable than multiple retentions of polymorphism.
The lengths of segments in the true tree are not so unequal that we
can more easily envisage retention events occurring in both of two
long segments than one retention in a short segment.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b), but also read the exchange
between Felsenstein and Sober (1986).
Usage
Here is a sample session with fdolpenny
% fdolpenny
Penny algorithm Dollo or polymorphism
Phylip character discrete states file: dolpenny.dat
Phylip dolpenny program output file [dolpenny.fdolpenny]:
How many
trees looked Approximate
at so far Length of How many percentage
(multiples shortest tree trees this long searched
of 100): found so far found so far so far
---------- ------------ ------------ ------------
1 3.00000 1 0.95
Output written to file "dolpenny.fdolpenny"
Trees also written onto file "dolpenny.treefile"
Penny algorithm Dollo or polymorphism
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-outfile] outfile [*.fdolpenny] Phylip dolpenny program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-ancfile properties Ancestral states file
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 0.000 or more)
-howmany integer [1000] How many groups of trees (Any integer
value)
-howoften integer [100] How often to report, in trees (Any
integer value)
-[no]simple boolean [Y] Branch and bound is simple
-method menu [d] Parsimony method (Values: d (Dollo); p
(Polymorphism))
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdolpenny] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-ancseq boolean [N] Print states at all nodes of tree
-stepbox boolean [N] Print out steps in each character
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
File containing one or more data sets
Discrete states file
[-outfile] (Parameter 2)
outfile
Phylip dolpenny program output file
Output file
<*>.fdolpenny
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-ancfile
properties
Ancestral states file
Property value(s)
-dothreshold
toggle
Use threshold parsimony
Toggle value Yes/No
No
-threshold
float
Threshold value
Number 0.000 or more
1
-howmany
integer
How many groups of trees
Any integer value
1000
-howoften
integer
How often to report, in trees
Any integer value
100
-[no]simple
boolean
Branch and bound is simple
Boolean value Yes/No
Yes
-method
list
Parsimony method
d
(Dollo)
p
(Polymorphism)
d
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdolpenny
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-ancseq
boolean
Print states at all nodes of tree
Boolean value Yes/No
No
-stepbox
boolean
Print out steps in each character
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fdolpenny reads discrete character data with "?", "P", "B" states
allowed. .
(0,1) Discrete character data
These programs are intended for the use of morphological
systematists who are dealing with discrete characters, or by molecular
evolutionists dealing with presence-absence data on restriction
sites. One of the programs (PARS) allows multistate characters, with
up to 8 states, plus the unknown state symbol "?". For the others, the
characters are assumed to be coded into a series of (0,1) two-state
characters. For most of the programs there are two other states
possible, "P", which stands for the state of Polymorphism for both
states (0 and 1), and "?", which stands for the state of ignorance: it
is the state "unknown", or "does not apply". The state "P" can also be
denoted by "B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding
a multistate character into a series of two-state (0,1)
characters. Suppose we had a character with four states whose
character-state tree had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We
can represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE,
DOLPENNY and DOLBOOT the multistate recoding does not necessarily work
properly, as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected
in a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for
unordered character states.
fdolpenny output format is standard. It includes a rooted
tree and, if the user selects option 4, a table of the numbers of
reversions or retentions of polymorphism necessary in each
character. If any of the ancestral states has been specified to be
unknown, a table of reconstructed ancestral states is also
provided. When reconstructing the placement of forward changes and
reversions under the Dollo method, keep in mind that each polymorphic
state in the input data will require one "last minute" reversion. This
is included in the tabulated counts. Thus if we have both states 0 and
1 at a tip of the tree the program will assume that the lineage had
state 1 up to the last minute, and then state 0 arose in that
population by reversion, without loss of state 1.
A table is available to be printed out after each tree, showing for
each branch whether there are known to be changes in the branch, and
what the states are inferred to have been at the top end of the
branch. If the inferred state is a "?" there will be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand.
If the A option is used, then the program will infer, for any
character whose ancestral state is unknown ("?") whether the ancestral
state 0 or 1 will give the best tree. If these are tied, then it may
not be possible for the program to infer the state in the internal
nodes, and these will all be printed as ".". If this has happened and
you want to know more about the states at the internal nodes, you will
find helpful to use DOLMOVE to display the tree and examine its
interior states, as the algorithm in DOLMOVE shows all that can be
known in this case about the interior states, including where there is
and is not amibiguity. The algorithm in DOLPENNY gives up more easily
on displaying these states.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is
needed when we use the trees to make a consensus tree of the results
of bootstrapping or jackknifing, to avoid overrepresenting replicates
that find many tied trees.
Output files for usage example
File: dolpenny.fdolpenny
Penny algorithm for Dollo or polymorphism parsimony, version 3.69.650
branch-and-bound to find all most parsimonious trees
requires a total of 3.000
3 trees in all found
+-----------------Delta
!
--2 +--------------Epsilon
! !
+--3 +-----------Gamma1
! !
+--6 +--------Alpha2
! !
+--1 +--Beta2
! +--5
+--4 +--Beta1
!
+-----Alpha1
+-----------------Delta
!
--2 +--------------Epsilon
! !
+--3 +-----------Gamma1
! !
+--6 +--Beta2
! +-----5
! ! +--Beta1
+--4
! +--Alpha2
+-----1
+--Alpha1
+-----------------Delta
!
--2 +--------------Epsilon
! !
+--3 +-----------Gamma1
! !
! ! +--Beta2
+--6 +--5
! +--4 +--Beta1
! ! !
+--1 +-----Alpha2
!
+--------Alpha1
Please help by correcting and extending the Wiki pages.
Function
Mixed parsimony algorithm
Description
Estimates phylogenies by some parsimony methods for discrete character
data with two states (0 and 1). Allows use of the Wagner parsimony
method, the Camin-Sokal parsimony method, or arbitrary mixtures of
these. Also reconstructs ancestral states and allows weighting of
characters (does not infer branch lengths).
Algorithm
MIX is a general parsimony program which carries out the Wagner and
Camin-Sokal parsimony methods in mixture, where each character can
have its method specified separately. The program defaults to carrying
out Wagner parsimony.
The Camin-Sokal parsimony method explains the data by assuming that
changes 0 --> 1 are allowed but not changes 1 --> 0. Wagner parsimony
allows both kinds of changes. (This under the assumption that 0 is the
ancestral state, though the program allows reassignment of the
ancestral state, in which case we must reverse the state numbers 0 and
1 throughout this discussion). The criterion is to find the tree which
requires the minimum number of changes. The Camin-Sokal method is due
to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
(1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
Ancestral states are known (Camin-Sokal) or unknown (Wagner).
Different characters evolve independently.
Different lineages evolve independently.
Changes 0 --> 1 are much more probable than changes 1 --> 0
(Camin-Sokal) or equally probable (Wagner).
Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the group
in question.
Other kinds of evolutionary event such as retention of polymorphism
are far less probable than 0 --> 1 changes.
Rates of evolution in different lineages are sufficiently low that two
changes in a long segment of the tree are far less probable than one
change in a short segment.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b), but also read the exchange
between Felsenstein and Sober (1986).
Usage
Here is a sample session with fmix
% fmix
Mixed parsimony algorithm
Phylip character discrete states file: mix.dat
Phylip tree file (optional):
Phylip mix program output file [mix.fmix]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
Output written to file "mix.fmix"
Trees also written onto file "mix.treefile"
Mixed parsimony algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fmix] Phylip mix program output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-ancfile properties Ancestral states file
-mixfile properties Mixture file
-method menu [Wagner] Choose the method to use (Values: w
(Wagner); c (Camin-Sokal); m (Mixed))
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-threshold float [$(infile.discretesize)] Threshold value
(Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fmix] Phylip tree output file (optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-ancseq boolean [N] Print states at all nodes of tree
-stepbox boolean [N] Print out steps in each character
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
File containing one or more data sets
Discrete states file
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip mix program output file
Output file
<*>.fmix
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-ancfile
properties
Ancestral states file
Property value(s)
-mixfile
properties
Mixture file
Property value(s)
-method
list
Choose the method to use
w
(Wagner)
c
(Camin-Sokal)
m
(Mixed)
Wagner
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-threshold
float
Threshold value
Number 1.000 or more
$(infile.discretesize)
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fmix
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-ancseq
boolean
Print states at all nodes of tree
Boolean value Yes/No
No
-stepbox
boolean
Print out steps in each character
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fmix reads discrete character data. States "?", "P", and "B"
are allowed.
(0,1) Discrete character data
These programs are intended for the use of morphological
systematists who are dealing with discrete characters, or by molecular
evolutionists dealing with presence-absence data on restriction
sites. One of the programs (PARS) allows multistate characters, with
up to 8 states, plus the unknown state symbol "?". For the others, the
characters are assumed to be coded into a series of (0,1) two-state
characters. For most of the programs there are two other states
possible, "P", which stands for the state of Polymorphism for both
states (0 and 1), and "?", which stands for the state of ignorance: it
is the state "unknown", or "does not apply". The state "P" can also be
denoted by "B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding
a multistate character into a series of two-state (0,1)
characters. Suppose we had a character with four states whose
character-state tree had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We
can represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE,
DOLPENNY and DOLBOOT the multistate recoding does not necessarily work
properly, as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected
in a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for
unordered character states.
fmix output is standard: a list of equally parsimonious trees,
which will be printed as rooted or unrooted depending on which is
appropriate, and, if the user chooses, a table of the number of
changes of state required in each character. If the Wagner option is
in force for a character, it may not be possible to unambiguously
locate the places on the tree where the changes occur, as there may be
multiple possibilities. If the user selects menu option 5, a table is
printed out after each tree, showing for each branch whether there are
known to be changes in the branch, and what the states are inferred to
have been at the top end of the branch. If the inferred state is a "?"
there will be multiple equally-parsimonious assignments of states; the
user must work these out for themselves by hand.
If the Camin-Sokal parsimony method is invoked and the Ancestors
option is also used, then the program will infer, for any character
whose ancestral state is unknown ("?") whether the ancestral state 0
or 1 will give the fewest state changes. If these are tied, then it
may not be possible for the program to infer the state in the internal
nodes, and these will all be printed as ".". If this has happened and
you want to know more about the states at the internal nodes, you will
find helpful to use MOVE to display the tree and examine its interior
states, as the algorithm in MOVE shows all that can be known in this
case about the interior states, including where there is and is not
amibiguity. The algorithm in MIX gives up more easily on displaying
these states.
If the A option is not used, then the program will assume 0 as the
ancestral state for those characters following the Camin-Sokal method,
and will assume that the ancestral state is unknown for those
characters following Wagner parsimony. If any characters have unknown
ancestral states, and if the resulting tree is rooted (even by
outgroup), a table will also be printed out showing the best guesses
of which are the ancestral states in each character. You will find it
useful to understand the difference between the Camin-Sokal parsimony
criterion with unknown ancestral state and the Wagner parsimony
criterion.
If the U (User Tree) option is used and more than one tree is
supplied, the program also performs a statistical test of each of
these trees against the best tree. This test, which is a version of
the test proposed by Alan Templeton (1983) and evaluated in a test
case by me (1985a). It is closely parallel to a test using log
likelihood differences invented by Kishino and Hasegawa (1989), and
uses the mean and variance of step differences between trees, taken
across characters. If the mean is more than 1.96 standard deviations
different then the trees are declared significantly different. The
program prints out a table of the steps for each tree, the differences
of each from the highest one, the variance of that quantity as
determined by the step differences at individual characters, and a
conclusion as to whether that tree is or is not significantly worse
than the best one. It is important to understand that the test assumes
that all the binary characters are evolving independently, which is
unlikely to be true for many suites of morphological characters.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sums of steps across
characters are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could
have been expected if they all had the same expected number of steps,
numbers of steps for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the lowest number of steps exceeds that
actually observed. Note that this sampling needs random numbers, and
so the program will prompt the user for a random number seed if one
has not already been supplied. With the two-tree KHT test no random
numbers are used.
In either the KHT or the SH test the program prints out a table of the
number of steps for each tree, the differences of each from the lowest
one, the variance of that quantity as determined by the differences of
the numbers of steps at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is
needed when we use the trees to make a consensus tree of the results
of bootstrapping or jackknifing, to avoid overrepresenting replicates
that find many tied trees.
Output files for usage example
File: mix.fmix
Mixed parsimony algorithm, version 3.69.650
Wagner parsimony method
4 trees in all found
+--Epsilon
+-----4
! +--Gamma
+--2
! ! +--Delta
--1 +-----3
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 9.000
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
--1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 9.000
+--------Epsilon
+--4
! ! +-----Gamma
! +--2
--1 ! +--Delta
! +--3
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 9.000
+--------Gamma
+--2
! ! +-----Epsilon
! +--4
--1 ! +--Delta
! +--3
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 9.000
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped sequences algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of
the package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
SEQBOOT is a general bootstrapping and data set translation tool. It
is intended to allow you to generate multiple data sets that are
resampled versions of the input data set. Since almost all programs in
the package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or
permuted. SEQBOOT can handle molecular sequences, binary characters,
restriction sites, or gene frequencies. It can also convert data sets
between Sequential and Interleaved format, and into the NEXUS format
or into a new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of
interest. For example, if you were using DNAPARS you would first run
SEQBOOT and make a file with 100 bootstrapped data sets. Then you
would give this file the proper name to have it be the input file for
DNAPARS. Running DNAPARS with the M (Multiple Data Sets) menu choice
and informing it to expect 100 data sets, you would generate a big
output file as well as a treefile with the trees from the 100 data
sets. This treefile could be renamed so that it would serve as the
input for CONSENSE. When CONSENSE is run the majority rule consensus
tree will result, showing the outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this
package. The same steps are necessary with all of them. Doing things
this way some of the intermediate files (the tree file from the
DNAPARS run, for example) can be used to summarize the results of the
bootstrap in other ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add
one extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me (Felsenstein,
1985b; see also Penny and Hendy, 1985). It involves creating a new
data set by sampling N characters randomly with replacement, so that
the resulting data set has the same size as the original, but some
characters have been left out and others are duplicated. The random
variation of the results from analyzing these bootstrapped data sets
can be shown statistically to be typical of the variation that you
would get from collecting new data sets. The method assumes that the
characters evolve independently, an assumption that may not be
realistic for many kinds of data.
The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial Bootstrap
method, and Shimodaira's (2002) AU method, both of which correct the
bias of bootstrap P values.
Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct for
it by samopling, not individual characters, but blocks of adjacent
characters. This is called a block bootstrap and was introduced by
Künsch (1989). If the correlations are believed to extend over some
number of characters, you choose a block size, B, that is larger than
this, and choose N/B blocks of size B. In its implementation here the
block bootstrap "wraps around" at the end of the characters (so that
if a block starts in the last B-1 characters, it continues by wrapping
around to the first character after it reaches the last
character). Note also that if you have a DNA sequence data set of an
exon of a coding region, you can ensure that equal numbers of first,
second, and third coding positions are sampled by using the block
bootstrap with B = 3.
Partial block-bootstrapping. Similar to partial bootstrapping except
sampling blocks rather than single characters.
Delete-half-jackknifing.. This alternative to the bootstrap involves
sampling a random half of the characters, and including them in the
data but dropping the others. The resulting data sets are half the
size of the original, and no characters are duplicated. The random
variation from doing this should be very similar to that obtained from
the bootstrap. The method is advocated by Wu (1986). It was mentioned
by me in my bootstrapping paper (Felsenstein, 1985b), and has been
available for many years in this program as an option. Note that, for
the present, block-jackknifing is not available, because I cannot
figure out how to do it straightforwardly when the block size is not a
divisor of the number of characters.
Delete-fraction jackknifing. Jackknifing is advocated by Farris
et. al. (1996) but as deleting a fraction 1/e (1/2.71828). This
retains too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it is
made available here as an option, with the user asked to supply the
fraction of characters that are to be retained.
Permuting species within characters. This method of resampling (well,
OK, it may not be best to call it resampling) was introduced by Archie
(1989) and Faith (1990; see also Faith and Cranston, 1991). It
involves permuting the columns of the data matrix separately. This
produces data matrices that have the same number and kinds of
characters but no taxonomic structure. It is used for different
purposes than the bootstrap, as it tests not the variation around an
estimated tree but the hypothesis that there is no taxonomic structure
in the data: if a statistic such as number of steps is significantly
smaller in the actual data than it is in replicates that are permuted,
then we can argue that there is some taxonomic structure in the data
(though perhaps it might be just the presence of aa pair of sibling
species).
Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For many
methods of tree inference this will make no difference to the outcome
(unless one has rates of evolution correlated among adjacent
sites). It is included as a possible step in carrying out a
permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so as
to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
Rewriting. This is not a resampling or permutation method: it simply
rewrites the data set into a different format. That format can be the
PHYLIP format. For molecular sequences and discrete morphological
character it can also be the NEXUS format. For molecular sequences one
other format is available, a new (and nonstandard) XML format of our
own devising. When the PHYLIP format is chosen the data set is
coverted between Interleaved and Sequential format. If it was read in
as Interleaved sequences, it will be written out as Sequential format,
and vice versa. The NEXUS format for molecular sequences is always
written as interleaved sequences. The XML format is different from
(though similar to) a number of other XML sequence alignment
formats. An example will be found below. Here is a table to links to
those other XML alignment formats:
Andrew Rambaut's
BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html
and http://evolve.zoo.ox.ac.uk/beast/referenindex.html
A format for alignments. There
is also a format for phylogenies
described there.
MSAML M
http://xml.coverpages.org/msaml-desc-dec.html
Defined by Paul Gordon of
University of Calgary. See his
big list of molecular biology
XML projects.
BSML
http://www.bsml.org/resources/default.asp
Bioinformatic Sequence
Markup Language
includes a multiple sequence
alignment XML format
Usage
Here is a sample session with fseqboot
% fseqboot -seed 3
Bootstrapped sequences algorithm
Input (aligned) sequence set: seqboot.dat
Phylip seqboot_seq program output file [seqboot.fseqboot]:
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "seqboot.fseqboot"
Done.
Bootstrapped sequences algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqset (Aligned) sequence set filename and optional
format, or reference (input USA)
[-outfile] outfile [*.fseqboot] Phylip seqboot_seq program
output file
Additional (Optional) qualifiers (* if not always prompted):
-categories properties File of input categories
-weights properties Weights file
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -rewriteformat menu [p] Output format (Values: p (PHYLIP); n
(NEXUS); x (XML))
* -seqtype menu [d] Output format (Values: d (dna); p
(protein); r (rna))
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqset
(Aligned) sequence set filename and optional format, or reference (input USA)
Readable set of sequences
Required
[-outfile] (Parameter 2)
outfile
Phylip seqboot_seq program output file
Output file
<*>.fseqboot
Additional (Optional) qualifiers
-categories
properties
File of input categories
Property value(s)
-weights
properties
Weights file
Property value(s)
-test
list
Choose test
b
(Bootstrap)
j
(Jackknife)
c
(Permute species for each character)
o
(Permute character order)
s
(Permute within species)
r
(Rewrite data)
b
-regular
toggle
Altered sampling fraction
Toggle value Yes/No
No
-fracsample
float
Samples as percentage of sites
Number from 0.100 to 100.000
100.0
-rewriteformat
list
Output format
p
(PHYLIP)
n
(NEXUS)
x
(XML)
p
-seqtype
list
Output format
d
(dna)
p
(protein)
r
(rna)
d
-blocksize
integer
Block size for bootstraping
Integer 1 or more
1
-reps
integer
How many replicates
Integer 1 or more
100
-justweights
list
Write out datasets or just weights
d
(Datasets)
w
(Weights)
d
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-printdata
boolean
Print out the data at start of run
Boolean value Yes/No
No
-[no]dotdiff
boolean
Use dot-differencing
Boolean value Yes/No
Yes
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqset qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fseqboot data files read by SEQBOOT are the standard ones for
the various kinds of data. For molecular sequences the sequences may
be either interleaved or sequential, and similarly for restriction
sites. Restriction sites data may either have or not have the third
argument, the number of restriction enzymes used. Discrete
morphological characters are always assumed to be in sequential
format. Gene frequencies data start with the number of species and the
number of loci, and then follow that by a line with the number of
alleles at each locus. The data for each locus may either have one
entry for each allele, or omit one allele at each locus. The details
of the formats are given in the main documentation file, and in the
documentation files for the groups of programsreads any normal
sequence USAs.
fseqboot output will contain the data sets generated by the
resampling process. Note that, when Gene Frequencies data is used or
when Discrete Morphological characters with the Factors option are
used, the number of characters in each data set may vary. It may also
vary if there are an odd number of characters or sites and the
Delete-Half-Jackknife resampling method is used, for then there will
be a 50% chance of choosing (n+1)/2 characters and a 50% chance of
choosing (n-1)/2 characters.
The Factors option causes the characters to be resampled together. If
(say) three adjacent characters all have the same factors characters,
so that they all are understood to be recoding one multistate
character, they will be resampled together as a group.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these
data avoid any result which is sensitive to the input order of species
from showing up repeatedly and thus appearing to have evidence in its
favor.
The numerical options 1 and 2 in the menu also affect the output
file. If 1 is chosen (it is off by default) the program will print the
original input data set on the output file before the resampled data
sets. I cannot actually see why anyone would want to do this. Option 2
toggles the feature (on by default) that prints out up to 20 times
during the resampling process a notification that the program has
completed a certain number of data sets. Thus if 100 resampled data
sets are being produced, every 5 data sets a line is printed saying
which data set has just been completed. This option should be turned
off if the program is running in background and silence is
desirable. At the end of execution the program will always (whatever
the setting of option 2) print a couple of lines saying that output
has been written to the output file.
Please help by correcting and extending the Wiki pages.
Function
Dollo and polymorphism parsimony algorithm
Description
Estimates phylogenies by the Dollo or polymorphism parsimony criteria
for discrete character data with two states (0 and 1). Also
reconstructs ancestral states and allows weighting of
characters. Dollo parsimony is particularly appropriate for
restriction sites data; with ancestor states specified as unknown it
may be appropriate for restriction fragments data.
Algorithm
This program carries out the Dollo and polymorphism parsimony
methods. The Dollo parsimony method was first suggested in print in
verbal form by Le Quesne (1974) and was first well-specified by Farris
(1977). The method is named after Louis Dollo since he was one of the
first to assert that in evolution it is harder to gain a complex
feature than to lose it. The algorithm explains the presence of the
state 1 by allowing up to one forward change 0-->1 and as many
reversions 1-->0 as are necessary to explain the pattern of states
seen. The program attempts to minimize the number of 1-->0 reversions
necessary.
The assumptions of this method are in effect:
We know which state is the ancestral one (state 0).
The characters are evolving independently.
Different lineages evolve independently.
The probability of a forward change (0-->1) is small over the
evolutionary times involved.
The probability of a reversion (1-->0) is also small, but still far
larger than the probability of a forward change, so that many
reversions are easier to envisage than even one extra forward change.
Retention of polymorphism for both states (0 and 1) is highly improbable.
The lengths of the segments of the true tree are not so unequal that
two changes in a long segment are as probable as one in a short
segment.
One problem can arise when using additive binary recoding to represent
a multistate character as a series of two-state characters. Unlike the
Camin-Sokal, Wagner, and Polymorphism methods, the Dollo method can
reconstruct ancestral states which do not exist. An example is given
in my 1979 paper. It will be necessary to check the output to make
sure that this has not occurred.
The polymorphism parsimony method was first used by me, and the
results published (without a clear specification of the method) by
Inger (1967). The method was independently published by Farris (1978a)
and by me (1979). The method assumes that we can explain the pattern
of states by no more than one origination (0-->1) of state 1, followed
by retention of polymorphism along as many segments of the tree as are
necessary, followed by loss of state 0 or of state 1 where
necessary. The program tries to minimize the total number of
polymorphic characters, where each polymorphism is counted once for
each segment of the tree in which it is retained.
The assumptions of the polymorphism parsimony method are in effect:
The ancestral state (state 0) is known in each character.
The characters are evolving independently of each other.
Different lineages are evolving independently.
Forward change (0-->1) is highly improbable over the length of time
involved in the evolution of the group.
Retention of polymorphism is also improbable, but far more probable
that forward change, so that we can more easily envisage much
polymorhism than even one additional forward change.
Once state 1 is reached, reoccurrence of state 0 is very improbable,
much less probable than multiple retentions of polymorphism.
The lengths of segments in the true tree are not so unequal that we
can more easily envisage retention events occurring in both of two
long segments than one retention in a short segment.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b), but also read the exchange
between Felsenstein and Sober (1986).
Usage
Here is a sample session with fdollop
% fdollop
Dollo and polymorphism parsimony algorithm
Phylip character discrete states file: dollop.dat
Phylip tree file (optional):
Phylip dollop program output file [dollop.fdollop]:
Dollo and polymorphism parsimony algorithm, version 3.69.650
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
.........
Output written to file "dollop.fdollop"
Trees also written onto file "dollop.treefile"
Dollo and polymorphism parsimony algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fdollop] Phylip dollop program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Phylip weights file (optional)
-ancfile properties Ancestral states file
-method menu [d] Parsimony method (Values: d (Dollo); p
(Polymorphism))
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-threshold float [$(infile.discretesize)] Threshold value
(Number 0.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdollop] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-ancseq boolean [N] Print states at all nodes of tree
-stepbox boolean [N] Print out steps in each character
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
File containing one or more data sets
Discrete states file
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip dollop program output file
Output file
<*>.fdollop
Additional (Optional) qualifiers
-weights
properties
Phylip weights file (optional)
Property value(s)
-ancfile
properties
Ancestral states file
Property value(s)
-method
list
Parsimony method
d
(Dollo)
p
(Polymorphism)
d
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-threshold
float
Threshold value
Number 0.000 or more
$(infile.discretesize)
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdollop
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-ancseq
boolean
Print states at all nodes of tree
Boolean value Yes/No
No
-stepbox
boolean
Print out steps in each character
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fdollop reads discrete character data with "?", "P", "B" states
allowed. .
(0,1) Discrete character data
These programs are intended for the use of morphological
systematists who are dealing with discrete characters, or by molecular
evolutionists dealing with presence-absence data on restriction
sites. One of the programs (PARS) allows multistate characters, with
up to 8 states, plus the unknown state symbol "?". For the others, the
characters are assumed to be coded into a series of (0,1) two-state
characters. For most of the programs there are two other states
possible, "P", which stands for the state of Polymorphism for both
states (0 and 1), and "?", which stands for the state of ignorance: it
is the state "unknown", or "does not apply". The state "P" can also be
denoted by "B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding
a multistate character into a series of two-state (0,1)
characters. Suppose we had a character with four states whose
character-state tree had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We
can represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE,
DOLPENNY and DOLBOOT the multistate recoding does not necessarily work
properly, as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected
in a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for
unordered character states.
fdollop output is standard: a list of equally parsimonious
trees, and, if the user selects menu option 4, a table of the numbers
of reversions or retentions of polymorphism necessary in each
character. If any of the ancestral states has been specified to be
unknown, a table of reconstructed ancestral states is also
provided. When reconstructing the placement of forward changes and
reversions under the Dollo method, keep in mind that each polymorphic
state in the input data will require one "last minute" reversion. This
is included in the tabulated counts. Thus if we have both states 0 and
1 at a tip of the tree the program will assume that the lineage had
state 1 up to the last minute, and then state 0 arose in that
population by reversion, without loss of state 1.
If the user selects menu option 5, a table is printed out after each
tree, showing for each branch whether there are known to be changes in
the branch, and what the states are inferred to have been at the top
end of the branch. If the inferred state is a "?" there may be
multiple equally-parsimonious assignments of states; the user must
work these out for themselves by hand.
If the A option is used, then the program will infer, for any
character whose ancestral state is unknown ("?") whether the ancestral
state 0 or 1 will give the best tree. If these are tied, then it may
not be possible for the program to infer the state in the internal
nodes, and these will all be printed as ".". If this has happened and
you want to know more about the states at the internal nodes, you will
find helpful to use DOLMOVE to display the tree and examine its
interior states, as the algorithm in DOLMOVE shows all that can be
known in this case about the interior states, including where there is
and is not amibiguity. The algorithm in DOLLOP gives up more easily on
displaying these states.
If the U (User Tree) option is used and more than one tree is
supplied, the program also performs a statistical test of each of
these trees against the best tree. This test, which is a version of
the test proposed by Alan Templeton (1983) and evaluated in a test
case by me (1985a). It is closely parallel to a test using log
likelihood differences invented by Kishino and Hasegawa (1989), and
uses the mean and variance of step differences between trees, taken
across characters. If the mean is more than 1.96 standard deviations
different then the trees are declared significantly different. The
program prints out a table of the steps for each tree, the differences
of each from the highest one, the variance of that quantity as
determined by the step differences at individual characters, and a
conclusion as to whether that tree is or is not significantly worse
than the best one. It is important to understand that the test assumes
that all the binary characters are evolving independently, which is
unlikely to be true for many suites of morphological characters.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sums of steps across
characters are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could
have been expected if they all had the same expected number of steps,
numbers of steps for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the lowest number of steps exceeds that
actually observed. Note that this sampling needs random numbers, and
so the program will prompt the user for a random number seed if one
has not already been supplied. With the two-tree KHT test no random
numbers are used.
In either the KHT or the SH test the program prints out a table of the
number of steps for each tree, the differences of each from the lowest
one, the variance of that quantity as determined by the differences of
the numbers of steps at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
If option 6 is left in its default state the trees found will be
written to a tree file, so that they are available to be used in other
programs. If the program finds multiple trees tied for best, all of
these are written out onto the output tree file. Each is followed by a
numerical weight in square brackets (such as [0.25000]). This is
needed when we use the trees to make a consensus tree of the results
of bootstrapping or jackknifing, to avoid overrepresenting replicates
that find many tied trees.
Output files for usage example
File: dollop.fdollop
Dollo and polymorphism parsimony algorithm, version 3.69.650
Dollo parsimony method
One most parsimonious tree found:
+-----------Delta
--3
! +--------Epsilon
+--4
! +-----Gamma
+--2
! +--Beta
+--1
+--Alpha
requires a total of 3.000
Please help by correcting and extending the Wiki pages.
Function
Interactive DNA parsimony
Description
Interactive construction of phylogenies from nucleic acid sequences,
with their evaluation by parsimony and compatibility and the display
of reconstructed ancestral bases. This can be used to find parsimony
or compatibility estimates by hand.
Algorithm
DNAMOVE is an interactive DNA parsimony program, inspired by Wayne
Maddison and David and Wayne Maddison's marvellous program MacClade,
which is written for Macintosh computers. DNAMOVE reads in a data set
which is prepared in almost the same format as one for the DNA
parsimony program DNAPARS. It allows the user to choose an initial
tree, and displays this tree on the screen. The user can look at
different sites and the way the nucleotide states are distributed on
that tree, given the most parsimonious reconstruction of state changes
for that particular tree. The user then can specify how the tree is to
be rearraranged, rerooted or written out to a file. By looking at
different rearrangements of the tree the user can manually search for
the most parsimonious tree, and can get a feel for how different sites
are affected by changes in the tree topology.
This program uses graphic characters that show the tree to best
advantage on some computer systems. Its graphic characters will work
best on MSDOS systems or MSDOS windows in Windows, and to any system
whose screen or terminals emulate ANSI standard terminals such as old
Digital VT100 terminals, Telnet programs, or VT100-compatible windows
in the X windowing system. For any other screen types, (such as
Macintosh windows) there is a generic option which does not make use
of screen graphics characters. The program will work well in those
cases, but the tree it displays will look a bit uglier.
This program carries out unrooted parsimony (analogous to Wagner
trees) (Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA
sequences. The method of Fitch (1971) is used to count the number of
changes of base needed on a given tree.
The assumptions of this method
are exactly analogous to those of MIX:
Each site evolves independently.
Different lineages evolve independently.
The probability of a base substitution at a given site is small over the lengths of time involved in a branch of the phylogeny.
The expected amounts of change in different branches of the phylogeny do not vary by so much that two changes in a high-rate branch are more probable than one change in a low-rate branch.
The expected amounts of change do not vary enough among sites that two changes in one site are more probable than one change in another.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b), but also read the exchange
between Felsenstein and Sober (1986).
Change from an occupied site to a deletion is counted as one
change. Reversion from a deletion to an occupied site is allowed and
is also counted as one change.
Usage
Here is a sample session with fdnamove
% fdnamove
Interactive DNA parsimony
Input (aligned) nucleotide sequence set(s): dnamove.dat
Phylip tree file (optional):
NEXT (R # + - S . T U W O F H J K L C ? X Q) (? for Help): Q
Do you want to write out the tree to a file? (Y or N): Y
5 species, 13 sites
Computing steps needed for compatibility in sites ...
(unrooted) 19.0 Steps 11 sites compatible
,-----------5:Epsilon
--9
! ,--------4:Delta
`--8
! ,-----3:Gamma
`--7
! ,--2:Beta
`--6
`--1:Alpha
Tree written to file "dnamove.treefile"
Interactive DNA parsimony
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall (Aligned) nucleotide sequence set(s)
filename and optional format, or reference
(input USA)
[-intreefile] tree Phylip tree file (optional)
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file - ignore sites with weight zero
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 1.000 or more)
-initialtree menu [Arbitary] Initial tree (Values: a
(Arbitary); u (User); s (Specify))
-screenwidth integer [80] Width of terminal screen in characters
(Any integer value)
-screenlines integer [24] Number of lines on screen (Any integer
value)
-outtreefile outfile [*.fdnamove] Phylip tree output file
(optional)
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
(Aligned) nucleotide sequence set(s) filename and optional format, or reference (input USA)
Readable sets of sequences
Required
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
Additional (Optional) qualifiers
-weights
properties
Weights file - ignore sites with weight zero
Property value(s)
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-dothreshold
toggle
Use threshold parsimony
Toggle value Yes/No
No
-threshold
float
Threshold value
Number 1.000 or more
1
-initialtree
list
Initial tree
a
(Arbitary)
u
(User)
s
(Specify)
Arbitary
-screenwidth
integer
Width of terminal screen in characters
Any integer value
80
-screenlines
integer
Number of lines on screen
Any integer value
24
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdnamove
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Please help by correcting and extending the Wiki pages.
Function
Continuous character contrasts
Description
Reads a tree from a tree file, and a data set with continuous
characters data, and produces the independent contrasts for those
characters, for use in any multivariate statistics package. Will also
produce covariances, regressions and correlations between characters
for those contrasts. Can also correct for within-species sampling
variation when individual phenotypes are available within a
population.
Algorithm
This program implements the contrasts calculation described in my 1985
paper on the comparative method (Felsenstein, 1985d). It reads in a
data set of the standard quantitative characters sort, and also a tree
from the treefile. It then forms the contrasts between species that,
according to that tree, are statistically independent. This is done
for each character. The contrasts are all standardized by branch
lengths (actually, square roots of branch lengths).
The method is explained in the 1985 paper. It assumes a Brownian
motion model. This model was introduced by Edwards and Cavalli-Sforza
(1964; Cavalli-Sforza and Edwards, 1967) as an approximation to the
evolution of gene frequencies. I have discussed (Felsenstein, 1973b,
1981c, 1985d, 1988b) the difficulties inherent in using it as a model
for the evolution of quantitative characters. Chief among these is
that the characters do not necessarily evolve independently or at
equal rates. This program allows one to evaluate this, if there is
independent information on the phylogeny. You can compute the variance
of the contrasts for each character, as a measure of the variance
accumulating per unit branch length. You can also test covariances of
characters.
The statistics that are printed out include the covariances between
all pairs of characters, the regressions of each character on each
other (column j is regressed on row i), and the correlations between
all pairs of characters. In assessing degress of freedom it is
important to realize that each contrast was taken to have expectation
zero, which is known because each contrast could as easily have been
computed xi-xj instead of xj-xi. Thus there is no loss of a degree of
freedom for estimation of a mean. The degrees of freedom is thus the
same as the number of contrasts, namely one less than the number of
species (tips). If you feed these contrasts into a multivariate
statistics program make sure that it knows that each variable has
expectation exactly zero.
Within-species variation
With the W option selected, CONTRAST analyzes data sets with variation
within species, using a model like that proposed by Michael Lynch
(1990). The method is described in vague terms in my book
(Felsenstein, 2004, pp. 441). If you select the W option for
within-species variation, the data set should have this structure (on
the left are the data, on the right my comments:
10 5 number of species, number of characters
Alpha 2 name of 1st species, # of individuals
2.01 5.3 1.5 -3.41 0.3 data for individual #1
1.98 4.3 2.1 -2.98 0.45 data for individual #2
Gammarus 3 name of 2nd species, # of individuals
6.57 3.1 2.0 -1.89 0.6 data for individual #1
7.62 3.4 1.9 -2.01 0.7 data for individual #2
6.02 3.0 1.9 -2.03 0.6 data for individual #3
... (and so on)
The covariances, correlations, and regressions for the "additive"
(between-species evolutionary variation) and "environmental"
(within-species phenotypic variation) are printed out (the maximum
likelihood estimates of each). The program also estimates the
within-species phenotypic variation in the case where the
between-species evolutionary covariances are forced to be zero. The
log-likelihoods of these two cases are compared and a likelihood ratio
test (LRT) is carried out. The program prints the result of this test
as a chi-square variate, and gives the number of degrees of freedom of
the LRT. You have to look up the chi-square variable on a table of the
chi-square distribution. The A option is available (if the W option is
invoked) to allow you to turn off the doing of this test if you want
to.
The log-likelihood of the data under the models with and without
between-species For the moment the program cannot handle the case
where within-species variation is to be taken into account but where
only species means are available. (It can handle cases where some
species have only one member in their sample).
We hope to fix this soon. We are also on our way to incorporating
full-sib, half-sib, or clonal groups within species, so as to do one
analysis for within-species genetic and between-species phylogenetic
variation.
The data set used as an example below is the example from a paper by
Michael Lynch (1990), his characters having been log-transformed. In
the case where there is only one specimen per species, Lynch's model
is identical to our model of within-species variation (for multiple
individuals per species it is not a subcase of his model).
Usage
Here is a sample session with fcontrast
% fcontrast
Continuous character contrasts
Input file: contrast.dat
Phylip tree file (optional): contrast.tree
Phylip contrast program output file [contrast.fcontrast]:
Output written to file "contrast.fcontrast"
Done.
Continuous character contrasts
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] frequencies File containing one or more sets of data
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fcontrast] Phylip contrast program output
file
Additional (Optional) qualifiers (* if not always prompted):
-varywithin boolean [N] Within-population variation in data
* -[no]reg boolean [Y] Print out correlations and regressions
* -writecont boolean [N] Print out contrasts
* -[no]nophylo boolean [Y] LRT test of no phylogenetic component,
with and without VarA
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
frequencies
File containing one or more sets of data
Frequency value(s)
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip contrast program output file
Output file
<*>.fcontrast
Additional (Optional) qualifiers
-varywithin
boolean
Within-population variation in data
Boolean value Yes/No
No
-[no]reg
boolean
Print out correlations and regressions
Boolean value Yes/No
Yes
-writecont
boolean
Print out contrasts
Boolean value Yes/No
No
-[no]nophylo
boolean
LRT test of no phylogenetic component, with and without VarA
Boolean value Yes/No
Yes
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fcontrast reads continuous character data.
Continuous character data
The programs in this group use gene frequencies and quantitative
character values. One (CONTML) constructs maximum likelihood estimates
of the phylogeny, another (GENDIST) computes genetic distances for use
in the distance matrix programs, and the third (CONTRAST) examines
correlation of traits as they evolve along a given phylogeny.
When the gene frequencies data are used in CONTML or GENDIST, this
involves the following assumptions:
Different lineages evolve independently.
After two lineages split, their characters change independently.
Each gene frequency changes by genetic drift, with or without mutation
(this varies from method to method).
Different loci or characters drift independently.
How these assumptions affect the methods will be seen in my papers on
inference of phylogenies from gene frequency and continuous character
data (Felsenstein, 1973b, 1981c, 1985c).
The input formats are fairly similar to the discrete-character
programs, but with one difference. When CONTML is used in the
gene-frequency mode (its usual, default mode), or when GENDIST is
used, the first line contains the number of species (or populations)
and the number of loci and the options information. There then follows
a line which gives the numbers of alleles at each locus, in
order. This must be the full number of alleles, not the number of
alleles which will be input: i. e. for a two-allele locus the number
should be 2, not 1. There then follow the species (population) data,
each species beginning on a new line. The first 10 characters are
taken as the name, and thereafter the values of the individual
characters are read free-format, preceded and separated by
blanks. They can go to a new line if desired, though of course not in
the middle of a number. Missing data is not allowed - an important
limitation. In the default configuration, for each locus, the numbers
should be the frequencies of all but one allele. The menu option A
(All) signals that the frequencies of all alleles are provided in the
input data -- the program will then automatically ignore the last of
them. So without the A option, for a three-allele locus there should
be two numbers, the frequencies of two of the alleles (and of course
it must always be the same two!). Here is a typical data set without
the A option:
The first line has the number of species (or populations) and the
number of loci. The second line has the number of alleles for each of
the 3 loci. The species lines have names (filled out to 10 characters
with blanks) followed by the gene frequencies of the 2 alleles for the
first locus, the 3 alleles for the second locus, and the 2 alleles for
the third locus. You can start a new line after any of these allele
frequencies, and continue to give the frequencies on that line
(without repeating the species name).
If all alleles of a locus are given, it is important to have them add
up to 1. Roundoff of the frequencies may cause the program to conclude
that the numbers do not sum to 1, and stop with an error message.
While many compilers may be more tolerant, it is probably wise to make
sure that each number, including the first, is preceded by a blank,
and that there are digits both preceding and following any decimal
points.
CONTML and CONTRAST also treat quantitative characters (the
continuous-characters mode in CONTML, which is option C). It is
assumed that each character is evolving according to a Brownian motion
model, at the same rate, and independently. In reality it is almost
always impossible to guarantee this. The issue is discussed at length
in my review article in Annual Review of Ecology and Systematics
(Felsenstein, 1988a), where I point out the difficulty of transforming
the characters so that they are not only genetically independent but
have independent selection acting on them. If you are going to use
CONTML to model evolution of continuous characters, then you should at
least make some attempt to remove genetic correlations between the
characters (usually all one can do is remove phenotypic correlations
by transforming the characters so that there is no within-population
covariance and so that the within-population variances of the
characters are equal -- this is equivalent to using Canonical
Variates). However, this will only guarantee that one has removed
phenotypic covariances between characters. Genetic covariances could
only be removed by knowing the coheritabilities of the characters,
which would require genetic experiments, and selective covariances
(covariances due to covariation of selection pressures) would require
knowledge of the sources and extent of selection pressure in all
variables.
CONTRAST is a program designed to infer, for a given phylogeny that is
provided to the program, the covariation between characters in a data
set. Thus we have a program in this set that allow us to take
information about the covariation and rates of evolution of characters
and make an estimate of the phylogeny (CONTML), and a program that
takes an estimate of the phylogeny and infers the variances and
covariances of the character changes. But we have no program that
infers both the phylogenies and the character covariation from the
same data set.
In the quantitative characters mode, a typical small data set would be:
Note that in the latter case, there is no line giving the numbers of
alleles at each locus. In this latter case no square-root
transformation of the coordinates is done: each is assumed to give
directly the position on the Brownian motion scale.
For further discussion of options and modifiable constants in CONTML,
GENDIST, and CONTRAST see the documentation files for those programs.
fcontrast statistics that are printed out include the
covariances between all pairs of characters, the regressions of each
character on each other (column j is regressed on row i), and the
correlations between all pairs of characters. In assessing degress of
freedom it is important to realize that each contrast was taken to
have expectation zero, which is known because each contrast could as
easily have been computed xi-xj instead of xj-xi. Thus there is no
loss of a degree of freedom for estimation of a mean. The degrees of
freedom is thus the same as the number of contrasts, namely one less
than the number of species (tips). If you feed these contrasts into a
multivariate statistics program make sure that it knows that each
variable has expectation exactly zero.
With the W option selected, the covariances, correlations, and
regressions for the "additive" (between-species evolutionary
variation) and "environmental" (within-species phenotypic variation)
are printed out (the maximum likelihood estimates of each). The
program also estimates the within-species phenotypic variation in the
case where the between-species evolutionary covariances are forced to
be zero. The log-likelihoods of these two cases are compared and a
likelihood ratio test (LRT) is carried out. The program prints the
result of this test as a chi-square variate, and gives the number of
degrees of freedom of the LRT. You have to look up the chi-square
variable on a table of the chi-square distribution. The A option is
available (if the W option is invoked) to allow you to turn off the
doing of this test if you want to.
Please help by correcting and extending the Wiki pages.
Function
DNA compatibility algorithm
Description
Estimates phylogenies from nucleic acid sequence data using the
compatibility criterion, which searches for the largest number of
sites which could have all states (nucleotides) uniquely evolved on
the same tree. Compatibility is particularly appropriate when sites
vary greatly in their rates of evolution, but we do not know in
advance which are the less reliable ones.
Algorithm
This program implements the compatibility method for DNA sequence
data. For a four-state character without a character-state tree, as in
DNA sequences, the usual clique theorems cannot be applied. The
approach taken in this program is to directly evaluate each tree
topology by counting how many substitutions are needed in each site,
comparing this to the minimum number that might be needed (one less
than the number of bases observed at that site), and then evaluating
the number of sites which achieve the minimum number. This is the
evaluation of the tree (the number of compatible sites), and the
topology is chosen so as to maximize that number.
Compatibility methods originated with Le Quesne's (1969) suggestion
that one ought to look for trees supported by the largest number of
perfectly fitting (compatible) characters. Fitch (1975) showed by
counterexample that one could not use the pairwise compatibility
methods used in CLIQUE to discover the largest clique of jointly
compatible characters.
The assumptions of this method are similar to those of CLIQUE. In a
paper in the Biological Journal of the Linnean Society (1981b) I
discuss this matter extensively. In effect, the assumptions are that:
Each character evolves independently.
Different lineages evolve independently.
The ancestral base at each site is unknown.
The rates of change in most sites over the time spans involved in the the divergence of the group are very small.
A few of the sites have very high rates of change.
We do not know in advance which are the high and which the low rate sites.
That these are the assumptions of compatibility methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that arguments such as
mine are invalid and that parsimony (and perhaps compatibility)
methods make no substantive assumptions such as these, see the papers
by Farris (1983) and Sober (1983a, 1983b, 1988), but also read the
exchange between Felsenstein and Sober (1986).
There is, however, some reason to believe that the present criterion
is not the proper way to correct for the presence of some sites with
high rates of change in nucleotide sequence data. It can be argued
that sites showing more than two nucleotide states, even if those are
compatible with the other sites, are also candidates for sites with
high rates of change. It might then be more proper to use DNAPARS with
the Threshold option with a threshold value of 2.
Change from an occupied site to a gap is counted as one
change. Reversion from a gap to an occupied site is allowed and is
also counted as one change. Note that this in effect assumes that a
gap N bases long is N separate events. This may be an
overcorrection. When we have nonoverlapping gaps, we could instead
code a gap as a single event by changing all but the first "-" in the
gap into "?" characters. In this way only the first base of the gap
causes the program to infer a change.
If the U (User Tree) option is used and more than one tree is
supplied, the program also performs a statistical test of each of
these trees against the one with highest likelihood. If there are two
user trees, the test done is one which is due to Kishino and Hasegawa
(1989), a version of a test originally introduced by Templeton
(1983). In this implementation it uses the mean and variance of
weighted compatibility differences between trees, taken across
sites. If the two trees compatibilities are more than 1.96 standard
deviations different then the trees are declared significantly
different.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of weighted
compatibilities of sites are computed for all pairs of trees. To test
whether the difference between each tree and the best one is larger
than could have been expected if they all had the same expected
compatibility, compatibilities for all trees are sampled with these
covariances and equal means (Shimodaira and Hasegawa's "least
favorable hypothesis"), and a P value is computed from the fraction of
times the difference between the tree's value and the highest
compatibility exceeds that actually observed. Note that this sampling
needs random numbers, and so the program will prompt the user for a
random number seed if one has not already been supplied. With the
two-tree KHT test no random numbers are used.
In either the KHT or the SH test the program prints out a table of the
compatibility of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the compatibility
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one.
The algorithm is a straightforward modification of DNAPARS, but with
some extra machinery added to calculate, as each species is added, how
many base changes are the minimum which could be required at that
site. The program runs fairly quickly.
Usage
Here is a sample session with fdnacomp
% fdnacomp -ancseq -stepbox -printdata
DNA compatibility algorithm
Input (aligned) nucleotide sequence set(s): dnacomp.dat
Phylip tree file (optional):
Phylip weights file (optional):
Phylip dnacomp program output file [dnacomp.fdnacomp]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
Output written to file "dnacomp.fdnacomp"
Trees also written onto file "dnacomp.treefile"
% fdnacomp
DNA compatibility algorithm
Input (aligned) nucleotide sequence set(s): dnacomp.dat
Phylip tree file (optional): dnacomptree.dat
Phylip weights file (optional):
Phylip dnacomp program output file [dnacomp.fdnacomp]:
Output written to file "dnacomp.fdnacomp"
Trees also written onto file "dnacomp.treefile"
DNA compatibility algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
-weights properties Phylip weights file (optional)
[-outfile] outfile [*.fdnacomp] Phylip dnacomp program output
file
Additional (Optional) qualifiers (* if not always prompted):
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnacomp] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print steps & compatibility at sites
-ancseq boolean [N] Print sequences at all nodes of tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
-weights
properties
Phylip weights file (optional)
Property value(s)
[-outfile] (Parameter 3)
outfile
Phylip dnacomp program output file
Output file
<*>.fdnacomp
Additional (Optional) qualifiers
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdnacomp
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-stepbox
boolean
Print steps & compatibility at sites
Boolean value Yes/No
No
-ancseq
boolean
Print sequences at all nodes of tree
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fdnacomp output is standard: if option 1 is toggled on, the
data is printed out, with the convention that "." means "the same as
in the first species". Then comes a list of equally parsimonious
trees, and (if option 2 is toggled on) a table of the number of
changes of state required in each character. If option 5 is toggled
on, a table is printed out after each tree, showing for each branch
whether there are known to be changes in the branch, and what the
states are inferred to have been at the top end of the branch. If the
inferred state is a "?" or one of the IUB ambiguity symbols, there
will be multiple equally-parsimonious assignments of states; the user
must work these out for themselves by hand. A "?" in the reconstructed
states means that in addition to one or more bases, a gap may or may
not be present. If option 6 is left in its default state the trees
found will be written to a tree file, so that they are available to be
used in other programs. If the program finds multiple trees tied for
best, all of these are written out onto the output tree file. Each is
followed by a numerical weight in square brackets (such as
[0.25000]). This is needed when we use the trees to make a consensus
tree of the results of bootstrapping or jackknifing, to avoid
overrepresenting replicates that find many tied trees.
Output files for usage example
File: dnacomp.fdnacomp
DNA compatibility algorithm, version 3.69.650
5 species, 13 sites
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
One most parsimonious tree found:
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
total number of compatible sites is 11.0
steps in each site:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0| 2 1 3 2 0 2 1 1 1
10| 1 1 1 3
compatibility (Y or N) of each site with this tree:
0123456789
*----------
0 ! YYNYYYYYY
10 !YYYN
From To Any Steps? State at upper node
1 AABGTSGCCA AAY
1 2 maybe AABGTCGCCA AAY
2 3 yes VAKDTCGCCA CAY
3 4 yes GGKATCTCGG CCY
4 Epsilon maybe GGGATCTCGG CCC
4 Delta yes GGTATTTCGG CCT
3 Gamma yes CATTTCGTCA CAA
2 Beta maybe AAGGTCGCCA AAC
1 Alpha maybe AACGTGGCCA AAT
File: dnacomp.treefile
((((Epsilon,Delta),Gamma),Beta),Alpha);
Output files for usage example 2
File: dnacomp.fdnacomp
DNA compatibility algorithm, version 3.69.650
User-defined tree:
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
total number of compatible sites is 11.0
Please help by correcting and extending the Wiki pages.
Function
Gene frequency and continuous character maximum likelihood
Description
Estimates phylogenies from gene frequency data by maximum likelihood
under a model in which all divergence is due to genetic drift in the
absence of new mutations. Does not assume a molecular clock. An
alternative method of analyzing this data is to compute Nei's genetic
distance and use one of the distance matrix programs. This program can
also do maximum likelihood analysis of continuous characters that
evolve by a Brownian Motion model, but it assumes that the characters
evolve at equal rates and in an uncorrelated fashion, so that it does
not take into account the usual correlations of characters.
Algorithm
This program estimates phylogenies by the restricted maximum
likelihood method based on the Brownian motion model. It is based on
the model of Edwards and Cavalli-Sforza (1964; Cavalli-Sforza and
Edwards, 1967). Gomberg (1966), Felsenstein (1973b, 1981c) and
Thompson (1975) have done extensive further work leading to efficient
algorithms. CONTML uses restricted maximum likelihood estimation
(REML), which is the criterion used by Felsenstein (1973b). The actual
algorithm is an iterative EM Algorithm (Dempster, Laird, and Rubin,
1977) which is guaranteed to always give increasing likelihoods. The
algorithm is described in detail in a paper of mine (Felsenstein,
1981c), which you should definitely consult if you are going to use
this program. Some simulation tests of it are given by Rohlf and
Wooten (1988) and Kim and Burgman (1988).
The default (gene frequency) mode treats the input as gene frequencies
at a series of loci, and square-root-transforms the allele frequencies
(constructing the frequency of the missing allele at each locus
first). This enables us to use the Brownian motion model on the
resulting coordinates, in an approximation equivalent to using
Cavalli-Sforza and Edwards's (1967) chord measure of genetic distance
and taking that to give distance between particles undergoing pure
Brownian motion. It assumes that each locus evolves independently by
pure genetic drift.
The alternative continuous characters mode (menu option C) treats the
input as a series of coordinates of each species in N dimensions. It
assumes that we have transformed the characters to remove correlations
and to standardize their variances.
A word about microsatellite data
Many current users of CONTML use it to analyze microsatellite
data. There are three ways to do this:
Coding each copy number as an allele, and feeding in the frequencies
of these alleles. As CONTML's gene frequency mode assumes that all
change is by genetic drift, this means that no copy number arises by
mutation during the divergence of the populations. Since
microsatellite loci have very high mutation rates, this is
questionable.
Use some other program, one not in the PHYLIP package, to compute
distances among the populations. Some of the programs that can do this
are RSTCalc, poptrfdos, Microsat, and Populations. Links to them can
be found at my Phylogeny Programs web site at
http://evolution.gs.washington.edu/phylip/software.html.
Those distance measures allow for mutation during the divergence of
the populations. But even they are not perfect -- they do not allow us
to use all the information contained in the gene frequency differences
of within a copy number allele. There is a need for a more complete
statistical treatment of inference of phylogenies from microsatellite
models, ones that take both mutation and genetic drift fully into
account.
Alternatively, there is the Brownian motion approximation to mean
population copy number. This is described in my book (Felsenstein,
2004, Chapter 15, pp. 242-245), and it is implicit also in the
microsatellite distances. Each locus is coded as a single continuous
character, the mean of the copy number in at that microsatellite locus
in that species. Thus if the species (or population) has frequencies
0.10, 0.24, 0.60, and 0.06 of alleles that have 18, 19, 20, and 21
copies, it is coded as having
0.10 X 18 + 0.24 X 19 + 0.60 X 20 + 0.06 X 21 = 19.62
copies. These values can, I believe, be calculated by a spreadsheet
program. Each microsatellite is represented by one character, and the
continuous character mode of CONTML is used (not the gene frequencies
mode). This coding allows for mutation that changes copy number. It
does not make complete use of all data, but neither does the treatment
of microsatellite gene frequencies as changing only genetic
drift. frequency
Usage
Here is a sample session with fcontml
% fcontml -printdata
Gene frequency and continuous character maximum likelihood
Input file: contml.dat
Phylip tree file (optional):
Phylip contml program output file [contml.fcontml]:
Adding species:
1. European
2. African
3. Chinese
4. American
5. Australian
Output written to file "contml.fcontml"
Tree also written onto file "contml.treefile"
Done.
Gene frequency and continuous character maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] frequencies File containing one or more sets of data
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fcontml] Phylip contml program output
file
Additional (Optional) qualifiers (* if not always prompted):
-datatype menu [g] Input type in infile (Values: g (Gene
frequencies); i (Continuous characters))
* -lengths boolean [N] Use branch lengths from user trees
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fcontml] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
frequencies
File containing one or more sets of data
Frequency value(s)
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip contml program output file
Output file
<*>.fcontml
Additional (Optional) qualifiers
-datatype
list
Input type in infile
g
(Gene frequencies)
i
(Continuous characters)
g
-lengths
boolean
Use branch lengths from user trees
Boolean value Yes/No
No
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-global
boolean
Global rearrangements
Boolean value Yes/No
No
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fcontml
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fcontml reads continuous character data.
Continuous character data
The programs in this group use gene frequencies and quantitative
character values. One (CONTML) constructs maximum likelihood estimates
of the phylogeny, another (GENDIST) computes genetic distances for use
in the distance matrix programs, and the third (CONTRAST) examines
correlation of traits as they evolve along a given phylogeny.
When the gene frequencies data are used in CONTML or GENDIST, this
involves the following assumptions:
Different lineages evolve independently.
After two lineages split, their characters change independently.
Each gene frequency changes by genetic drift, with or without mutation
(this varies from method to method).
Different loci or characters drift independently.
How these assumptions affect the methods will be seen in my papers on
inference of phylogenies from gene frequency and continuous character
data (Felsenstein, 1973b, 1981c, 1985c).
The input formats are fairly similar to the discrete-character
programs, but with one difference. When CONTML is used in the
gene-frequency mode (its usual, default mode), or when GENDIST is
used, the first line contains the number of species (or populations)
and the number of loci and the options information. There then follows
a line which gives the numbers of alleles at each locus, in
order. This must be the full number of alleles, not the number of
alleles which will be input: i. e. for a two-allele locus the number
should be 2, not 1. There then follow the species (population) data,
each species beginning on a new line. The first 10 characters are
taken as the name, and thereafter the values of the individual
characters are read free-format, preceded and separated by
blanks. They can go to a new line if desired, though of course not in
the middle of a number. Missing data is not allowed - an important
limitation. In the default configuration, for each locus, the numbers
should be the frequencies of all but one allele. The menu option A
(All) signals that the frequencies of all alleles are provided in the
input data -- the program will then automatically ignore the last of
them. So without the A option, for a three-allele locus there should
be two numbers, the frequencies of two of the alleles (and of course
it must always be the same two!). Here is a typical data set without
the A option:
The first line has the number of species (or populations) and the
number of loci. The second line has the number of alleles for each of
the 3 loci. The species lines have names (filled out to 10 characters
with blanks) followed by the gene frequencies of the 2 alleles for the
first locus, the 3 alleles for the second locus, and the 2 alleles for
the third locus. You can start a new line after any of these allele
frequencies, and continue to give the frequencies on that line
(without repeating the species name).
If all alleles of a locus are given, it is important to have them add
up to 1. Roundoff of the frequencies may cause the program to conclude
that the numbers do not sum to 1, and stop with an error message.
While many compilers may be more tolerant, it is probably wise to make
sure that each number, including the first, is preceded by a blank,
and that there are digits both preceding and following any decimal
points.
CONTML and CONTRAST also treat quantitative characters (the
continuous-characters mode in CONTML, which is option C). It is
assumed that each character is evolving according to a Brownian motion
model, at the same rate, and independently. In reality it is almost
always impossible to guarantee this. The issue is discussed at length
in my review article in Annual Review of Ecology and Systematics
(Felsenstein, 1988a), where I point out the difficulty of transforming
the characters so that they are not only genetically independent but
have independent selection acting on them. If you are going to use
CONTML to model evolution of continuous characters, then you should at
least make some attempt to remove genetic correlations between the
characters (usually all one can do is remove phenotypic correlations
by transforming the characters so that there is no within-population
covariance and so that the within-population variances of the
characters are equal -- this is equivalent to using Canonical
Variates). However, this will only guarantee that one has removed
phenotypic covariances between characters. Genetic covariances could
only be removed by knowing the coheritabilities of the characters,
which would require genetic experiments, and selective covariances
(covariances due to covariation of selection pressures) would require
knowledge of the sources and extent of selection pressure in all
variables.
CONTRAST is a program designed to infer, for a given phylogeny that is
provided to the program, the covariation between characters in a data
set. Thus we have a program in this set that allow us to take
information about the covariation and rates of evolution of characters
and make an estimate of the phylogeny (CONTML), and a program that
takes an estimate of the phylogeny and infers the variances and
covariances of the character changes. But we have no program that
infers both the phylogenies and the character covariation from the
same data set.
In the quantitative characters mode, a typical small data set would be:
Note that in the latter case, there is no line giving the numbers of
alleles at each locus. In this latter case no square-root
transformation of the coordinates is done: each is assumed to give
directly the position on the Brownian motion scale.
For further discussion of options and modifiable constants in CONTML,
GENDIST, and CONTRAST see the documentation files for those programs.
fcontml output has a standard appearance. The topology of the
tree is given by an unrooted tree diagram. The lengths (in time or in
expected amounts of variance) are given in a table below the topology,
and a rough confidence interval given for each length. Negative lower
bounds on length indicate that rearrangements may be acceptable.
The units of length are amounts of expected accumulated variance (not
time). The log likelihood (natural log) of each tree is also given,
and it is indicated how many topologies have been tried. The tree does
not necessarily have all tips contemporary, and the log likelihood may
be either positive or negative (this simply corresponds to whether the
density function does or does not exceed 1) and a negative log
likelihood does not indicate any error. The log likelihood allows
various formal likelihood ratio hypothesis tests. The description of
the tree includes approximate standard errors on the lengths of
segments of the tree. These are calculated by considering only the
curvature of the likelihood surface as the length of the segment is
varied, holding all other lengths constant. As such they are most
probably underestimates of the variance, and hence may give too much
confidence in the given tree.
One should use caution in interpreting the likelihoods that are
printed out. If the model is wrong, it will not be possible to use the
likelihoods to make formal statistical statements. Thus, if gene
frequencies are being analyzed, but the gene frequencies change not
only by genetic drift, but also by mutation, the model is not
correct. It would be as well-justified in this case to use GENDIST to
compute the Nei (1972) genetic distance and then use FITCH, KITSCH or
NEIGHBOR to make a tree. If continuous characters are being analyzed,
but if the characters have not been transformed to new coordinates
that evolve independently and at equal rates, then the model is also
violated and no statistical analysis is possible. Doing such a
transformation is not easy, and usually not even possible.
If the U (User Tree) option is used and more than one tree is
supplied, the program also performs a statistical test of each of
these trees against the one with highest likelihood. If there are two
user trees, the test done is one which is due to Kishino and Hasegawa
(1989), a version of a test originally introduced by Templeton
(1983). In this implementation it uses the mean and variance of
log-likelihood differences between trees, taken across loci. If the
two trees means are more than 1.96 standard deviations different then
the trees are declared significantly different. This use of the
empirical variance of log-likelihood differences is more robust and
nonparametric than the classical likelihood ratio test, and may to
some extent compensate for the any lack of realism in the model
underlying this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. The version
used here is a multivariate normal approximation to their test; it is
due to Shimodaira (1998). The variances and covariances of the sum of
log likelihoods across loci are computed for all pairs of trees. To
test whether the difference between each tree and the best one is
larger than could have been expected if they all had the same expected
log-likelihood, log-likelihoods for all trees are sampled with these
covariances and equal means (Shimodaira and Hasegawa's "least
favorable hypothesis"), and a P value is computed from the fraction of
times the difference between the tree's value and the highest
log-likelihood exceeds that actually observed. Note that this sampling
needs random numbers, and so the program will prompt the user for a
random number seed if one has not already been supplied. With the
two-tree KHT test no random numbers are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one.
One problem which sometimes arises is that the program is fed two
species (or populations) with identical transformed gene frequencies:
this can happen if sample sizes are small and/or many loci are
monomorphic. In this case the program "gets its knickers in a twist"
and can divide by zero, usually causing a crash. If you suspect that
this has happened, check for two species with identical
coordinates. If you find them, eliminate one from the problem: the two
must always show up as being at the same point on the tree anyway.
Please help by correcting and extending the Wiki pages.
Function
Calculate distance between two sets of trees
Description
Computes the Branch Score distance between trees, which allows for
differences in tree topology and which also makes use of branch
lengths. Also computes the Robinson-Foulds symmetric difference
distance between trees, which allows for differences in tree topology
but does not use branch lengths.
Algorithm
This program computes distances between trees. Two distances are
computed, the Branch Score Distance of Kuhner and Felsenstein (1994),
and the more widely known Symmetric Difference of Robinson and Foulds
(1981). The Branch Score Distance uses branch lengths, and can only be
calculated when the trees have lengths on all branches. The Symmetric
Difference does not use branch length information, only the tree
topologies. It must also be borne in mind that neither distance has
any immediate statistical interpretation -- we cannot say whether a
larger distance is significantly larger than a smaller one.
These distances are computed by considering all possible branches that
could exist on the the two trees. Each branch divides the set of
species into two groups -- the ones connected to one end of the branch
and the ones connected to the other. This makes a partition of the
full set of species. (in Newick notation)
((A,C),(D,(B,E)))
has two internal branches. One induces the partition {A, C | B, D, E}
and the other induces the partition {A, C, D | B, E}. A different tree
with the same set of species,
(((A,D),C),(B,E))
has internal branches that correspond to the two partitions {A, C, D |
B, E} and {A, D | B, C, E}. Note that the other branches, all of which
are external branches, induce partitions that separate one species
from all the others. Thus there are 5 partitions like this: {C | A, B,
D, E} on each of these trees. These are always present on all trees,
provided that each tree has each species at the end of its own branch.
In the case of the Branch Score distance, each partition that does
exist on a tree also has a branch length associated with it. Thus if
the tree is
The list of partitions and their branch lengths is:
{A | B, C, D, E} 0.1
{D | A, B, C, E} 0.25
{A, D | B, C, E} 0.05
{C | A, B, D, E} 0.01
{A, D, C | B, E} 0.4
{B | A, C, D, E} 0.3
{E | A, B, C, D} 0.8
Note that the tree is being treated as unrooted here, so that the
branch lengths on either side of the rootmost node are summed up to
get a branch length of 0.4.
The Branch Score Distance imagines us as having made a list of all
possible partitions, the ones shown above and also all 7 other
possible partitions, which correspond to branches that are not found
in this tree. These are assigned branch lengths of 0. For two trees,
we imagine constructing these lists, and then summing the squared
differences between the branch lengths. Thus if both trees have
branches {A, D | B, C, E}, the sum contains the square of the
difference between the branch lengths. If one tree has the branch and
the other doesn't, it contains the square of the difference between
the branch length and zero (in other words, the square of that branch
length). If both trees do not have a particular branch, nothing is
added to the sum because the difference is then between 0 and 0.
The Branch Score Distance takes this sum of squared differences and
computes its square root. Note that it has some desirable
properties. When small branches differ in tree topology, it is not
very big. When branches are both present but differ in length, it is
affected.
The Symmetric Difference is simply a count of how many partitions
there are, among the two trees, that are on one tree and not on the
other. In the example above there are two partitions, {A, C | B, D, E}
and {A, D | B, C, E}, each of which is present on only one of the two
trees. The Symmetric Difference between the two trees is therefore
2. When the two trees are fully resolved bifurcating trees, their
symmetric distance must be an even number; it can range from 0 to
twice the number of internal branches, which for n species is 4n-6.
Note the relationship between the two distances. If all trees have all
their branches have length 1.0, the Branch Score Distance is the
square of the Symmetric Difference, as each branch that is present in
one but not in the other results in 1.0 being added to the sum of
squared differences.
We have assumed that nothing is lost if the trees are treated as
unrooted trees. It is easy to define a counterpart to the Branch Score
Distance and one to the Symmetric Difference for these rooted
trees. Each branch then defines a set of species, namely the clade
defined by that branch. Thus if the first of the two trees above were
considered as a rooted tree it would define the three clades {A, C},
{B, D, E}, and {B, E}. The Branch Score Distance is computed from the
branch lengths for all possible sets of species, with 0 put for each
set that does not occur on that tree. The table above will be nearly
the same, but with two entries instead of one for the sets on either
side of the root, {A C D} and {B E}. The Symmetric Difference between
two rooted trees is simply the count of the number of clades that are
defined by one but not by the other. For the second tree the clades
would be {A, D}, {B, C, E}, and {B, E}. The Symmetric Difference
between thee two rooted trees would then be 4.
Although the examples we have discussed have involved fully
bifurcating trees, the input trees can have multifurcations. This does
not cause any complication for the Branch Score Distance. For the
Symmetric Difference, it can lead to distances that are odd numbers.
However, note one strong restriction. The trees should all have the
same list of species. If you use one set of species in the first two
trees, and another in the second two, and choose distances for
adjacent pairs, the distances will be incorrect and will depend on the
order of these pairs in the input tree file, in odd ways.
Usage
Here is a sample session with ftreedistpair
% ftreedistpair -style s
Calculate distance between two sets of trees
Phylip tree file: treedist.dat
Second phylip tree file: treedist.dat
Phylip treedist program output file [treedist.ftreedistpair]:
Done.
Calculate distance between two sets of trees
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-bintreefile] tree Second phylip tree file
[-outfile] outfile [*.ftreedistpair] Phylip treedist program
output file
Additional (Optional) qualifiers:
-dtype menu [b] Distance type (Values: s (Symmetric
difference); b (Branch score distance))
-pairing menu [l] Tree pairing method (Values: c
(Distances between corresponding pairs each
tree file); l (Distances between all
possible pairs in each tree file))
-style menu [v] Distances output option (Values: f
(Full_matrix); v (Verbose, one pair per
line); s (Sparse, one pair per line))
-noroot boolean [N] Trees to be treated as rooted
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-progress boolean [N] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-intreefile] (Parameter 1)
tree
Phylip tree file
Phylogenetic tree
[-bintreefile] (Parameter 2)
tree
Second phylip tree file
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip treedist program output file
Output file
<*>.ftreedistpair
Additional (Optional) qualifiers
-dtype
list
Distance type
s
(Symmetric difference)
b
(Branch score distance)
b
-pairing
list
Tree pairing method
c
(Distances between corresponding pairs each tree file)
l
(Distances between all possible pairs in each tree file)
l
-style
list
Distances output option
f
(Full_matrix)
v
(Verbose, one pair per line)
s
(Sparse, one pair per line)
v
-noroot
boolean
Trees to be treated as rooted
Boolean value Yes/No
No
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-progress
boolean
Print indications of progress of run
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
ftreedistpair reads two input tree files. The tree files may
either have the number of trees on their first line, or not. If the
number of trees is given, it is actually ignored and all trees in the
tree file are considered, even if there are more trees than indicated
by the number. There is no maximum number of trees that can be
processed but, if you feed in too many, there may be an error message
about running out of memory. The problem is particularly acute if you
choose the option to examine all possible pairs of trees one from each
of two input tree files. Thus if there are 1,000 trees in the input
tree file, keep in mind that all possible pairs means 1,000,000 pairs
to be examined!
If any of the four types of analysis are selected, the user must
specify how they want the results presented.
The Full matrix (choice F) is a table showing all distances. It is
written onto the output file. The table is presented as groups of 10
columns. Here is the Full matrix for the 12 trees in the input tree
file which is given as an example at the end of this page.
The Full matrix is only available for analyses P and L (not for A or
C).
Option V (Verbose) writes one distance per line. The Verbose output is
the default. Here it is for the example data set given below:
Tree distance program, version 3.6
Symmetric differences between adjacent pairs of trees:
Trees 1 and 2: 4
Trees 3 and 4: 10
Trees 5 and 6: 4
Trees 7 and 8: 4
Trees 9 and 10: 4
Trees 11 and 12: 10
Option S (Sparse or terse) is similar except that all that is given on
each line are the numbers of the two trees and the distance, separated
by blanks. This may be a convenient format if you want to write a
program to read these numbers in, and you want to spare yourself the
effort of having the program wade through the words on each line in
the Verbose output. The first four lines of the Sparse output are
titles that your program would want to skip past. Here is the Sparse
output for the example trees.
Please help by correcting and extending the Wiki pages.
Function
Penny algorithm for DNA
Description
Finds all most parsimonious phylogenies for nucleic acid sequences by
branch-and-bound search. This may not be practical (depending on the
data) for more than 10-11 species or so.
Algorithm
DNAPENNY is a program that will find all of the most parsimonious
trees implied by your data when the nucleic acid sequence parsimony
criterion is employed. It does so not by examining all possible trees,
but by using the more sophisticated "branch and bound" algorithm, a
standard computer science search strategy first applied to
phylogenetic inference by Hendy and Penny (1982). (J. S. Farris
[personal communication, 1975] had also suggested that this strategy,
which is well-known in computer science, might be applied to
phylogenies, but he did not publish this suggestion).
There is, however, a price to be paid for the certainty that one has
found all members of the set of most parsimonious trees. The problem
of finding these has been shown (Graham and Foulds, 1982; Day, 1983)
to be NP-complete, which is equivalent to saying that there is no fast
algorithm that is guaranteed to solve the problem in all cases (for a
discussion of NP-completeness, see the Scientific American article by
Lewis and Papadimitriou, 1978). The result is that this program,
despite its algorithmic sophistication, is VERY SLOW.
The program should be slower than the other tree-building programs in
the package, but useable up to about ten species. Above this it will
bog down rapidly, but exactly when depends on the data and on how much
computer time you have (it may be more effective in the hands of
someone who can let a microcomputer grind all night than for someone
who has the "benefit" of paying for time on the campus mainframe
computer). IT IS VERY IMPORTANT FOR YOU TO GET A FEEL FOR HOW LONG THE
PROGRAM WILL TAKE ON YOUR DATA. This can be done by running it on
subsets of the species, increasing the number of species in the run
until you either are able to treat the full data set or know that the
program will take unacceptably long on it. (Making a plot of the
logarithm of run time against species number may help to project run
times).
The Algorithm
The search strategy used by DNAPENNY starts by making a tree
consisting of the first two species (the first three if the tree is to
be unrooted). Then it tries to add the next species in all possible
places (there are three of these). For each of the resulting trees it
evaluates the number of base substitutions. It adds the next species
to each of these, again in all possible spaces. If this process would
continue it would simply generate all possible trees, of which there
are a very large number even when the number of species is moderate
(34,459,425 with 10 species). Actually it does not do this, because
the trees are generated in a particular order and some of them are
never generated.
This is because the order in which trees are generated is not quite as
implied above, but is a "depth-first search". This means that first
one adds the third species in the first possible place, then the
fourth species in its first possible place, then the fifth and so on
until the first possible tree has been produced. For each tree the
number of steps is evaluated. Then one "backtracks" by trying the
alternative placements of the last species. When these are exhausted
one tries the next placement of the next-to-last species. The order of
placement in a depth-first search is like this for a four-species case
(parentheses enclose monophyletic groups):
Make tree of first two species: (A,B)
Add C in first place: ((A,B),C)
Add D in first place: (((A,D),B),C)
Add D in second place: ((A,(B,D)),C)
Add D in third place: (((A,B),D),C)
Add D in fourth place: ((A,B),(C,D))
Add D in fifth place: (((A,B),C),D)
Add C in second place: ((A,C),B)
Add D in first place: (((A,D),C),B)
Add D in second place: ((A,(C,D)),B)
Add D in third place: (((A,C),D),B)
Add D in fourth place: ((A,C),(B,D))
Add D in fifth place: (((A,C),B),D)
Add C in third place: (A,(B,C))
Add D in first place: ((A,D),(B,C))
Add D in second place: (A,((B,D),C))
Add D in third place: (A,(B,(C,D)))
Add D in fourth place: (A,((B,C),D))
Add D in fifth place: ((A,(B,C)),D)
Among these fifteen trees you will find all of the four-species rooted
trees, each exactly once (the parentheses each enclose a monophyletic
group). As displayed above, the backtracking depth-first search
algorithm is just another way of producing all possible trees one at a
time. The branch and bound algorithm consists of this with one
change. As each tree is constructed, including the partial trees such
as (A,(B,C)), its number of steps is evaluated. In addition a
prediction is made as to how many steps will be added, at a minimum,
as further species are added.
This is done by counting how many sites which are invariant in the
data up the most recent species added will ultimately show variation
when further species are added. Thus if 20 sites vary among species A,
B, and C and their root, and if tree ((A,C),B) requires 24 steps, then
if there are 8 more sites which will be seen to vary when species D is
added, we can immediately say that no matter how we add D, the
resulting tree can have no less than 24 + 8 = 32 steps. The point of
all this is that if a previously-found tree such as ((A,B),(C,D))
required only 30 steps, then we know that there is no point in even
trying to add D to ((A,C),B). We have computed the bound that enables
us to cut off a whole line of inquiry (in this case five trees) and
avoid going down that particular branch any farther.
The branch-and-bound algorithm thus allows us to find all most
parsimonious trees without generating all possible trees. How much of
a saving this is depends strongly on the data. For very clean (nearly
"Hennigian") data, it saves much time, but on very messy data it will
still take a very long time.
The algorithm in the program differs from the one outlined here in
some essential details: it investigates possibilities in the order of
their apparent promise. This applies to the order of addition of
species, and to the places where they are added to the tree. After the
first two-species tree is constructed, the program tries adding each
of the remaining species in turn, each in the best possible place it
can find. Whichever of those species adds (at a minimum) the most
additional steps is taken to be the one to be added next to the
tree. When it is added, it is added in turn to places which cause the
fewest additional steps to be added. This sounds a bit complex, but it
is done with the intention of eliminating regions of the search of all
possible trees as soon as possible, and lowering the bound on tree
length as quickly as possible. This process of evaluating which
species to add in which order goes on the first time the search makes
a tree; thereafter it uses that order.
The program keeps a list of all the most parsimonious trees found so
far. Whenever it finds one that has fewer losses than these, it clears
out the list and restarts it with that tree. In the process the bound
tightens and fewer possibilities need be investigated. At the end the
list contains all the shortest trees. These are then printed out. It
should be mentioned that the program CLIQUE for finding all largest
cliques also works by branch-and-bound. Both problems are NP-complete
but for some reason CLIQUE runs far faster. Although their worst-case
behavior is bad for both programs, those worst cases occur far more
frequently in parsimony problems than in compatibility problems.
Controlling Run Times
Among the quantities available to be set from the menu of DNAPENNY,
two (howoften and howmany) are of particular importance. As DNAPENNY
goes along it will keep count of how many trees it has
examined. Suppose that howoften is 100 and howmany is 1000, the
default settings. Every time 100 trees have been examined, DNAPENNY
will print out a line saying how many multiples of 100 trees have now
been examined, how many steps the most parsimonious tree found so far
has, how many trees of with that number of steps have been found, and
a very rough estimate of what fraction of all trees have been looked
at so far.
When the number of these multiples printed out reaches the number
howmany (say 1000), the whole algorithm aborts and prints out that it
has not found all most parsimonious trees, but prints out what is has
got so far anyway. These trees need not be any of the most
parsimonious trees: they are simply the most parsimonious ones found
so far. By setting the product (howoften times howmany) large you can
make the algorithm less likely to abort, but then you risk getting
bogged down in a gigantic computation. You should adjust these
constants so that the program cannot go beyond examining the number of
trees you are reasonably willing to pay for (or wait for). In their
initial setting the program will abort after looking at 100,000
trees. Obviously you may want to adjust howoften in order to get more
or fewer lines of intermediate notice of how many trees have been
looked at so far. Of course, in small cases you may never even reach
the first multiple of howoften, and nothing will be printed out except
some headings and then the final trees.
The indication of the approximate percentage of trees searched so far
will be helpful in judging how much farther you would have to go to
get the full search. Actually, since that fraction is the fraction of
the set of all possible trees searched or ruled out so far, and since
the search becomes progressively more efficient, the approximate
fraction printed out will usually be an underestimate of how far along
the program is, sometimes a serious underestimate.
A constant at the beginning of the program that affects the result is
"maxtrees", which controls the maximum number of trees that can be
stored. Thus if maxtrees is 25, and 32 most parsimonious trees are
found, only the first 25 of these are stored and printed out. If
maxtrees is increased, the program does not run any slower but
requires a little more intermediate storage space. I recommend that
maxtrees be kept as large as you can, provided you are willing to look
at an output with that many trees on it! Initially, maxtrees is set to
100 in the distribution copy.
Method and Options
The counting of the length of trees is done by an
algorithm nearly identical to the corresponding algorithms in DNAPARS,
and thus the remainder of this document will be nearly identical to
the DNAPARS document.
This program carries out unrooted parsimony (analogous to Wagner
trees) (Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA
sequences. The method of Fitch (1971) is used to count the number of
changes of base needed on a given tree. The assumptions of this method
are exactly analogous to those of DNAPARS:
Each site evolves independently.
Different lineages evolve independently.
The probability of a base substitution at a given site is small over
the lengths of time involved in a branch of the phylogeny.
The expected amounts of change in different branches of the phylogeny
do not vary by so much that two changes in a high-rate branch are more
probable than one change in a low-rate branch.
The expected amounts of change do not vary enough among sites that two
changes in one site are more probable than one change in another.
Change from an occupied site to a deletion is counted as one
change. Reversion from a deletion to an occupied site is allowed and
is also counted as one change.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b), but also read the exchange
between Felsenstein and Sober (1986).
Change from an occupied site to a deletion is counted as one
change. Reversion from a deletion to an occupied site is allowed and
is also counted as one change. Note that this in effect assumes that a
deletion N bases long is N separate events.
Usage
Here is a sample session with fdnapenny
% fdnapenny
Penny algorithm for DNA
Input (aligned) nucleotide sequence set(s): dnapenny.dat
Phylip dnapenny program output file [dnapenny.fdnapenny]:
justweights: false
numwts: 0
How many
trees looked Approximate
at so far Length of How many percentage
(multiples shortest tree trees this short searched
of 100): found so far found so far so far
---------- ------------ ------------ ------------
1 9.0 2 0.11
2 8.0 3 6.67
3 8.0 9 20.00
4 8.0 9 86.67
Output written to file "dnapenny.fdnapenny"
Trees also written onto file "dnapenny.treefile"
Penny algorithm for DNA
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-outfile] outfile [*.fdnapenny] Phylip dnapenny program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties (no help text) properties value
-howoften integer [100] How often to report, in trees (Any
integer value)
-howmany integer [1000] How many groups of trees (Any integer
value)
-[no]simple boolean [Y] Branch and bound is simple
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1.0] Threshold value (Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnapenny] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print out steps in each site
-ancseq boolean [N] Print sequences at all nodes of tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-outfile] (Parameter 2)
outfile
Phylip dnapenny program output file
Output file
<*>.fdnapenny
Additional (Optional) qualifiers
-weights
properties
(no help text) properties value
Property value(s)
-howoften
integer
How often to report, in trees
Any integer value
100
-howmany
integer
How many groups of trees
Any integer value
1000
-[no]simple
boolean
Branch and bound is simple
Boolean value Yes/No
Yes
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-dothreshold
toggle
Use threshold parsimony
Toggle value Yes/No
No
-threshold
float
Threshold value
Number 1.000 or more
1.0
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdnapenny
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-stepbox
boolean
Print out steps in each site
Boolean value Yes/No
No
-ancseq
boolean
Print sequences at all nodes of tree
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fdnapenny output is standard: if option 1 is toggled on, the
data is printed out, with the convention that "." means "the same as
in the first species". Then comes a list of equally parsimonious
trees, and (if option 2 is toggled on) a table of the number of
changes of state required in each character. If option 5 is toggled
on, a table is printed out after each tree, showing for each branch
whether there are known to be changes in the branch, and what the
states are inferred to have been at the top end of the branch. If the
inferred state is a "?" or one of the IUB ambiguity symbols, there
will be multiple equally-parsimonious assignments of states; the user
must work these out for themselves by hand. A "?" in the reconstructed
states means that in addition to one or more bases, a deletion may or
may not be present. If option 6 is left in its default state the trees
found will be written to a tree file, so that they are available to be
used in other programs. If the program finds multiple trees tied for
best, all of these are written out onto the output tree file. Each is
followed by a numerical weight in square brackets (such as
[0.25000]). This is needed when we use the trees to make a consensus
tree of the results of bootstrapping or jackknifing, to avoid
overrepresenting replicates that find many tied trees.
Output files for usage example
File: dnapenny.fdnapenny
Penny algorithm for DNA, version 3.69.650
branch-and-bound to find all most parsimonious trees
requires a total of 8.000
9 trees in all found
+--------------------Alpha1
!
! +-----------Alpha2
! !
1 +-----4 +--Epsilon
! ! ! +-----6
! ! ! ! +--Delta
! ! +--5
+--2 ! +--Gamma2
! +-----7
! +--Gamma1
!
! +--Beta2
+--------------3
+--Beta1
remember: this is an unrooted tree!
+--------------------Alpha1
!
! +-----------Alpha2
! !
1 +-----4 +--------Gamma2
! ! ! !
! ! +--7 +--Epsilon
! ! ! +--6
+--2 +--5 +--Delta
! !
! +-----Gamma1
!
! +--Beta2
+--------------3
+--Beta1
[Part of this file has been deleted for brevity]
+--5 +--Delta
!
+-----Gamma1
remember: this is an unrooted tree!
+--------------------Alpha1
!
! +-----Alpha2
1 +-----------2
! ! ! +--Beta2
! ! +--3
! ! +--Beta1
+--4
! +-----Gamma2
! +--7
! ! ! +--Epsilon
+--------5 +--6
! +--Delta
!
+--------Gamma1
remember: this is an unrooted tree!
+--------------------Alpha1
!
! +-----Alpha2
1 +-----------2
! ! ! +--Beta2
! ! +--3
! ! +--Beta1
+--4
! +--Epsilon
! +-----6
! ! +--Delta
+--------5
! +--Gamma2
+-----7
+--Gamma1
remember: this is an unrooted tree!
Please help by correcting and extending the Wiki pages.
Function
Calculate distances between trees
Description
Computes the Branch Score distance between trees, which allows for
differences in tree topology and which also makes use of branch
lengths. Also computes the Robinson-Foulds symmetric difference
distance between trees, which allows for differences in tree topology
but does not use branch lengths.
Algorithm
This program computes distances between trees. Two distances are
computed, the Branch Score Distance of Kuhner and Felsenstein (1994),
and the more widely known Symmetric Difference of Robinson and Foulds
(1981). The Branch Score Distance uses branch lengths, and can only be
calculated when the trees have lengths on all branches. The Symmetric
Difference does not use branch length information, only the tree
topologies. It must also be borne in mind that neither distance has
any immediate statistical interpretation -- we cannot say whether a
larger distance is significantly larger than a smaller one.
These distances are computed by considering all possible branches that
could exist on the the two trees. Each branch divides the set of
species into two groups -- the ones connected to one end of the branch
and the ones connected to the other. This makes a partition of the
full set of species. (in Newick notation)
((A,C),(D,(B,E)))
has two internal branches. One induces the partition {A, C | B, D, E}
and the other induces the partition {A, C, D | B, E}. A different tree
with the same set of species,
(((A,D),C),(B,E))
has internal branches that correspond to the two partitions {A, C, D |
B, E} and {A, D | B, C, E}. Note that the other branches, all of which
are external branches, induce partitions that separate one species
from all the others. Thus there are 5 partitions like this: {C | A, B,
D, E} on each of these trees. These are always present on all trees,
provided that each tree has each species at the end of its own branch.
In the case of the Branch Score distance, each partition that does
exist on a tree also has a branch length associated with it. Thus if
the tree is
The list of partitions and their branch lengths is:
{A | B, C, D, E} 0.1
{D | A, B, C, E} 0.25
{A, D | B, C, E} 0.05
{C | A, B, D, E} 0.01
{A, D, C | B, E} 0.4
{B | A, C, D, E} 0.3
{E | A, B, C, D} 0.8
Note that the tree is being treated as unrooted here, so that the
branch lengths on either side of the rootmost node are summed up to
get a branch length of 0.4.
The Branch Score Distance imagines us as having made a list of all
possible partitions, the ones shown above and also all 7 other
possible partitions, which correspond to branches that are not found
in this tree. These are assigned branch lengths of 0. For two trees,
we imagine constructing these lists, and then summing the squared
differences between the branch lengths. Thus if both trees have
branches {A, D | B, C, E}, the sum contains the square of the
difference between the branch lengths. If one tree has the branch and
the other doesn't, it contains the square of the difference between
the branch length and zero (in other words, the square of that branch
length). If both trees do not have a particular branch, nothing is
added to the sum because the difference is then between 0 and 0.
The Branch Score Distance takes this sum of squared differences and
computes its square root. Note that it has some desirable
properties. When small branches differ in tree topology, it is not
very big. When branches are both present but differ in length, it is
affected.
The Symmetric Difference is simply a count of how many partitions
there are, among the two trees, that are on one tree and not on the
other. In the example above there are two partitions, {A, C | B, D, E}
and {A, D | B, C, E}, each of which is present on only one of the two
trees. The Symmetric Difference between the two trees is therefore
2. When the two trees are fully resolved bifurcating trees, their
symmetric distance must be an even number; it can range from 0 to
twice the number of internal branches, which for n species is 4n-6.
Note the relationship between the two distances. If all trees have all
their branches have length 1.0, the Branch Score Distance is the
square of the Symmetric Difference, as each branch that is present in
one but not in the other results in 1.0 being added to the sum of
squared differences.
We have assumed that nothing is lost if the trees are treated as
unrooted trees. It is easy to define a counterpart to the Branch Score
Distance and one to the Symmetric Difference for these rooted
trees. Each branch then defines a set of species, namely the clade
defined by that branch. Thus if the first of the two trees above were
considered as a rooted tree it would define the three clades {A, C},
{B, D, E}, and {B, E}. The Branch Score Distance is computed from the
branch lengths for all possible sets of species, with 0 put for each
set that does not occur on that tree. The table above will be nearly
the same, but with two entries instead of one for the sets on either
side of the root, {A C D} and {B E}. The Symmetric Difference between
two rooted trees is simply the count of the number of clades that are
defined by one but not by the other. For the second tree the clades
would be {A, D}, {B, C, E}, and {B, E}. The Symmetric Difference
between thee two rooted trees would then be 4.
Although the examples we have discussed have involved fully
bifurcating trees, the input trees can have multifurcations. This does
not cause any complication for the Branch Score Distance. For the
Symmetric Difference, it can lead to distances that are odd numbers.
However, note one strong restriction. The trees should all have the
same list of species. If you use one set of species in the first two
trees, and another in the second two, and choose distances for
adjacent pairs, the distances will be incorrect and will depend on the
order of these pairs in the input tree file, in odd ways.
Usage
Here is a sample session with ftreedist
% ftreedist
Calculate distances between trees
Phylip tree file: treedist.dat
Phylip treedist program output file [treedist.ftreedist]:
Output written to file "treedist.ftreedist"
Done.
% ftreedist -dtype s
Calculate distances between trees
Phylip tree file: treedist2.dat
Phylip treedist program output file [treedist2.ftreedist]:
Output written to file "treedist2.ftreedist"
Done.
Calculate distances between trees
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-outfile] outfile [*.ftreedist] Phylip treedist program output
file
Additional (Optional) qualifiers:
-dtype menu [b] Distance type (Values: s (Symmetric
difference); b (Branch score distance))
-pairing menu [a] Tree pairing method (Values: a
(Distances between adjacent pairs in tree
file); p (Distances between all possible
pairs in tree file))
-style menu [v] Distances output option (Values: f (Full
matrix); v (Verbose, one pair per line); s
(Sparse, one pair per line))
-noroot boolean [N] Trees to be treated as rooted
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-intreefile] (Parameter 1)
tree
Phylip tree file
Phylogenetic tree
[-outfile] (Parameter 2)
outfile
Phylip treedist program output file
Output file
<*>.ftreedist
Additional (Optional) qualifiers
-dtype
list
Distance type
s
(Symmetric difference)
b
(Branch score distance)
b
-pairing
list
Tree pairing method
a
(Distances between adjacent pairs in tree file)
p
(Distances between all possible pairs in tree file)
a
-style
list
Distances output option
f
(Full matrix)
v
(Verbose, one pair per line)
s
(Sparse, one pair per line)
v
-noroot
boolean
Trees to be treated as rooted
Boolean value Yes/No
No
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
ftreedist reads one input tree file. If the number of trees is
given, it is actually ignored and all trees in the tree file are
considered, even if there are more trees than indicated by the
number. There is no maximum number of trees that can be processed but,
if you feed in too many, there may be an error message about running
out of memory. The problem is particularly acute if you choose the
option to examine all possible pairs of trees in an input tree
file. Thus if there are 1,000 trees in the input tree file, keep in
mind that all possible pairs means 1,000,000 pairs to be examined!
If any of the four types of analysis are selected, the user must
specify how they want the results presented.
The Full matrix (choice F) is a table showing all distances. It is
written onto the output file. The table is presented as groups of 10
columns. Here is the Full matrix for the 12 trees in the input tree
file which is given as an example at the end of this page.
The Full matrix is only available for analyses P and L (not for A or
C).
Option V (Verbose) writes one distance per line. The Verbose output is
the default. Here it is for the example data set given below:
Tree distance program, version 3.6
Symmetric differences between adjacent pairs of trees:
Trees 1 and 2: 4
Trees 3 and 4: 10
Trees 5 and 6: 4
Trees 7 and 8: 4
Trees 9 and 10: 4
Trees 11 and 12: 10
Option S (Sparse or terse) is similar except that all that is given on
each line are the numbers of the two trees and the distance, separated
by blanks. This may be a convenient format if you want to write a
program to read these numbers in, and you want to spare yourself the
effort of having the program wade through the words on each line in
the Verbose output. The first four lines of the Sparse output are
titles that your program would want to skip past. Here is the Sparse
output for the example trees.
1 2 4
3 4 10
5 6 4
7 8 4
9 10 4
11 12 10
Output files for usage example
File: treedist.ftreedist
Tree distance program, version 3.69.650
Branch score distances between adjacent pairs of trees:
Trees 1 and 2: 2.000000e-01
Trees 3 and 4: 3.162278e-01
Trees 5 and 6: 2.000000e-01
Trees 7 and 8: 2.000000e-01
Trees 9 and 10: 2.000000e-01
Trees 11 and 12: 3.162278e-01
Output files for usage example 2
File: treedist2.ftreedist
Tree distance program, version 3.69.650
Symmetric differences between adjacent pairs of trees:
Trees 1 and 2: 4
Trees 3 and 4: 10
Trees 5 and 6: 4
Trees 7 and 8: 4
Trees 9 and 10: 4
Trees 11 and 12: 10
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Function
Phylogenies from distance matrix by N-J or UPGMA method
Description
An implementation by Mary Kuhner and John Yamato of Saitou and Nei's
"Neighbor Joining Method," and of the UPGMA (Average Linkage
clustering) method. Neighbor Joining is a distance matrix method
producing an unrooted tree without the assumption of a clock. UPGMA
does assume a clock. The branch lengths are not optimized by the least
squares criterion but the methods are very fast and thus can handle
much larger data sets.
Algorithm
This program implements the Neighbor-Joining method of Saitou and Nei
(1987) and the UPGMA method of clustering. The program was written by
Mary Kuhner and Jon Yamato, using some code from program FITCH. An
important part of the code was translated from FORTRAN code from the
neighbor-joining program written by Naruya Saitou and by Li Jin, and
is used with the kind permission of Drs. Saitou and Jin.
NEIGHBOR constructs a tree by successive clustering of lineages,
setting branch lengths as the lineages join. The tree is not
rearranged thereafter. The tree does not assume an evolutionary clock,
so that it is in effect an unrooted tree. It should be somewhat
similar to the tree obtained by FITCH. The program cannot evaluate a
User tree, nor can it prevent branch lengths from becoming
negative. However the algorithm is far faster than FITCH or
KITSCH. This will make it particularly effective in their place for
large studies or for bootstrap or jackknife resampling studies which
require runs on multiple data sets.
The UPGMA option constructs a tree by successive (agglomerative)
clustering using an average-linkage method of clustering. It has some
relationship to KITSCH, in that when the tree topology turns out the
same, the branch lengths with UPGMA will turn out to be the same as
with the P = 0 option of KITSCH.
The programs FITCH, KITSCH, and NEIGHBOR are for dealing with data
which comes in the form of a matrix of pairwise distances between all
pairs of taxa, such as distances based on molecular sequence data,
gene frequency genetic distances, amounts of DNA hybridization, or
immunological distances. In analyzing these data, distance matrix
programs implicitly assume that:
Each distance is measured independently from the others: no item of
data contributes to more than one distance.
The distance between each pair of taxa is drawn from a distribution
with an expectation which is the sum of values (in effect amounts of
evolution) along the tree from one tip to the other. The variance of
the distribution is proportional to a power p of the expectation.
These assumptions can be traced in the least squares methods of
programs FITCH and KITSCH but it is not quite so easy to see them in
operation in the Neighbor-Joining method of NEIGHBOR, where the
independence assumptions is less obvious.
THESE TWO ASSUMPTIONS ARE DUBIOUS IN MOST CASES: independence will not
be expected to be true in most kinds of data, such as genetic
distances from gene frequency data. For genetic distance data in which
pure genetic drift without mutation can be assumed to be the mechanism
of change CONTML may be more appropriate. However, FITCH, KITSCH, and
NEIGHBOR will not give positively misleading results (they will not
make a statistically inconsistent estimate) provided that additivity
holds, which it will if the distance is computed from the original
data by a method which corrects for reversals and parallelisms in
evolution. If additivity is not expected to hold, problems are more
severe. A short discussion of these matters will be found in a review
article of mine (1984a). For detailed, if sometimes irrelevant,
controversy see the papers by Farris (1981, 1985, 1986) and myself
(1986, 1988b).
For genetic distances from gene frequencies, FITCH, KITSCH, and
NEIGHBOR may be appropriate if a neutral mutation model can be assumed
and Nei's genetic distance is used, or if pure drift can be assumed
and either Cavalli-Sforza's chord measure or Reynolds, Weir, and
Cockerham's (1983) genetic distance is used. However, in the latter
case (pure drift) CONTML should be better.
Restriction site and restriction fragment data can be treated by
distance matrix methods if a distance such as that of Nei and Li
(1979) is used. Distances of this sort can be computed in PHYLIp by
the program RESTDIST.
For nucleic acid sequences, the distances computed in DNADIST allow
correction for multiple hits (in different ways) and should allow one
to analyse the data under the presumption of additivity. In all of
these cases independence will not be expected to hold. DNA
hybridization and immunological distances may be additive and
independent if transformed properly and if (and only if) the standards
against which each value is measured are independent. (This is rarely
exactly true).
FITCH and the Neighbor-Joining option of NEIGHBOR fit a tree which has
the branch lengths unconstrained. KITSCH and the UPGMA option of
NEIGHBOR, by contrast, assume that an "evolutionary clock" is valid,
according to which the true branch lengths from the root of the tree
to each tip are the same: the expected amount of evolution in any
lineage is proportional to elapsed time.
Usage
Here is a sample session with fneighbor
% fneighbor
Phylogenies from distance matrix by N-J or UPGMA method
Phylip distance matrix file: neighbor.dat
Phylip neighbor program output file [neighbor.fneighbor]:
Cycle 4: species 1 ( 0.91769) joins species 2 ( 0.76891)
Cycle 3: node 1 ( 0.42027) joins species 3 ( 0.35793)
Cycle 2: species 6 ( 0.15168) joins species 7 ( 0.11752)
Cycle 1: node 1 ( 0.04648) joins species 4 ( 0.28469)
last cycle:
node 1 ( 0.02696) joins species 5 ( 0.15393) joins node 6 ( 0.03982)
Output written on file "neighbor.fneighbor"
Tree written on file "neighbor.treefile"
Done.
Phylogenies from distance matrix by N-J or UPGMA method
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-datafile] distances Phylip distance matrix file
[-outfile] outfile [*.fneighbor] Phylip neighbor program output
file
Additional (Optional) qualifiers (* if not always prompted):
-matrixtype menu [s] Type of data matrix (Values: s (Square);
u (Upper triangular); l (Lower triangular))
-treetype menu [n] Neighbor-joining or UPGMA tree (Values:
n (Neighbor-joining); u (UPGMA))
* -outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-jumble toggle [N] Randomise input order of species
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-replicates boolean [N] Subreplicates
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fneighbor] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-datafile] (Parameter 1)
distances
Phylip distance matrix file
Distance matrix
[-outfile] (Parameter 2)
outfile
Phylip neighbor program output file
Output file
<*>.fneighbor
Additional (Optional) qualifiers
-matrixtype
list
Type of data matrix
s
(Square)
u
(Upper triangular)
l
(Lower triangular)
s
-treetype
list
Neighbor-joining or UPGMA tree
n
(Neighbor-joining)
u
(UPGMA)
n
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-jumble
toggle
Randomise input order of species
Toggle value Yes/No
No
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-replicates
boolean
Subreplicates
Boolean value Yes/No
No
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fneighbor
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fneighbor output consists of an tree (rooted if UPGMA, unrooted
if Neighbor-Joining) and the lengths of the interior segments. The
Average Percent Standard Deviation is not computed or printed out. If
the tree found by Neighbor is fed into FITCH as a User Tree, it will
compute this quantity if one also selects the N option of FITCH to
ensure that none of the branch lengths is re-estimated.
As NEIGHBOR runs it prints out an account of the successive clustering
levels, if you allow it to. This is mostly for reassurance and can be
suppressed using menu option 2. In this printout of cluster levels the
word "OTU" refers to a tip species, and the word "NODE" to an interior
node of the resulting tree.
Please help by correcting and extending the Wiki pages.
Function
Protein distance algorithm
Description
Computes a distance measure for protein sequences, using maximum
likelihood estimates based on the Dayhoff PAM matrix, the JTT matrix
model, the PBM model, Kimura's 1983 approximation to these, or a model
based on the genetic code plus a constraint on changing to a different
category of amino acid. The distances can also be corrected for
gamma-distributed and gamma-plus-invariant-sites-distributed rates of
change in different sites. Rates of evolution can vary among sites in
a prespecified way, and also according to a Hidden Markov model. The
program can also make a table of percentage similarity among
sequences. The distances can be used in the distance matrix programs.
Algorithm
This program uses protein sequences to compute a distance matrix,
under four different models of amino acid replacement. It can also
compute a table of similarity between the amino acid sequences. The
distance for each pair of species estimates the total branch length
between the two species, and can be used in the distance matrix
programs FITCH, KITSCH or NEIGHBOR. This is an alternative to use of
the sequence data itself in the parsimony program PROTPARS.
The program reads in protein sequences and writes an output file
containing the distance matrix or similarity table. The five models of
amino acid substitution are one which is based on the Jones, Taylor
and Thornton (1992) model of amino acid change, the PMB model
(Veerassamy, Smith and Tillier, 2004) which is derived from the Blocks
database of conserved protein motifs, one based on the PAM matrixes of
Margaret Dayhoff, one due to Kimura (1983) which approximates it based
simply on the fraction of similar amino acids, and one based on a
model in which the amino acids are divided up into groups, with change
occurring based on the genetic code but with greater difficulty of
changing between groups. The program correctly takes into account a
variety of sequence ambiguities.
The five methods are:
(1) The Dayhoff PAM matrix. This uses Dayhoff's PAM 001 matrix from
Dayhoff (1979), page 348. The PAM model is an empirical one that
scales probabilities of change from one amino acid to another in terms
of a unit which is an expected 1% change between two amino acid
sequences. The PAM 001 matrix is used to make a transition probability
matrix which allows prediction of the probability of changing from any
one amino acid to any other, and also predicts equilibrium amino acid
composition. The program assumes that these probabilities are correct
and bases its computations of distance on them. The distance that is
computed is scaled in units of expected fraction of amino acids
changed. This is a unit such that 1.0 is 100 PAM's.
(2) The Jones-Taylor-Thornton model. This is similar to the Dayhoff
PAM model, except that it is based on a recounting of the number of
observed changes in amino acids by Jones, Taylor, and Thornton
(1992). They used a much larger sample of protein sequences than did
Dayhoff. The distance is scaled in units of the expected fraction of
amino acids changed (100 PAM's). Because its sample is so much larger
this model is to be preferred over the original Dayhoff PAM model. It
is the default model in this program.
(3) The PMB (Probability Matrix from Blocks) model. This is derived
using the Blocks database of conserved protein motifs. It will be
described in a paper by Veerassamy, Smith and Tillier
(2004). Elisabeth Tillier kindly made the matrices available for this
model.
(4) Kimura's distance. This is a rough-and-ready distance formula for
approximating PAM distance by simply measuring the fraction of amino
acids, p, that differs between two sequences and computing the
distance as (Kimura, 1983)
D = - loge ( 1 - p - 0.2 p2 ).
This is very quick to do but has some obvious limitations. It does not take into account which amino acids differ or to what amino acids they change, so some information is lost. The units of the distance measure are fraction of amino acids differing, as also in the case of the PAM distance. If the fraction of amino acids differing gets larger than 0.8541 the distance becomes infinite.
(5) The Categories distance. This is my own concoction. I imagined a
nucleotide sequence changing according to Kimura's 2-parameter model,
with the exception that some changes of amino acids are less likely
than others. The amino acids are grouped into a series of
categories. Any base change that does not change which category the
amino acid is in is allowed, but if an amino acid changes category
this is allowed only a certain fraction of the time. The fraction is
called the "ease" and there is a parameter for it, which is 1.0 when
all changes are allowed and near 0.0 when changes between categories
are nearly impossible.
In this option I have allowed the user to select the
Transition/Transversion ratio, which of several genetic codes to use,
and which categorization of amino acids to use. There are three of
them, a somewhat random sample:
The George-Hunt-Barker (1988) classification of amino acids,
A classification provided by my colleague Ben Hall when I asked him for one,
One I found in an old "baby biochemistry" book (Conn and Stumpf,
1963), which contains most of the biochemistry I was ever taught, and
all that I ever learned.
Interestingly enough, all of them are consisten with the same linear
ordering of amino acids, which they divide up in different ways. For
the Categories model I have set as default the George/Hunt/Barker
classification with the "ease" parameter set to 0.457 which is
approximately the value implied by the empirical rates in the Dayhoff
PAM matrix.
The method uses, as I have noted, Kimura's (1980) 2-parameter model of
DNA change. The Kimura "2-parameter" model allows for a difference
between transition and transversion rates. Its transition probability
matrix for a short interval of time is:
To: A G C T
---------------------------------
A | 1-a-2b a b b
From: G | a 1-a-2b b b
C | b b 1-a-2b a
T | b b a 1-a-2b
where a is u dt, the product of the rate of transitions per unit time
and dt is the length dt of the time interval, and b is v dt, the
product of half the rate of transversions (i.e., the rate of a
specific transversion) and the length dt of the time interval.
Each distance that is calculated is an estimate, from that particular
pair of species, of the divergence time between those two species. The
Kimura distance is straightforward to compute. The other two are
considerably slower, and they look at all positions, and find that
distance which makes the likelihood highest. This likelihood is in
effect the length of the internal branch in a two-species tree that
connects these two species. Its likelihood is just the product, under
the model, of the probabilities of each position having the (one or)
two amino acids that are actually found. This is fairly slow to
compute.
The computation proceeds from an eigenanalysis (spectral
decomposition) of the transition probability matrix. In the case of
the PAM 001 matrix the eigenvalues and eigenvectors are precomputed
and are hard-coded into the program in over 400 statements. In the
case of the Categories model the program computes the eigenvalues and
eigenvectors itself, which will add a delay. But the delay is
independent of the number of species as the calculation is done only
once, at the outset.
The actual algorithm for estimating the distance is in both cases a
bisection algorithm which tries to find the point at which the
derivative os the likelihood is zero. Some of the kinds of ambiguous
amino acids like "glx" are correctly taken into account. However, gaps
are treated as if they are unkown nucleotides, which means those
positions get dropped from that particular comparison. However, they
are not dropped from the whole analysis. You need not eliminate
regions containing gaps, as long as you are reasonably sure of the
alignment there.
Note that there is an assumption that we are looking at all positions,
including those that have not changed at all. It is important not to
restrict attention to some positions based on whether or not they have
changed; doing that would bias the distances by making them too large,
and that in turn would cause the distances to misinterpret the meaning
of those positions that had changed.
The program can now correct distances for unequal rates of change at
different amino acid positions. This correction, which was introduced
for DNA sequences by Jin and Nei (1990), assumes that the distribution
of rates of change among amino acid positions follows a Gamma
distribution. The user is asked for the value of a parameter that
determines the amount of variation of rates among amino acid
positions. Instead of the more widely-known coefficient alpha,
PROTDIST uses the coefficient of variation (ratio of the standard
deviation to the mean) of rates among amino acid positions. . So if
there is 20% variation in rates, the CV is is 0.20. The square of the
C.V. is also the reciprocal of the better-known "shape parameter",
alpha, of the Gamma distribution, so in this case the shape parameter
alpha = 1/(0.20*0.20) = 25. If you want to achieve a particular value
of alpha, such as 10, you will want to use a CV of 1/sqrt(100) = 1/10
= 0.1.
In addition to the five distance calculations, the program can also
compute a table of similarities between amino acid sequences. These
values are the fractions of amino acid positions identical between the
sequences. The diagonal values are 1.0000. No attempt is made to count
similarity of nonidentical amino acids, so that no credit is given for
having (for example) different hydrophobic amino acids at the
corresponding positions in the two sequences. This option has been
requested by many users, who need it for descriptive purposes. It is
not intended that the table be used for inferring the tree.
Usage
Here is a sample session with fprotdist
% fprotdist
Protein distance algorithm
Input (aligned) protein sequence set(s): protdist.dat
Phylip distance matrix output file [protdist.fprotdist]:
Computing distances:
Alpha
Beta .
Gamma ..
Delta ...
Epsilon ....
Output written to file "protdist.fprotdist"
Done.
Protein distance algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-outfile] outfile [*.fprotdist] Phylip distance matrix output
file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
-method menu [j] Choose the method to use (Values: j
(Jones-Taylor-Thornton matrix); h
(Henikoff/Tiller PMB matrix); d (Dayhoff PAM
matrix); k (Kimura formula); s (Similarity
table); c (Categories model))
* -gammatype menu [c] Rate variation among sites (Values: g
(Gamma distributed rates); i
(Gamma+invariant sites); c (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -aacateg menu [G] Choose the category to use (Values: G
(George/Hunt/Barker (Cys), (Met Val Leu
Ileu), (Gly Ala Ser Thr Pro)); C (Chemical
(Cys Met), (Val Leu Ileu Gly Ala Ser Thr),
(Pro)); H (Hall (Cys), (Met Val Leu Ileu),
(Gly Ala Ser Thr),(Pro)))
* -whichcode menu [u] Which genetic code (Values: u
(Universal); c (Ciliate); m (Universal
mitochondrial); v (Vertebrate
mitochondrial); f (Fly mitochondrial); y
(Yeast mitochondrial))
* -ease float [0.457] Prob change category (1.0=easy)
(Number from 0.000 to 1.000)
* -ttratio float [2.0] Transition/transversion ratio (Number
0.000 or more)
* -basefreq array [0.25 0.25 0.25 0.25] Base frequencies for A
C G T/U (use blanks to separate)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-outfile] (Parameter 2)
outfile
Phylip distance matrix output file
Output file
<*>.fprotdist
Additional (Optional) qualifiers
-ncategories
integer
Number of substitution rate categories
Integer from 1 to 9
1
-rate
array
Rate for each category
List of floating point numbers
-categories
properties
File of substitution rate categories
Property value(s)
-weights
properties
Weights file
Property value(s)
-method
list
Choose the method to use
j
(Jones-Taylor-Thornton matrix)
h
(Henikoff/Tiller PMB matrix)
d
(Dayhoff PAM matrix)
k
(Kimura formula)
s
(Similarity table)
c
(Categories model)
j
-gammatype
list
Rate variation among sites
g
(Gamma distributed rates)
i
(Gamma+invariant sites)
c
(Constant rate)
c
-gammacoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-invarcoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-aacateg
list
Choose the category to use
G
(George/Hunt/Barker (Cys), (Met Val Leu Ileu), (Gly Ala Ser Thr Pro))
C
(Chemical (Cys Met), (Val Leu Ileu Gly Ala Ser Thr), (Pro))
H
(Hall (Cys), (Met Val Leu Ileu), (Gly Ala Ser Thr),(Pro))
G
-whichcode
list
Which genetic code
u
(Universal)
c
(Ciliate)
m
(Universal mitochondrial)
v
(Vertebrate mitochondrial)
f
(Fly mitochondrial)
y
(Yeast mitochondrial)
u
-ease
float
Prob change category (1.0=easy)
Number from 0.000 to 1.000
0.457
-ttratio
float
Transition/transversion ratio
Number 0.000 or more
2.0
-basefreq
array
Base frequencies for A C G T/U (use blanks to separate)
List of floating point numbers
0.25 0.25 0.25 0.25
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fprotdist output contains on its first line the number of
species. The distance matrix is then printed in standard form, with
each species starting on a new line with the species name, followed by
the distances to the species in order. These continue onto a new line
after every nine distances. The distance matrix is square with zero
distances on the diagonal. In general the format of the distance
matrix is such that it can serve as input to any of the distance
matrix programs.
If the similarity table is selected, the table that is produced is not
in a format that can be used as input to the distance matrix
programs. it has a heading, and the species names are also put at the
tops of the columns of the table (or rather, the first 8 characters of
each species name is there, the other two characters omitted to save
space). There is not an option to put the table into a format that can
be read by the distance matrix programs, nor is there one to make it
into a table of fractions of difference by subtracting the similarity
values from 1. This is done deliberately to make it more difficult for
the use to use these values to construct trees. The similarity values
are not corrected for multiple changes, and their use to construct
trees (even after converting them to fractions of difference) would be
wrong, as it would lead to severe conflict between the distant pairs
of sequences and the close pairs of sequences.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the
menu selections. The output file begins by giving the number of
species and the number of characters, and the identity of the distance
measure that is being used.
In the Categories model of substitution, the distances printed out are
scaled in terms of expected numbers of substitutions, counting both
transitions and transversions but not replacements of a base by
itself, and scaled so that the average rate of change is set to
1.0. For the Dayhoff PAM and Kimura models the distance are scaled in
terms of the expected numbers of amino acid substitutions per site. Of
course, when a branch is twice as long this does not mean that there
will be twice as much net change expected along it, since some of the
changes may occur in the same site and overlie or even reverse each
other. The branch lengths estimates here are in terms of the expected
underlying numbers of changes. That means that a branch of length 0.26
is 26 times as long as one which would show a 1% difference between
the protein (or nucleotide) sequences at the beginning and end of the
branch. But we would not expect the sequences at the beginning and end
of the branch to be 26% different, as there would be some overlaying
of changes.
One problem that can arise is that two or more of the species can be
so dissimilar that the distance between them would have to be
infinite, as the likelihood rises indefinitely as the estimated
divergence time increases. For example, with the Kimura model, if the
two sequences differ in 85.41% or more of their positions then the
estimate of divergence time would be infinite. Since there is no way
to represent an infinite distance in the output file, the program
regards this as an error, issues a warning message indicating which
pair of species are causing the problem, and computes a distance of
-1.0.
Please help by correcting and extending the Wiki pages.
Function
Nucleic acid sequence invariants method
Description
For nucleic acid sequence data on four species, computes Lake's and
Cavender's phylogenetic invariants, which test alternative tree
topologies. The program also tabulates the frequencies of occurrence
of the different nucleotide patterns. Lake's invariants are the method
which he calls "evolutionary parsimony".
Algorithm
This program reads in nucleotide sequences for four species and
computes the phylogenetic invariants discovered by James Cavender
(Cavender and Felsenstein, 1987) and James Lake (1987). Lake's method
is also called by him "evolutionary parsimony". I prefer Cavender's
more mathematically precise term "invariants", as the method bears
somewhat more relationship to likelihood methods than to
parsimony. The invariants are mathematical formulas (in the present
case linear or quadratic) in the EXPECTED frequencies of site patterns
which are zero for all trees of a given tree topology, irrespective of
branch lengths. We can consider at a given site that if there are no
ambiguities, we could have for four species the nucleotide patterns
(considering the same site across all four species) AAAA, AAAC, AAAG,
... through TTTT, 256 patterns in all.
The invariants are formulas in the expected pattern frequencies, not
the observed pattern frequencies. When they are computed using the
observed pattern frequencies, we will usually find that they are not
precisely zero even when the model is correct and we have the correct
tree topology. Only as the number of nucleotides scored becomes
infinite will the observed pattern frequencies approach their
expectations; otherwise, we must do a statistical test of the
invariants.
Some explanation of invariants will be found in the above papers, and
also in my recent review article on statistical aspects of inferring
phylogenies (Felsenstein, 1988b). Although invariants have some
important advantages, their validity also depends on symmetry
assumptions that may not be satisfied. In the discussion below suppose
that the possible unrooted phylogenies are I: ((A,B),(C,D)), II:
((A,C),(B,D)), and III: ((A,D),(B,C)).
Lake's Invariants, Their Testing and Assumptions
Lake's invariants are fairly simple to describe: the patterns involved
are only those in which there are two purines and two pyrimidines at a
site. Thus a site with AACT would affect the invariants, but a site
with AAGG would not. Let us use (as Lake does) the symbols 1, 2, 3,
and 4, with the proviso that 1 and 2 are either both of the purines or
both of the pyrimidines; 3 and 4 are the other two nucleotides. Thus 1
and 2 always differ by a transition; so do 3 and 4. Lake's invariants,
expressed in terms of expected frequencies, are the three quantities:
He showed that invariants (2) and (3) are zero under Topology I, (1)
and (3) are zero under topology II, and (1) and (2) are zero under
Topology III. If, for example, we see a site with pattern ACGC, we can
start by setting 1=A. Then 2 must be G. We can then set 3=C (so that 4
is T). Thus its pattern type, making those substitutions, is
1323. P(1323) is the expected probability of the type of pattern which
includes ACGC, TGAG, GTAT, etc.
Lake's invariants are easily tested with observed frequencies. For
example, the first of them is a test of whether there are as many
sites of types 1133 and 1234 as there are of types 1134 and 1233; this
is easily tested with a chi-square test or, as in this program, with
an exact binomial test. Note that with several invariants to test, we
risk overestimating the significance of results if we simply accept
the nominal 95% levels of significance (Li and Guoy, 1990).
Lake's invariants assume that each site is evolving independently, and
that starting from any base a transversion is equally likely to end up
at each of the two possible bases (thus, an A undergoing a
transversion is equally likely to end up as a C or a T, and similarly
for the other four bases from which one could start. Interestingly,
Lake's results do not assume that rates of evolution are the same at
all sites. The result that the total of 1133 and 1234 is expected to
be the same as the total of 1134 and 1233 is unaffected by the fact
that we may have aggregated the counts over classes of sites evolving
at different rates.
Cavender's Invariants, Their Testing and Assumptions
Cavender's invariants (Cavender and Felsenstein, 1987) are for the
case of a character with two states. In the nucleic acid case we can
classify nucleotides into two states, R and Y (Purine and Pyrimidine)
and then use the two-state results. Cavender starts, as before, with
the pattern frequencies. Coding purines as R and pyrimidines as Y, the
patterns types are RRRR, RRRY, and so on until YYYY, a total of 16
types. Cavender found quadratic functions of the expected frequencies
of these 16 types that were expected to be zero under a given
phylogeny, irrespective of branch lengths. Two invariants (called K
and L) were found for each tree topology. The L invariants are
particularly easy to understand. If we have the tree topology
((A,B),(C,D)), then in the case of two symmetric states, the event
that A and B have the same state should be independent of whether C
and D have the same state, as the events determining these happen in
different parts of the tree. We can set up a contingency table:
C = D C =/= D
------------------------------
|
A = B | YYYY, YYRR, YYYR, YYRY,
| RRRR, RRYY RRYR, RRRY
|
A =/= B | YRYY, YRRR, YRYR, YRRY,
| RYYY, RYRR RYYR, RYRY
and we expect that the events C = D and A = B will be
independent. Cavender's L invariant for this tree topology is simply
the negative of the crossproduct difference,
P(A=/=B and C=D) P(A=B and C=/=D) - P(A=B and C=D) P(A=/=B and C=/=D).
One of these L invariants is defined for each of the three tree
topologies. They can obviously be tested simply by doing a chi-square
test on the contingency table. The one corresponding to the correct
topology should be statistically indistinguishable from zero. Again,
there is a possible multiple tests problem if all three are tested at
a nominal value of 95%.
The K invariants are differences between the L invariants. When one of
the tables is expected to have crossproduct difference zero, the other
two are expected to be nonzero, and also to be equal. So the
difference of their crossproduct differences can be taken; this is the
K invariant. It is not so easily tested.
The assumptions of Cavender's invariants are different from those of
Lake's. One obviously need not assume anything about the frequencies
of, or transitions among, the two different purines or the two
different pyrimidines. However one does need to assume independent
events at each site, and one needs to assume that the Y and R states
are symmetric, that the probability per unit time that a Y changes
into an R is the same as the probability that an R changes into a Y,
so that we expect equal frequencies of the two states. There is also
an assumption that all sites are changing between these two states at
the same expected rate. This assumption is not needed for Lake's
invariants, since expectations of sums are equal to sums of
expectations, but for Cavender's it is, since products of expectations
are not equal to expectations of products.
It is helpful to have both sorts of invariants available; with further
work we may appreciate what other invaraints there are for various
models of nucleic acid change.
Nucleic acid sequence invariants method
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
-weights properties Phylip weights file (optional)
[-outfile] outfile [*.fdnainvar] Phylip dnainvar program output
file
Additional (Optional) qualifiers (* if not always prompted):
-printdata boolean [N] Print data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing to display results
-[no]printpattern boolean [Y] Print counts of patterns
-[no]printinvariant boolean [Y] Print invariants
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
-weights
properties
Phylip weights file (optional)
Property value(s)
[-outfile] (Parameter 2)
outfile
Phylip dnainvar program output file
Output file
<*>.fdnainvar
Additional (Optional) qualifiers
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]dotdiff
boolean
Use dot-differencing to display results
Boolean value Yes/No
Yes
-[no]printpattern
boolean
Print counts of patterns
Boolean value Yes/No
Yes
-[no]printinvariant
boolean
Print invariants
Boolean value Yes/No
Yes
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fdnainvar output consists first (if option 1 is selected) of a
reprinting of the input data, then (if option 2 is on) tables of
observed pattern frequencies and pattern type frequencies. A table
will be printed out, in alphabetic order AAAA through TTTT of all the
patterns that appear among the sites and the number of times each
appears. This table will be invaluable for computation of any other
invariants. There follows another table, of pattern types, using the
1234 notation, in numerical order 1111 through 1234, of the number of
times each type of pattern appears. In this computation all sites at
which there are any ambiguities or deletions are omitted. Cavender's
invariants could actually be computed from sites that have only Y or R
ambiguities; this will be done in the next release of this program.
If option 3 is on the invariants are then printed out, together with
their statistical tests. For Lake's invariants the two sums which are
expected to be equal are printed out, and then the result of an
one-tailed exact binomial test which tests whether the difference is
expected to be this positive or more. The P level is given (but
remember the multiple-tests problem!).
For Cavender's L invariants the contingency tables are given. Each is
tested with a one-tailed chi-square test. It is possible that the
expected numbers in some categories could be too small for valid use
of this test; the program does not check for this. It is also possible
that the chi-square could be significant but in the wrong direction;
this is not tested in the current version of the program. To check it
beware of a chi-square greater than 3.841 but with a positive
invariant. The invariants themselves are computed, as the difference
of cross-products. Their absolute magnitudes are not important, but
which one is closest to zero may be indicative. Significantly nonzero
invariants should be negative if the model is valid. The K invariants,
which are simply differences among the L invariants, are also printed
out without any test on them being conducted. Note that it is possible
to use the bootstrap utility SEQBOOT to create multiple data sets, and
from the output from sunning all of these get the empirical
variability of these quadratic invariants.
Output files for usage example
File: dnainvar.fdnainvar
Nucleic acid sequence Invariants method, version 3.69.650
4 species, 13 sites
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta ..G..C.... ..C
Gamma C.TT.C.T.. C.A
Delta GGTA.TT.GG CC.
Pattern Number of times
AAAC 1
AAAG 2
AACC 1
AACG 1
CCCG 1
CCTC 1
CGTT 1
GCCT 1
GGGT 1
GGTA 1
TCAT 1
TTTT 1
Symmetrized patterns (1, 2 = the two purines and 3, 4 = the two pyrimidines
or 1, 2 = the two pyrimidines and 3, 4 = the two purines)
1111 1
1112 2
1113 3
1121 1
1132 2
1133 1
1231 1
1322 1
1334 1
Tree topologies (unrooted):
I: ((Alpha,Beta),(Gamma,Delta))
II: ((Alpha,Gamma),(Beta,Delta))
III: ((Alpha,Delta),(Beta,Gamma))
[Part of this file has been deleted for brevity]
different purine:pyrimidine ratios from 1:1.
Tree I:
Contingency Table
2 8
1 2
Quadratic invariant = 4.0
Chi-square = 0.23111 (not significant)
Tree II:
Contingency Table
1 5
1 6
Quadratic invariant = -1.0
Chi-square = 0.01407 (not significant)
Tree III:
Contingency Table
1 2
6 4
Quadratic invariant = 8.0
Chi-square = 0.66032 (not significant)
Cavender's quadratic invariants (type K) using purines vs. pyrimidines
(these are expected to be zero for the correct tree topology)
They will be misled if there are substantially
different evolutionary rate between sites, or
different purine:pyrimidine ratios from 1:1.
No statistical test is done on them here.
Tree I: -9.0
Tree II: 4.0
Tree III: 5.0
Please help by correcting and extending the Wiki pages.
Function
Interactive mixed method parsimony
Description
Interactive construction of phylogenies from discrete character data
with two states (0 and 1). Evaluates parsimony and compatibility
criteria for those phylogenies and displays reconstructed states
throughout the tree. This can be used to find parsimony or
compatibility estimates by hand.
Algorithm
MOVE is an interactive parsimony program, inspired by Wayne Maddison
and David Maddison's marvellous program MacClade, which is written for
Apple Macintosh computers. MOVE reads in a data set which is prepared
in almost the same format as one for the mixed method parsimony
program MIX. It allows the user to choose an initial tree, and
displays this tree on the screen. The user can look at different
characters and the way their states are distributed on that tree,
given the most parsimonious reconstruction of state changes for that
particular tree. The user then can specify how the tree is to be
rearraranged, rerooted or written out to a file. By looking at
different rearrangements of the tree the user can manually search for
the most parsimonious tree, and can get a feel for how different
characters are affected by changes in the tree topology.
This program is compatible with fewer computer systems than the other
programs in PHYLIP. It can be adapted to MSDOS systems or to any
system whose screen or terminals emulate DEC VT100 terminals (such as
Telnet programs for logging in to remote computers over a TCP/IP
network, VT100-compatible windows in the X windowing system, and any
terminal compatible with ANSI standard terminals). For any other
screen types, there is a generic option which does not make use of
screen graphics characters to display the character states. This will
be less effective, as the states will be less easy to see when
displayed.
MOVE uses as its numerical criterion the Wagner and Camin-Sokal
parsimony methods in mixture, where each character can have its method
specified separately. The program defaults to carrying out Wagner
parsimony.
The Camin-Sokal parsimony method explains the data by assuming that
changes 0 --> 1 are allowed but not changes 1 --> 0. Wagner parsimony
allows both kinds of changes. (This under the assumption that 0 is the
ancestral state, though the program allows reassignment of the
ancestral state, in which case we must reverse the state numbers 0 and
1 throughout this discussion). The criterion is to find the tree which
requires the minimum number of changes. The Camin- Sokal method is due
to Camin and Sokal (1965) and the Wagner method to Eck and Dayhoff
(1966) and to Kluge and Farris (1969).
Here are the assumptions of these two methods:
Ancestral states are known (Camin-Sokal) or unknown (Wagner).
Different characters evolve independently.
Different lineages evolve independently.
Changes 0 --> 1 are much more probable than changes 1 --> 0
(Camin-Sokal) or equally probable (Wagner).
Both of these kinds of changes are a priori improbable over the
evolutionary time spans involved in the differentiation of the group
in question.
Other kinds of evolutionary event such as retention of polymorphism
are far less probable than 0 --> 1 changes.
Rates of evolution in different lineages are sufficiently low that two
changes in a long segment of the tree are far less probable than one
change in a short segment.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b), but also read the exchange
between Felsenstein and Sober (1986).
Usage
Here is a sample session with fmove
% fmove
Interactive mixed method parsimony
Phylip character discrete states file: move.dat
Phylip tree file (optional):
NEXT? (R # + - S . T U W O F H J K L C ? X Q) (? for Help): Q
Do you want to write out the tree to a file? (Y or N): Y
5 species, 6 characters
Wagner parsimony method
Computing steps needed for compatibility in characters...
(unrooted) 8.0 Steps 4 chars compatible
,-----------5:Epsilon
--9
! ,--------4:Delta
`--8
! ,-----3:Gamma
`--7
! ,--2:Beta
`--6
`--1:Alpha
Tree written to file "move.treefile"
Interactive mixed method parsimony
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing data set
[-intreefile] tree Phylip tree file (optional)
Additional (Optional) qualifiers:
-weights properties Weights file
-ancfile properties Ancestral states file
-factorfile properties Factors file
-method menu [Wagner] Choose the method to use (Values: w
(Wagner); c (Camin-Sokal); m (Mixed))
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-threshold float [$(infile.discretesize)] Threshold value
(Number 0.000 or more)
-initialtree menu [Arbitary] Initial tree (Values: a
(Arbitary); u (User); s (Specify))
-screenwidth integer [80] Width of terminal screen in characters
(Any integer value)
-screenlines integer [24] Number of lines on screen (Any integer
value)
-outtreefile outfile [*.fmove] Phylip tree output file (optional)
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
File containing data set
Discrete states file
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-ancfile
properties
Ancestral states file
Property value(s)
-factorfile
properties
Factors file
Property value(s)
-method
list
Choose the method to use
w
(Wagner)
c
(Camin-Sokal)
m
(Mixed)
Wagner
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-threshold
float
Threshold value
Number 0.000 or more
$(infile.discretesize)
-initialtree
list
Initial tree
a
(Arbitary)
u
(User)
s
(Specify)
Arbitary
-screenwidth
integer
Width of terminal screen in characters
Any integer value
80
-screenlines
integer
Number of lines on screen
Any integer value
24
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fmove
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
The fmove input data file is set up almost identically to the
data files for MIX.
Please help by correcting and extending the Wiki pages.
Function
Fitch-Margoliash method with contemporary tips
Description
Estimates phylogenies from distance matrix data under the
"ultrametric" model which is the same as the additive tree model
except that an evolutionary clock is assumed. The Fitch-Margoliash
criterion and other least squares criteria, or the Minimum Evolution
criterion are possible. This program will be useful with distances
computed from molecular sequences, restriction sites or fragments
distances, with distances from DNA hybridization measurements, and
with genetic distances computed from gene frequencies.
Algorithm
This program carries out the Fitch-Margoliash and Least Squares
methods, plus a variety of others of the same family, with the
assumption that all tip species are contemporaneous, and that there is
an evolutionary clock (in effect, a molecular clock). This means that
branches of the tree cannot be of arbitrary length, but are
constrained so that the total length from the root of the tree to any
species is the same. The quantity minimized is the same weighted sum
of squares described in the Distance Matrix Methods documentation
file.
The programs FITCH, KITSCH, and NEIGHBOR are for dealing with data
which comes in the form of a matrix of pairwise distances between all
pairs of taxa, such as distances based on molecular sequence data,
gene frequency genetic distances, amounts of DNA hybridization, or
immunological distances. In analyzing these data, distance matrix
programs implicitly assume that:
Each distance is measured independently from the others: no item of
data contributes to more than one distance.
The distance between each pair of taxa is drawn from a distribution
with an expectation which is the sum of values (in effect amounts of
evolution) along the tree from one tip to the other. The variance of
the distribution is proportional to a power p of the expectation.
These assumptions can be traced in the least squares methods of
programs FITCH and KITSCH but it is not quite so easy to see them in
operation in the Neighbor-Joining method of NEIGHBOR, where the
independence assumptions is less obvious.
THESE TWO ASSUMPTIONS ARE DUBIOUS IN MOST CASES: independence will not
be expected to be true in most kinds of data, such as genetic
distances from gene frequency data. For genetic distance data in which
pure genetic drift without mutation can be assumed to be the mechanism
of change CONTML may be more appropriate. However, FITCH, KITSCH, and
NEIGHBOR will not give positively misleading results (they will not
make a statistically inconsistent estimate) provided that additivity
holds, which it will if the distance is computed from the original
data by a method which corrects for reversals and parallelisms in
evolution. If additivity is not expected to hold, problems are more
severe. A short discussion of these matters will be found in a review
article of mine (1984a). For detailed, if sometimes irrelevant,
controversy see the papers by Farris (1981, 1985, 1986) and myself
(1986, 1988b).
For genetic distances from gene frequencies, FITCH, KITSCH, and
NEIGHBOR may be appropriate if a neutral mutation model can be assumed
and Nei's genetic distance is used, or if pure drift can be assumed
and either Cavalli-Sforza's chord measure or Reynolds, Weir, and
Cockerham's (1983) genetic distance is used. However, in the latter
case (pure drift) CONTML should be better.
Restriction site and restriction fragment data can be treated by
distance matrix methods if a distance such as that of Nei and Li
(1979) is used. Distances of this sort can be computed in PHYLIp by
the program RESTDIST.
For nucleic acid sequences, the distances computed in DNADIST allow
correction for multiple hits (in different ways) and should allow one
to analyse the data under the presumption of additivity. In all of
these cases independence will not be expected to hold. DNA
hybridization and immunological distances may be additive and
independent if transformed properly and if (and only if) the standards
against which each value is measured are independent. (This is rarely
exactly true).
FITCH and the Neighbor-Joining option of NEIGHBOR fit a tree which has
the branch lengths unconstrained. KITSCH and the UPGMA option of
NEIGHBOR, by contrast, assume that an "evolutionary clock" is valid,
according to which the true branch lengths from the root of the tree
to each tip are the same: the expected amount of evolution in any
lineage is proportional to elapsed time.
The method may be considered as providing an estimate of the
phylogeny. Alternatively, it can be considered as a phenetic
clustering of the tip species. This method minimizes an objective
function, the sum of squares, not only setting the levels of the
clusters so as to do so, but rearranging the hierarchy of clusters to
try to find alternative clusterings that give a lower overall sum of
squares. When the power option P is set to a value of P = 0.0, so that
we are minimizing a simple sum of squares of the differences between
the observed distance matrix and the expected one, the method is very
close in spirit to Unweighted Pair Group Arithmetic Average Clustering
(UPGMA), also called Average-Linkage Clustering. If the topology of
the tree is fixed and there turn out to be no branches of negative
length, its result should be the same as UPGMA in that case. But since
it tries alternative topologies and (unless the N option is set) it
combines nodes that otherwise could result in a reversal of levels, it
is possible for it to give a different, and better, result than simple
sequential clustering. Of course UPGMA itself is available as an
option in program NEIGHBOR.
An important use of this method will be to do a formal statistical
test of the evolutionary clock hypothesis. This can be done by
comparing the sums of squares achieved by FITCH and by KITSCH, BUT
SOME CAVEATS ARE NECESSARY. First, the assumption is that the observed
distances are truly independent, that no original data item
contributes to more than one of them (not counting the two reciprocal
distances from i to j and from j to i). THIS WILL NOT HOLD IF THE
DISTANCES ARE OBTAINED FROM GENE FREQUENCIES, FROM MORPHOLOGICAL
CHARACTERS, OR FROM MOLECULAR SEQUENCES. It may be invalid even for
immunological distances and levels of DNA hybridization, provided that
the use of common standard for all members of a row or column allows
an error in the measurement of the standard to affect all these
distances simultaneously. It will also be invalid if the numbers have
been collected in experimental groups, each measured by taking
differences from a common standard which itself is measured with
error. Only if the numbers in different cells are measured from
independent standards can we depend on the statistical model. The
details of the test and the assumptions are discussed in my review
paper on distance methods (Felsenstein, 1984a). For further and
sometimes irrelevant controversy on these matters see the papers by
Farris (1981, 1985, 1986) and myself (Felsenstein, 1986, 1988b).
A second caveat is that the distances must be expected to rise
linearly with time, not according to any other curve. Thus it may be
necessary to transform the distances to achieve an expected
linearity. If the distances have an upper limit beyond which they
could not go, this is a signal that linearity may not hold. It is also
VERY important to choose the power P at a value that results in the
standard deviation of the variation of the observed from the expected
distances being the P/2-th power of the expected distance.
To carry out the test, fit the same data with both FITCH and KITSCH,
and record the two sums of squares. If the topology has turned out the
same, we have N = n(n-1)/2 distances which have been fit with 2n-3
parameters in FITCH, and with n-1 parameters in KITSCH. Then the
difference between S(K) and S(F) has d1 = n-2 degrees of freedom. It
is statistically independent of the value of S(F), which has d2 =
N-(2n-3) degrees of freedom. The ratio of mean squares
[S(K)-S(F)]/d1
----------------
S(F)/d2
should, under the evolutionary clock, have an F distribution with n-2
and N-(2n-3) degrees of freedom respectively. The test desired is that
the F ratio is in the upper tail (say the upper 5%) of its
distribution. If the S (subreplication) option is in effect, the above
degrees of freedom must be modified by noting that N is not n(n-1)/2
but is the sum of the numbers of replicates of all cells in the
distance matrix read in, which may be either square or triangular. A
further explanation of the statistical test of the clock is given in a
paper of mine (Felsenstein, 1986).
The program uses a similar tree construction method to the other
programs in the package and, like them, is not guaranteed to give the
best-fitting tree. The assignment of the branch lengths for a given
topology is a least squares fit, subject to the constraints against
negative branch lengths, and should not be able to be improved
upon. KITSCH runs more quickly than FITCH.
Usage
Here is a sample session with fkitsch
% fkitsch
Fitch-Margoliash method with contemporary tips
Phylip distance matrix file: kitsch.dat
Phylip tree file (optional):
Phylip kitsch program output file [kitsch.fkitsch]:
Adding species:
1. Bovine
2. Mouse
3. Gibbon
4. Orang
5. Gorilla
6. Chimp
7. Human
Doing global rearrangements
!-------------!
.............
Output written to file "kitsch.fkitsch"
Tree also written onto file "kitsch.treefile"
Done.
Fitch-Margoliash method with contemporary tips
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-datafile] distances File containing one or more distance
matrices
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fkitsch] Phylip kitsch program output
file
Additional (Optional) qualifiers (* if not always prompted):
-matrixtype menu [s] Type of data matrix (Values: s (Square);
u (Upper triangular); l (Lower triangular))
-minev boolean [N] Minimum evolution
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-power float [2.0] Power (Any numeric value)
-negallowed boolean [N] Negative branch lengths allowed
-replicates boolean [N] Subreplicates
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fkitsch] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-datafile] (Parameter 1)
distances
File containing one or more distance matrices
Distance matrix
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip kitsch program output file
Output file
<*>.fkitsch
Additional (Optional) qualifiers
-matrixtype
list
Type of data matrix
s
(Square)
u
(Upper triangular)
l
(Lower triangular)
s
-minev
boolean
Minimum evolution
Boolean value Yes/No
No
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-power
float
Power
Any numeric value
2.0
-negallowed
boolean
Negative branch lengths allowed
Boolean value Yes/No
No
-replicates
boolean
Subreplicates
Boolean value Yes/No
No
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fkitsch
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fkitsch requires a bifurcating tree, unlike FITCH, which
requires an unrooted tree with a trifurcation at its base. Thus the
tree shown below would be written:
((D,E),(C,(A,B)));
If a tree with a trifurcation at the base is by mistake fed into the U
option of KITSCH then some of its species (the entire rightmost furc,
in fact) will be ignored and too small a tree read in. This should
result in an error message and the program should stop. It is
important to understand the difference between the User Tree formats
for KITSCH and FITCH. You may want to use RETREE to convert a user
tree that is suitable for FITCH into one suitable for KITSCH or vice
versa.
fkitsch output is a rooted tree, together with the sum of
squares, the number of tree topologies searched, and, if the power P
is at its default value of 2.0, the Average Percent Standard Deviation
is also supplied. The lengths of the branches of the tree are given in
a table, that also shows for each branch the time at the upper end of
the branch. "Time" here really means cumulative branch length from the
root, going upwards (on the printed diagram, rightwards). For each
branch, the "time" given is for the node at the right (upper) end of
the branch. It is important to realize that the branch lengths are not
exactly proportional to the lengths drawn on the printed tree diagram!
In particular, short branches are exaggerated in the length on that
diagram so that they are more visible.
Output files for usage example
File: kitsch.fkitsch
7 Populations
Fitch-Margoliash method with contemporary tips, version 3.69.650
__ __ 2
\ \ (Obs - Exp)
Sum of squares = /_ /_ ------------
2
i j Obs
negative branch lengths not allowed
+-------Human
+-6
+----5 +-------Chimp
! !
+---4 +---------Gorilla
! !
+------------------------3 +--------------Orang
! !
+----2 +------------------Gibbon
! !
--1 +-------------------------------------------Mouse
!
+------------------------------------------------Bovine
Sum of squares = 0.107
Average percent standard deviation = 5.16213
From To Length Height
---- -- ------ ------
6 Human 0.13460 0.81285
5 6 0.02836 0.67825
6 Chimp 0.13460 0.81285
4 5 0.07638 0.64990
5 Gorilla 0.16296 0.81285
3 4 0.06639 0.57352
4 Orang 0.23933 0.81285
2 3 0.42923 0.50713
3 Gibbon 0.30572 0.81285
1 2 0.07790 0.07790
2 Mouse 0.73495 0.81285
1 Bovine 0.81285 0.81285
Please help by correcting and extending the Wiki pages.
Function
Calculate distance matrix from restriction sites or fragments
Description
Distances calculated from restriction sites data or restriction
fragments data. The restriction sites option is the one to use to also
make distances for RAPDs or AFLPs.
Algorithm
Restdist reads the same restriction sites format as RESTML and
computes a restriction sites distance. It can also compute a
restriction fragments distance. The original restriction fragments and
restriction sites distance methods were introduced by Nei and Li
(1979). Their original method for restriction fragments is also
available in this program, although its default methods are my
modifications of the original Nei and Li methods.
These two distances assume that the restriction sites are accidental
byproducts of random change of nucleotide sequences. For my
restriction sites distance the DNA sequences are assumed to be
changing according to the Kimura 2-parameter model of DNA change
(Kimura, 1980). The user can set the transition/transversion rate for
the model. For my restriction fragments distance there is there is an
implicit assumption of a Jukes-Cantor (1969) model of change, The user
can also set the parameter of a correction for unequal rates of
evolution between sites in the DNA sequences, using a Gamma
distribution of rates among sites. The Jukes-Cantor model is also
implicit in the restriction fragments distance of Nei and Li(1979). It
does not allow us to correct for a Gamma distribution of rates among
sites.
Restriction Sites Distance
The restriction sites distances use data coded for the presence of
absence of individual restriction sites (usually as + and - or 0 and
1). My distance is based on the proportion, out of all sites observed
in one species or the other, which are present in both species. This
is done to correct for the ascertainment of sites, for the fact that
we are not aware of many sites because they do not appear in any
species.
My distance starts by computing from the particular pair of species
the fraction
n++
f = ---------------------
n++ + 1/2 (n+- + n-+)
where n++ is the number of sites contained in both species, n+- is the
number of sites contained in the first of the two species but not in
the second, and n-+ is the number of sites contained in the second of
the two species but not in the first. This is the fraction of sites
that are present in one species which are present in both. Since the
number of sites present in the two species will often differ, the
denominator is the average of the number of sites found in the two
species.
If each restriction site is s nucleotides long, the probability that a
restriction site is present in the other species, given that it is
present in a species, is
Qs,
`where Q is the probability that a nucleotide has no net change as one
goes from the one species to the other. It may have changed in
between; we are interested in the probability that that nucleotide
site is in the same base in both species, irrespective of what has
happened in between. The distance is then computed by finding the
branch length of a two-species tree (connecting these two species with
a single branch) such that Q equals the s-th root of f. For this the
program computes Q for various values of branch length, iterating them
by a Newton-Raphson algorithm until the two quantities are equal.
The resulting distance should be numerically close to the original
restriction sites distance of Nei and Li (1979) when divergence is
small. Theirs computes the probability of retention of a site in a way
that assumes that the site is present in the common ancestor of the
two species. Ours does not make this assumption. It is inspired by
theirs, but differs in this detail. Their distance also assumes a
Jukes-Cantor (1969) model of base change, and does not allow for
transitions being more frequent than transversions. In this sense mine
generalizes theres somewhat. Their distance does include, as mine does
as well, a correction for Gamma distribution of rate of change among
nucleotide sites.
I have made their original distance available here
Restriction Fragments Distance
For restriction fragments data we use a different distance. If we
average over all restriction fragment lengths, each at its own
expected frequency, the probability that the fragment will still be in
existence after a certain amount of branch length, we must take into
account the probability that the two restriction sites at the ends of
the fragment do not mutate, and the probability that no new
restriction site occurs within the fragment in that amount of branch
length. The result for a restriction site length of s is:
Q2s
f = --------
2 - Qs
(The details of the derivation will be given in my forthcoming book
Inferring Phylogenies (to be published by Sinauer Associates in
2001). Given the observed fraction of restriction sites retained, f,
we can solve a quadratic equation from the above expression for
Qs. That makes it easy to obtain a value of Q, and the branch length
can then be estimated by adjusting it so the probability of a base not
changing is equal to that value. Alternatively, if we use the Nei and
Li (1979) restriction fragments distance, this involves solving for g
in the nonlinear equation
g = [ f (3 - 2g) ]1/4
and then the distance is given by
d = - (2/r) loge(g)
where r is the length of the restriction site.
Comparing these two restriction fragments distances in a case where
their underlying DNA model is the same (which is when the
transition/transversion ratio of the modified model is set to 0.5),
you will find that they are very close to each other, differing very
little at small distances, with the modified distance become smaller
than the Nei/Li distance at larger distances. It will therefore matter
very little which one you use.
A Comment About RAPDs and AFLPs
Although these distances are designed for restriction sites and
restriction fragments data, they can be applied to RAPD and AFLP data
as well. RAPD (Randomly Amplified Polymorphic DNA) and AFLP (Amplified
Fragment Length Polymorphism) data consist of presence or absence of
individual bands on a gel. The bands are segments of DNA with PCR
primers at each end. These primers are defined sequences of known
length (often about 10 nucleotides each). For AFLPs the reolevant
length is the primer length, plus three nucleotides. Mutation in these
sequences makes them no longer be primers, just as in the case of
restriction sites. Thus a pair of 10-nucleotide primers will behave
much the same as a 20-nucleotide restriction site, for RAPDs (26 for
AFLPs). You can use the restriction sites distance as the distance
between RAPD or AFLP patterns if you set the proper value for the
total length of the site to the total length of the primers (plus 6 in
the case of AFLPs). Of course there are many possible sources of noise
in these data, including confusing fragments of similar length for
each other and having primers near each other in the genome, and these
are not taken into account in the statistical model used here.
Usage
Here is a sample session with frestdist
% frestdist
Calculate distance matrix from restriction sites or fragments
Input file: restdist.dat
Phylip restdist program output file [restdist.frestdist]:
Restriction site or fragment distances, version 3.69.650
Distances calculated for species
Alpha ....
Beta ...
Gamma ..
Delta .
Epsilon
Distances written to file "restdist.frestdist"
Done.
Calculate distance matrix from restriction sites or fragments
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-data] discretestates File containing one or more sets of
restriction data
[-outfile] outfile [*.frestdist] Phylip restdist program output
file
Additional (Optional) qualifiers (* if not always prompted):
-[no]restsites boolean [Y] Restriction sites (put N if you want
restriction fragments)
-neili boolean [N] Use original Nei/Li model (default uses
modified Nei/Li model)
* -gammatype boolean [N] Gamma distributed rates among sites
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
-ttratio float [2.0] Transition/transversion ratio (Number
0.001 or more)
-sitelength integer [6] Site length (Integer 1 or more)
-lower boolean [N] Lower triangular distance matrix
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-data] (Parameter 1)
discretestates
File containing one or more sets of restriction data
Discrete states file
[-outfile] (Parameter 2)
outfile
Phylip restdist program output file
Output file
<*>.frestdist
Additional (Optional) qualifiers
-[no]restsites
boolean
Restriction sites (put N if you want restriction fragments)
Boolean value Yes/No
Yes
-neili
boolean
Use original Nei/Li model (default uses modified Nei/Li model)
Boolean value Yes/No
No
-gammatype
boolean
Gamma distributed rates among sites
Boolean value Yes/No
No
-gammacoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ttratio
float
Transition/transversion ratio
Number 0.001 or more
2.0
-sitelength
integer
Site length
Integer 1 or more
6
-lower
boolean
Lower triangular distance matrix
Boolean value Yes/No
No
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
frestdist input is fairly standard, with one addition. As usual
the first line of the file gives the number of species and the number
of sites, but there is also a third number, which is the number of
different restriction enzymes that were used to detect the restriction
sites. Thus a data set with 10 species and 35 different sites,
representing digestion with 4 different enzymes, would have the first
line of the data file look like this:
10 35 4
The site data are in standard form. Each species starts with a species
name whose maximum length is given by the constant "nmlngth" (whose
value in the program as distributed is 10 characters). The name
should, as usual, be padded out to that length with blanks if
necessary. The sites data then follows, one character per site (any
blanks will be skipped and ignored). Like the DNA and protein sequence
data, the restriction sites data may be either in the "interleaved"
form or the "sequential" form. Note that if you are analyzing
restriction sites data with the programs DOLLOP or MIX or other
discrete character programs, at the moment those programs do not use
the "aligned" or "interleaved" data format. Therefore you may want to
avoid that format when you have restriction sites data that you will
want to feed into those programs.
The presence of a site is indicated by a "+" and the absence by a
"-". I have also allowed the use of "1" and "0" as synonyms for "+"
and "-", for compatibility with MIX and DOLLOP which do not allow "+"
and "-". If the presence of the site is unknown (for example, if the
DNA containing it has been deleted so that one does not know whether
it would have contained the site) then the state "?" can be used to
indicate that the state of this site is unknown.
frestdist output contains on its first line the number of
species. The distance matrix is then printed in standard form, with
each species starting on a new line with the species name, followed by
the distances to the species in order. These continue onto a new line
after every nine distances. If the L option is used, the matrix or
distances is in lower triangular form, so that only the distances to
the other species that precede each species are printed. Otherwise the
distance matrix is square with zero distances on the diagonal. In
general the format of the distance matrix is such that it can serve as
input to any of the distance matrix programs.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the
menu selections. The output file begins by giving the number of
species and the number of characters.
The distances printed out are scaled in terms of expected numbers of
substitutions per DNA site, counting both transitions and
transversions but not replacements of a base by itself, and scaled so
that the average rate of change, averaged over all sites analyzed, is
set to 1.0. Thus when the G option is used, the rate of change at one
site may be higher than at another, but their mean is expected to be
1.
Please help by correcting and extending the Wiki pages.
Function
Estimates nucleotide phylogeny by maximum likelihood
Description
Same as DNAML but assumes a molecular clock. The use of the two
programs together permits a likelihood ratio test of the molecular
clock hypothesis to be made.
Estimates phylogenies from nucleotide sequences by maximum
likelihood. The model employed allows for unequal expected frequencies
of the four nucleotides, for unequal rates of transitions and
transversions, and for different (prespecified) rates of change in
different categories of sites, and also use of a Hidden Markov model
of rates, with the program inferring which sites have which
rates. This also allows gamma-distribution and gamma-plus-invariant
sites distributions of rates across sites.
Algorithm
This program implements the maximum likelihood method for DNA
sequences under the constraint that the trees estimated must be
consistent with a molecular clock. The molecular clock is the
assumption that the tips of the tree are all equidistant, in branch
length, from its root. This program is indirectly related to
DNAML. Details of the algorithm are not yet published, but many
aspects of it are similar to DNAML, and these are published in the
paper by Felsenstein and Churchill (1996). The model of base
substitution allows the expected frequencies of the four bases to be
unequal, allows the expected frequencies of transitions and
transversions to be unequal, and has several ways of allowing
different rates of evolution at different sites.
The assumptions of the model are:
Each site in the sequence evolves independently.
Different lineages evolve independently.
There is a molecular clock.
Each site undergoes substitution at an expected rate which is chosen
from a series of rates (each with a probability of occurrence) which
we specify.
All relevant sites are included in the sequence, not just those that
have changed or those that are "phylogenetically informative".
A substitution consists of one of two sorts of events:
The first kind of event consists of the replacement of the existing
base by a base drawn from a pool of purines or a pool of pyrimidines
(depending on whether the base being replaced was a purine or a
pyrimidine). It can lead either to no change or to a transition.
The second kind of event consists of the replacement of the existing base by a base drawn at random from a pool of bases at known frequencies, independently of the identity of the base which is being replaced. This could lead either to a no change, to a transition or to a transversion.
The ratio of the two purines in the purine replacement pool is the same as their ratio in the overall pool, and similarly for the pyrimidines.
The ratios of transitions to transversions can be set by the user. The
substitution process can be diagrammed as follows: Suppose that you
specified A, C, G, and T base frequencies of 0.24, 0.28, 0.27, and
0.21.
First kind of event:
Determine whether the existing base is a purine or a pyrimidine.
Draw from the proper pool:
Purine pool: Pyrimidine pool:
| | | |
| 0.4706 A | | 0.5714 C |
| 0.5294 G | | 0.4286 T |
| (ratio is | | (ratio is |
| 0.24 : 0.27) | | 0.28 : 0.21) |
|_______________| |_______________|
Second kind of event:
Draw from the overall pool:
| |
| 0.24 A |
| 0.28 C |
| 0.27 G |
| 0.21 T |
|__________________|
Note that if the existing base is, say, an A, the first kind of event
has a 0.4706 probability of "replacing" it by another A. The second
kind of event has a 0.24 chance of replacing it by another A. This
rather disconcerting model is used because it has nice mathematical
properties that make likelihood calculations far easier. A closely
similar, but not precisely identical model having different rates of
transitions and transversions has been used by Hasegawa
et. al. (1985b). The transition probability formulas for the current
model were given (with my permission) by Kishino and Hasegawa
(1989). Another explanation is available in the paper by Felsenstein
and Churchill (1996).
Note the assumption that we are looking at all sites, including those
that have not changed at all. It is important not to restrict
attention to some sites based on whether or not they have changed;
doing that would bias branch lengths by making them too long, and that
in turn would cause the method to misinterpret the meaning of those
sites that had changed.
This program uses a Hidden Markov Model (HMM) method of inferring
different rates of evolution at different sites. This was described in
a paper by me and Gary Churchill (1996). It allows us to specify to
the program that there will be a number of different possible
evolutionary rates, what the prior probabilities of occurrence of each
is, and what the average length of a patch of sites all having the
same rate. The rates can also be chosen by the program to approximate
a Gamma distribution of rates, or a Gamma distribution plus a class of
invariant sites. The program computes the the likelihood by summing it
over all possible assignments of rates to sites, weighting each by its
prior probability of occurrence.
For example, if we have used the C and A options (described below) to
specify that there are three possible rates of evolution, 1.0, 2.4,
and 0.0, that the prior probabilities of a site having these rates are
0.4, 0.3, and 0.3, and that the average patch length (number of
consecutive sites with the same rate) is 2.0, the program will sum the
likelihood over all possibilities, but giving less weight to those
that (say) assign all sites to rate 2.4, or that fail to have
consecutive sites that have the same rate.
The Hidden Markov Model framework for rate variation among sites was
independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of rates; we
allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant sites.
This feature effectively removes the artificial assumption that all
sites have the same rate, and also means that we need not know in
advance the identities of the sites that have a particular rate of
evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each site (for example, we might want first,
second, and third codon positions in a protein coding sequence to be
three different categories. This is done with the categories input
file and the C option. We then specify (using the menu) the relative
rates of evolution of sites in the different categories. For example,
we might specify that first, second, and third positions evolve at
relative rates of 1.0, 0.8, and 2.7.
If both user-assigned rate categories and Hidden Markov Model rates
are allowed, the program assumes that the actual rate at a site is the
product of the user-assigned category rate and the Hidden Markov Model
regional rate. (This may not always make perfect biological sense: it
would be more natural to assume some upper bound to the rate, as we
have discussed in the Felsenstein and Churchill paper). Nevertheless
you may want to use both types of rate variation.
Usage
Here is a sample session with fdnamlk
% fdnamlk -printdata -ncategories 2 -categories "1111112222222" -rate "1.0 2.0" -gammatype h -nhmmcategories 5 -hmmrates "0.264 1.413 3.596 7.086 12.641" -hmmprobabilities "0.522 0.399 0.076 0.0036 0.000023" -lambda 1.5 -weight "0111111111110"
Estimates nucleotide phylogeny by maximum likelihood
Input (aligned) nucleotide sequence set(s): dnaml.dat
Phylip tree file (optional):
Phylip dnamlk program output file [dnaml.fdnamlk]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "dnaml.fdnamlk"
Tree also written onto file "dnaml.treefile"
Done.
Estimates nucleotide phylogeny by maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fdnamlk] Phylip dnamlk program output
file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
-ttratio float [2.0] Transition/transversion ratio (Number
0.001 or more)
-[no]freqsfrom toggle [Y] Use empirical base frequencies from
seqeunce input
* -basefreq array [0.25 0.25 0.25 0.25] Base frequencies for A
C G T/U (use blanks to separate)
-gammatype menu [Constant rate] Rate variation among sites
(Values: g (Gamma distributed rates); i
(Gamma+invariant sites); h (User defined HMM
of rates); n (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ngammacat integer [1] Number of categories (1-9) (Integer from
1 to 9)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ninvarcat integer [1] Number of categories (1-9) including one
for invariant sites (Integer from 1 to 9)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -nhmmcategories integer [1] Number of HMM rate categories (Integer
from 1 to 9)
* -hmmrates array [1.0] HMM category rates
* -hmmprobabilities array [1.0] Probability for each HMM category
* -adjsite boolean [N] Rates at adjacent sites correlated
* -lambda float [1.0] Mean block length of sites having the
same rate (Number 1.000 or more)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
* -lengths boolean [N] Use branch lengths from user trees
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnamlk] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-hypstate boolean [N] Reconstruct hypothetical sequence
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip dnamlk program output file
Output file
<*>.fdnamlk
Additional (Optional) qualifiers
-ncategories
integer
Number of substitution rate categories
Integer from 1 to 9
1
-rate
array
Rate for each category
List of floating point numbers
-categories
properties
File of substitution rate categories
Property value(s)
-weights
properties
Weights file
Property value(s)
-ttratio
float
Transition/transversion ratio
Number 0.001 or more
2.0
-[no]freqsfrom
toggle
Use empirical base frequencies from seqeunce input
Toggle value Yes/No
Yes
-basefreq
array
Base frequencies for A C G T/U (use blanks to separate)
List of floating point numbers
0.25 0.25 0.25 0.25
-gammatype
list
Rate variation among sites
g
(Gamma distributed rates)
i
(Gamma+invariant sites)
h
(User defined HMM of rates)
n
(Constant rate)
Constant rate
-gammacoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ngammacat
integer
Number of categories (1-9)
Integer from 1 to 9
1
-invarcoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ninvarcat
integer
Number of categories (1-9) including one for invariant sites
Integer from 1 to 9
1
-invarfrac
float
Fraction of invariant sites
Number from 0.000 to 1.000
0.0
-nhmmcategories
integer
Number of HMM rate categories
Integer from 1 to 9
1
-hmmrates
array
HMM category rates
List of floating point numbers
1.0
-hmmprobabilities
array
Probability for each HMM category
List of floating point numbers
1.0
-adjsite
boolean
Rates at adjacent sites correlated
Boolean value Yes/No
No
-lambda
float
Mean block length of sites having the same rate
Number 1.000 or more
1.0
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-global
boolean
Global rearrangements
Boolean value Yes/No
No
-lengths
boolean
Use branch lengths from user trees
Boolean value Yes/No
No
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdnamlk
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-hypstate
boolean
Reconstruct hypothetical sequence
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
-->
fdnamlk output starts by giving the number of species, the
number of sites, and the base frequencies for A, C, G, and T that have
been specified. It then prints out the transition/transversion ratio
that was specified or used by default. It also uses the base
frequencies to compute the actual transition/transversion ratio
implied by the parameter.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of sites is printed, as well as
the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the
menu option to print them out, with the base sequences printed in
groups of ten bases along the lines of the Genbank and EMBL
formats. The trees found are printed as a rooted tree topology. The
internal nodes are numbered arbitrarily for the sake of
identification. The number of trees evaluated so far and the log
likelihood of the tree are also given. The branch lengths in the
diagram are roughly proportional to the estimated branch lengths,
except that very short branches are printed out at least three
characters in length so that the connections can be seen.
A table is printed showing the length of each tree segment, and the
time (in units of expected nucleotide substitutions per site) of each
fork in the tree, measured from the root of the tree. I have not
attempted in include code for approximate confidence limits on branch
points, as I have done for branch lengths in DNAML, both because of
the extreme crudeness of that test, and because the variation of times
for different forks would be highly correlated.
The log likelihood printed out with the final tree can be used to
perform various likelihood ratio tests. One can, for example, compare
runs with different values of the expected transition/transversion
ratio to determine which value is the maximum likelihood estimate, and
what is the allowable range of values (using a likelihood ratio test,
which you will find described in mathematical statistics books). One
could also estimate the base frequencies in the same way. Both of
these, particularly the latter, require multiple runs of the program
to evaluate different possible values, and this might get expensive.
This program makes possible a (reasonably) legitimate statistical test
of the molecular clock. To do such a test, run DNAML and DNAMLK on the
same data. If the trees obtained are of the same topology (when
considered as unrooted), it is legitimate to compare their likelihoods
by the likelihood ratio test. In DNAML the likelihood has been
computed by estimating 2n-3 branch lengths, if their are n tips on the
tree. In DNAMLK it has been computed by estimating n-1 branching times
(in effect, n-1 branch lengths). The difference in the number of
parameters is (2n-3)-(n-1) = n-2. To perform the test take the
difference in log likelihoods between the two runs (DNAML should be
the higher of the two, barring numerical iteration difficulties) and
double it. Look this up on a chi-square distribution with n-2 degrees
of freedom. If the result is significant, the log likelihood has been
significantly increased by allowing all 2n-3 branch lengths to be
estimated instead of just n-1, and molecular clock may be rejected.
If the U (User Tree) option is used and more than one tree is
supplied, and the program is not told to assume autocorrelation
between the rates at different sites, the program also performs a
statistical test of each of these trees against the one with highest
likelihood. If there are two user trees, the test done is one which is
due to Kishino and Hasegawa (1989), a version of a test originally
introduced by Templeton (1983). In this implementation it uses the
mean and variance of log-likelihood differences between trees, taken
across sites. If the two trees' means are more than 1.96 standard
deviations different then the trees are declared significantly
different. This use of the empirical variance of log-likelihood
differences is more robust and nonparametric than the classical
likelihood ratio test, and may to some extent compensate for the any
lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods
across sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could
have been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the highest log-likelihood exceeds that
actually observed. Note that this sampling needs random numbers, and
so the program will prompt the user for a random number seed if one
has not already been supplied. With the two-tree KHT test no random
numbers are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one. However the
test is not available if we assume that there is autocorrelation of
rates at neighboring sites (option A) and is not done in those cases.
The branch lengths printed out are scaled in terms of expected numbers
of substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate
of change, averaged over all sites analyzed, is set to 1.0 if there
are multiple categories of sites. This means that whether or not there
are multiple categories of sites, the expected fraction of change for
very small branches is equal to the branch length. Of course, when a
branch is twice as long this does not mean that there will be twice as
much net change expected along it, since some of the changes occur in
the same site and overlie or even reverse each other. The branch
length estimates here are in terms of the expected underlying numbers
of changes. That means that a branch of length 0.26 is 26 times as
long as one which would show a 1% difference between the nucleotide
sequences at the beginning and end of the branch. But we would not
expect the sequences at the beginning and end of the branch to be 26%
different, as there would be some overlaying of changes.
Because of limitations of the numerical algorithm, branch length
estimates of zero will often print out as small numbers such as
0.00001. If you see a branch length that small, it is really estimated
to be of zero length.
Another possible source of confusion is the existence of negative
values for the log likelihood. This is not really a problem; the log
likelihood is not a probability but the logarithm of a
probability. When it is negative it simply means that the
corresponding probability is less than one (since we are seeing its
logarithm). The log likelihood is maximized by being made more
positive: -30.23 is worse than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what site categories
contributed the most to the final likelihood. This combination of HMM
rate categories need not have contributed a majority of the
likelihood, just a plurality. Still, it will be helpful as a view of
where the program infers that the higher and lower rates are. Note
that the use in this calculations of the prior probabilities of
different rates, and the average patch length, gives this inference a
"smoothed" appearance: some other combination of rates might make a
greater contribution to the likelihood, but be discounted because it
conflicts with this prior information. See the example output below to
see what this printout of rate categories looks like.
A second list will also be printed out, showing for each site which
rate accounted for the highest fraction of the likelihood. If the
fraction of the likelihood accounted for is less than 95%, a dot is
printed instead.
Option 3 in the menu controls whether the tree is printed out into the
output file. This is on by default, and usually you will want to leave
it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees
which are written onto the output tree file, rather than the trees
printed on the output file. To keep the output file from becoming too
large, it may be wisest to use option 3 to prevent trees being printed
onto the output file.
Option 4 in the menu controls whether the tree estimated by the
program is written onto a tree file. The default name of this output
tree file is "outtree". If the U option is in effect, all the
user-defined trees are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated
at each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species
which are the input sequences). In that table, if a site has a base
which accounts for more than 95% of the likelihood, it is printed in
capital letters (A rather than a). If the best nucleotide accounts for
less than 50% of the likelihood, the program prints out an ambiguity
code (such as M for "A or C") for the set of nucleotides which, taken
together, account for more half of the likelihood. The ambiguity codes
are listed in the sequence programs documentation file. One limitation
of the current version of the program is that when there are multiple
HMM rates (option R) the reconstructed nucleotides are based on only
the single assignment of rates to sites which accounts for the largest
amount of the likelihood. Thus the assessment of 95% of the
likelihood, in tabulating the ancestral states, refers to 95% of the
likelihood that is accounted for by that particular combination of
rates.
Output files for usage example
File: dnaml.fdnamlk
Nucleic acid sequence Maximum Likelihood method, version 3.69.650
5 species, 13 sites
Site categories are:
1111112222 222
Sites are weighted as follows:
01111 11111 110
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
Empirical Base Frequencies:
A 0.23636
C 0.29091
G 0.25455
T(U) 0.21818
Transition/transversion ratio = 2.000000
State in HMM Rate of change Probability
1 0.264 0.522
2 1.413 0.399
3 3.596 0.076
4 7.086 0.0036
5 12.641 0.000023
Site category Rate of change
1 1.000
2 2.000
+-Epsilon
+---------------------------------------------------------4
! +-Delta
--3
! +-------Gamma
+---------------------------------------------------2
! +-Beta
+-----1
+-Alpha
Ln Likelihood = -57.98242
Ancestor Node Node Height Length
-------- ---- ---- ------ ------
root 3
3 4 4.01604 4.01604
4 Epsilon 4.15060 0.13456
4 Delta 4.15060 0.13456
3 2 3.59089 3.59089
2 Gamma 4.15060 0.55971
2 1 3.99329 0.40240
1 Beta 4.15060 0.15731
1 Alpha 4.15060 0.15731
Combination of categories that contributes the most to the likelihood:
1132121111 211
Most probable category at each site if > 0.95 probability ("." otherwise)
.......... ...
Please help by correcting and extending the Wiki pages.
Function
Protein parsimony algorithm
Description
Estimates phylogenies from protein sequences (input using the standard
one-letter code for amino acids) using the parsimony method, in a
variant which counts only those nucleotide changes that change the
amino acid, on the assumption that silent changes are more easily
accomplished.
Algorithm
This program infers an unrooted phylogeny from protein sequences,
using a new method intermediate between the approaches of Eck and
Dayhoff (1966) and Fitch (1971). Eck and Dayhoff (1966) allowed any
amino acid to change to any other, and counted the number of such
changes needed to evolve the protein sequences on each given
phylogeny. This has the problem that it allows replacements which are
not consistent with the genetic code, counting them equally with
replacements that are consistent. Fitch, on the other hand, counted
the minimum number of nucleotide substitutions that would be needed to
achieve the given protein sequences. This counts silent changes
equally with those that change the amino acid.
The present method insists that any changes of amino acid be
consistent with the genetic code so that, for example, lysine is
allowed to change to methionine but not to proline. However, changes
between two amino acids via a third are allowed and counted as two
changes if each of the two replacements is individually allowed. This
sometimes allows changes that at first sight you would think should be
outlawed. Thus we can change from phenylalanine to glutamine via
leucine in two steps total. Consulting the genetic code, you will find
that there is a leucine codon one step away from a phenylalanine
codon, and a leucine codon one step away from glutamine. But they are
not the same leucine codon. It actually takes three base substitutions
to get from either of the phenylalanine codons TTT and TTC to either
of the glutamine codons CAA or CAG. Why then does this program count
only two? The answer is that recent DNA sequence comparisons seem to
show that synonymous changes are considerably faster and easier than
ones that change the amino acid. We are assuming that, in effect,
synonymous changes occur so much more readily that they need not be
counted. Thus, in the chain of changes TTT (Phe) --> CTT (Leu) --> CTA
(Leu) --> CAA (Glu), the middle one is not counted because it does not
change the amino acid (leucine).
To maintain consistency with the genetic code, it is necessary for the
program internally to treat serine as two separate states (ser1 and
ser2) since the two groups of serine codons are not adjacent in the
code. Changes to the state "deletion" are counted as three steps to
prevent the algorithm from assuming unnecessary deletions. The state
"unknown" is simply taken to mean that the amino acid, which has not
been determined, will in each part of a tree that is evaluated be
assumed be whichever one causes the fewest steps.
The assumptions of this method (which has not been described in the
literature), are thus something like this:
Change in different sites is independent. Change in different
lineages is independent. The probability of a base substitution that
changes the amino acid sequence is small over the lengths of time
involved in a branch of the phylogeny. The expected amounts of change
in different branches of the phylogeny do not vary by so much that two
changes in a high-rate branch are more probable than one change in a
low-rate branch. The expected amounts of change do not vary enough
among sites that two changes in one site are more probable than one
change in another. The probability of a base change that is
synonymous is much higher than the probability of a change that is not
synonymous. That these are the assumptions of parsimony methods has
been documented in a series of papers of mine: (1973a, 1978b, 1979,
1981b, 1983b, 1988b). For an opposing view arguing that the parsimony
methods make no substantive assumptions such as these, see the works
by Farris (1983) and Sober (1983a, 1983b, 1988), but also read the
exchange between Felsenstein and Sober (1986).
The input for the program is fairly standard. The first line contains
the number of species and the number of amino acid positions (counting
any stop codons that you want to include).
Next come the species data. Each sequence starts on a new line, has a
ten-character species name that must be blank-filled to be of that
length, followed immediately by the species data in the one-letter
code. The sequences must either be in the "interleaved" or
"sequential" formats described in the Molecular Sequence Programs
document. The I option selects between them. The sequences can have
internal blanks in the sequence but there must be no extra blanks at
the end of the terminated line. Note that a blank is not a valid
symbol for a deletion.
The protein sequences are given by the one-letter code used by
described in the Molecular Sequence Programs documentation file. Note
that if two polypeptide chains are being used that are of different
length owing to one terminating before the other, they should be coded
as (say)
HIINMA*????
HIPNMGVWABT
since after the stop codon we do not definitely know that there has
been a deletion, and do not know what amino acid would have been
there. If DNA studies tell us that there is DNA sequence in that
region, then we could use "X" rather than "?". Note that "X" means an
unknown amino acid, but definitely an amino acid, while "?" could mean
either that or a deletion. The distinction is often significant in
regions where there are deletions: one may want to encode a six-base
deletion as "-?????" since that way the program will only count one
deletion, not six deletion events, when the deletion arises. However,
if there are overlapping deletions it may not be so easy to know what
coding is correct.
One will usually want to use "?" after a stop codon, if one does not
know what amino acid is there. If the DNA sequence has been observed
there, one probably ought to resist putting in the amino acids that
this DNA would code for, and one should use "X" instead, because under
the assumptions implicit in this parsimony method, changes to any
noncoding sequence are much easier than changes in a coding region
that change the amino acid, so that they shouldn't be counted anyway!
The form of this information is the standard one described in the main
documentation file. For the U option the tree provided must be a
rooted bifurcating tree, with the root placed anywhere you want, since
that root placement does not affect anything.
Usage
Here is a sample session with fprotpars
% fprotpars
Protein parsimony algorithm
Input (aligned) protein sequence set(s): protpars.dat
Phylip tree file (optional):
Phylip protpars program output file [protpars.fprotpars]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements
!---------!
.........
.........
Output written to file "protpars.fprotpars"
Trees also written onto file "protpars.treefile"
Done.
% fprotpars -option
Protein parsimony algorithm
Input (aligned) protein sequence set(s): protpars.dat
Phylip tree file (optional):
Phylip weights file (optional): protparswts.dat
Number of times to randomise [0]:
Species number to use as outgroup [0]:
Use threshold parsimony [N]:
Genetic codes
U : Universal
M : Mitochondrial
V : Vertebrate mitochondrial
F : Fly mitochondrial
Y : Yeast mitochondrial
Use which genetic code [Universal]:
Phylip protpars program output file [protpars.fprotpars]:
Write out trees to tree file [Y]:
Phylip tree output file (optional) [protpars.treefile]:
Print data at start of run [N]:
Print indications of progress of run [Y]:
Print out tree [Y]:
Print steps at each site [N]:
Print sequences at all nodes of tree [N]:
Weights set # 1:
Adding species:
1. Delta
2. Alpha
3. Gamma
4. Epsilon
5. Beta
Doing global rearrangements
!---------!
.........
.........
Output written to file "protpars.fprotpars"
Trees also written onto file "protpars.treefile"
Weights set # 2:
Adding species:
1. Epsilon
2. Alpha
3. Delta
4. Gamma
5. Beta
Doing global rearrangements
!---------!
.........
.........
Output written to file "protpars.fprotpars"
Trees also written onto file "protpars.treefile"
Done.
Protein parsimony algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fprotpars] Phylip protpars program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Phylip weights file (optional)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 1.000 or more)
-whichcode menu [Universal] Use which genetic code (Values:
U (Universal); M (Mitochondrial); V
(Vertebrate mitochondrial); F (Fly
mitochondrial); Y (Yeast mitochondrial))
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fprotpars] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print steps at each site
-ancseq boolean [N] Print sequences at all nodes of tree
* -[no]dotdiff boolean [Y] Use dot differencing to display results
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip protpars program output file
Output file
<*>.fprotpars
Additional (Optional) qualifiers
-weights
properties
Phylip weights file (optional)
Property value(s)
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-dothreshold
toggle
Use threshold parsimony
Toggle value Yes/No
No
-threshold
float
Threshold value
Number 1.000 or more
1
-whichcode
list
Use which genetic code
U
(Universal)
M
(Mitochondrial)
V
(Vertebrate mitochondrial)
F
(Fly mitochondrial)
Y
(Yeast mitochondrial)
Universal
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fprotpars
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-stepbox
boolean
Print steps at each site
Boolean value Yes/No
No
-ancseq
boolean
Print sequences at all nodes of tree
Boolean value Yes/No
No
-[no]dotdiff
boolean
Use dot differencing to display results
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fprotpars output is standard: if option 1 is toggled on, the
data is printed out, with the convention that "." means "the same as
in the first species". Then comes a list of equally parsimonious
trees, and (if option 2 is toggled on) a table of the number of
changes of state required in each position. If option 5 is toggled on,
a table is printed out after each tree, showing for each branch
whether there are known to be changes in the branch, and what the
states are inferred to have been at the top end of the branch. This is
a reconstruction of the ancestral sequences in the tree. If you choose
option 5, a menu item "." appears which gives you the opportunity to
turn off dot-differencing so that complete ancestral sequences are
shown. If the inferred state is a "?" there will be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand. If option 6 is left in its default state
the trees found will be written to a tree file, so that they are
available to be used in other programs. If the program finds multiple
trees tied for best, all of these are written out onto the output tree
file. Each is followed by a numerical weight in square brackets (such
as [0.25000]). This is needed when we use the trees to make a
consensus tree of the results of bootstrapping or jackknifing, to
avoid overrepresenting replicates that find many tied trees.
If the U (User Tree) option is used and more than one tree is
supplied, the program also performs a statistical test of each of
these trees against the best tree. This test, which is a version of
the test proposed by Alan Templeton (1983) and evaluated in a test
case by me (1985a). It is closely parallel to a test using log
likelihood differences due to Kishino and Hasegawa (1989), and uses
the mean and variance of step differences between trees, taken across
positions. If the mean is more than 1.96 standard deviations different
then the trees are declared significantly different. The program
prints out a table of the steps for each tree, the differences of each
from the best one, the variance of that quantity as determined by the
step differences at individual positions, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
Output files for usage example
File: protpars.fprotpars
Protein parsimony algorithm, version 3.69.650
3 trees in all found
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
+--Epsilon
+-----4
! +--Delta
+--3
! ! +--Gamma
1 +-----2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 16.000
Protein parsimony algorithm, version 3.69.650
5 species, 10 sites
Name Sequences
---- ---------
Alpha ABCDEFGHIK
Beta ..--......
Gamma ?...S..*??
Delta CIK.......
Epsilon DIK.......
3 trees in all found
+-----------Beta
!
1 +--------Gamma
! !
+--2 +--Epsilon
! +--4
+--3 +--Delta
!
+-----Alpha
remember: (although rooted by outgroup) this is an unrooted tree!
requires a total of 14.000
steps in each position:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0! 3 1 5 3 2 0 0 2 0
10! 0
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
root 1 AN??EFGHIK
1 Beta maybe .B--......
[Part of this file has been deleted for brevity]
root 1 AN??EFGHIK
1 Beta maybe .B--......
1 2 maybe ..CD......
2 3 maybe ?.........
3 4 yes .IK.......
4 Epsilon maybe D.........
4 Delta yes C.........
3 Gamma yes ?B..S..*??
2 Alpha maybe .B........
+-----------Beta
!
1 +--Epsilon
! +-----4
! ! +--Delta
+--3
! +--Gamma
+-----2
+--Alpha
remember: (although rooted by outgroup) this is an unrooted tree!
requires a total of 14.000
steps in each position:
0 1 2 3 4 5 6 7 8 9
*-----------------------------------------
0! 3 1 5 3 2 0 0 2 0
10! 0
From To Any Steps? State at upper node
( . means same as in the node below it on tree)
root 1 AN??EFGHIK
1 Beta maybe .B--......
1 3 yes ..?D......
3 4 yes ?IK.......
4 Epsilon maybe D.........
4 Delta yes C.........
3 2 yes ..C.......
2 Gamma yes ?B..S..*??
2 Alpha maybe .B........
Protein parsimony algorithm, version 3.69.650
Data set # 1:
3 trees in all found
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 25.000
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 25.000
+--Epsilon
+-----4
[Part of this file has been deleted for brevity]
+--------Gamma
+--2
! ! +-----Epsilon
! +--4
1 ! +--Delta
! +--3
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 24.000
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 24.000
+--Epsilon
+-----4
! +--Delta
+--3
! ! +--Gamma
1 +-----2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 24.000
Protein parsimony algorithm, version 3.69.650
Weights set # 1:
3 trees in all found
+--------Gamma
!
+--2 +--Epsilon
! ! +--4
! +--3 +--Delta
1 !
! +-----Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 14.000
+--Epsilon
+--4
+--3 +--Delta
! !
+--2 +-----Gamma
! !
1 +--------Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 14.000
[Part of this file has been deleted for brevity]
+--Epsilon
+-----4
! +--Delta
+--3
! ! +--Gamma
1 +-----2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 2.000
+--------Delta
+--3
! ! +-----Epsilon
! +--4
1 ! +--Gamma
! +--2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 2.000
+--------Epsilon
+--4
! ! +-----Delta
! +--3
1 ! +--Gamma
! +--2
! +--Beta
!
+-----------Alpha
remember: this is an unrooted tree!
requires a total of 2.000
Please help by correcting and extending the Wiki pages.
Function
DNA parsimony algorithm
Description
Estimates phylogenies by the parsimony method using nucleic acid
sequences. Allows use the full IUB ambiguity codes, and estimates
ancestral nucleotide states. Gaps treated as a fifth nucleotide
state. It can also do transversion parsimony. Can cope with
multifurcations, reconstruct ancestral states, use 0/1 character
weights, and infer branch lengths
Algorithm
This program carries out unrooted parsimony (analogous to Wagner
trees) (Eck and Dayhoff, 1966; Kluge and Farris, 1969) on DNA
sequences. The method of Fitch (1971) is used to count the number of
changes of base needed on a given tree. The assumptions of this method
are analogous to those of MIX:
Each site evolves independently.
Different lineages evolve independently.
The probability of a base substitution at a given site
is small over the lengths of time involved in a branch of the
phylogeny.
The expected amounts of change in different branches of
the phylogeny do not vary by so much that two changes in a high-rate
branch are more probable than one change in a low-rate branch.
The expected amounts of change do not vary enough among sites that two
changes in one site are more probable than one change in another.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b, 1988), but also read the
exchange between Felsenstein and Sober (1986).
Change from an occupied site to a deletion is counted as one
change. Reversion from a deletion to an occupied site is allowed and
is also counted as one change. Note that this in effect assumes that a
deletion N bases long is N separate events.
Dnapars can handle both bifurcating and multifurcating trees. In doing
its search for most parsimonious trees, it adds species not only by
creating new forks in the middle of existing branches, but it also
tries putting them at the end of new branches which are added to
existing forks. Thus it searches among both bifurcating and
multifurcating trees. If a branch in a tree does not have any
characters which might change in that branch in the most parsimonious
tree, it does not save that tree. Thus in any tree that results, a
branch exists only if some character has a most parsimonious
reconstruction that would involve change in that branch.
It also saves a number of trees tied for best (you can alter the
number it saves using the V option in the menu). When rearranging
trees, it tries rearrangements of all of the saved trees. This makes
the algorithm slower than earlier versions of Dnapars.
The input data is standard. The first line of the input file contains
the number of species and the number of sites.
Next come the species data. Each sequence starts on a new line, has a
ten-character species name that must be blank-filled to be of that
length, followed immediately by the species data in the one-letter
code. The sequences must either be in the "interleaved" or
"sequential" formats described in the Molecular Sequence Programs
document. The I option selects between them. The sequences can have
internal blanks in the sequence but there must be no extra blanks at
the end of the terminated line. Note that a blank is not a valid
symbol for a deletion.
Usage
Here is a sample session with fdnapars
% fdnapars
DNA parsimony algorithm
Input (aligned) nucleotide sequence set(s): dnapars.dat
Phylip tree file (optional):
Phylip dnapars program output file [dnapars.fdnapars]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements on the first of the trees tied for best
!---------!
.........
.........
Collapsing best trees
.
Output written to file "dnapars.fdnapars"
Tree also written onto file "dnapars.treefile"
Done.
DNA parsimony algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fdnapars] Phylip dnapars program output
file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-maxtrees integer [10000] Number of trees to save (Integer
from 1 to 1000000)
* -[no]thorough toggle [Y] More thorough search
* -[no]rearrange boolean [Y] Rearrange on just one best tree
-transversion boolean [N] Use transversion parsimony
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1.0] Threshold value (Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnapars] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-stepbox boolean [N] Print out steps in each site
-ancseq boolean [N] Print sequences at all nodes of tree
-[no]treeprint boolean [Y] Print out tree
* -[no]dotdiff boolean [Y] Use dot differencing to display results
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip dnapars program output file
Output file
<*>.fdnapars
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-maxtrees
integer
Number of trees to save
Integer from 1 to 1000000
10000
-[no]thorough
toggle
More thorough search
Toggle value Yes/No
Yes
-[no]rearrange
boolean
Rearrange on just one best tree
Boolean value Yes/No
Yes
-transversion
boolean
Use transversion parsimony
Boolean value Yes/No
No
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-dothreshold
toggle
Use threshold parsimony
Toggle value Yes/No
No
-threshold
float
Threshold value
Number 1.000 or more
1.0
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdnapars
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-stepbox
boolean
Print out steps in each site
Boolean value Yes/No
No
-ancseq
boolean
Print sequences at all nodes of tree
Boolean value Yes/No
No
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-[no]dotdiff
boolean
Use dot differencing to display results
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fdnapars output is standard: if option 1 is toggled on, the
data is printed out, with the convention that "." means "the same as
in the first species". Then comes a list of equally parsimonious
trees. Each tree has branch lengths. These are computed using an
algorithm published by Hochbaum and Pathria (1997) which I first heard
of from Wayne Maddison who invented it independently of them. This
algorithm averages the number of reconstructed changes of state over
all sites a over all possible most parsimonious placements of the
changes of state among branches. Note that it does not correct in any
way for multiple changes that overlay each other.
If option 2 is toggled on a table of the number of changes of state
required in each character is also printed. If option 5 is toggled on,
a table is printed out after each tree, showing for each branch
whether there are known to be changes in the branch, and what the
states are inferred to have been at the top end of the branch. This is
a reconstruction of the ancestral sequences in the tree. If you choose
option 5, a menu item "." appears which gives you the opportunity to
turn off dot-differencing so that complete ancestral sequences are
shown. If the inferred state is a "?" or one of the IUB ambiguity
symbols, there will be multiple equally-parsimonious assignments of
states; the user must work these out for themselves by hand. A "?" in
the reconstructed states means that in addition to one or more bases,
a deletion may or may not be present. If option 6 is left in its
default state the trees found will be written to a tree file, so that
they are available to be used in other programs.
If the U (User Tree) option is used and more than one tree is
supplied, the program also performs a statistical test of each of
these trees against the best tree. This test, which is a version of
the test proposed by Alan Templeton (1983) and evaluated in a test
case by me (1985a). It is closely parallel to a test using log
likelihood differences due to Kishino and Hasegawa (1989), and uses
the mean and variance of step differences between trees, taken across
sites. If the mean is more than 1.96 standard deviations different
then the trees are declared significantly different. The program
prints out a table of the steps for each tree, the differences of each
from the best one, the variance of that quantity as determined by the
step differences at individual sites, and a conclusion as to whether
that tree is or is not significantly worse than the best one. If the U
(User Tree) option is used and more than one tree is supplied, and the
program is not told to assume autocorrelation between the rates at
different sites, the program also performs a statistical test of each
of these trees against the one with highest likelihood. If there are
two user trees, this is a version of the test proposed by Alan
Templeton (1983) and evaluated in a test case by me (1985a). It is
closely parallel to a test using log likelihood differences due to
Kishino and Hasegawa (1989) It uses the mean and variance of the
differences in the number of steps between trees, taken across
sites. If the two trees' means are more than 1.96 standard deviations
different, then the trees are declared significantly different.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sums of steps across
sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could
have been expected if they all had the same expected number of steps,
numbers of steps for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the lowest number of steps exceeds that
actually observed. Note that this sampling needs random numbers, and
so the program will prompt the user for a random number seed if one
has not already been supplied. With the two-tree KHT test no random
numbers are used.
In either the KHT or the SH test the program prints out a table of the
number of steps for each tree, the differences of each from the lowest
one, the variance of that quantity as determined by the differences of
the numbers of steps at individual sites, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
Option 6 in the menu controls whether the tree estimated by the
program is written onto a tree file. The default name of this output
tree file is "outtree". If the U option is in effect, all the
user-defined trees are written to the output tree file. If the program
finds multiple trees tied for best, all of these are written out onto
the output tree file. Each is followed by a numerical weight in square
brackets (such as [0.25000]). This is needed when we use the trees to
make a consensus tree of the results of bootstrapping or jackknifing,
to avoid overrepresenting replicates that find many tied trees.
Output files for usage example
File: dnapars.fdnapars
DNA parsimony algorithm, version 3.69.650
One most parsimonious tree found:
+-----Epsilon
+----------------------------3
+------------2 +-------Delta
| |
| +----------------Gamma
|
1----Beta
|
+---------Alpha
requires a total of 19.000
between and length
------- --- ------
1 2 0.217949
2 3 0.487179
3 Epsilon 0.096154
3 Delta 0.134615
2 Gamma 0.275641
1 Beta 0.076923
1 Alpha 0.173077
Please help by correcting and extending the Wiki pages.
Function
Protein phylogeny by maximum likelihood
Description
Same as PROML but assumes a molecular clock. The use of the two
programs together permits a likelihood ratio test of the molecular
clock hypothesis to be made.
Estimates phylogenies from protein amino acid sequences by maximum
likelihood. The PAM, JTT, or PMB models can be employed, and also use
of a Hidden Markov model of rates, with the program inferring which
sites have which rates. This also allows gamma-distribution and
gamma-plus-invariant sites distributions of rates across sites. It
also allows different rates of change at known sites.
Algorithm
This program implements the maximum likelihood method for protein
amino acid sequences under the constraint that the trees estimated
must be consistent with a molecular clock. The molecular clock is the
assumption that the tips of the tree are all equidistant, in branch
length, from its root. This program is indirectly related to PROML. It
uses the Dayhoff probability model of change between amino acids. Its
algorithmic details are not yet published, but many of them are
similar to DNAMLK.
The assumptions of the model are:
Each position in the sequence evolves independently.
Different lineages evolve independently.
Each position undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of occurrence)
which we specify.
All relevant positions are included in the sequence, not just those
that have changed or those that are "phylogenetically informative".
The probabilities of change between amino acids are given by the model
of Jones,
Taylor, and Thornton (1992), the PMB model of Veerassamy, Smith and
Tillier (2004), or the PAM model of Dayhoff (Dayhoff and Eck, 1968;
Dayhoff et. al., 1979).
Note the assumption that we are looking at all positions, including
those that have not changed at all. It is important not to restrict
attention to some positions based on whether or not they have changed;
doing that would bias branch lengths by making them too long, and that
in turn would cause the method to misinterpret the meaning of those
positions that had changed.
This program uses a Hidden Markov Model (HMM) method of inferring
different rates of evolution at different amino acid positions. This
was described in a paper by me and Gary Churchill (1996). It allows us
to specify to the program that there will be a number of different
possible evolutionary rates, what the prior probabilities of
occurrence of each is, and what the average length of a patch of
positions all having the same rate. The rates can also be chosen by
the program to approximate a Gamma distribution of rates, or a Gamma
distribution plus a class of invariant positions. The program computes
the likelihood by summing it over all possible assignments of rates to
positions, weighting each by its prior probability of occurrence.
For example, if we have used the C and A options (described below) to
specify that there are three possible rates of evolution, 1.0, 2.4,
and 0.0, that the prior probabilities of a position having these rates
are 0.4, 0.3, and 0.3, and that the average patch length (number of
consecutive positions with the same rate) is 2.0, the program will sum
the likelihood over all possibilities, but giving less weight to those
that (say) assign all positions to rate 2.4, or that fail to have
consecutive positions that have the same rate.
The Hidden Markov Model framework for rate variation among positions
was independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of rates; we
allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant positions.
This feature effectively removes the artificial assumption that all
positions have the same rate, and also means that we need not know in
advance the identities of the positions that have a particular rate of
evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each positions (for example, we might want
amino acid positions in the active site of a protein to change more
slowly than other positions. This is done with the categories input
file and the C option. We then specify (using the menu) the relative
rates of evolution of amino acid positions in the different
categories. For example, we might specify that positions in the active
site evolve at relative rates of 0.2 compared to 1.0 at other
positions. If we are assuming that a particular position maintains a
cysteine bridge to another, we may want to put it in a category of
positions (including perhaps the initial position of the protein
sequence which maintains methionine) which changes at a rate of 0.0.
If both user-assigned rate categories and Hidden Markov Model rates
are allowed, the program assumes that the actual rate at a position is
the product of the user-assigned category rate and the Hidden Markov
Model regional rate. (This may not always make perfect biological
sense: it would be more natural to assume some upper bound to the
rate, as we have discussed in the Felsenstein and Churchill
paper). Nevertheless you may want to use both types of rate variation.
Usage
Here is a sample session with fpromlk
% fpromlk
Protein phylogeny by maximum likelihood
Input (aligned) protein sequence set(s): promlk.dat
Phylip tree file (optional):
Phylip promlk program output file [promlk.fpromlk]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "promlk.fpromlk"
Tree also written onto file "promlk.treefile"
Done.
Protein phylogeny by maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fpromlk] Phylip promlk program output
file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
* -lengths boolean [N] Use branch lengths from user trees
-model menu [Jones-Taylor-Thornton] Probability model
for amino acid change (Values: j
(Jones-Taylor-Thornton); h (Henikoff/Tillier
PMBs); d (Dayhoff PAM))
-gammatype menu [n] Rate variation among sites (Values: g
(Gamma distributed rates); i
(Gamma+invariant sites); h (User defined HMM
of rates); n (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ngammacat integer [1] Number of categories (1-9) (Integer from
1 to 9)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ninvarcat integer [1] Number of categories (1-9) including one
for invariant sites (Integer from 1 to 9)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -nhmmcategories integer [1] Number of HMM rate categories (Integer
from 1 to 9)
* -hmmrates array [1.0] HMM category rates
* -hmmprobabilities array [1.0] Probability for each HMM category
* -adjsite boolean [N] Rates at adjacent sites correlated
* -lambda float [1.0] Mean block length of sites having the
same rate (Number 1.000 or more)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fpromlk] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-hypstate boolean [N] Reconstruct hypothetical sequence
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip promlk program output file
Output file
<*>.fpromlk
Additional (Optional) qualifiers
-ncategories
integer
Number of substitution rate categories
Integer from 1 to 9
1
-rate
array
Rate for each category
List of floating point numbers
-categories
properties
File of substitution rate categories
Property value(s)
-weights
properties
Weights file
Property value(s)
-lengths
boolean
Use branch lengths from user trees
Boolean value Yes/No
No
-model
list
Probability model for amino acid change
j
(Jones-Taylor-Thornton)
h
(Henikoff/Tillier PMBs)
d
(Dayhoff PAM)
Jones-Taylor-Thornton
-gammatype
list
Rate variation among sites
g
(Gamma distributed rates)
i
(Gamma+invariant sites)
h
(User defined HMM of rates)
n
(Constant rate)
n
-gammacoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ngammacat
integer
Number of categories (1-9)
Integer from 1 to 9
1
-invarcoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ninvarcat
integer
Number of categories (1-9) including one for invariant sites
Integer from 1 to 9
1
-invarfrac
float
Fraction of invariant sites
Number from 0.000 to 1.000
0.0
-nhmmcategories
integer
Number of HMM rate categories
Integer from 1 to 9
1
-hmmrates
array
HMM category rates
List of floating point numbers
1.0
-hmmprobabilities
array
Probability for each HMM category
List of floating point numbers
1.0
-adjsite
boolean
Rates at adjacent sites correlated
Boolean value Yes/No
No
-lambda
float
Mean block length of sites having the same rate
Number 1.000 or more
1.0
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-global
boolean
Global rearrangements
Boolean value Yes/No
No
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fpromlk
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-hypstate
boolean
Reconstruct hypothetical sequence
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fpromlk output starts by giving the number of species, the
number of amino acid positions.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of positions is printed, as
well as the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the
menu option to print them out, with the base sequences printed in
groups of ten amino acids. The trees found are printed as a rooted
tree topology. The internal nodes are numbered arbitrarily for the
sake of identification. The number of trees evaluated so far and the
log likelihood of the tree are also given. The branch lengths in the
diagram are roughly proportional to the estimated branch lengths,
except that very short branches are printed out at least three
characters in length so that the connections can be seen. The unit of
branch length is the expected fraction of amino acids changed (so that
1.0 is 100 PAMs).
A table is printed showing the length of each tree segment, and the
time (in units of expected amino acid substitutions per position) of
each fork in the tree, measured from the root of the tree. I have not
attempted in include code for approximate confidence limits on branch
points, as I have done for branch lengths in PROML, both because of
the extreme crudeness of that test, and because the variation of times
for different forks would be highly correlated.
The log likelihood printed out with the final tree can be used to
perform various likelihood ratio tests. One can, for example, compare
runs with different values of the relative rate of change in the
active site and in the rest of the protein to determine which value is
the maximum likelihood estimate, and what is the allowable range of
values (using a likelihood ratio test, which you will find described
in mathematical statistics books). One could also estimate the base
frequencies in the same way. Both of these, particularly the latter,
require multiple runs of the program to evaluate different possibl
values, and this might get expensive.
This program makes possible a (reasonably) legitimate statistical test
of the molecular clock. To do such a test, run PROML and PROMLK on the
same data. If the trees obtained are of the same topology (when
considered as unrooted), it is legitimate to compare their likelihoods
by the likelihood ratio test. In PROML the likelihood has been
computed by estimating 2n-3 branch lengths, if their are n tips on the
tree. In PROMLK it has been computed by estimating n-1 branching times
(in effect, n-1 branch lengths). The difference in the number of
parameters is (2n-3)-(n-1) = n-2. To perform the test take the
difference in log likelihoods between the two runs (PROML should be
the higher of the two, barring numerical iteration difficulties) and
double it. Look this up on a chi-square distribution with n-2 degrees
of freedom. If the result is significant, the log likelihood has been
significantly increased by allowing all 2n-3 branch lengths to be
estimated instead of just n-1, and molecular clock may be rejected.
If the U (User Tree) option is used and more than one tree is
supplied, and the program is not told to assume autocorrelation
between the rates at different amino acid positions, the program also
performs a statistical test of each of these trees against the one
with highest likelihood. If there are two user trees, the test done is
one which is due to Kishino and Hasegawa (1989), a version of a test
originally introduced by Templeton (1983). In this implementation it
uses the mean and variance of log-likelihood differences between
trees, taken across amino acid positions. If the two trees' means are
more than 1.96 standard deviations different then the trees are
declared significantly different. This use of the empirical variance
of log-likelihood differences is more robust and nonparametric than
the classical likelihood ratio test, and may to some extent compensate
for the any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods
across amino acid positions are computed for all pairs of trees. To
test whether the difference between each tree and the best one is
larger than could have been expected if they all had the same expected
log-likelihood, log-likelihoods for all trees are sampled with these
covariances and equal means (Shimodaira and Hasegawa's "least
favorable hypothesis"), and a P value is computed from the fraction of
times the difference between the tree's value and the highest
log-likelihood exceeds that actually observed. Note that this sampling
needs random numbers, and so the program will prompt the user for a
random number seed if one has not already been supplied. With the
two-tree KHT test no random numbers are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one. However the
test is not available if we assume that there is autocorrelation of
rates at neighboring positions (option A) and is not done in those
cases.
The branch lengths printed out are scaled in terms of 100 times the
expected numbers of amino acid substitutions, scaled so that the
average rate of change, averaged over all the positions analyzed, is
set to 100.0, if there are multiple categories of positions. This
means that whether or not there are multiple categories of positions,
the expected percentage of change for very small branches is equal to
the branch length. Of course, when a branch is twice as long this does
not mean that there will be twice as much net change expected along
it, since some of the changes occur in the same position and overlie
or even reverse each other. underlying numbers of changes. That means
that a branch of length 26 is 26 times as long as one which would show
a 1% difference between the amino acid sequences at the beginning and
end of the branch, but we would not expect the sequences at the
beginning and end of the branch to be 26% different, as there would be
some overlaying of changes.
Because of limitations of the numerical algorithm, branch length
estimates of zero will often print out as small numbers such as
0.00001. If you see a branch length that small, it is really estimated
to be of zero length.
Another possible source of confusion is the existence of negative
values for the log likelihood. This is not really a problem; the log
likelihood is not a probability but the logarithm of a
probability. When it is negative it simply means that the
corresponding probability is less than one (since we are seeing its
logarithm). The log likelihood is maximized by being made more
positive: -30.23 is worse than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what amino acid position
categories contributed the most to the final likelihood. This
combination of HMM rate categories need not have contributed a
majority of the likelihood, just a plurality. Still, it will be
helpful as a view of where the program infers that the higher and
lower rates are. Note that the use in this calculations of the prior
probabilities of different rates, and the average patch length, gives
this inference a "smoothed" appearance: some other combination of
rates might make a greater contribution to the likelihood, but be
discounted because it conflicts with this prior information. See the
example output below to see what this printout of rate categories
looks like. A second list will also be printed out, showing for each
position which rate accounted for the highest fraction of the
likelihood. If the fraction of the likelihood accounted for is less
than 95%, a dot is printed instead.
Option 3 in the menu controls whether the tree is printed out into the
output file. This is on by default, and usually you will want to leave
it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees
which are written onto the output tree file, rather than the trees
printed on the output file. To keep the output file from becoming too
large, it may be wisest to use option 3 to prevent trees being printed
onto the output file.
Option 4 in the menu controls whether the tree estimated by the
program is written onto a tree file. The default name of this output
tree file is "outtree". If the U option is in effect, all the
user-defined trees are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated
at each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species
which are the input sequences). The symbol printed out is for the
amino acid which accounts for the largest fraction of the likelihood
at that position. In that table, if a position has an amino acid which
accounts for more than 95% of the likelihood, its symbol printed in
capital letters (W rather than w). One limitation of the current
version of the program is that when there are multiple HMM rates
(option R) the reconstructed amino acids are based on only the single
assignment of rates to positions which accounts for the largest amount
of the likelihood. Thus the assessment of 95% of the likelihood, in
tabulating the ancestral states, refers to 95% of the likelihood that
is accounted for by that particular combination of rates.
Please help by correcting and extending the Wiki pages.
Function
Plots a cladogram- or phenogram-like rooted tree diagram
Description
Plots rooted phylogenies, cladograms, circular trees and phenograms in
a wide variety of user-controllable formats. The program is
interactive and allows previewing of the tree on PC, Macintosh, or X
Windows screens, or on Tektronix or Digital graphics terminals. Final
output can be to a file formatted for one of the drawing programs, for
a ray-tracing or VRML browser, or one at can be sent to a laser
printer (such as Postscript or PCL-compatible printers), on graphics
screens or terminals, on pen plotters or on dot matrix printers
capable of graphics.
Similar to DRAWTREE but plots rooted phylogenies.
Algorithm
DRAWGRAM interactively plots a cladogram- or phenogram-like rooted
tree diagram, with many options including orientation of tree and
branches, style of tree, label sizes and angles, tree depth, margin
sizes, stem lengths, and placement of nodes in the tree. Particularly
if you can use your computer to preview the plot, you can very
effectively adjust the details of the plotting to get just the kind of
plot you want.
To understand the working of DRAWGRAM and DRAWTREE, you should first
read the Tree Drawing Programs web page in this documentation.
As with DRAWTREE, to run DRAWGRAM you need a compiled copy of the
program, a font file, and a tree file. The tree file has a default
name of intree. The font file has a default name of "fontfile". If
there is no file of that name, the program will ask you for the name
of a font file (we provide ones that have the names font1 through
font6). Once you decide on a favorite one of these, you could make a
copy of it and call it fontfile, and it will then be used by
default. Note that the program will get confused if the input tree
file has the number of trees on the first line of the file, so that
numbr may have to be removed.
Usage
Here is a sample session with fdrawgram
% fdrawgram -previewer n
Plots a cladogram- or phenogram-like rooted tree diagram
Phylip tree file: drawgram.tree
Phylip drawgram output file [drawgram.fdrawgram]:
DRAWGRAM from PHYLIP version 3.69.650
Reading tree ...
Tree has been read.
Loading the font ....
Font loaded.
Writing plot file ...
Plot written to file "drawgram.fdrawgram"
Done.
Plots a cladogram- or phenogram-like rooted tree diagram
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-plotfile] outfile [*.fdrawgram] Phylip drawgram output file
Additional (Optional) qualifiers (* if not always prompted):
-[no]grows boolean [Y] Tree grows horizontally
-style menu [c] Tree style output (Values: c (cladogram
(v-shaped)); p (phenogram (branches are
square)); v (curvogram (branches are 1/4 out
of an ellipse)); e (eurogram (branches
angle outward, then up)); s (swooporam
(branches curve outward then reverse)); o
(circular tree))
-plotter menu [l] Plotter or printer the tree will be
drawn on (Values: l (Postscript printer file
format); m (PICT format (for drawing
programs)); j (HP 75 DPI Laserjet PCL file
format); s (HP 150 DPI Laserjet PCL file
format); y (HP 300 DPI Laserjet PCL file
format); w (MS-Windows Bitmap); f (FIG 2.0
drawing program format); a (Idraw drawing
program format); z (VRML Virtual Reality
Markup Language file); n (PCX 640x350 file
format (for drawing programs)); p (PCX
800x600 file format (for drawing programs));
q (PCX 1024x768 file format (for drawing
programs)); k (TeKtronix 4010 graphics
terminal); x (X Bitmap format); v (POVRAY 3D
rendering program file); r (Rayshade 3D
rendering program file); h (Hewlett-Packard
pen plotter (HPGL file format)); d (DEC
ReGIS graphics (VT240 terminal)); e (Epson
MX-80 dot-matrix printer); c
(Prowriter/Imagewriter dot-matrix printer);
t (Toshiba 24-pin dot-matrix printer); o
(Okidata dot-matrix printer); b (Houston
Instruments plotter); u (other (one you have
inserted code for)))
-previewer menu [x] Previewing device (Values: n (Will not
be previewed); I i (MSDOS graphics screen
m:Macintosh screens); x (X Windows display);
w (MS Windows display); k (TeKtronix 4010
graphics terminal); d (DEC ReGIS graphics
(VT240 terminal)); o (Other (one you have
inserted code for)))
-lengths boolean [N] Use branch lengths from user trees
* -labelrotation float [90.0] Angle of labels (0 degrees is
horizontal for a tree growing vertically)
(Number from 0.000 to 360.000)
-[no]rescaled toggle [Y] Automatically rescale branch lengths
* -bscale float [1.0] Centimeters per unit branch length
(Any numeric value)
-treedepth float [0.53] Depth of tree as fraction of its
breadth (Number from 0.100 to 100.000)
-stemlength float [0.05] Stem length as fraction of tree depth
(Number from 0.010 to 100.000)
-nodespace float [0.3333] Character height as fraction of tip
spacing (Number from 0.100 to 100.000)
-nodeposition menu [c] Position of interior nodes (Values: i
(Intermediate between their immediate
descendants); w (Weighted average of tip
positions); c (Centered among their ultimate
descendants); n (Innermost of immediate
descendants); v (So tree is v shaped))
* -xmargin float [1.65] Horizontal margin (cm) (Number 0.100
or more)
* -ymargin float [2.16] Vertical margin (cm) (Number 0.100 or
more)
* -xrayshade float [1.65] Horizontal margin (pixels) for
Rayshade output (Number 0.100 or more)
* -yrayshade float [2.16] Vertical margin (pixels) for Rayshade
output (Number 0.100 or more)
-paperx float [20.63750] Paper width (Any numeric value)
-papery float [26.98750] Paper height (Number 0.100 or
more)
-pagesheight float [1] Number of trees across height of page
(Number 1.000 or more)
-pageswidth float [1] Number of trees across width of page
(Number 1.000 or more)
-hpmargin float [0.41275] Horizontal overlap (cm) (Number
0.001 or more)
-vpmargin float [0.53975] Vertical overlap (cm) (Number
0.001 or more)
Advanced (Unprompted) qualifiers:
-fontfile string [font1] Fontfile name (Any string)
Associated qualifiers:
"-plotfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-intreefile] (Parameter 1)
tree
Phylip tree file
Phylogenetic tree
[-plotfile] (Parameter 2)
outfile
Phylip drawgram output file
Output file
<*>.fdrawgram
Additional (Optional) qualifiers
-[no]grows
boolean
Tree grows horizontally
Boolean value Yes/No
Yes
-style
list
Tree style output
c
(cladogram (v-shaped))
p
(phenogram (branches are square))
v
(curvogram (branches are 1/4 out of an ellipse))
e
(eurogram (branches angle outward, then up))
s
(swooporam (branches curve outward then reverse))
o
(circular tree)
c
-plotter
list
Plotter or printer the tree will be drawn on
l
(Postscript printer file format)
m
(PICT format (for drawing programs))
j
(HP 75 DPI Laserjet PCL file format)
s
(HP 150 DPI Laserjet PCL file format)
y
(HP 300 DPI Laserjet PCL file format)
w
(MS-Windows Bitmap)
f
(FIG 2.0 drawing program format)
a
(Idraw drawing program format)
z
(VRML Virtual Reality Markup Language file)
n
(PCX 640x350 file format (for drawing programs))
p
(PCX 800x600 file format (for drawing programs))
q
(PCX 1024x768 file format (for drawing programs))
k
(TeKtronix 4010 graphics terminal)
x
(X Bitmap format)
v
(POVRAY 3D rendering program file)
r
(Rayshade 3D rendering program file)
h
(Hewlett-Packard pen plotter (HPGL file format))
d
(DEC ReGIS graphics (VT240 terminal))
e
(Epson MX-80 dot-matrix printer)
c
(Prowriter/Imagewriter dot-matrix printer)
t
(Toshiba 24-pin dot-matrix printer)
o
(Okidata dot-matrix printer)
b
(Houston Instruments plotter)
u
(other (one you have inserted code for))
l
-previewer
list
Previewing device
n
(Will not be previewed)
I i
(MSDOS graphics screen m:Macintosh screens)
x
(X Windows display)
w
(MS Windows display)
k
(TeKtronix 4010 graphics terminal)
d
(DEC ReGIS graphics (VT240 terminal))
o
(Other (one you have inserted code for))
x
-lengths
boolean
Use branch lengths from user trees
Boolean value Yes/No
No
-labelrotation
float
Angle of labels (0 degrees is horizontal for a tree growing vertically)
Number from 0.000 to 360.000
90.0
-[no]rescaled
toggle
Automatically rescale branch lengths
Toggle value Yes/No
Yes
-bscale
float
Centimeters per unit branch length
Any numeric value
1.0
-treedepth
float
Depth of tree as fraction of its breadth
Number from 0.100 to 100.000
0.53
-stemlength
float
Stem length as fraction of tree depth
Number from 0.010 to 100.000
0.05
-nodespace
float
Character height as fraction of tip spacing
Number from 0.100 to 100.000
0.3333
-nodeposition
list
Position of interior nodes
i
(Intermediate between their immediate descendants)
w
(Weighted average of tip positions)
c
(Centered among their ultimate descendants)
n
(Innermost of immediate descendants)
v
(So tree is v shaped)
c
-xmargin
float
Horizontal margin (cm)
Number 0.100 or more
1.65
-ymargin
float
Vertical margin (cm)
Number 0.100 or more
2.16
-xrayshade
float
Horizontal margin (pixels) for Rayshade output
Number 0.100 or more
1.65
-yrayshade
float
Vertical margin (pixels) for Rayshade output
Number 0.100 or more
2.16
-paperx
float
Paper width
Any numeric value
20.63750
-papery
float
Paper height
Number 0.100 or more
26.98750
-pagesheight
float
Number of trees across height of page
Number 1.000 or more
1
-pageswidth
float
Number of trees across width of page
Number 1.000 or more
1
-hpmargin
float
Horizontal overlap (cm)
Number 0.001 or more
0.41275
-vpmargin
float
Vertical overlap (cm)
Number 0.001 or more
0.53975
Advanced (Unprompted) qualifiers
-fontfile
string
Fontfile name
Any string
font1
Associated qualifiers
"-plotfile" associated outfile qualifiers
-odirectory2 -odirectory_plotfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fdrawgram reads ...
Input files for usage example
File: drawgram.tree
(Delta,(Epsilon,(Gamma,(Beta,Alpha))));
Output file format
fdrawgram
output ...
Output files for usage example
Graphics File: drawgram.fdrawgram
Data files
The font file has a default name of "fontfile". If there is no file of
that name, the program will ask you for the name of a font file (we
provide ones that have the names font1 through font6). Once you decide
on a favorite one of these, you could make a copy of it and call it
fontfile, and it will then be used by default.
Please help by correcting and extending the Wiki pages.
Function
Estimate nucleotide phylogeny by maximum likelihood
Description
Estimates phylogenies from nucleotide sequences by maximum
likelihood. The model employed allows for unequal expected frequencies
of the four nucleotides, for unequal rates of transitions and
transversions, and for different (prespecified) rates of change in
different categories of sites, and also use of a Hidden Markov model
of rates, with the program inferring which sites have which
rates. This also allows gamma-distribution and gamma-plus-invariant
sites distributions of rates across sites.
Algorithm
This program implements the maximum likelihood method for DNA
sequences. The present version is faster than earlier versions of
DNAML. Details of the algorithm are published in the paper by
Felsenstein and Churchill (1996). The model of base substitution
allows the expected frequencies of the four bases to be unequal,
allows the expected frequencies of transitions and transversions to be
unequal, and has several ways of allowing different rates of evolution
at different sites.
The assumptions of the present model are:
Each site in the sequence evolves independently.
Different lineages evolve independently.
Each site undergoes substitution at an expected rate which is chosen
from a series of rates (each with a probability of occurrence) which
we specify.
All relevant sites are included in the sequence, not just those that
have changed or those that are "phylogenetically informative".
A substitution consists of one of two sorts of events:
The first kind of event consists of the replacement of the
existing base by a base drawn from a pool of purines or a pool of
pyrimidines (depending on whether the base being replaced was a purine
or a pyrimidine). It can lead either to no change or to a transition.
The second kind of event consists of the replacement of the
existing base by a base drawn at random from a pool of bases at known
frequencies, independently of the identity of the base which is being
replaced. This could lead either to a no change, to a transition or to
a transversion.
The ratio of the two purines in the purine replacement pool is the
same as their ratio in the overall pool, and similarly for the
pyrimidines.
The ratios of transitions to transversions can be set by the user. The
substitution process can be diagrammed as follows: Suppose that you
specified A, C, G, and T base frequencies of 0.24, 0.28, 0.27, and
0.21.
First kind of event:
Determine whether the existing base is a purine or a pyrimidine.
Draw from the proper pool:
Purine pool: Pyrimidine pool:
| | | |
| 0.4706 A | | 0.5714 C |
| 0.5294 G | | 0.4286 T |
| (ratio is | | (ratio is |
| 0.24 : 0.27) | | 0.28 : 0.21) |
|_______________| |_______________|
Second kind of event:
Draw from the overall pool:
| |
| 0.24 A |
| 0.28 C |
| 0.27 G |
| 0.21 T |
|__________________|
Note that if the existing base is, say, an A, the first kind of event
has a 0.4706 probability of "replacing" it by another A. The second
kind of event has a 0.24 chance of replacing it by another A. This
rather disconcerting model is used because it has nice mathematical
properties that make likelihood calculations far easier. A closely
similar, but not precisely identical model having different rates of
transitions and transversions has been used by Hasegawa
et. al. (1985b). The transition probability formulas for the current
model were given (with my permission) by Kishino and Hasegawa
(1989). Another explanation is available in the paper by Felsenstein
and Churchill (1996).
Note the assumption that we are looking at all sites, including those
that have not changed at all. It is important not to restrict
attention to some sites based on whether or not they have changed;
doing that would bias branch lengths by making them too long, and that
in turn would cause the method to misinterpret the meaning of those
sites that had changed.
This program uses a Hidden Markov Model (HMM) method of inferring
different rates of evolution at different sites. This was described in
a paper by me and Gary Churchill (1996). It allows us to specify to
the program that there will be a number of different possible
evolutionary rates, what the prior probabilities of occurrence of each
is, and what the average length of a patch of sites all having the
same rate. The rates can also be chosen by the program to approximate
a Gamma distribution of rates, or a Gamma distribution plus a class of
invariant sites. The program computes the the likelihood by summing it
over all possible assignments of rates to sites, weighting each by its
prior probability of occurrence.
For example, if we have used the C and A options (described below) to
specify that there are three possible rates of evolution, 1.0, 2.4,
and 0.0, that the prior probabilities of a site having these rates are
0.4, 0.3, and 0.3, and that the average patch length (number of
consecutive sites with the same rate) is 2.0, the program will sum the
likelihood over all possibilities, but giving less weight to those
that (say) assign all sites to rate 2.4, or that fail to have
consecutive sites that have the same rate.
The Hidden Markov Model framework for rate variation among sites was
independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of rates; we
allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant sites.
This feature effectively removes the artificial assumption that all
sites have the same rate, and also means that we need not know in
advance the identities of the sites that have a particular rate of
evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each site (for example, we might want first,
second, and third codon positions in a protein coding sequence to be
three different categories. This is done with the categories input
file and the C option. We then specify (using the menu) the relative
rates of evolution of sites in the different categories. For example,
we might specify that first, second, and third positions evolve at
relative rates of 1.0, 0.8, and 2.7.
If both user-assigned rate categories and Hidden Markov Model rates
are allowed, the program assumes that the actual rate at a site is the
product of the user-assigned category rate and the Hidden Markov Model
regional rate. (This may not always make perfect biological sense: it
would be more natural to assume some upper bound to the rate, as we
have discussed in the Felsenstein and Churchill paper). Nevertheless
you may want to use both types of rate variation.
Estimate nucleotide phylogeny by maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fdnaml] Phylip dnaml program output file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
* -lengths boolean [N] Use branch lengths from user trees
-ttratio float [2.0] Transition/transversion ratio (Number
0.001 or more)
-[no]freqsfrom toggle [Y] Use empirical base frequencies from
seqeunce input
* -basefreq array [0.25 0.25 0.25 0.25] Base frequencies for A
C G T/U (use blanks to separate)
-gammatype menu [Constant rate] Rate variation among sites
(Values: g (Gamma distributed rates); i
(Gamma+invariant sites); h (User defined HMM
of rates); n (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ngammacat integer [1] Number of categories (1-9) (Integer from
1 to 9)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ninvarcat integer [1] Number of categories (1-9) including one
for invariant sites (Integer from 1 to 9)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -nhmmcategories integer [1] Number of HMM rate categories (Integer
from 1 to 9)
* -hmmrates array [1.0] HMM category rates
* -hmmprobabilities array [1.0] Probability for each HMM category
* -adjsite boolean [N] Rates at adjacent sites correlated
* -lambda float [1.0] Mean block length of sites having the
same rate (Number 1.000 or more)
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]rough boolean [Y] Speedier but rougher analysis
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fdnaml] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-hypstate boolean [N] Reconstruct hypothetical sequence
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip dnaml program output file
Output file
<*>.fdnaml
Additional (Optional) qualifiers
-ncategories
integer
Number of substitution rate categories
Integer from 1 to 9
1
-rate
array
Rate for each category
List of floating point numbers
-categories
properties
File of substitution rate categories
Property value(s)
-weights
properties
Weights file
Property value(s)
-lengths
boolean
Use branch lengths from user trees
Boolean value Yes/No
No
-ttratio
float
Transition/transversion ratio
Number 0.001 or more
2.0
-[no]freqsfrom
toggle
Use empirical base frequencies from seqeunce input
Toggle value Yes/No
Yes
-basefreq
array
Base frequencies for A C G T/U (use blanks to separate)
List of floating point numbers
0.25 0.25 0.25 0.25
-gammatype
list
Rate variation among sites
g
(Gamma distributed rates)
i
(Gamma+invariant sites)
h
(User defined HMM of rates)
n
(Constant rate)
Constant rate
-gammacoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ngammacat
integer
Number of categories (1-9)
Integer from 1 to 9
1
-invarcoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ninvarcat
integer
Number of categories (1-9) including one for invariant sites
Integer from 1 to 9
1
-invarfrac
float
Fraction of invariant sites
Number from 0.000 to 1.000
0.0
-nhmmcategories
integer
Number of HMM rate categories
Integer from 1 to 9
1
-hmmrates
array
HMM category rates
List of floating point numbers
1.0
-hmmprobabilities
array
Probability for each HMM category
List of floating point numbers
1.0
-adjsite
boolean
Rates at adjacent sites correlated
Boolean value Yes/No
No
-lambda
float
Mean block length of sites having the same rate
Number 1.000 or more
1.0
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-global
boolean
Global rearrangements
Boolean value Yes/No
No
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-[no]rough
boolean
Speedier but rougher analysis
Boolean value Yes/No
Yes
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdnaml
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-hypstate
boolean
Reconstruct hypothetical sequence
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fdnaml output starts by giving the number of species, the
number of sites, and the base frequencies for A, C, G, and T that have
been specified. It then prints out the transition/transversion ratio
that was specified or used by default. It also uses the base
frequencies to compute the actual transition/transversion ratio
implied by the parameter.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of sites is printed, as well as
the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the
menu option to print them out, with the base sequences printed in
groups of ten bases along the lines of the Genbank and EMBL
formats. The trees found are printed as an unrooted tree topology
(possibly rooted by outgroup if so requested). The internal nodes are
numbered arbitrarily for the sake of identification. The number of
trees evaluated so far and the log likelihood of the tree are also
given. Note that the trees printed out have a trifurcation at the
base. The branch lengths in the diagram are roughly proportional to
the estimated branch lengths, except that very short branches are
printed out at least three characters in length so that the
connections can be seen.
A table is printed showing the length of each tree segment (in units
of expected nucleotide substitutions per site), as well as (very)
rough confidence limits on their lengths. If a confidence limit is
negative, this indicates that rearrangement of the tree in that region
is not excluded, while if both limits are positive, rearrangement is
still not necessarily excluded because the variance calculation on
which the confidence limits are based results in an underestimate,
which makes the confidence limits too narrow.
In addition to the confidence limits, the program performs a crude
Likelihood Ratio Test (LRT) for each branch of the tree. The program
computes the ratio of likelihoods with and without this branch length
forced to zero length. This done by comparing the likelihoods changing
only that branch length. A truly correct LRT would force that branch
length to zero and also allow the other branch lengths to adjust to
that. The result would be a likelihood ratio closer to 1. Therefore
the present LRT will err on the side of being too significant. YOU ARE
WARNED AGAINST TAKING IT TOO SERIOUSLY. If you want to get a better
likelihood curve for a branch length you can do multiple runs with
different prespecified lengths for that branch, as discussed above in
the discussion of the L option.
One should also realize that if you are looking not at a
previously-chosen branch but at all branches, that you are seeing the
results of multiple tests. With 20 tests, one is expected to reach
significance at the P = .05 level purely by chance. You should
therefore use a much more conservative significance level, such as .05
divided by the number of tests. The significance of these tests is
shown by printing asterisks next to the confidence interval on each
branch length. It is important to keep in mind that both the
confidence limits and the tests are very rough and approximate, and
probably indicate more significance than they should. Nevertheless,
maximum likelihood is one of the few methods that can give you any
indication of its own error; most other methods simply fail to warn
the user that there is any error! (In fact, whole philosophical
schools of taxonomists exist whose main point seems to be that there
isn't any error, that the "most parsimonious" tree is the best tree by
definition and that's that).
The log likelihood printed out with the final tree can be used to
perform various likelihood ratio tests. One can, for example, compare
runs with different values of the expected transition/transversion
ratio to determine which value is the maximum likelihood estimate, and
what is the allowable range of values (using a likelihood ratio test,
which you will find described in mathematical statistics books). One
could also estimate the base frequencies in the same way. Both of
these, particularly the latter, require multiple runs of the program
to evaluate different possible values, and this might get expensive.
If the U (User Tree) option is used and more than one tree is
supplied, and the program is not told to assume autocorrelation
between the rates at different sites, the program also performs a
statistical test of each of these trees against the one with highest
likelihood. If there are two user trees, the test done is one which is
due to Kishino and Hasegawa (1989), a version of a test originally
introduced by Templeton (1983). In this implementation it uses the
mean and variance of log-likelihood differences between trees, taken
across sites. If the two trees' means are more than 1.96 standard
deviations different then the trees are declared significantly
different. This use of the empirical variance of log-likelihood
differences is more robust and nonparametric than the classical
likelihood ratio test, and may to some extent compensate for the any
lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods
across sites are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could
have been expected if they all had the same expected log-likelihood,
log-likelihoods for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the highest log-likelihood exceeds that
actually observed. Note that this sampling needs random numbers, and
so the program will prompt the user for a random number seed if one
has not already been supplied. With the two-tree KHT test no random
numbers are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one. However the
test is not available if we assume that there is autocorrelation of
rates at neighboring sites (option A) and is not done in those cases.
The branch lengths printed out are scaled in terms of expected numbers
of substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate
of change, averaged over all sites analyzed, is set to 1.0 if there
are multiple categories of sites. This means that whether or not there
are multiple categories of sites, the expected fraction of change for
very small branches is equal to the branch length. Of course, when a
branch is twice as long this does not mean that there will be twice as
much net change expected along it, since some of the changes occur in
the same site and overlie or even reverse each other. The branch
length estimates here are in terms of the expected underlying numbers
of changes. That means that a branch of length 0.26 is 26 times as
long as one which would show a 1% difference between the nucleotide
sequences at the beginning and end of the branch. But we would not
expect the sequences at the beginning and end of the branch to be 26%
different, as there would be some overlaying of changes.
Confidence limits on the branch lengths are also given. Of course a
negative value of the branch length is meaningless, and a confidence
limit overlapping zero simply means that the branch length is not
necessarily significantly different from zero. Because of limitations
of the numerical algorithm, branch length estimates of zero will often
print out as small numbers such as 0.00001. If you see a branch length
that small, it is really estimated to be of zero length. Note that
versions 2.7 and earlier of this program printed out the branch
lengths in terms of expected probability of change, so that they were
scaled differently.
Another possible source of confusion is the existence of negative
values for the log likelihood. This is not really a problem; the log
likelihood is not a probability but the logarithm of a
probability. When it is negative it simply means that the
corresponding probability is less than one (since we are seeing its
logarithm). The log likelihood is maximized by being made more
positive: -30.23 is worse than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what site categories
contributed the most to the final likelihood. This combination of HMM
rate categories need not have contributed a majority of the
likelihood, just a plurality. Still, it will be helpful as a view of
where the program infers that the higher and lower rates are. Note
that the use in this calculations of the prior probabilities of
different rates, and the average patch length, gives this inference a
"smoothed" appearance: some other combination of rates might make a
greater contribution to the likelihood, but be discounted because it
conflicts with this prior information. See the example output below to
see what this printout of rate categories looks like. A second list
will also be printed out, showing for each site which rate accounted
for the highest fraction of the likelihood. If the fraction of the
likelihood accounted for is less than 95%, a dot is printed instead.
Option 3 in the menu controls whether the tree is printed out into the
output file. This is on by default, and usually you will want to leave
it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees
which are written onto the output tree file, rather than the trees
printed on the output file. To keep the output file from becoming too
large, it may be wisest to use option 3 to prevent trees being printed
onto the output file.
Option 4 in the menu controls whether the tree estimated by the
program is written onto a tree file. The default name of this output
tree file is "outtree". If the U option is in effect, all the
user-defined trees are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated
at each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species
which are the input sequences). In that table, if a site has a base
which accounts for more than 95% of the likelihood, it is printed in
capital letters (A rather than a). If the best nucleotide accounts for
less than 50% of the likelihood, the program prints out an ambiguity
code (such as M for "A or C") for the set of nucleotides which, taken
together, account for more half of the likelihood. The ambiguity codes
are listed in the sequence programs documentation file. One limitation
of the current version of the program is that when there are multiple
HMM rates (option R) the reconstructed nucleotides are based on only
the single assignment of rates to sites which accounts for the largest
amount of the likelihood. Thus the assessment of 95% of the
likelihood, in tabulating the ancestral states, refers to 95% of the
likelihood that is accounted for by that particular combination of
rates.
Output files for usage example
File: dnaml.fdnaml
Nucleic acid sequence Maximum Likelihood method, version 3.69.650
5 species, 13 sites
Site categories are:
1111112222 222
Sites are weighted as follows:
01111 11111 110
Name Sequences
---- ---------
Alpha AACGTGGCCA AAT
Beta AAGGTCGCCA AAC
Gamma CATTTCGTCA CAA
Delta GGTATTTCGG CCT
Epsilon GGGATCTCGG CCC
Empirical Base Frequencies:
A 0.23636
C 0.29091
G 0.25455
T(U) 0.21818
Transition/transversion ratio = 2.000000
State in HMM Rate of change Probability
1 0.264 0.522
2 1.413 0.399
3 3.596 0.076
4 7.086 0.0036
5 12.641 0.000023
Site category Rate of change
1 1.000
2 2.000
+Epsilon
+--------------------------------------------------------3
+--2 +-Delta
| |
| +Beta
|
1------Gamma
|
+-Alpha
remember: this is an unrooted tree!
Ln Likelihood = -57.87892
Between And Length Approx. Confidence Limits
------- --- ------ ------- ---------- ------
1 Alpha 0.26766 ( zero, 0.80513) *
1 2 0.04687 ( zero, 0.48388)
2 3 7.59821 ( zero, 22.01485) **
3 Epsilon 0.00006 ( zero, 0.46205)
3 Delta 0.27319 ( zero, 0.73380) **
2 Beta 0.00006 ( zero, 0.44052)
1 Gamma 0.95677 ( zero, 2.46186) **
* = significantly positive, P < 0.05
** = significantly positive, P < 0.01
Combination of categories that contributes the most to the likelihood:
1132121111 211
Most probable category at each site if > 0.95 probability ("." otherwise)
.......... ...
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped genetic frequencies algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of
the package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
FFREQBOOT is a gene frequency specific version of SEQBOOT.
SEQBOOT is a general bootstrapping and data set translation tool. It
is intended to allow you to generate multiple data sets that are
resampled versions of the input data set. Since almost all programs in
the package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or
permuted. SEQBOOT can handle molecular sequences, binary characters,
restriction sites, or gene frequencies. It can also convert data sets
between Sequential and Interleaved format, and into the NEXUS format
or into a new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of
interest. For example, if you were using DNAPARS you would first run
SEQBOOT and make a file with 100 bootstrapped data sets. Then you
would give this file the proper name to have it be the input file for
DNAPARS. Running DNAPARS with the M (Multiple Data Sets) menu choice
and informing it to expect 100 data sets, you would generate a big
output file as well as a treefile with the trees from the 100 data
sets. This treefile could be renamed so that it would serve as the
input for CONSENSE. When CONSENSE is run the majority rule consensus
tree will result, showing the outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this
package. The same steps are necessary with all of them. Doing things
this way some of the intermediate files (the tree file from the
DNAPARS run, for example) can be used to summarize the results of the
bootstrap in other ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add
one extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me (Felsenstein,
1985b; see also Penny and Hendy, 1985). It involves creating a new
data set by sampling N characters randomly with replacement, so that
the resulting data set has the same size as the original, but some
characters have been left out and others are duplicated. The random
variation of the results from analyzing these bootstrapped data sets
can be shown statistically to be typical of the variation that you
would get from collecting new data sets. The method assumes that the
characters evolve independently, an assumption that may not be
realistic for many kinds of data.
The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial Bootstrap
method, and Shimodaira's (2002) AU method, both of which correct the
bias of bootstrap P values.
Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct for
it by samopling, not individual characters, but blocks of adjacent
characters. This is called a block bootstrap and was introduced by
Künsch (1989). If the correlations are believed to extend over some
number of characters, you choose a block size, B, that is larger than
this, and choose N/B blocks of size B. In its implementation here the
block bootstrap "wraps around" at the end of the characters (so that
if a block starts in the last B-1 characters, it continues by wrapping
around to the first character after it reaches the last
character). Note also that if you have a DNA sequence data set of an
exon of a coding region, you can ensure that equal numbers of first,
second, and third coding positions are sampled by using the block
bootstrap with B = 3.
Partial block-bootstrapping. Similar to partial bootstrapping except
sampling blocks rather than single characters.
Delete-half-jackknifing.. This alternative to the bootstrap involves
sampling a random half of the characters, and including them in the
data but dropping the others. The resulting data sets are half the
size of the original, and no characters are duplicated. The random
variation from doing this should be very similar to that obtained from
the bootstrap. The method is advocated by Wu (1986). It was mentioned
by me in my bootstrapping paper (Felsenstein, 1985b), and has been
available for many years in this program as an option. Note that, for
the present, block-jackknifing is not available, because I cannot
figure out how to do it straightforwardly when the block size is not a
divisor of the number of characters.
Delete-fraction jackknifing. Jackknifing is advocated by Farris
et. al. (1996) but as deleting a fraction 1/e (1/2.71828). This
retains too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it is
made available here as an option, with the user asked to supply the
fraction of characters that are to be retained.
Permuting species within characters. This method of resampling (well,
OK, it may not be best to call it resampling) was introduced by Archie
(1989) and Faith (1990; see also Faith and Cranston, 1991). It
involves permuting the columns of the data matrix separately. This
produces data matrices that have the same number and kinds of
characters but no taxonomic structure. It is used for different
purposes than the bootstrap, as it tests not the variation around an
estimated tree but the hypothesis that there is no taxonomic structure
in the data: if a statistic such as number of steps is significantly
smaller in the actual data than it is in replicates that are permuted,
then we can argue that there is some taxonomic structure in the data
(though perhaps it might be just the presence of aa pair of sibling
species).
Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For many
methods of tree inference this will make no difference to the outcome
(unless one has rates of evolution correlated among adjacent
sites). It is included as a possible step in carrying out a
permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so as
to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
Rewriting. This is not a resampling or permutation method: it simply
rewrites the data set into a different format. That format can be the
PHYLIP format. For molecular sequences and discrete morphological
character it can also be the NEXUS format. For molecular sequences one
other format is available, a new (and nonstandard) XML format of our
own devising. When the PHYLIP format is chosen the data set is
coverted between Interleaved and Sequential format. If it was read in
as Interleaved sequences, it will be written out as Sequential format,
and vice versa. The NEXUS format for molecular sequences is always
written as interleaved sequences. The XML format is different from
(though similar to) a number of other XML sequence alignment
formats. An example will be found below. Here is a table to links to
those other XML alignment formats:
Andrew Rambaut's
BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html
and http://evolve.zoo.ox.ac.uk/beast/referenindex.html
A format for alignments. There
is also a format for phylogenies
described there.
MSAML M
http://xml.coverpages.org/msaml-desc-dec.html
Defined by Paul Gordon of
University of Calgary. See his
big list of molecular biology
XML projects.
BSML
http://www.bsml.org/resources/default.asp
Bioinformatic Sequence
Markup Language
includes a multiple sequence
alignment XML format
Usage
Here is a sample session with ffreqboot
% ffreqboot -seed 3
Bootstrapped genetic frequencies algorithm
Input file: freqboot.dat
Phylip seqboot_freq program output file [freqboot.ffreqboot]:
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "freqboot.ffreqboot"
Done.
Bootstrapped genetic frequencies algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] frequencies (no help text) frequencies value
[-outfile] outfile [*.ffreqboot] Phylip seqboot_freq program
output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
frequencies
(no help text) frequencies value
Frequency value(s)
[-outfile] (Parameter 2)
outfile
Phylip seqboot_freq program output file
Output file
<*>.ffreqboot
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-test
list
Choose test
b
(Bootstrap)
j
(Jackknife)
c
(Permute species for each character)
o
(Permute character order)
s
(Permute within species)
r
(Rewrite data)
b
-regular
toggle
Altered sampling fraction
Toggle value Yes/No
No
-fracsample
float
Samples as percentage of sites
Number from 0.100 to 100.000
100.0
-blocksize
integer
Block size for bootstraping
Integer 1 or more
1
-reps
integer
How many replicates
Integer 1 or more
100
-justweights
list
Write out datasets or just weights
d
(Datasets)
w
(Weights)
d
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-printdata
boolean
Print out the data at start of run
Boolean value Yes/No
No
-[no]dotdiff
boolean
Use dot-differencing
Boolean value Yes/No
Yes
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
ffreqboot data files read by SEQBOOT are the standard ones for
the various kinds of data. For molecular sequences the sequences may
be either interleaved or sequential, and similarly for restriction
sites. Restriction sites data may either have or not have the third
argument, the number of restriction enzymes used. Discrete
morphological characters are always assumed to be in sequential
format. Gene frequencies data start with the number of species and the
number of loci, and then follow that by a line with the number of
alleles at each locus. The data for each locus may either have one
entry for each allele, or omit one allele at each locus. The details
of the formats are given in the main documentation file, and in the
documentation files for the groups of programsreads any normal
sequence USAs.
ffreqboot output will contain the data sets generated by the
resampling process. Note that, when Gene Frequencies data is used or
when Discrete Morphological characters with the Factors option are
used, the number of characters in each data set may vary. It may also
vary if there are an odd number of characters or sites and the
Delete-Half-Jackknife resampling method is used, for then there will
be a 50% chance of choosing (n+1)/2 characters and a 50% chance of
choosing (n-1)/2 characters.
The Factors option causes the characters to be resampled together. If
(say) three adjacent characters all have the same factors characters,
so that they all are understood to be recoding one multistate
character, they will be resampled together as a group.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these
data avoid any result which is sensitive to the input order of species
from showing up repeatedly and thus appearing to have evidence in its
favor.
The numerical options 1 and 2 in the menu also affect the output
file. If 1 is chosen (it is off by default) the program will print the
original input data set on the output file before the resampled data
sets. I cannot actually see why anyone would want to do this. Option 2
toggles the feature (on by default) that prints out up to 20 times
during the resampling process a notification that the program has
completed a certain number of data sets. Thus if 100 resampled data
sets are being produced, every 5 data sets a line is printed saying
which data set has just been completed. This option should be turned
off if the program is running in background and silence is
desirable. At the end of execution the program will always (whatever
the setting of option 2) print a couple of lines saying that output
has been written to the output file.
Please help by correcting and extending the Wiki pages.
Function
Nucleic acid sequence distance matrix program
Description
Computes four different distances between species from nucleic acid
sequences. The distances can then be used in the distance matrix
programs. The distances are the Jukes-Cantor formula, one based on
Kimura's 2- parameter method, the F84 model used in DNAML, and the
LogDet distance. The distances can also be corrected for
gamma-distributed and gamma-plus-invariant-sites-distributed rates of
change in different sites. Rates of evolution can vary among sites in
a prespecified way, and also according to a Hidden Markov model. The
program can also make a table of percentage similarity among
sequences.
Algorithm
This program uses nucleotide sequences to compute a distance matrix,
under four different models of nucleotide substitution. It can also
compute a table of similarity between the nucleotide sequences. The
distance for each pair of species estimates the total branch length
between the two species, and can be used in the distance matrix
programs FITCH, KITSCH or NEIGHBOR. This is an alternative to use of
the sequence data itself in the maximum likelihood program DNAML or
the parsimony program DNAPARS.
The program reads in nucleotide sequences and writes an output file
containing the distance matrix, or else a table of similarity between
sequences. The four models of nucleotide substitution are those of
Jukes and Cantor (1969), Kimura (1980), the F84 model (Kishino and
Hasegawa, 1989; Felsenstein and Churchill, 1996), and the model
underlying the LogDet distance (Barry and Hartigan, 1987; Lake, 1994;
Steel, 1994; Lockhart et. al., 1994). All except the LogDet distance
can be made to allow for for unequal rates of substitution at
different sites, as Jin and Nei (1990) did for the Jukes-Cantor
model. The program correctly takes into account a variety of sequence
ambiguities, although in cases where they exist it can be slow.
Jukes and Cantor's (1969) model assumes that there is independent
change at all sites, with equal probability. Whether a base changes is
independent of its identity, and when it changes there is an equal
probability of ending up with each of the other three bases. Thus the
transition probability matrix (this is a technical term from
probability theory and has nothing to do with transitions as opposed
to transversions) for a short period of time dt is:
To: A G C T
---------------------------------
A | 1-3a a a a
From: G | a 1-3a a a
C | a a 1-3a a
T | a a a 1-3a
where a is u dt, the product of the rate of substitution per unit
time (u) and the length dt of the time interval. For longer periods of
time this implies that the probability that two sequences will differ
at a given site is:
p = 3/4 ( 1 - e- 4/3 u t)
and hence that if we observe p, we can compute an estimate of the
branch length ut by inverting this to get
ut = - 3/4 loge ( 1 - 4/3 p )
The Kimura "2-parameter" model is almost as symmetric as this, but
allows for a difference between transition and transversion rates. Its
transition probability matrix for a short interval of time is:
To: A G C T
---------------------------------
A | 1-a-2b a b b
From: G | a 1-a-2b b b
C | b b 1-a-2b a
T | b b a 1-a-2b
where a is u dt, the product of the rate of transitions per unit time
and dt is the length dt of the time interval, and b is v dt, the
product of half the rate of transversions (i.e., the rate of a
specific transversion) and the length dt of the time interval.
The F84 model incorporates different rates of transition and
transversion, but also allowing for different frequencies of the four
nucleotides. It is the model which is used in DNAML, the maximum
likelihood nucelotide sequence phylogenies program in this
package. You will find the model described in the document for that
program. The transition probabilities for this model are given by
Kishino and Hasegawa (1989), and further explained in a paper by me
and Gary Churchill (1996).
The LogDet distance allows a fairly general model of substitution. It
computes the distance from the determinant of the empirically observed
matrix of joint probabilities of nucleotides in the two species. An
explanation of it is available in the chapter by Swofford et,
al. (1996).
The first three models are closely related. The DNAML model reduces to
Kimura's two-parameter model if we assume that the equilibrium
frequencies of the four bases are equal. The Jukes-Cantor model in
turn is a special case of the Kimura 2-parameter model where a =
b. Thus each model is a special case of the ones that follow it,
Jukes-Cantor being a special case of both of the others.
The Jin and Nei (1990) correction for variation in rate of evolution
from site to site can be adapted to all of the first three models. It
assumes that the rate of substitution varies from site to site
according to a gamma distribution, with a coefficient of variation
that is specified by the user. The user is asked for it when choosing
this option in the menu.
Each distance that is calculated is an estimate, from that particular
pair of species, of the divergence time between those two species. For
the Jukes- Cantor model, the estimate is computed using the formula
for ut given above, as long as the nucleotide symbols in the two
sequences are all either A, C, G, T, U, N, X, ?, or - (the latter four
indicate a deletion or an unknown nucleotide. This estimate is a
maximum likelihood estimate for that model. For the Kimura 2-parameter
model, with only these nucleotide symbols, formulas special to that
estimate are also computed. These are also, in effect, computing the
maximum likelihood estimate for that model. In the Kimura case it
depends on the observed sequences only through the sequence length and
the observed number of transition and transversion differences between
those two sequences. The calculation in that case is a maximum
likelihood estimate and will differ somewhat from the estimate
obtained from the formulas in Kimura's original paper. That formula
was also a maximum likelihood estimate, but with the
transition/transversion ratio estimated empirically, separately for
each pair of sequences. In the present case, one overall preset
transition/transversion ratio is used which makes the computations
harder but achieves greater consistency between different comparisons.
For the F84 model, or for any of the models where one or both
sequences contain at least one of the other ambiguity codons such as
Y, R, etc., a maximum likelihood calculation is also done using code
which was originally written for DNAML. Its disadvantage is that it is
slow. The resulting distance is in effect a maximum likelihood
estimate of the divergence time (total branch length between) the two
sequences. However the present program will be much faster than
versions earlier than 3.5, because I have speeded up the iterations.
The LogDet model computes the distance from the determinant of the
matrix of co-occurrence of nucleotides in the two species, according
to the formula
D = - 1/4(loge(|F|) - 1/2loge(fA1fC1fG1fT1fA2fC2fG2fT2))
Where F is a matrix whose (i,j) element is the fraction of sites at
which base i occurs in one species and base j occurs in the other. fji
is the fraction of sites at which species i has base j. The LogDet
distance cannot cope with ambiguity codes. It must have completely
defined sequences. One limitation of the LogDet distance is that it
may be infinite sometimes, if there are too many changes between
certain pairs of nucleotides. This can be particularly noticeable with
distances computed from bootstrapped sequences. Note that there is an
assumption that we are looking at all sites, including those that have
not changed at all. It is important not to restrict attention to some
sites based on whether or not they have changed; doing that would bias
the distances by making them too large, and that in turn would cause
the distances to misinterpret the meaning of those sites that had
changed.
For all of these distance methods, the program allows us to specify
that "third position" bases have a different rate of substitution than
first and second positions, that introns have a different rate than
exons, and so on. The Categories option which does this allows us to
make up to 9 categories of sites and specify different rates of change
for them.
In addition to the four distance calculations, the program can also
compute a table of similarities between nucleotide sequences. These
values are the fractions of sites identical between the sequences. The
diagonal values are 1.0000. No attempt is made to count similarity of
nonidentical nucleotides, so that no credit is given for having (for
example) different purines at corresponding sites in the two
sequences. This option has been requested by many users, who need it
for descriptive purposes. It is not intended that the table be used
for inferring the tree.
Usage
Here is a sample session with fdnadist
% fdnadist
Nucleic acid sequence distance matrix program
Input (aligned) nucleotide sequence set(s): dnadist.dat
Distance methods
f : F84 distance model
k : Kimura 2-parameter distance
j : Jukes-Cantor distance
l : LogDet distance
s : Similarity table
Choose the method to use [F84 distance model]:
Phylip distance matrix output file [dnadist.fdnadist]:
Distances calculated for species
Alpha ....
Beta ...
Gamma ..
Delta .
Epsilon
Distances written to file "dnadist.fdnadist"
Done.
Nucleic acid sequence distance matrix program
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
-method menu [F84 distance model] Choose the method to
use (Values: f (F84 distance model); k
(Kimura 2-parameter distance); j
(Jukes-Cantor distance); l (LogDet
distance); s (Similarity table))
[-outfile] outfile [*.fdnadist] Phylip distance matrix output
file
Additional (Optional) qualifiers (* if not always prompted):
* -gammatype menu [No distribution parameters used] Gamma
distribution (Values: g (Gamma distributed
rates); i (Gamma+invariant sites); n (No
distribution parameters used))
* -ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array [1.0] Category rates
* -categories properties File of substitution rate categories
-weights properties Weights file
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -ttratio float [2.0] Transition/transversion ratio (Number
0.001 or more)
* -[no]freqsfrom toggle [Y] Use empirical base frequencies from
seqeunce input
* -basefreq array [0.25 0.25 0.25 0.25] Base frequencies for A
C G T/U (use blanks to separate)
-lower boolean [N] Output as a lower triangular distance
matrix
-humanreadable boolean [@($(method)==s?Y:N)] Output as a
human-readable distance matrix
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
-method
list
Choose the method to use
f
(F84 distance model)
k
(Kimura 2-parameter distance)
j
(Jukes-Cantor distance)
l
(LogDet distance)
s
(Similarity table)
F84 distance model
[-outfile] (Parameter 2)
outfile
Phylip distance matrix output file
Output file
<*>.fdnadist
Additional (Optional) qualifiers
-gammatype
list
Gamma distribution
g
(Gamma distributed rates)
i
(Gamma+invariant sites)
n
(No distribution parameters used)
No distribution parameters used
-ncategories
integer
Number of substitution rate categories
Integer from 1 to 9
1
-rate
array
Category rates
List of floating point numbers
1.0
-categories
properties
File of substitution rate categories
Property value(s)
-weights
properties
Weights file
Property value(s)
-gammacoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-invarfrac
float
Fraction of invariant sites
Number from 0.000 to 1.000
0.0
-ttratio
float
Transition/transversion ratio
Number 0.001 or more
2.0
-[no]freqsfrom
toggle
Use empirical base frequencies from seqeunce input
Toggle value Yes/No
Yes
-basefreq
array
Base frequencies for A C G T/U (use blanks to separate)
List of floating point numbers
0.25 0.25 0.25 0.25
-lower
boolean
Output as a lower triangular distance matrix
Boolean value Yes/No
No
-humanreadable
boolean
Output as a human-readable distance matrix
Boolean value Yes/No
@($(method)==s?Y:N)
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fdnadist output contains on its first line the number of
species. The distance matrix is then printed in standard form, with
each species starting on a new line with the species name, followed by
the distances to the species in order. These continue onto a new line
after every nine distances. If the L option is used, the matrix or
distances is in lower triangular form, so that only the distances to
the other species that precede each species are printed. Otherwise the
distance matrix is square with zero distances on the diagonal. In
general the format of the distance matrix is such that it can serve as
input to any of the distance matrix programs.
If the option to print out the data is selected, the output file will
precede the data by more complete information on the input and the
menu selections. The output file begins by giving the number of
species and the number of characters, and the identity of the distance
measure that is being used.
If the C (Categories) option is used a table of the relative rates of
expected substitution at each category of sites is printed, and a
listing of the categories each site is in.
There will then follow the equilibrium frequencies of the four
bases. If the Jukes-Cantor or Kimura distances are used, these will
necessarily be 0.25 : 0.25 : 0.25 : 0.25. The output then shows the
transition/transversion ratio that was specified or used by
default. In the case of the Jukes-Cantor distance this will always be
0.5. The transition-transversion parameter (as opposed to the ratio)
is also printed out: this is used within the program and can be
ignored. There then follow the data sequences, with the base sequences
printed in groups of ten bases along the lines of the Genbank and EMBL
formats.
The distances printed out are scaled in terms of expected numbers of
substitutions, counting both transitions and transversions but not
replacements of a base by itself, and scaled so that the average rate
of change, averaged over all sites analyzed, is set to 1.0 if there
are multiple categories of sites. This means that whether or not there
are multiple categories of sites, the expected fraction of change for
very small branches is equal to the branch length. Of course, when a
branch is twice as long this does not mean that there will be twice as
much net change expected along it, since some of the changes may occur
in the same site and overlie or even reverse each other. The branch
lengths estimates here are in terms of the expected underlying numbers
of changes. That means that a branch of length 0.26 is 26 times as
long as one which would show a 1% difference between the nucleotide
sequences at the beginning and end of the branch. But we would not
expect the sequences at the beginning and end of the branch to be 26%
different, as there would be some overlaying of changes.
One problem that can arise is that two or more of the species can be
so dissimilar that the distance between them would have to be
infinite, as the likelihood rises indefinitely as the estimated
divergence time increases. For example, with the Jukes-Cantor model,
if the two sequences differ in 75% or more of their positions then the
estimate of dovergence time would be infinite. Since there is no way
to represent an infinite distance in the output file, the program
regards this as an error, issues an error message indicating which
pair of species are causing the problem, and stops. It might be that,
had it continued running, it would have also run into the same problem
with other pairs of species. If the Kimura distance is being used
there may be no error message; the program may simply give a large
distance value (it is iterating towards infinity and the value is just
where the iteration stopped). Likewise some maximum likelihood
estimates may also become large for the same reason (the sequences
showing more divergence than is expected even with infinite branch
length). I hope in the future to add more warning messages that would
alert the user the this.
If the similarity table is selected, the table that is produced is not
in a format that can be used as input to the distance matrix
programs. it has a heading, and the species names are also put at the
tops of the columns of the table (or rather, the first 8 characters of
each species name is there, the other two characters omitted to save
space). There is not an option to put the table into a format that can
be read by the distance matrix programs, nor is there one to make it
into a table of fractions of difference by subtracting the similarity
values from 1. This is done deliberately to make it more difficult for
the use to use these values to construct trees. The similarity values
are not corrected for multiple changes, and their use to construct
trees (even after converting them to fractions of difference) would be
wrong, as it would lead to severe conflict between the distant pairs
of sequences and the close pairs of sequences.
Please help by correcting and extending the Wiki pages.
Function
Protein phylogeny by maximum likelihood
Description
Estimates phylogenies from protein amino acid sequences by maximum
likelihood. The PAM, JTT, or PMB models can be employed, and also use
of a Hidden Markov model of rates, with the program inferring which
sites have which rates. This also allows gamma-distribution and
gamma-plus-invariant sites distributions of rates across sites. It
also allows different rates of change at known sites.
Algorithm
This program implements the maximum likelihood method for protein
amino acid sequences. It uses the either the Jones-Taylor-Thornton or
the Dayhoff probability model of change between amino acids. The
assumptions of these present models are:
Each position in the sequence evolves independently.
Different lineages evolve independently.
Each position undergoes substitution at an expected rate which is
chosen from a series of rates (each with a probability of occurrence)
which we specify.
All relevant positions are included in the sequence, not just those
that have changed or those that are "phylogenetically informative".
The probabilities of change between amino acids are given by the model
of Jones, Taylor, and Thornton (1992), the PMB model of Veerassamy,
Smith and Tillier (2004), or the PAM model of Dayhoff (Dayhoff and
Eck, 1968; Dayhoff et. al., 1979).
Note the assumption that we are looking at all positions, including
those that have not changed at all. It is important not to restrict
attention to some positions based on whether or not they have changed;
doing that would bias branch lengths by making them too long, and that
in turn would cause the method to misinterpret the meaning of those
positions that had changed.
This program uses a Hidden Markov Model (HMM) method of inferring
different rates of evolution at different amino acid positions. This
was described in a paper by me and Gary Churchill (1996). It allows us
to specify to the program that there will be a number of different
possible evolutionary rates, what the prior probabilities of
occurrence of each is, and what the average length of a patch of
positions all having the same rate. The rates can also be chosen by
the program to approximate a Gamma distribution of rates, or a Gamma
distribution plus a class of invariant positions. The program computes
the the likelihood by summing it over all possible assignments of
rates to positions, weighting each by its prior probability of
occurrence.
For example, if we have used the C and A options (described below) to
specify that there are three possible rates of evolution, 1.0, 2.4,
and 0.0, that the prior probabilities of a position having these rates
are 0.4, 0.3, and 0.3, and that the average patch length (number of
consecutive positions with the same rate) is 2.0, the program will sum
the likelihood over all possibilities, but giving less weight to those
that (say) assign all positions to rate 2.4, or that fail to have
consecutive positions that have the same rate.
The Hidden Markov Model framework for rate variation among positions
was independently developed by Yang (1993, 1994, 1995). We have
implemented a general scheme for a Hidden Markov Model of rates; we
allow the rates and their prior probabilities to be specified
arbitrarily by the user, or by a discrete approximation to a Gamma
distribution of rates (Yang, 1995), or by a mixture of a Gamma
distribution and a class of invariant positions.
This feature effectively removes the artificial assumption that all
positions have the same rate, and also means that we need not know in
advance the identities of the positions that have a particular rate of
evolution.
Another layer of rate variation also is available. The user can assign
categories of rates to each positions (for example, we might want
amino acid positions in the active site of a protein to change more
slowly than other positions. This is done with the categories input
file and the C option. We then specify (using the menu) the relative
rates of evolution of amino acid positions in the different
categories. For example, we might specify that positions in the active
site evolve at relative rates of 0.2 compared to 1.0 at other
positions. If we are assuming that a particular position maintains a
cysteine bridge to another, we may want to put it in a category of
positions (including perhaps the initial position of the protein
sequence which maintains methionine) which changes at a rate of 0.0.
If both user-assigned rate categories and Hidden Markov Model rates
are allowed, the program assumes that the actual rate at a position is
the product of the user-assigned category rate and the Hidden Markov
Model regional rate. (This may not always make perfect biological
sense: it would be more natural to assume some upper bound to the
rate, as we have discussed in the Felsenstein and Churchill
paper). Nevertheless you may want to use both types of rate variation.
Usage
Here is a sample session with fproml
% fproml
Protein phylogeny by maximum likelihood
Input (aligned) protein sequence set(s): proml.dat
Phylip tree file (optional):
Phylip proml program output file [proml.fproml]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Output written to file "proml.fproml"
Tree also written onto file "proml.treefile"
Done.
Protein phylogeny by maximum likelihood
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-sequence] seqsetall File containing one or more sequence
alignments
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fproml] Phylip proml program output file
Additional (Optional) qualifiers (* if not always prompted):
-ncategories integer [1] Number of substitution rate categories
(Integer from 1 to 9)
* -rate array Rate for each category
* -categories properties File of substitution rate categories
-weights properties Weights file
* -lengths boolean [N] Use branch lengths from user trees
-model menu [Jones-Taylor-Thornton] Probability model
for amino acid change (Values: j
(Jones-Taylor-Thornton); h (Henikoff/Tillier
PMBs); d (Dayhoff PAM))
-gammatype menu [Constant rate] Rate variation among sites
(Values: g (Gamma distributed rates); i
(Gamma+invariant sites); h (User defined HMM
of rates); n (Constant rate))
* -gammacoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ngammacat integer [1] Number of categories (1-9) (Integer from
1 to 9)
* -invarcoefficient float [1] Coefficient of variation of substitution
rate among sites (Number 0.001 or more)
* -ninvarcat integer [1] Number of categories (1-9) including one
for invariant sites (Integer from 1 to 9)
* -invarfrac float [0.0] Fraction of invariant sites (Number
from 0.000 to 1.000)
* -nhmmcategories integer [1] Number of HMM rate categories (Integer
from 1 to 9)
* -hmmrates array [1.0] HMM category rates
* -hmmprobabilities array [1.0] Probability for each HMM category
* -adjsite boolean [N] Rates at adjacent sites correlated
* -lambda float [1.0] Mean block length of sites having the
same rate (Number 1.000 or more)
* -njumble integer [0] Number of times to randomise, choose 0
if you don't want to randomise (Integer 0 or
more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
* -global boolean [N] Global rearrangements
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]rough boolean [Y] Speedier but rougher analysis
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fproml] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-hypstate boolean [N] Reconstruct hypothetical sequence
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-sequence" associated qualifiers
-sbegin1 integer Start of each sequence to be used
-send1 integer End of each sequence to be used
-sreverse1 boolean Reverse (if DNA)
-sask1 boolean Ask for begin/end/reverse
-snucleotide1 boolean Sequence is nucleotide
-sprotein1 boolean Sequence is protein
-slower1 boolean Make lower case
-supper1 boolean Make upper case
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-sdbname1 string Database name
-sid1 string Entryname
-ufo1 string UFO features
-fformat1 string Features format
-fopenfile1 string Features file name
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-sequence] (Parameter 1)
seqsetall
File containing one or more sequence alignments
Readable sets of sequences
Required
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip proml program output file
Output file
<*>.fproml
Additional (Optional) qualifiers
-ncategories
integer
Number of substitution rate categories
Integer from 1 to 9
1
-rate
array
Rate for each category
List of floating point numbers
-categories
properties
File of substitution rate categories
Property value(s)
-weights
properties
Weights file
Property value(s)
-lengths
boolean
Use branch lengths from user trees
Boolean value Yes/No
No
-model
list
Probability model for amino acid change
j
(Jones-Taylor-Thornton)
h
(Henikoff/Tillier PMBs)
d
(Dayhoff PAM)
Jones-Taylor-Thornton
-gammatype
list
Rate variation among sites
g
(Gamma distributed rates)
i
(Gamma+invariant sites)
h
(User defined HMM of rates)
n
(Constant rate)
Constant rate
-gammacoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ngammacat
integer
Number of categories (1-9)
Integer from 1 to 9
1
-invarcoefficient
float
Coefficient of variation of substitution rate among sites
Number 0.001 or more
1
-ninvarcat
integer
Number of categories (1-9) including one for invariant sites
Integer from 1 to 9
1
-invarfrac
float
Fraction of invariant sites
Number from 0.000 to 1.000
0.0
-nhmmcategories
integer
Number of HMM rate categories
Integer from 1 to 9
1
-hmmrates
array
HMM category rates
List of floating point numbers
1.0
-hmmprobabilities
array
Probability for each HMM category
List of floating point numbers
1.0
-adjsite
boolean
Rates at adjacent sites correlated
Boolean value Yes/No
No
-lambda
float
Mean block length of sites having the same rate
Number 1.000 or more
1.0
-njumble
integer
Number of times to randomise, choose 0 if you don't want to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-global
boolean
Global rearrangements
Boolean value Yes/No
No
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-[no]rough
boolean
Speedier but rougher analysis
Boolean value Yes/No
Yes
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fproml
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-hypstate
boolean
Reconstruct hypothetical sequence
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-sequence" associated seqsetall qualifiers
-sbegin1 -sbegin_sequence
integer
Start of each sequence to be used
Any integer value
0
-send1 -send_sequence
integer
End of each sequence to be used
Any integer value
0
-sreverse1 -sreverse_sequence
boolean
Reverse (if DNA)
Boolean value Yes/No
N
-sask1 -sask_sequence
boolean
Ask for begin/end/reverse
Boolean value Yes/No
N
-snucleotide1 -snucleotide_sequence
boolean
Sequence is nucleotide
Boolean value Yes/No
N
-sprotein1 -sprotein_sequence
boolean
Sequence is protein
Boolean value Yes/No
N
-slower1 -slower_sequence
boolean
Make lower case
Boolean value Yes/No
N
-supper1 -supper_sequence
boolean
Make upper case
Boolean value Yes/No
N
-scircular1 -scircular_sequence
boolean
Sequence is circular
Boolean value Yes/No
N
-squick1 -squick_sequence
boolean
Read id and sequence only
Boolean value Yes/No
N
-sformat1 -sformat_sequence
string
Input sequence format
Any string
-iquery1 -iquery_sequence
string
Input query fields or ID list
Any string
-ioffset1 -ioffset_sequence
integer
Input start position offset
Any integer value
0
-sdbname1 -sdbname_sequence
string
Database name
Any string
-sid1 -sid_sequence
string
Entryname
Any string
-ufo1 -ufo_sequence
string
UFO features
Any string
-fformat1 -fformat_sequence
string
Features format
Any string
-fopenfile1 -fopenfile_sequence
string
Features file name
Any string
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fproml output starts by giving the number of species and the
number of amino acid positions.
If the R (HMM rates) option is used a table of the relative rates of
expected substitution at each category of positions is printed, as
well as the probabilities of each of those rates.
There then follow the data sequences, if the user has selected the
menu option to print them, with the sequences printed in groups of ten
amino acids. The trees found are printed as an unrooted tree topology
(possibly rooted by outgroup if so requested). The internal nodes are
numbered arbitrarily for the sake of identification. The number of
trees evaluated so far and the log likelihood of the tree are also
given. Note that the trees printed out have a trifurcation at the
base. The branch lengths in the diagram are roughly proportional to
the estimated branch lengths, except that very short branches are
printed out at least three characters in length so that the
connections can be seen. The unit of branch length is the expected
fraction of amino acids changed (so that 1.0 is 100 PAMs).
A table is printed showing the length of each tree segment (in units
of expected amino acid substitutions per position), as well as (very)
rough confidence limits on their lengths. If a confidence limit is
negative, this indicates that rearrangement of the tree in that region
is not excluded, while if both limits are positive, rearrangement is
still not necessarily excluded because the variance calculation on
which the confidence limits are based results in an underestimate,
which makes the confidence limits too narrow.
In addition to the confidence limits, the program performs a crude
Likelihood Ratio Test (LRT) for each branch of the tree. The program
computes the ratio of likelihoods with and without this branch length
forced to zero length. This done by comparing the likelihoods changing
only that branch length. A truly correct LRT would force that branch
length to zero and also allow the other branch lengths to adjust to
that. The result would be a likelihood ratio closer to 1. Therefore
the present LRT will err on the side of being too significant. YOU ARE
WARNED AGAINST TAKING IT TOO SERIOUSLY. If you want to get a better
likelihood curve for a branch length you can do multiple runs with
different prespecified lengths for that branch, as discussed above in
the discussion of the L option.
One should also realize that if you are looking not at a
previously-chosen branch but at all branches, that you are seeing the
results of multiple tests. With 20 tests, one is expected to reach
significance at the P = .05 level purely by chance. You should
therefore use a much more conservative significance level, such as .05
divided by the number of tests. The significance of these tests is
shown by printing asterisks next to the confidence interval on each
branch length. It is important to keep in mind that both the
confidence limits and the tests are very rough and approximate, and
probably indicate more significance than they should. Nevertheless,
maximum likelihood is one of the few methods that can give you any
indication of its own error; most other methods simply fail to warn
the user that there is any error! (In fact, whole philosophical
schools of taxonomists exist whose main point seems to be that there
isn't any error, that the "most parsimonious" tree is the best tree by
definition and that's that).
The log likelihood printed out with the final tree can be used to
perform various likelihood ratio tests. One can, for example, compare
runs with different values of the relative rate of change in the
active site and in the rest of the protein to determine which value is
the maximum likelihood estimate, and what is the allowable range of
values (using a likelihood ratio test, which you will find described
in mathematical statistics books). One could also estimate the base
frequencies in the same way. Both of these, particularly the latter,
require multiple runs of the program to evaluate different possible
values, and this might get expensive.
If the U (User Tree) option is used and more than one tree is
supplied, and the program is not told to assume autocorrelation
between the rates at different amino acid positions, the program also
performs a statistical test of each of these trees against the one
with highest likelihood. If there are two user trees, the test done is
one which is due to Kishino and Hasegawa (1989), a version of a test
originally introduced by Templeton (1983). In this implementation it
uses the mean and variance of log-likelihood differences between
trees, taken across amino acid positions. If the two trees' means are
more than 1.96 standard deviations different then the trees are
declared significantly different. This use of the empirical variance
of log-likelihood differences is more robust and nonparametric than
the classical likelihood ratio test, and may to some extent compensate
for the any lack of realism in the model underlying this program.
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sum of log likelihoods
across amino acid positions are computed for all pairs of trees. To
test whether the difference between each tree and the best one is
larger than could have been expected if they all had the same expected
log-likelihood, log-likelihoods for all trees are sampled with these
covariances and equal means (Shimodaira and Hasegawa's "least
favorable hypothesis"), and a P value is computed from the fraction of
times the difference between the tree's value and the highest
log-likelihood exceeds that actually observed. Note that this sampling
needs random numbers, and so the program will prompt the user for a
random number seed if one has not already been supplied. With the
two-tree KHT test no random numbers are used.
In either the KHT or the SH test the program prints out a table of the
log-likelihoods of each tree, the differences of each from the highest
one, the variance of that quantity as determined by the log-likelihood
differences at individual sites, and a conclusion as to whether that
tree is or is not significantly worse than the best one. However the
test is not available if we assume that there is autocorrelation of
rates at neighboring positions (option A) and is not done in those
cases.
The branch lengths printed out are scaled in terms of 100 times the
expected numbers of amino acid substitutions, scaled so that the
average rate of change, averaged over all the positions analyzed, is
set to 100.0, if there are multiple categories of positions. This
means that whether or not there are multiple categories of positions,
the expected percentage of change for very small branches is equal to
the branch length. Of course, when a branch is twice as long this does
not mean that there will be twice as much net change expected along
it, since some of the changes occur in the same position and overlie
or even reverse each other. underlying numbers of changes. That means
that a branch of length 26 is 26 times as long as one which would show
a 1% difference between the amino acid sequences at the beginning and
end of the branch, but we would not expect the sequences at the
beginning and end of the branch to be 26% different, as there would be
some overlaying of changes.
Confidence limits on the branch lengths are also given. Of course a
negative value of the branch length is meaningless, and a confidence
limit overlapping zero simply means that the branch length is not
necessarily significantly different from zero. Because of limitations
of the numerical algorithm, branch length estimates of zero will often
print out as small numbers such as 0.00001. If you see a branch length
that small, it is really estimated to be of zero length.
Another possible source of confusion is the existence of negative
values for the log likelihood. This is not really a problem; the log
likelihood is not a probability but the logarithm of a
probability. When it is negative it simply means that the
corresponding probability is less than one (since we are seeing its
logarithm). The log likelihood is maximized by being made more
positive: -30.23 is worse than -29.14.
At the end of the output, if the R option is in effect with multiple
HMM rates, the program will print a list of what amino acid position
categories contributed the most to the final likelihood. This
combination of HMM rate categories need not have contributed a
majority of the likelihood, just a plurality. Still, it will be
helpful as a view of where the program infers that the higher and
lower rates are. Note that the use in this calculations of the prior
probabilities of different rates, and the average patch length, gives
this inference a "smoothed" appearance: some other combination of
rates might make a greater contribution to the likelihood, but be
discounted because it conflicts with this prior information. See the
example output below to see what this printout of rate categories
looks like. A second list will also be printed out, showing for each
position which rate accounted for the highest fraction of the
likelihood. If the fraction of the likelihood accounted for is less
than 95%, a dot is printed instead.
Option 3 in the menu controls whether the tree is printed out into the
output file. This is on by default, and usually you will want to leave
it this way. However for runs with multiple data sets such as
bootstrapping runs, you will primarily be interested in the trees
which are written onto the output tree file, rather than the trees
printed on the output file. To keep the output file from becoming too
large, it may be wisest to use option 3 to prevent trees being printed
onto the output file.
Option 4 in the menu controls whether the tree estimated by the
program is written onto a tree file. The default name of this output
tree file is "outtree". If the U option is in effect, all the
user-defined trees are written to the output tree file.
Option 5 in the menu controls whether ancestral states are estimated
at each node in the tree. If it is in effect, a table of ancestral
sequences is printed out (including the sequences in the tip species
which are the input sequences). The symbol printed out is for the
amino acid which accounts for the largest fraction of the likelihood
at that position. In that table, if a position has an amino acid which
accounts for more than 95% of the likelihood, its symbol printed in
capital letters (W rather than w). One limitation of the current
version of the program is that when there are multiple HMM rates
(option R) the reconstructed amino acids are based on only the single
assignment of rates to positions which accounts for the largest amount
of the likelihood. Thus the assessment of 95% of the likelihood, in
tabulating the ancestral states, refers to 95% of the likelihood that
is accounted for by that particular combination of rates.
Please help by correcting and extending the Wiki pages.
Function
Largest clique program
Description
Finds the largest clique of mutually compatible characters, and the
phylogeny which they recommend, for discrete character data with two
states. The largest clique (or all cliques within a given size range
of the largest one) are found by a very fast branch and bound search
method. The method does not allow for missing data. For such cases the
T (Threshold) option of PARS or MIX may be a useful
alternative. Compatibility methods are particular useful when some
characters are of poor quality and the rest of good quality, but when
it is not known in advance which ones are which.
Algorithm
This program uses the compatibility method for unrooted two-state
characters to obtain the largest cliques of characters and the trees
which they suggest. This approach originated in the work of Le Quesne
(1969), though the algorithms were not precisely specified until the
later work of Estabrook, Johnson, and McMorris (1976a, 1976b). These
authors proved the theorem that a group of two-state characters which
were pairwise compatible would be jointly compatible. This program
uses an algorithm inspired by the Kent Fiala - George Estabrook
program CLINCH, though closer in detail to the algorithm of Bron and
Kerbosch (1973). I am indebted to Kent Fiala for pointing out that
paper to me, and to David Penny for decribing to me his
branch-and-bound approach to finding largest cliques, from which I
have also borrowed. I am particularly grateful to Kent Fiala for
catching a bug in versions 2.0 and 2.1 which resulted in those
versions failing to find all of the cliques which they should. The
program computes a compatibility matrix for the characters, then uses
a recursive procedure to examine all possible cliques of characters.
After one pass through all possible cliques, the program knows the
size of the largest clique, and during a second pass it prints out the
cliques of the right size. It also, along with each clique, prints out
the tree suggested by that clique.
ASSUMPTIONS
Basically the following assumptions are made:
Each character evolves independently.
Different lineages evolve independently.
The ancestral state is not known.
Each character has a small chance of being one which evolves so
rapidly, or is so thoroughly misinterpreted, that it provides no
information on the tree.
The probability of a single change in a character (other than in
the high rate characters) is low but not as low as the probability of
being one of these "bad" characters.
The probability of two changes in a low-rate character is much
less than the probability that it is a high-rate character.
The true tree has segments which are not so unequal in length that
two changes in a long are as easy to envisage as one change in a short
segment.
The assumptions of compatibility methods have been treated in several
of my papers (1978b, 1979, 1981b, 1988b), especially the 1981
paper. For an opposing view arguing that the parsimony methods make no
substantive assumptions such as these, see the papers by Farris (1983)
and Sober (1983a, 1983b), but also read the exchange between
Felsenstein and Sober (1986).
A constant available for alteration at the beginning of the program is
the form width, "FormWide", which you may want to change to make it as
large as possible consistent with the page width available on your
output device, so as to avoid the output of cliques and of trees
getting wrapped around unnecessarily.
Usage
Here is a sample session with fclique
% fclique
Largest clique program
Phylip discrete states file: clique.dat
Phylip clique program output file [clique.fclique]:
Output written to file "clique.fclique"
Tree written on file "clique.treefile"
Done.
Largest clique program
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates Phylip discrete states file
[-outfile] outfile [*.fclique] Phylip clique program output
file
Additional (Optional) qualifiers (* if not always prompted):
-ancfile properties Phylip ancestral states file (optional)
-factorfile properties Phylip multistate factors file (optional)
-weights properties Phylip weights file (optional)
-cliqmin integer [0] Minimum clique size (Integer 0 or more)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fclique] Phylip tree output file
(optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-printcomp boolean [N] Print out compatibility matrix
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
Phylip discrete states file
Discrete states file
[-outfile] (Parameter 2)
outfile
Phylip clique program output file
Output file
<*>.fclique
Additional (Optional) qualifiers
-ancfile
properties
Phylip ancestral states file (optional)
Property value(s)
-factorfile
properties
Phylip multistate factors file (optional)
Property value(s)
-weights
properties
Phylip weights file (optional)
Property value(s)
-cliqmin
integer
Minimum clique size
Integer 0 or more
0
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fclique
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-printcomp
boolean
Print out compatibility matrix
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
Input to the algorithm is standard, but the "?", "P", and "B" states
are not allowed. This is a serious limitation of this program. If you
want to find large cliques in data that have "?" states, I recommend
that you use fmix instead with the -Threshold option and the value
of the threshold set to 2.0. The theory underlying this is given in my
paper on character weighting (Felsenstein, 1981b).
fclique reads discrete character data with 2 states.
Please help by correcting and extending the Wiki pages.
Function
Interactive tree rearrangement
Description
Reads in a tree (with branch lengths if necessary) and allows you to
reroot the tree, to flip branches, to change species names and branch
lengths, and then write the result out. Can be used to convert between
rooted and unrooted trees, and to write the tree into a preliminary
version of a new XML tree file format which is under development and
which is described in the RETREE documentation web page.
Algorithm
RETREE is a tree editor. It reads in a tree, or allows the user to
construct one, and displays this tree on the screen. The user then can
specify how the tree is to be rearranged, rerooted or written out to a
file.
The input trees are in one file (with default file name intree), the
output trees are written into another (outtree). The user can reroot,
flip branches, change names of species, change or remove branch
lengths, and move around to look at various parts of the tree if it is
too large to fit on the screen. The trees can be multifurcating at any
level, although the user is warned that many PHYLIP programs still
cannot handle multifurcations above the root, or even at the root.
A major use for this program will be to change rootedness of trees so
that a rooted tree derived from one program can be fed in as an
unrooted tree to another (you are asked about this when you give the
command to write out the tree onto the tree output file). It will also
be useful for specifying the length of a branch in a tree where you
want a program like DNAML, DNAMLK, FITCH, or CONTML to hold that
branch length constant (see the L suboption of the User Tree option in
those programs. It will also be useful for changing the order of
species for purely cosmetic reasons for DRAWGRAM and DRAWTREE,
including using the Midpoint method of rooting the tree. It can also
be used to write out a tree file in the Nexus format used by Paup and
MacClade or in our XML tree file format.
This program uses graphic characters that show the tree to best
advantage on some computer systems. Its graphic characters will work
best on MSDOS systems or MSDOS windows in Windows, and to any system
whose screen or terminals emulate ANSI standard terminals such as old
Digitial VT100 terminals, Telnet programs, or VT100-compatible windows
in the X windowing system. For any other screen types, (such as
Macintosh windows) there is a generic option which does not make use
of screen graphics characters. The program will work well in those
cases, but the tree it displays will look a bit uglier.
Usage
Here is a sample session with fretree
% fretree
Interactive tree rearrangement
Number of species [0]: 10
Phylip tree file: retree.dat
Phylip tree output file [retree.treefile]:
NEXT? (R . U W O T F D B N H J K L C + ? X Q) (? for Help): Q
Do you want to write out the tree to a file? (Y or N): Y
Enter R if the tree is to be rooted, OR enter U if the tree is to be unrooted: U
Tree written to file "retree.treefile"
Reading tree file ...
,>>1:Human
,>22
,>21 `>>2:Chimp
! !
,>20 `>>>>>3:Gorilla
! !
,>>>>>>>>>>19 `>>>>>>>>4:Orang
! !
,>18 `>>>>>>>>>>>5:Gibbon
! !
! ! ,>>>>>>>>6:Barbary Ma
! `>>>>>>>>>>>>>23
! ! ,>>>>>7:Crab-e. Ma
,>>>>>>>17 `>24
! ! ! ,>>8:Rhesus Mac
! ! `>25
! ! `>>9:Jpn Macaq
,>16 !
! ! `>>>>>>>>>>>>>>>>>>>>>>>>>10:Squir. Mon
! !
! ! ,>11:Tarsier
** 7 lines below screen **
Interactive tree rearrangement
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-spp] integer [0] Number of species (Any integer value)
[-intreefile] tree Phylip tree file
[-outtreefile] outfile [*.fretree] Phylip tree output file
Additional (Optional) qualifiers:
-initialtree menu [Arbitary] Initial tree (Values: a
(Arbitary); u (User); s (Specify))
-format menu [p] Format to write trees (Values: p
(PHYLIP); n (NEXUS); x (XML))
-screenwidth integer [80] Width of terminal screen in characters
(Any integer value)
-vscreenwidth integer [80] Width of plotting area in characters
(Any integer value)
-screenlines integer [24] Number of lines on screen (Any integer
value)
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outtreefile" associated qualifiers
-odirectory3 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-spp] (Parameter 1)
integer
Number of species
Any integer value
0
[-intreefile] (Parameter 2)
tree
Phylip tree file
Phylogenetic tree
[-outtreefile] (Parameter 3)
outfile
Phylip tree output file
Output file
<*>.fretree
Additional (Optional) qualifiers
-initialtree
list
Initial tree
a
(Arbitary)
u
(User)
s
(Specify)
Arbitary
-format
list
Format to write trees
p
(PHYLIP)
n
(NEXUS)
x
(XML)
p
-screenwidth
integer
Width of terminal screen in characters
Any integer value
80
-vscreenwidth
integer
Width of plotting area in characters
Any integer value
80
-screenlines
integer
Number of lines on screen
Any integer value
24
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outtreefile" associated outfile qualifiers
-odirectory3 -odirectory_outtreefile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
The N (output file format) option allows the user to
specify that the tree files that are written by the program will be in
one of three formats:
The PHYLIP default file format (the Newick standard) used by the
programs in this package.
The Nexus format defined by David Swofford and by Wayne Maddison
and David Maddison for their programs PAUP and MacClade. A tree file
written in Nexus format should be directly readable by those programs
(They also have options to read a regular PHYLIP tree file as well).
An XML tree file format which we have defined.
The XML tree file format is fairly simple. The tree file, which may
have multiple trees, is enclosed in a pair of <PHYLOGENIES>
... </PHYLOGENIES> tags. Each tree is included in tags <PHYLOGENY>
... </PHYLOGENY>. Each branch of the tree is enclosed in a pair of
tags <CLADE> ... </CLADE>, which enclose the branch and all its
descendants. If the branch has a length, this is given by the LENGTH
attribute of the CLADE tag, so that the pair of tags looks like this:
<CLADE LENGTH="0.09362"> ... </CLADE>
A tip of the tree is at the end of a branch (and hence that branch is enclosed in a pair of <CLADE> ... </CLADE> tags). Its name is enclosed by <NAME> ... </NAME> tags. Here is an XML tree:
The indentation is for readability but is not part of the XML tree
standard, which ignores that kind of white space.
What programs can read an XML tree? None right now, not even PHYLIP
programs! But soon our lab's LAMARC package will have programs that
can read an XML tree. XML is rapidly becoming the standard for
representing and interchanging complex data -- it is time to have an
XML tree standard. Certain extensions are obvious (to represent the
bootstrap proportion for a branch, use BOOTP=0.83 in the CLADE tag,
for example).
There are other proposals for an XML tree standard. They have many
similarities to this one, but are not identical to it. At the moment
there is no mechanism in place for deciding between them other than
seeing which get widely used. Here are links to other proposals:
Taxonomic Markup Language
http://www.albany.edu/~gilmr/pubxml/.
and preprint at
xml.coverpages.org/gilmour-TML.pdf
published in the paper by
Ron Gilmour (2000).
Andrew Rambaut's
BEAST XML phylogeny format
See page 9 of PDF of BEAST manual at
http://evolve.zoo.ox.ac.uk/beast/
An XML format for phylogenies is sketchly described there.
treeml
http://www.nomencurator.org/InfoVis2003/download/treeml.dtd
(see also example: )
http://www.cs.umd.edu/hcil/iv03contest/datasets/treeml-sample.xml
Jean-Daniel Fekete's DTD
for a tree XML file
The W (screen and window Width) option specifies the width in
characters of the area which the trees will be plotted to fit
into. This is by default 80 characters so that they will fit on a
normal width terminal. The actual width of the display on the terminal
(normally 80 characters) will be regarded as a window displaying part
of the tree. Thus you could set the "plotting area" to 132 characters,
and inform the program that the screen width is 80 characters. Then
the program will display only part of the tree at any one time.
Please help by correcting and extending the Wiki pages.
Function
Compute genetic distances from gene frequencies
Description
Computes one of three different genetic distance formulas from gene
frequency data. The formulas are Nei's genetic distance, the
Cavalli-Sforza chord measure, and the genetic distance of Reynolds
et. al. The former is appropriate for data in which new mutations
occur in an infinite isoalleles neutral mutation model, the latter two
for a model without mutation and with pure genetic drift. The
distances are written to a file in a format appropriate for input to
the distance matrix programs.
Algorithm
This program computes any one of three measures of genetic distance
from a set of gene frequencies in different populations (or
species). The three are Nei's genetic distance (Nei, 1972),
Cavalli-Sforza's chord measure (Cavalli- Sforza and Edwards, 1967) and
Reynolds, Weir, and Cockerham's (1983) genetic distance. These are
written to an output file in a format that can be read by the distance
matrix phylogeny programs FITCH and KITSCH.
The three measures have somewhat different assumptions. All assume
that all differences between populations arise from genetic
drift. Nei's distance is formulated for an infinite isoalleles model
of mutation, in which there is a rate of neutral mutation and each
mutant is to a completely new alleles. It is assumed that all loci
have the same rate of neutral mutation, and that the genetic
variability initially in the population is at equilibrium between
mutation and genetic drift, with the effective population size of each
population remaining constant.
Nei's distance is:
\ \
/_ /_ p1mi p2mi
m i
D = - ln ( ------------------------------------- ).
\ \ \ \
[ /_ /_ p1mi2]1/2 [ /_ /_ p2mi2]1/2
m i m i
where m is summed over loci, i over alleles at the m-th locus, and where
p1mi
is the frequency of the i-th allele at the m-th locus in population
1. Subject to the above assumptions, Nei's genetic distance is
expected, for a sample of sufficiently many equivalent loci, to rise
linearly with time.
The other two genetic distances assume that there is no mutation, and
that all gene frequency changes are by genetic drift alone. However
they do not assume that population sizes have remained constant and
equal in all populations. They cope with changing population size by
having expectations that rise linearly not with time, but with the sum
over time of 1/N, where N is the effective population size. Thus if
population size doubles, genetic drift will be taking place more
slowly, and the genetic distance will be expected to be rising only
half as fast with respect to time. Both genetic distances are
different estimators of the same quantity under the same model.
Cavalli-Sforza's chord distance is given by
\ \ \
D2 = 4 /_ [ 1 - /_ p1mi1/2 p 2mi1/2] / /_ (am - 1)
m i m
where m indexes the loci, where i is summed over the alleles at the
m-th locus, and where a is the number of alleles at the m-th locus. It
can be shown that this distance always satisfies the triangle
inequality. Note that as given here it is divided by the number of
degrees of freedom, the sum of the numbers of alleles minus one. The
quantity which is expected to rise linearly with amount of genetic
drift (sum of 1/N over time) is D squared, the quantity computed
above, and that is what is written out into the distance matrix.
Reynolds, Weir, and Cockerham's (1983) genetic distance is
\ \
/_ /_ [ p1mi - p2mi]2
m i
D2 = --------------------------------------
\ \
2 /_ [ 1 - /_ p1mi p2mi ]
m i
where the notation is as before and D2 is the quantity that is
expected to rise linearly with cumulated genetic drift.
Having computed one of these genetic distances, one which you feel is
appropriate to the biology of the situation, you can use it as the
input to the programs FITCH, KITSCH or NEIGHBOR. Keep in mind that the
statistical model in those programs implicitly assumes that the
distances in the input table have independent errors. For any measure
of genetic distance this will not be true, as bursts of random genetic
drift, or sampling events in drawing the sample of individuals from
each population, cause fluctuations of gene frequency that affect many
distances simultaneously. While this is not expected to bias the
estimate of the phylogeny, it does mean that the weighing of evidence
from all the different distances in the table will not be done with
maximal efficiency. One issue is which value of the P (Power)
parameter should be used. This depends on how the variance of a
distance rises with its expectation. For Cavalli-Sforza's chord
distance, and for the Reynolds et. al. distance it can be shown that
the variance of the distance will be proportional to the square of its
expectation; this suggests a value of 2 for P, which the default value
for FITCH and KITSCH (there is no P option in NEIGHBOR).
If you think that the pure genetic drift model is appropriate, and are
thus tempted to use the Cavalli-Sforza or Reynolds et. al. distances,
you might consider using the maximum likelihood program CONTML
instead. It will correctly weigh the evidence in that case. Like those
genetic distances, it uses approximations that break down as loci
start to drift all the way to fixation. Although Nei's distance will
not break down in that case, it makes other assumptions about equality
of substitution rates at all loci and constancy of population sizes.
qThe most important thing to remember is that genetic distance is not
an abstract, idealized measure of "differentness". It is an estimate
of a parameter (time or cumulated inverse effective population size)
of the model which is thought to have generated the differences we
see. As an estimate, it has statistical properties that can be
assessed, and we should never have to choose between genetic distances
based on their aesthetic properties, or on the personal prestige of
their originators. Considering them as estimates focuses us on the
questions which genetic distances are intended to answer, for if there
are none there is no reason to compute them. For further perspective
on genetic distances, I recommend my own paper evaluating Reynolds,
Weir, and Cockerham (1983), and the material in Nei's book (Nei,
1987).
Usage
Here is a sample session with fgendist
% fgendist
Compute genetic distances from gene frequencies
Phylip gendist program input file: gendist.dat
Phylip gendist program output file [gendist.fgendist]:
Distances calculated for species
European .
African ..
Chinese ...
American ....
Australian .....
Distances written to file "gendist.fgendist"
Done.
Compute genetic distances from gene frequencies
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] frequencies File containing one or more sets of data
[-outfile] outfile [*.fgendist] Phylip gendist program output
file
Additional (Optional) qualifiers:
-method menu [n] Which method to use (Values: n (Nei
genetic distance); c (Cavalli-Sforza chord
measure); r (Reynolds genetic distance))
-[no]progress boolean [Y] Print indications of progress of run
-lower boolean [N] Lower triangular distance matrix
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
frequencies
File containing one or more sets of data
Frequency value(s)
[-outfile] (Parameter 2)
outfile
Phylip gendist program output file
Output file
<*>.fgendist
Additional (Optional) qualifiers
-method
list
Which method to use
n
(Nei genetic distance)
c
(Cavalli-Sforza chord measure)
r
(Reynolds genetic distance)
n
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-lower
boolean
Lower triangular distance matrix
Boolean value Yes/No
No
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fgendist reads continuous character data
Continuous character data
The programs in this group use gene frequencies and quantitative
character values. One (CONTML) constructs maximum likelihood estimates
of the phylogeny, another (GENDIST) computes genetic distances for use
in the distance matrix programs, and the third (CONTRAST) examines
correlation of traits as they evolve along a given phylogeny.
When the gene frequencies data are used in CONTML or GENDIST, this
involves the following assumptions:
Different lineages evolve independently.
After two lineages split, their characters change independently.
Each gene frequency changes by genetic drift, with or without mutation
(this varies from method to method).
Different loci or characters drift independently.
How these assumptions affect the methods will be seen in my papers on
inference of phylogenies from gene frequency and continuous character
data (Felsenstein, 1973b, 1981c, 1985c).
The input formats are fairly similar to the discrete-character
programs, but with one difference. When CONTML is used in the
gene-frequency mode (its usual, default mode), or when GENDIST is
used, the first line contains the number of species (or populations)
and the number of loci and the options information. There then follows
a line which gives the numbers of alleles at each locus, in
order. This must be the full number of alleles, not the number of
alleles which will be input: i. e. for a two-allele locus the number
should be 2, not 1. There then follow the species (population) data,
each species beginning on a new line. The first 10 characters are
taken as the name, and thereafter the values of the individual
characters are read free-format, preceded and separated by
blanks. They can go to a new line if desired, though of course not in
the middle of a number. Missing data is not allowed - an important
limitation. In the default configuration, for each locus, the numbers
should be the frequencies of all but one allele. The menu option A
(All) signals that the frequencies of all alleles are provided in the
input data -- the program will then automatically ignore the last of
them. So without the A option, for a three-allele locus there should
be two numbers, the frequencies of two of the alleles (and of course
it must always be the same two!). Here is a typical data set without
the A option:
The first line has the number of species (or populations) and the
number of loci. The second line has the number of alleles for each of
the 3 loci. The species lines have names (filled out to 10 characters
with blanks) followed by the gene frequencies of the 2 alleles for the
first locus, the 3 alleles for the second locus, and the 2 alleles for
the third locus. You can start a new line after any of these allele
frequencies, and continue to give the frequencies on that line
(without repeating the species name).
If all alleles of a locus are given, it is important to have them add
up to 1. Roundoff of the frequencies may cause the program to conclude
that the numbers do not sum to 1, and stop with an error message.
While many compilers may be more tolerant, it is probably wise to make
sure that each number, including the first, is preceded by a blank,
and that there are digits both preceding and following any decimal
points.
CONTML and CONTRAST also treat quantitative characters (the
continuous-characters mode in CONTML, which is option C). It is
assumed that each character is evolving according to a Brownian motion
model, at the same rate, and independently. In reality it is almost
always impossible to guarantee this. The issue is discussed at length
in my review article in Annual Review of Ecology and Systematics
(Felsenstein, 1988a), where I point out the difficulty of transforming
the characters so that they are not only genetically independent but
have independent selection acting on them. If you are going to use
CONTML to model evolution of continuous characters, then you should at
least make some attempt to remove genetic correlations between the
characters (usually all one can do is remove phenotypic correlations
by transforming the characters so that there is no within-population
covariance and so that the within-population variances of the
characters are equal -- this is equivalent to using Canonical
Variates). However, this will only guarantee that one has removed
phenotypic covariances between characters. Genetic covariances could
only be removed by knowing the coheritabilities of the characters,
which would require genetic experiments, and selective covariances
(covariances due to covariation of selection pressures) would require
knowledge of the sources and extent of selection pressure in all
variables.
CONTRAST is a program designed to infer, for a given phylogeny that is
provided to the program, the covariation between characters in a data
set. Thus we have a program in this set that allow us to take
information about the covariation and rates of evolution of characters
and make an estimate of the phylogeny (CONTML), and a program that
takes an estimate of the phylogeny and infers the variances and
covariances of the character changes. But we have no program that
infers both the phylogenies and the character covariation from the
same data set.
In the quantitative characters mode, a typical small data set would be:
Note that in the latter case, there is no line giving the numbers of
alleles at each locus. In this latter case no square-root
transformation of the coordinates is done: each is assumed to give
directly the position on the Brownian motion scale.
For further discussion of options and modifiable constants in CONTML,
GENDIST, and CONTRAST see the documentation files for those programs.
fgendist output simply contains on its first line the number of
species (or populations). Each species (or population) starts a new
line, with its name printed out first, and then and there are up to
nine genetic distances printed on each line, in the standard format
used as input by the distance matrix programs. The output, in its
default form, is ready to be used in the distance matrix programs.
Output files for usage example
File: gendist.fgendist
5
European 0.000000 0.078002 0.080749 0.066805 0.103014
African 0.078002 0.000000 0.234698 0.104975 0.227281
Chinese 0.080749 0.234698 0.000000 0.053879 0.063275
American 0.066805 0.104975 0.053879 0.000000 0.134756
Australian 0.103014 0.227281 0.063275 0.134756 0.000000
Please help by correcting and extending the Wiki pages.
Function
Multistate to binary recoding program
Description
Takes discrete multistate data with character state trees and produces
the corresponding data set with two states (0 and 1). Written by
Christopher Meacham. This program was formerly used to accomodate
multistate characters in MIX, but this is less necessary now that PARS
is available.
Algorithm
This program factors a data set that contains multistate characters,
creating a data set consisting entirely of binary (0,1) characters
that, in turn, can be used as input to any of the other discrete
character programs in this package, except for PARS. Besides this
primary function, FACTOR also provides an easy way of deleting
characters from a data set. The input format for FACTOR is very
similar to the input format for the other discrete character programs
except for the addition of character-state tree descriptions.
Note that this program has no way of converting an unordered
multistate character into binary characters. Fortunately, PARS has
joined the package, and it enables unordered multistate characters, in
which any state can change to any other in one step, to be analyzed
with parsimony.
FACTOR is really for a different case, that in which there are
multiple states related on a "character state tree", which specifies
for each state which other states it can change to. That graph of
states is assumed to be a tree, with no loops in it.
Usage
Here is a sample session with ffactor
% ffactor
Multistate to binary recoding program
Phylip factor program input file: factor.dat
Phylip factor program output file [factor.ffactor]:
Data matrix written on file "factor.ffactor"
Done.
Multistate to binary recoding program
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] infile Phylip factor program input file
[-outfile] outfile [*.ffactor] Phylip factor program output
file
Additional (Optional) qualifiers:
-anc boolean [N] Put ancestral states in output file
-factors boolean [N] Put factors information in output file
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers:
-outfactorfile outfile [*.ffactor] Phylip factor data output file
(optional)
-outancfile outfile [*.ffactor] Phylip ancestor data output file
(optional)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outfactorfile" associated qualifiers
-odirectory string Output directory
"-outancfile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
infile
Phylip factor program input file
Input file
Required
[-outfile] (Parameter 2)
outfile
Phylip factor program output file
Output file
<*>.ffactor
Additional (Optional) qualifiers
-anc
boolean
Put ancestral states in output file
Boolean value Yes/No
No
-factors
boolean
Put factors information in output file
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
-outfactorfile
outfile
Phylip factor data output file (optional)
Output file
<*>.ffactor
-outancfile
outfile
Phylip ancestor data output file (optional)
Output file
<*>.ffactor
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
"-outfactorfile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
"-outancfile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
ffactor reads character state tree data.
This program factors a data set that contains multistate characters,
creating a data set consisting entirely of binary (0,1) characters
that, in turn, can be used as input to any of the other discrete
character programs in this package, except for PARS. Besides this
primary function, FACTOR also provides an easy way of deleting
characters from a data set. The input format for FACTOR is very
similar to the input format for the other discrete character programs
except for the addition of character-state tree descriptions.
Note that this program has no way of converting an unordered
multistate character into binary characters. Fortunately, PARS has
joined the package, and it enables unordered multistate characters, in
which any state can change to any other in one step, to be analyzed
with parsimony.
FACTOR is really for a different case, that in which there are
multiple states related on a "character state tree", which specifies
for each state which other states it can change to. That graph of
states is assumed to be a tree, with no loops in it.
First line
The first line of the input file should contain the number of species
and the number of multistate characters. This first line is followed
by the lines describing the character-state trees, one description per
line. The species information constitutes the last part of the
file. Any number of lines may be used for a single species.
The first line is free format with the number of species first,
separated by at least one blank (space) from the number of multistate
characters, which in turn is separated by at least one blank from the
options, if present.
Character-state tree descriptions
The character-state trees are described in free format. The character
number of the multistate character is given first followed by the
description of the tree itself. Each description must be completed on
a single line. Each character that is to be factored must have a
description, and the characters must be described in the order that
they occur in the input, that is, in numerical order.
The tree is described by listing the pairs of character states that
are adjacent to each other in the character-state tree. The two
character states in each adjacent pair are separated by a colon
(":"). If character fifteen has this character state tree for possible
states "A", "B", "C", and "D":
A ---- B ---- C
|
|
|
D
then the character-state tree description would be
15 A:B B:C D:B
Note that either symbol may appear first. The ancestral state is
identified, if desired, by putting it "adjacent" to a period. If we
wanted to root character fifteen at state C:
A <--- B <--- C
|
|
V
D
we could write
15 B:D A:B C:B .:C
Both the order in which the pairs are listed and the order of the
symbols in each pair are arbitrary. However, each pair may only appear
once in the list. Any symbols may be used for a character state in the
input except the character that signals the connection between two
states (in the distribution copy this is set to ":"), ".", and, of
course, a blank. Blanks are ignored completely in the tree description
so that even B:DA:BC:B.:C or B : DA : BC : B. : C would be equivalent
to the above example. However, at least one blank must separate the
character number from the tree description.
Deleting characters from a data set
If no description line appears in the input for a particular
character, then that character will be omitted from the output. If the
character number is given on the line, but no character-state tree is
provided, then the symbol for the character in the input will be
copied directly to the output without change. This is useful for
characters that are already coded "0" and "1". Characters can be
deleted from a data set simply by listing only those that are to
appear in the output.
Terminating the list of tree descriptions
The last character-state tree description should be followed by a line
containing the number "999". This terminates processing of the trees
and indicates the beginning of the species information.
Species information
The format for the species information is basically identical to the
other discrete character programs. The first ten character positions
are allotted to the species name (this value may be changed by
altering the value of the constant nmlngth at the beginning of the
program). The character states follow and may be continued to as many
lines as desired. There is no current method for indicating
polymorphisms. It is possible to either put blanks between characters
or not.
There is a method for indicating uncertainty about states. There is
one character value that stands for "unknown". If this appears in the
input data then "?" is written out in all the corresponding positions
in the output file. The character value that designates "unknown" is
given in the constant unkchar at the beginning of the program, and can
be changed by changing that constant. It is set to "?" in the
distribution copy.
The first line of ffactor output will contain the number of
species and the number of binary characters in the factored data set
followed by the letter "A" if the A option was specified in the
input. If option F was specified, the next line will begin
"FACTORS". If option A was specified, the line describing the ancestor
will follow next. Finally, the factored characters will be written for
each species in the format required for input by the other discrete
programs in the package. The maximum length of the output lines is 80
characters, but this maximum length can be changed prior to
compilation.
In fact, the format of the output file for the A and F options is not
correct for the current release of PHYLIP. We need to change their
output to write a factors file and an ancestors file instead of
putting the Factors and Ancestors information into the data file.
The output should be checked for error messages. Errors will occur in
the character-state tree descriptions if the format is incorrect
(colons in the wrong place, etc.), if more than one root is specified,
if the tree contains loops (and hence is not a tree), and if the tree
is not connected, e.g.
A:B B:C D:E
describes
A ---- B ---- C D ---- E
This "tree" is in two unconnected pieces. An error will also occur if
a symbol appears in the data set that is not in the tree description
for that character. Blanks at the end of lines when the species
information is continued to a new line will cause this kind of error.
Please help by correcting and extending the Wiki pages.
Function
Majority-rule and strict consensus tree
Description
Computes consensus trees by the majority-rule consensus tree method,
which also allows one to easily find the strict consensus tree. Is not
able to compute the Adams consensus tree. Trees are input in a tree
file in standard nested-parenthesis notation, which is produced by
many of the tree estimation programs in the package. This program can
be used as the final step in doing bootstrap analyses for many of the
methods in the package.
Algorithm
fconsense reads a file of computer-readable trees and prints
out (and may also write out onto a file) a consensus tree. At the
moment it carries out a family of consensus tree methods called the Ml
methods (Margush and McMorris, 1981). These include strict consensus
and majority rule consensus. Basically the consensus tree consists of
monophyletic groups that occur as often as possible in the data. If a
group occurs in more than a fraction l of all the input trees it will
definitely appear in the consensus tree.
The tree printed out has at each fork a number indicating how many
times the group which consists of the species to the right of
(descended from) the fork occurred. Thus if we read in 15 trees and
find that a fork has the number 15, that group occurred in all of the
trees. The strict consensus tree consists of all groups that occurred
100% of the time, the rest of the resolution being ignored. The tree
printed out here includes groups down to 50%, and below it until the
tree is fully resolved.
The majority rule consensus tree consists of all groups that occur
more than 50% of the time. Any other percentage level between 50% and
100% can also be used, and that is why the program in effect carries
out a family of methods. You have to decide on the percentage level,
figure out for yourself what number of occurrences that would be
(e.g. 15 in the above case for 100%), and resolutely ignore any group
below that number. Do not use numbers at or below 50%, because some
groups occurring (say) 35% of the time will not be shown on the
tree. The collection of all groups that occur 35% or more of the time
may include two groups that are mutually self contradictory and cannot
appear in the same tree. In this program, as the default method I have
included groups that occur less than 50% of the time, working
downwards in their frequency of occurrence, as long as they continue
to resolve the tree and do not contradict more frequent groups. In
this respect the method is similar to the Nelson consensus method
(Nelson, 1979) as explicated by Page (1989) although it is not
identical to it.
The program can also carry out Strict consensus, Majority Rule
consensus without the extension which adds groups until the tree is
fully resolved, and other members of the Ml family, where the user
supplied the fraction of times the group must appear in the input
trees to be included in the consensus tree. For the moment the program
cannot carry out any other consensus tree method, such as Adams
consensus (Adams, 1972, 1986) or methods based on quadruples of
species (Estabrook, McMorris, and Meacham, 1985).
Usage
Here is a sample session with fconsense
% fconsense
Majority-rule and strict consensus tree
Phylip tree file: consense.dat
Phylip consense program output file [consense.fconsense]:
Consensus tree written to file "consense.treefile"
Output written to file "consense.fconsense"
Done.
Majority-rule and strict consensus tree
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-intreefile] tree Phylip tree file
[-outfile] outfile [*.fconsense] Phylip consense program output
file
Additional (Optional) qualifiers (* if not always prompted):
-method menu [mre] Consensus method (Values: s (strict
consensus tree); mr (Majority Rule); mre
(Majority Rule (extended)); ml (Minimum
fraction (0.5 to 1.0)))
* -mlfrac float [0.5] Fraction (l) of times a branch must
appear (Number from 0.500 to 1.000)
-root toggle [N] Trees to be treated as Rooted
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fconsense] Phylip tree output file
(optional)
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-[no]prntsets boolean [Y] Print out the sets of species
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-intreefile] (Parameter 1)
tree
Phylip tree file
Phylogenetic tree
[-outfile] (Parameter 2)
outfile
Phylip consense program output file
Output file
<*>.fconsense
Additional (Optional) qualifiers
-method
list
Consensus method
s
(strict consensus tree)
mr
(Majority Rule)
mre
(Majority Rule (extended))
ml
(Minimum fraction (0.5 to 1.0))
mre
-mlfrac
float
Fraction (l) of times a branch must appear
Number from 0.500 to 1.000
0.5
-root
toggle
Trees to be treated as Rooted
Toggle value Yes/No
No
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fconsense
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-[no]prntsets
boolean
Print out the sets of species
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
fconsense output is a list of the species (in the order in
which they appear in the first tree, which is the numerical order used
in the program), a list of the subsets that appear in the consensus
tree, a list of those that appeared in one or another of the
individual trees but did not occur frequently enough to get into the
consensus tree, followed by a diagram showing the consensus tree. The
lists of subsets consists of a row of symbols, each either "." or
"*". The species that are in the set are marked by "*". Every ten
species there is a blank, to help you keep track of the alignment of
columns. The order of symbols corresponds to the order of species in
the species list. Thus a set that consisted of the second, seventh,
and eighth out of 13 species would be represented by:
.*....**.. ...
Note that if the trees are unrooted the final tree will have one
group, consisting of every species except the Outgroup (which by
default is the first species encountered on the first tree), which
always appears. It will not be listed in either of the lists of sets,
but it will be shown in the final tree as occurring all of the
time. This is hardly surprising: in telling the program that this
species is the outgroup we have specified that the set consisting of
all of the others is always a monophyletic set. So this is not to be
taken as interesting information, despite its dramatic appearance.
Output files for usage example
File: consense.fconsense
Consensus tree program, version 3.69.650
Species in order:
1. A
2. B
3. H
4. D
5. J
6. G
7. E
8. F
9. I
10. C
Sets included in the consensus tree
Set (species in order) How many times out of 9.00
.......**. 9.00
..******** 9.00
..****.*** 6.00
..***..... 6.00
..***....* 6.00
..*.*..... 4.00
..***..*** 2.00
Sets NOT included in consensus tree:
Set (species in order) How many times out of 9.00
.....**... 3.00
.....***** 3.00
..**...... 3.00
.....****. 3.00
..****...* 2.00
.....*.**. 2.00
..*.****** 2.00
....****** 2.00
...******* 1.00
Extended majority rule consensus tree
CONSENSUS TREE:
the numbers on the branches indicate the number
of times the partition of the species into the two sets
which are separated by that branch occurred
among the trees, out of 9.00 trees
+-----------------------C
|
+--6.00-| +-------H
| | +--4.00-|
| +--6.00-| +-------J
+--2.00-| |
| | +---------------D
| |
+--6.00-| | +-------F
| | +------------------9.00-|
| | +-------I
+--9.00-| |
| | +---------------------------------------G
+-------| |
| | +-----------------------------------------------E
| |
| +-------------------------------------------------------B
|
+---------------------------------------------------------------A
remember: this is an unrooted tree!
Note that the lengths on the tree on the output tree file are not
branch lengths but the number of times that each group appeared in the
input trees. This number is the sum of the weights of the trees in
which it appeared, so that if there are 11 trees, ten of them having
weight 0.1 and one weight 1.0, a group that appeared in the last tree
and in 6 others would be shown as appearing 1.6 times and its branch
length will be 1.6. This means that if you take the consensus tree
from the output tree file and try to draw it, the branch lengths will
be strange. I am often asked how to put the correct branch lengths on
these (this is one of our Frequently Asked Questions).
There is no simple answer to this. It depends on what "correct"
means. For example, if you have a group of species that shows up in
80% of the trees, and the branch leading to that group has average
length 0.1 among that 80%, is the "correct" length 0.1? Or is it (0.80
x 0.1)? There is no simple answer.
However, if you want to take the consensus tree as an estimate of the
true tree (rather than as an indicator of the conflicts among trees)
you may be able to use the User Tree (option U) mode of the phylogeny
program that you used, and use it to put branch lengths on that
tree. Thus, if you used DNAML, you can take the consensus tree, make
sure it is an unrooted tree, and feed that to DNAML using the original
data set (before bootstrapping) and DNAML's option U. As DNAML wants
an unrooted tree, you may have to use RETREE to make the tree unrooted
(using the W option of RETREE and choosing the unrooted option within
it). Of course you will also want to change the tree file name from
"outree" to "intree".
If you used a phylogeny program that does not infer branch lengths,
you might want to use a different one (such as FITCH or DNAML) to
infer the branch lengths, again making sure the tree is unrooted, if
the program needs that.
Please help by correcting and extending the Wiki pages.
Function
Discrete character parsimony
Description
Multistate discrete-characters parsimony method. Up to 8 states (as
well as "?") are allowed. Cannot do Camin-Sokal or Dollo
Parsimony. Can cope with multifurcations, reconstruct ancestral
states, use character weights, and infer branch lengths.
Algorithm
PARS is a general parsimony program which carries out the Wagner
parsimony method with multiple states. Wagner parsimony allows changes
among all states. The criterion is to find the tree which requires the
minimum number of changes. The Wagner method was originated by Eck and
Dayhoff (1966) and by Kluge and Farris (1969). Here are its
assumptions:
Ancestral states are unknown unknown.
Different characters evolve independently.
Different lineages evolve independently.
Changes to all other states are equally probable (Wagner).
These changes are a priori improbable over the evolutionary time spans
involved in the differentiation of the group in question.
Other kinds of evolutionary event such as retention of polymorphism
are far less probable than these state changes.
Rates of evolution in different lineages are sufficiently low that two
changes in a long segment of the tree are far less probable than one
change in a short segment.
That these are the assumptions of parsimony methods has been
documented in a series of papers of mine: (1973a, 1978b, 1979, 1981b,
1983b, 1988b). For an opposing view arguing that the parsimony methods
make no substantive assumptions such as these, see the papers by
Farris (1983) and Sober (1983a, 1983b), but also read the exchange
between Felsenstein and Sober (1986).
Usage
Here is a sample session with fpars
% fpars
Discrete character parsimony
Input file: pars.dat
Phylip tree file (optional):
Phylip pars program output file [pars.fpars]:
Adding species:
1. Alpha
2. Beta
3. Gamma
4. Delta
5. Epsilon
Doing global rearrangements on the first of the trees tied for best
!---------!
.........
.........
Collapsing best trees
.
Output written to file "pars.fpars"
Tree also written onto file "pars.treefile"
Done.
Discrete character parsimony
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more data sets
[-intreefile] tree Phylip tree file (optional)
[-outfile] outfile [*.fpars] Phylip pars program output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-method menu [Wagner] Choose the parsimony method to use
(Values: w (Wagner); c (Camin-Sokal))
-maxtrees integer [100] Number of trees to save (Integer from
1 to 1000000)
* -[no]thorough toggle [Y] More thorough search
* -[no]rearrange boolean [Y] Rearrange on just one best tree
* -njumble integer [0] Number of times to randomise (Integer 0
or more)
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-outgrno integer [0] Species number to use as outgroup
(Integer 0 or more)
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 1.000 or more)
-[no]trout toggle [Y] Write out trees to tree file
* -outtreefile outfile [*.fpars] Phylip tree output file (optional)
-printdata boolean [N] Print data at start of run
-[no]progress boolean [Y] Print indications of progress of run
-[no]treeprint boolean [Y] Print out tree
-stepbox boolean [N] Print steps at each site
-ancseq boolean [N] Print states at all nodes of tree
* -[no]dotdiff boolean [Y] Use dot differencing to display results
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory3 string Output directory
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
File containing one or more data sets
Discrete states file
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
[-outfile] (Parameter 3)
outfile
Phylip pars program output file
Output file
<*>.fpars
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-method
list
Choose the parsimony method to use
w
(Wagner)
c
(Camin-Sokal)
Wagner
-maxtrees
integer
Number of trees to save
Integer from 1 to 1000000
100
-[no]thorough
toggle
More thorough search
Toggle value Yes/No
Yes
-[no]rearrange
boolean
Rearrange on just one best tree
Boolean value Yes/No
Yes
-njumble
integer
Number of times to randomise
Integer 0 or more
0
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-outgrno
integer
Species number to use as outgroup
Integer 0 or more
0
-dothreshold
toggle
Use threshold parsimony
Toggle value Yes/No
No
-threshold
float
Threshold value
Number 1.000 or more
1
-[no]trout
toggle
Write out trees to tree file
Toggle value Yes/No
Yes
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fpars
-printdata
boolean
Print data at start of run
Boolean value Yes/No
No
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
-[no]treeprint
boolean
Print out tree
Boolean value Yes/No
Yes
-stepbox
boolean
Print steps at each site
Boolean value Yes/No
No
-ancseq
boolean
Print states at all nodes of tree
Boolean value Yes/No
No
-[no]dotdiff
boolean
Use dot differencing to display results
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory3 -odirectory_outfile
string
Output directory
Any string
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fpars reads discrete characters input, except that multiple
states (up to 9 of them) are allowed. Any characters other than "?"
are allowed as states, up to a maximum of 9 states. In fact, one can
use different symbols in different columns of the data matrix,
although it is rather unlikely that you would want to do that. The
symbols you can use are:
The digits 0-9,
The letters A-Z and a-z,
The symbols "!\"#$%&'()*+,-./:;<=>?@\[\\]^_`\{|}~
(of these, probably only + and - will be of interest to most users).
But note that these do not include blank (" "). Blanks in the input
data are simply skipped by the program, so that they can be used to
make characters into groups for ease of viewing. The "?" (question
mark) symbol has special meaning. It is allowed in the input but is
not available as the symbol of a state. Rather, it means that the
state is unknown.
PARS can handle both bifurcating and multifurcating trees. In doing
its search for most parsimonious trees, it adds species not only by
creating new forks in the middle of existing branches, but it also
tries putting them at the end of new branches which are added to
existing forks. Thus it searches among both bifurcating and
multifurcating trees. If a branch in a tree does not have any
characters which might change in that branch in the most parsimonious
tree, it does not save that tree. Thus in any tree that results, a
branch exists only if some character has a most parsimonious
reconstruction that would involve change in that branch.
It also saves a number of trees tied for best (you can alter the
number it saves using the V option in the menu). When rearranging
trees, it tries rearrangements of all of the saved trees. This makes
the algorithm slower than earlier programs such as MIX.
(0,1) Discrete character data
These programs are intended for the use of morphological
systematists who are dealing with discrete characters, or by molecular
evolutionists dealing with presence-absence data on restriction
sites. One of the programs (PARS) allows multistate characters, with
up to 8 states, plus the unknown state symbol "?". For the others, the
characters are assumed to be coded into a series of (0,1) two-state
characters. For most of the programs there are two other states
possible, "P", which stands for the state of Polymorphism for both
states (0 and 1), and "?", which stands for the state of ignorance: it
is the state "unknown", or "does not apply". The state "P" can also be
denoted by "B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding
a multistate character into a series of two-state (0,1)
characters. Suppose we had a character with four states whose
character-state tree had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We
can represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE,
DOLPENNY and DOLBOOT the multistate recoding does not necessarily work
properly, as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected
in a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for
unordered character states.
fpars output is standard: if option 1 is toggled on, the data is
printed out, with the convention that "." means "the same as in the
first species". Then comes a list of equally parsimonious trees. Each
tree has branch lengths. These are computed using an algorithm
published by Hochbaum and Pathria (1997) which I first heard of from
Wayne Maddison who invented it independently of them. This algorithm
averages the number of reconstructed changes of state over all sites a
over all possible most parsimonious placements of the changes of state
among branches. Note that it does not correct in any way for multiple
changes that overlay each other.
If option 2 is toggled on a table of the number of changes of state
required in each character is also printed. If option 5 is toggled on,
a table is printed out after each tree, showing for each branch
whether there are known to be changes in the branch, and what the
states are inferred to have been at the top end of the branch. This is
a reconstruction of the ancestral sequences in the tree. If you choose
option 5, a menu item D appears which gives you the opportunity to
turn off dot-differencing so that complete ancestral sequences are
shown. If the inferred state is a "?", there will be multiple
equally-parsimonious assignments of states; the user must work these
out for themselves by hand. If option 6 is left in its default state
the trees found will be written to a tree file, so that they are
available to be used in other programs. If the program finds multiple
trees tied for best, all of these are written out onto the output tree
file. Each is followed by a numerical weight in square brackets (such
as [0.25000]). This is needed when we use the trees to make a
consensus tree of the results of bootstrapping or jackknifing, to
avoid overrepresenting replicates that find many tied trees.
If the U (User Tree) option is used and more than one tree is
supplied, the program also performs a statistical test of each of
these trees against the best tree. This test, which is a version of
the test proposed by Alan Templeton (1983) and evaluated in a test
case by me (1985a). It is closely parallel to a test using log
likelihood differences due to Kishino and Hasegawa (1989), and uses
the mean and variance of step differences between trees, taken across
sites. If the mean is more than 1.96 standard deviations different
then the trees are declared significantly different. The program
prints out a table of the steps for each tree, the differences of each
from the best one, the variance of that quantity as determined by the
step differences at individual sites, and a conclusion as to whether
that tree is or is not significantly worse than the best one. It is
important to understand that the test assumes that all the discrete
characters are evolving independently, which is unlikely to be true
for
If there are more than two trees, the test done is an extension of the
KHT test, due to Shimodaira and Hasegawa (1999). They pointed out that
a correction for the number of trees was necessary, and they
introduced a resampling method to make this correction. In the version
used here the variances and covariances of the sums of steps across
characters are computed for all pairs of trees. To test whether the
difference between each tree and the best one is larger than could
have been expected if they all had the same expected number of steps,
numbers of steps for all trees are sampled with these covariances and
equal means (Shimodaira and Hasegawa's "least favorable hypothesis"),
and a P value is computed from the fraction of times the difference
between the tree's value and the lowest number of steps exceeds that
actually observed. Note that this sampling needs random numbers, and
so the program will prompt the user for a random number seed if one
has not already been supplied. With the two-tree KHT test no random
numbers are used.
In either the KHT or the SH test the program prints out a table of the
number of steps for each tree, the differences of each from the lowest
one, the variance of that quantity as determined by the differences of
the numbers of steps at individual characters, and a conclusion as to
whether that tree is or is not significantly worse than the best one.
Option 6 in the menu controls whether the tree estimated by the
program is written onto a tree file. The default name of this output
tree file is "outtree". If the U option is in effect, all the
user-defined trees are written to the output tree file.
Output files for usage example
File: pars.fpars
Discrete character parsimony algorithm, version 3.69.650
One most parsimonious tree found:
+Epsilon
+----------------3
+--------2 +-------------------------Delta
| |
| +Gamma
|
1----------------Beta
|
+Alpha
requires a total of 8.000
between and length
------- --- ------
1 2 1.00
2 3 2.00
3 Epsilon 0.00
3 Delta 3.00
2 Gamma 0.00
1 Beta 2.00
1 Alpha 0.00
Please help by correcting and extending the Wiki pages.
Function
Interactive Dollo or polymorphism parsimony
Description
Interactive construction of phylogenies from discrete character data
with two states (0 and 1) using the Dollo or polymorphism parsimony
criteria. Evaluates parsimony and compatibility criteria for those
phylogenies and displays reconstructed states throughout the
tree. This can be used to find parsimony or compatibility estimates by
hand.
Algorithm
DOLMOVE is an interactive parsimony program which uses the Dollo and
Polymorphism parsimony criteria. It is inspired on Wayne Maddison and
David Maddison's marvellous program MacClade, which is written for
Apple MacIntosh computers. DOLMOVE reads in a data set which is
prepared in almost the same format as one for the Dollo and
polymorhism parsimony program DOLLOP. It allows the user to choose an
initial tree, and displays this tree on the screen. The user can look
at different characters and the way their states are distributed on
that tree, given the most parsimonious reconstruction of state changes
for that particular tree. The user then can specify how the tree is to
be rearraranged, rerooted or written out to a file. By looking at
different rearrangements of the tree the user can manually search for
the most parsimonious tree, and can get a feel for how different
characters are affected by changes in the tree topology.
This program is compatible with fewer computer systems than the other
programs in PHYLIP. It can be adapted to PCDOS systems or to any
system whose screen or terminals emulate DEC VT100 terminals (such as
Telnet programs for logging in to remote computers over a TCP/IP
network, VT100-compatible windows in the X windowing system, and any
terminal compatible with ANSI standard terminals). For any other
screen types, there is a generic option which does not make use of
screen graphics characters to display the character states. This will
be less effective, as the states will be less easy to see when
displayed.
Usage
Here is a sample session with fdolmove
% fdolmove
Interactive Dollo or polymorphism parsimony
Phylip character discrete states file: dolmove.dat
Phylip tree file (optional):
NEXT? (R # + - S . T U W O F H J K L C ? X Q) (? for Help): Q
Do you want to write out the tree to a file? (Y or N): Y
Interactive Dollo or polymorphism parsimony, version 3.69.650
5 species, 6 characters
Computing steps needed for compatibility in sites ...
(unrooted) 5.0 Steps 4 chars compatible
Dollo
,-----------5:Epsilon
--9
! ,--------4:Delta
`--8
! ,-----3:Gamma
`--7
! ,--2:Beta
`--6
`--1:Alpha
Tree written to file "dolmove.treefile"
Interactive Dollo or polymorphism parsimony
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing data set
[-intreefile] tree Phylip tree file (optional)
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-ancfile properties Ancestral states file
-factorfile properties Factors file
-method menu [d] Parsimony method (Values: d (Dollo); p
(Polymorphism))
-dothreshold toggle [N] Use threshold parsimony
* -threshold float [1] Threshold value (Number 0.000 or more)
-initialtree menu [Arbitary] Initial tree (Values: a
(Arbitary); u (User); s (Specify))
-screenwidth integer [80] Width of terminal screen in characters
(Any integer value)
-screenlines integer [24] Number of lines on screen (Any integer
value)
-outtreefile outfile [*.fdolmove] Phylip tree output file
(optional)
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outtreefile" associated qualifiers
-odirectory string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
File containing data set
Discrete states file
[-intreefile] (Parameter 2)
tree
Phylip tree file (optional)
Phylogenetic tree
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-ancfile
properties
Ancestral states file
Property value(s)
-factorfile
properties
Factors file
Property value(s)
-method
list
Parsimony method
d
(Dollo)
p
(Polymorphism)
d
-dothreshold
toggle
Use threshold parsimony
Toggle value Yes/No
No
-threshold
float
Threshold value
Number 0.000 or more
1
-initialtree
list
Initial tree
a
(Arbitary)
u
(User)
s
(Specify)
Arbitary
-screenwidth
integer
Width of terminal screen in characters
Any integer value
80
-screenlines
integer
Number of lines on screen
Any integer value
24
-outtreefile
outfile
Phylip tree output file (optional)
Output file
<*>.fdolmove
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outtreefile" associated outfile qualifiers
-odirectory
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
fdolmove reads discrete character data with "?", "P", "B" states
allowed. .
(0,1) Discrete character data
These programs are intended for the use of morphological
systematists who are dealing with discrete characters, or by molecular
evolutionists dealing with presence-absence data on restriction
sites. One of the programs (PARS) allows multistate characters, with
up to 8 states, plus the unknown state symbol "?". For the others, the
characters are assumed to be coded into a series of (0,1) two-state
characters. For most of the programs there are two other states
possible, "P", which stands for the state of Polymorphism for both
states (0 and 1), and "?", which stands for the state of ignorance: it
is the state "unknown", or "does not apply". The state "P" can also be
denoted by "B", for "both".
There is a method invented by Sokal and Sneath (1963) for linear
sequences of character states, and fully developed for branching
sequences of character states by Kluge and Farris (1969) for recoding
a multistate character into a series of two-state (0,1)
characters. Suppose we had a character with four states whose
character-state tree had the rooted form:
1 ---> 0 ---> 2
|
|
V
3
so that 1 is the ancestral state and 0, 2 and 3 derived states. We
can represent this as three two-state characters:
Old State New States
--- ----- --- ------
0 001
1 000
2 011
3 101
The three new states correspond to the three arrows in the above
character state tree. Possession of one of the new states corresponds
to whether or not the old state had that arrow in its ancestry. Thus
the first new state corresponds to the bottommost arrow, which only
state 3 has in its ancestry, the second state to the rightmost of the
top arrows, and the third state to the leftmost top arrow. This coding
will guarantee that the number of times that states arise on the tree
(in programs MIX, MOVE, PENNY and BOOT) or the number of polymorphic
states in a tree segment (in the Polymorphism option of DOLLOP,
DOLMOVE, DOLPENNY and DOLBOOT) will correctly correspond to what would
have been the case had our programs been able to take multistate
characters into account. Although I have shown the above character
state tree as rooted, the recoding method works equally well on
unrooted multistate characters as long as the connections between the
states are known and contain no loops.
However, in the default option of programs DOLLOP, DOLMOVE,
DOLPENNY and DOLBOOT the multistate recoding does not necessarily work
properly, as it may lead the program to reconstruct nonexistent state
combinations such as 010. An example of this problem is given in my
paper on alternative phylogenetic methods (1979).
If you have multistate character data where the states are connected
in a branching "character state tree" you may want to do the binary
recoding yourself. Thanks to Christopher Meacham, the package contains
a program, FACTOR, which will do the recoding itself. For details see
the documentation file for FACTOR.
We now also have the program PARS, which can do parsimony for
unordered character states.
If the A option is used, then the program will infer, for any
character whose ancestral state is unknown ("?") whether the ancestral
state 0 or 1 will give the fewest changes (according to the criterion
in use). If these are tied, then it may not be possible for the
program to infer the state in the internal nodes, and many of these
will be shown as "?". If the A option is not used, then the program
will assume 0 as the ancestral state.
When reconstructing the placement of forward changes and reversions
under the Dollo method, keep in mind that each polymorphic state in
the input data will require one "last minute" reversion. This is
included in the counts. Thus if we have both states 0 and 1 at a tip
of the tree the program will assume that the lineage had state 1 up to
the last minute, and then state 0 arose in that population by
reversion, without loss of state 1.
When DOLMOVE calculates the number of characters compatible with the
tree, it will take the F option into account and count the multistate
characters as units, counting a character as compatible with the tree
only when all of the binary characters corresponding to it are
compatible with the tree.
Please help by correcting and extending the Wiki pages.
Function
Bootstrapped restriction sites algorithm
Description
Reads in a data set, and produces multiple data sets from it by
bootstrap resampling. Since most programs in the current version of
the package allow processing of multiple data sets, this can be used
together with the consensus tree program CONSENSE to do bootstrap (or
delete-half-jackknife) analyses with most of the methods in this
package. This program also allows the Archie/Faith technique of
permutation of species within characters. It can also rewrite a data
set to convert it from between the PHYLIP Interleaved and Sequential
forms, and into a preliminary version of a new XML sequence alignment
format which is under development
Algorithm
FRESTBOOT is a restriction site specific version of SEQBOOT.
SEQBOOT is a general bootstrapping and data set translation tool. It
is intended to allow you to generate multiple data sets that are
resampled versions of the input data set. Since almost all programs in
the package can analyze these multiple data sets, this allows almost
anything in this package to be bootstrapped, jackknifed, or
permuted. SEQBOOT can handle molecular sequences, binary characters,
restriction sites, or gene frequencies. It can also convert data sets
between Sequential and Interleaved format, and into the NEXUS format
or into a new XML sequence alignment format.
To carry out a bootstrap (or jackknife, or permutation test) with some
method in the package, you may need to use three programs. First, you
need to run SEQBOOT to take the original data set and produce a large
number of bootstrapped or jackknifed data sets (somewhere between 100
and 1000 is usually adequate). Then you need to find the phylogeny
estimate for each of these, using the particular method of
interest. For example, if you were using DNAPARS you would first run
SEQBOOT and make a file with 100 bootstrapped data sets. Then you
would give this file the proper name to have it be the input file for
DNAPARS. Running DNAPARS with the M (Multiple Data Sets) menu choice
and informing it to expect 100 data sets, you would generate a big
output file as well as a treefile with the trees from the 100 data
sets. This treefile could be renamed so that it would serve as the
input for CONSENSE. When CONSENSE is run the majority rule consensus
tree will result, showing the outcome of the analysis.
This may sound tedious, but the run of CONSENSE is fast, and that of
SEQBOOT is fairly fast, so that it will not actually take any longer
than a run of a single bootstrap program with the same original data
and the same number of replicates. This is not very hard and allows
bootstrapping or jackknifing on many of the methods in this
package. The same steps are necessary with all of them. Doing things
this way some of the intermediate files (the tree file from the
DNAPARS run, for example) can be used to summarize the results of the
bootstrap in other ways than the majority rule consensus method does.
If you are using the Distance Matrix programs, you will have to add
one extra step to this, calculating distance matrices from each of the
replicate data sets, using DNADIST or GENDIST. So (for example) you
would run SEQBOOT, then run DNADIST using the output of SEQBOOT as its
input, then run (say) NEIGHBOR using the output of DNADIST as its
input, and then run CONSENSE using the tree file from NEIGHBOR as its
input.
The resampling methods available are:
The bootstrap. Bootstrapping was invented by Bradley Efron in 1979,
and its use in phylogeny estimation was introduced by me (Felsenstein,
1985b; see also Penny and Hendy, 1985). It involves creating a new
data set by sampling N characters randomly with replacement, so that
the resulting data set has the same size as the original, but some
characters have been left out and others are duplicated. The random
variation of the results from analyzing these bootstrapped data sets
can be shown statistically to be typical of the variation that you
would get from collecting new data sets. The method assumes that the
characters evolve independently, an assumption that may not be
realistic for many kinds of data.
The partial bootstrap.. This is the bootstrap where fewer than the
full number of characters are sampled. The user is asked for the
fraction of characters to be sampled. It is primarily useful in
carrying out Zharkikh and Li's (1995) Complete And Partial Bootstrap
method, and Shimodaira's (2002) AU method, both of which correct the
bias of bootstrap P values.
Block-bootstrapping. One pattern of departure from indeopendence of
character evolution is correlation of evolution in adjacent
characters. When this is thought to have occurred, we can correct for
it by samopling, not individual characters, but blocks of adjacent
characters. This is called a block bootstrap and was introduced by
Künsch (1989). If the correlations are believed to extend over some
number of characters, you choose a block size, B, that is larger than
this, and choose N/B blocks of size B. In its implementation here the
block bootstrap "wraps around" at the end of the characters (so that
if a block starts in the last B-1 characters, it continues by wrapping
around to the first character after it reaches the last
character). Note also that if you have a DNA sequence data set of an
exon of a coding region, you can ensure that equal numbers of first,
second, and third coding positions are sampled by using the block
bootstrap with B = 3.
Partial block-bootstrapping. Similar to partial bootstrapping except
sampling blocks rather than single characters.
Delete-half-jackknifing.. This alternative to the bootstrap involves
sampling a random half of the characters, and including them in the
data but dropping the others. The resulting data sets are half the
size of the original, and no characters are duplicated. The random
variation from doing this should be very similar to that obtained from
the bootstrap. The method is advocated by Wu (1986). It was mentioned
by me in my bootstrapping paper (Felsenstein, 1985b), and has been
available for many years in this program as an option. Note that, for
the present, block-jackknifing is not available, because I cannot
figure out how to do it straightforwardly when the block size is not a
divisor of the number of characters.
Delete-fraction jackknifing. Jackknifing is advocated by Farris
et. al. (1996) but as deleting a fraction 1/e (1/2.71828). This
retains too many characters and will lead to overconfidence in the
resulting groups when there are conflicting characters. However it is
made available here as an option, with the user asked to supply the
fraction of characters that are to be retained.
Permuting species within characters. This method of resampling (well,
OK, it may not be best to call it resampling) was introduced by Archie
(1989) and Faith (1990; see also Faith and Cranston, 1991). It
involves permuting the columns of the data matrix separately. This
produces data matrices that have the same number and kinds of
characters but no taxonomic structure. It is used for different
purposes than the bootstrap, as it tests not the variation around an
estimated tree but the hypothesis that there is no taxonomic structure
in the data: if a statistic such as number of steps is significantly
smaller in the actual data than it is in replicates that are permuted,
then we can argue that there is some taxonomic structure in the data
(though perhaps it might be just the presence of aa pair of sibling
species).
Permuting characters. This simply permutes the order of the
characters, the same reordering being applied to all species. For many
methods of tree inference this will make no difference to the outcome
(unless one has rates of evolution correlated among adjacent
sites). It is included as a possible step in carrying out a
permutation test of homogeneity of characters (such as the
Incongruence Length Difference test).
Permuting characters separately for each species. This is a method
introduced by Steel, Lockhart, and Penny (1993) to permute data so as
to destroy all phylogenetic structure, while keeping the base
composition of each species the same as before. It shuffles the
character order separately for each species.
Rewriting. This is not a resampling or permutation method: it simply
rewrites the data set into a different format. That format can be the
PHYLIP format. For molecular sequences and discrete morphological
character it can also be the NEXUS format. For molecular sequences one
other format is available, a new (and nonstandard) XML format of our
own devising. When the PHYLIP format is chosen the data set is
coverted between Interleaved and Sequential format. If it was read in
as Interleaved sequences, it will be written out as Sequential format,
and vice versa. The NEXUS format for molecular sequences is always
written as interleaved sequences. The XML format is different from
(though similar to) a number of other XML sequence alignment
formats. An example will be found below. Here is a table to links to
those other XML alignment formats:
Andrew Rambaut's
BEAST XML format
http://evolve.zoo.ox.ac.uk/beast/introXML.html
and http://evolve.zoo.ox.ac.uk/beast/referenindex.html
A format for alignments. There
is also a format for phylogenies
described there.
MSAML M
http://xml.coverpages.org/msaml-desc-dec.html
Defined by Paul Gordon of
University of Calgary. See his
big list of molecular biology
XML projects.
BSML
http://www.bsml.org/resources/default.asp
Bioinformatic Sequence
Markup Language
includes a multiple sequence
alignment XML format
Usage
Here is a sample session with frestboot
% frestboot -seed 3
Bootstrapped restriction sites algorithm
Input file: restboot.dat
Phylip seqboot_rest program output file [restboot.frestboot]:
completed replicate number 10
completed replicate number 20
completed replicate number 30
completed replicate number 40
completed replicate number 50
completed replicate number 60
completed replicate number 70
completed replicate number 80
completed replicate number 90
completed replicate number 100
Output written to file "restboot.frestboot"
Done.
Bootstrapped restriction sites algorithm
Version: EMBOSS:6.6.0.0
Standard (Mandatory) qualifiers:
[-infile] discretestates File containing one or more sets of
restriction data
[-outfile] outfile [*.frestboot] Phylip seqboot_rest program
output file
Additional (Optional) qualifiers (* if not always prompted):
-weights properties Weights file
-test menu [b] Choose test (Values: b (Bootstrap); j
(Jackknife); c (Permute species for each
character); o (Permute character order); s
(Permute within species); r (Rewrite data))
* -regular toggle [N] Altered sampling fraction
* -fracsample float [100.0] Samples as percentage of sites
(Number from 0.100 to 100.000)
* -rewriteformat menu [p] Output format (Values: p (PHYLIP); n
(NEXUS); x (XML))
* -blocksize integer [1] Block size for bootstraping (Integer 1
or more)
* -reps integer [100] How many replicates (Integer 1 or
more)
* -justweights menu [d] Write out datasets or just weights
(Values: d (Datasets); w (Weights))
-enzymes boolean [N] Is the number of enzymes present in
input file
* -seed integer [1] Random number seed between 1 and 32767
(must be odd) (Integer from 1 to 32767)
-printdata boolean [N] Print out the data at start of run
* -[no]dotdiff boolean [Y] Use dot-differencing
-[no]progress boolean [Y] Print indications of progress of run
Advanced (Unprompted) qualifiers: (none)
Associated qualifiers:
"-outfile" associated qualifiers
-odirectory2 string Output directory
General qualifiers:
-auto boolean Turn off prompts
-stdout boolean Write first file to standard output
-filter boolean Read first file from standard input, write
first file to standard output
-options boolean Prompt for standard and additional values
-debug boolean Write debug output to program.dbg
-verbose boolean Report some/full command line options
-help boolean Report command line options and exit. More
information on associated and general
qualifiers can be found with -help -verbose
-warning boolean Report warnings
-error boolean Report errors
-fatal boolean Report fatal errors
-die boolean Report dying program messages
-version boolean Report version number and exit
Qualifier
Type
Description
Allowed values
Default
Standard (Mandatory) qualifiers
[-infile] (Parameter 1)
discretestates
File containing one or more sets of restriction data
Discrete states file
[-outfile] (Parameter 2)
outfile
Phylip seqboot_rest program output file
Output file
<*>.frestboot
Additional (Optional) qualifiers
-weights
properties
Weights file
Property value(s)
-test
list
Choose test
b
(Bootstrap)
j
(Jackknife)
c
(Permute species for each character)
o
(Permute character order)
s
(Permute within species)
r
(Rewrite data)
b
-regular
toggle
Altered sampling fraction
Toggle value Yes/No
No
-fracsample
float
Samples as percentage of sites
Number from 0.100 to 100.000
100.0
-rewriteformat
list
Output format
p
(PHYLIP)
n
(NEXUS)
x
(XML)
p
-blocksize
integer
Block size for bootstraping
Integer 1 or more
1
-reps
integer
How many replicates
Integer 1 or more
100
-justweights
list
Write out datasets or just weights
d
(Datasets)
w
(Weights)
d
-enzymes
boolean
Is the number of enzymes present in input file
Boolean value Yes/No
No
-seed
integer
Random number seed between 1 and 32767 (must be odd)
Integer from 1 to 32767
1
-printdata
boolean
Print out the data at start of run
Boolean value Yes/No
No
-[no]dotdiff
boolean
Use dot-differencing
Boolean value Yes/No
Yes
-[no]progress
boolean
Print indications of progress of run
Boolean value Yes/No
Yes
Advanced (Unprompted) qualifiers
(none)
Associated qualifiers
"-outfile" associated outfile qualifiers
-odirectory2 -odirectory_outfile
string
Output directory
Any string
General qualifiers
-auto
boolean
Turn off prompts
Boolean value Yes/No
N
-stdout
boolean
Write first file to standard output
Boolean value Yes/No
N
-filter
boolean
Read first file from standard input, write first file to standard output
Boolean value Yes/No
N
-options
boolean
Prompt for standard and additional values
Boolean value Yes/No
N
-debug
boolean
Write debug output to program.dbg
Boolean value Yes/No
N
-verbose
boolean
Report some/full command line options
Boolean value Yes/No
Y
-help
boolean
Report command line options and exit. More information on associated and general qualifiers can be found with -help -verbose
Boolean value Yes/No
N
-warning
boolean
Report warnings
Boolean value Yes/No
Y
-error
boolean
Report errors
Boolean value Yes/No
Y
-fatal
boolean
Report fatal errors
Boolean value Yes/No
Y
-die
boolean
Report dying program messages
Boolean value Yes/No
Y
-version
boolean
Report version number and exit
Boolean value Yes/No
N
Input file format
frestboot data files read by SEQBOOT are the standard ones for
the various kinds of data. For molecular sequences the sequences may
be either interleaved or sequential, and similarly for restriction
sites. Restriction sites data may either have or not have the third
argument, the number of restriction enzymes used. Discrete
morphological characters are always assumed to be in sequential
format. Gene frequencies data start with the number of species and the
number of loci, and then follow that by a line with the number of
alleles at each locus. The data for each locus may either have one
entry for each allele, or omit one allele at each locus. The details
of the formats are given in the main documentation file, and in the
documentation files for the groups of programsreads any normal
sequence USAs.
frestboot output will contain the data sets generated by the
resampling process. Note that, when Gene Frequencies data is used or
when Discrete Morphological characters with the Factors option are
used, the number of characters in each data set may vary. It may also
vary if there are an odd number of characters or sites and the
Delete-Half-Jackknife resampling method is used, for then there will
be a 50% chance of choosing (n+1)/2 characters and a 50% chance of
choosing (n-1)/2 characters.
The Factors option causes the characters to be resampled together. If
(say) three adjacent characters all have the same factors characters,
so that they all are understood to be recoding one multistate
character, they will be resampled together as a group.
The order of species in the data sets in the output file will vary
randomly. This is a precaution to help the programs that analyze these
data avoid any result which is sensitive to the input order of species
from showing up repeatedly and thus appearing to have evidence in its
favor.
The numerical options 1 and 2 in the menu also affect the output
file. If 1 is chosen (it is off by default) the program will print the
original input data set on the output file before the resampled data
sets. I cannot actually see why anyone would want to do this. Option 2
toggles the feature (on by default) that prints out up to 20 times
during the resampling process a notification that the program has
completed a certain number of data sets. Thus if 100 resampled data
sets are being produced, every 5 data sets a line is printed saying
which data set has just been completed. This option should be turned
off if the program is running in background and silence is
desirable. At the end of execution the program will always (whatever
the setting of option 2) print a couple of lines saying that output
has been written to the output file.
Written (2004) - Joe Felsenstein, University of Washington.
Converted (August 2004) to an EMBASSY program by the EMBOSS team.
Target users
This program is intended to be used by everyone and everything, from naive users to embedded scripts.
Comments
None
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$(am__remove_distdir)
test -d "$(distdir)" || mkdir "$(distdir)"
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list='$(DISTFILES)'; \
dist_files=`for file in $$list; do echo $$file; done | \
sed -e "s|^$$srcdirstrip/||;t" \
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case $$dist_files in \
*/*) $(MKDIR_P) `echo "$$dist_files" | \
sed '/\//!d;s|^|$(distdir)/|;s,/[^/]*$$,,' | \
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for file in $$dist_files; do \
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find "$(distdir)/$$file" -type d ! -perm -700 -exec chmod u+rwx {} \;; \
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if test -d $(srcdir)/$$file && test $$d != $(srcdir); then \
cp -fpR $(srcdir)/$$file "$(distdir)$$dir" || exit 1; \
find "$(distdir)/$$file" -type d ! -perm -700 -exec chmod u+rwx {} \;; \
fi; \
cp -fpR $$d/$$file "$(distdir)$$dir" || exit 1; \
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test -f "$(distdir)/$$file" \
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done
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$(am__relativize); \
new_distdir=$$reldir; \
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$(am__relativize); \
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dist-hook
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tardir=$(distdir) && $(am__tar) | GZIP=$(GZIP_ENV) gzip -c >$(distdir).tar.gz
$(am__post_remove_distdir)
dist-bzip2: distdir
tardir=$(distdir) && $(am__tar) | BZIP2=$${BZIP2--9} bzip2 -c >$(distdir).tar.bz2
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dist-lzip: distdir
tardir=$(distdir) && $(am__tar) | lzip -c $${LZIP_OPT--9} >$(distdir).tar.lz
$(am__post_remove_distdir)
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tardir=$(distdir) && $(am__tar) | XZ_OPT=$${XZ_OPT--e} xz -c >$(distdir).tar.xz
$(am__post_remove_distdir)
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tardir=$(distdir) && $(am__tar) | compress -c >$(distdir).tar.Z
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shar $(distdir) | GZIP=$(GZIP_ENV) gzip -c >$(distdir).shar.gz
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*.tar.gz*) \
GZIP=$(GZIP_ENV) gzip -dc $(distdir).tar.gz | $(am__untar) ;;\
*.tar.bz2*) \
bzip2 -dc $(distdir).tar.bz2 | $(am__untar) ;;\
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xz -dc $(distdir).tar.xz | $(am__untar) ;;\
*.tar.Z*) \
uncompress -c $(distdir).tar.Z | $(am__untar) ;;\
*.shar.gz*) \
GZIP=$(GZIP_ENV) gzip -dc $(distdir).shar.gz | unshar ;;\
*.zip*) \
unzip $(distdir).zip ;;\
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chmod -R a-w $(distdir); chmod u+w $(distdir)
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check-am: all-am
check: check-recursive
all-am: Makefile
installdirs: installdirs-recursive
installdirs-am:
install: install-recursive
install-exec: install-exec-recursive
install-data: install-data-recursive
uninstall: uninstall-recursive
install-am: all-am
@$(MAKE) $(AM_MAKEFLAGS) install-exec-am install-data-am
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install-strip:
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$(MAKE) $(AM_MAKEFLAGS) INSTALL_PROGRAM="$(INSTALL_STRIP_PROGRAM)" \
install_sh_PROGRAM="$(INSTALL_STRIP_PROGRAM)" INSTALL_STRIP_FLAG=-s \
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$(MAKE) $(AM_MAKEFLAGS) INSTALL_PROGRAM="$(INSTALL_STRIP_PROGRAM)" \
install_sh_PROGRAM="$(INSTALL_STRIP_PROGRAM)" INSTALL_STRIP_FLAG=-s \
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mostlyclean-generic:
clean-generic:
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clean: clean-recursive
clean-am: clean-generic clean-libtool mostlyclean-am
distclean: distclean-recursive
-rm -f $(am__CONFIG_DISTCLEAN_FILES)
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distclean-am: clean-am distclean-generic distclean-libtool \
distclean-tags
dvi: dvi-recursive
dvi-am:
html: html-recursive
html-am:
info: info-recursive
info-am:
install-data-am:
install-dvi: install-dvi-recursive
install-dvi-am:
install-exec-am:
install-html: install-html-recursive
install-html-am:
install-info: install-info-recursive
install-info-am:
install-man:
install-pdf: install-pdf-recursive
install-pdf-am:
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install-ps-am:
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pdf: pdf-recursive
pdf-am:
ps: ps-recursive
ps-am:
uninstall-am:
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tags-recursive
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dist-xz dist-zip distcheck distclean distclean-generic \
distclean-libtool distclean-tags distcleancheck distdir \
distuninstallcheck dvi dvi-am html html-am info info-am \
install install-am install-data install-data-am install-dvi \
install-dvi-am install-exec install-exec-am install-html \
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# tar to pick up the other directories
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dist-hook:
tar cBf - emboss_acd | ( cd $(distdir); tar xBf - ; cd emboss_acd; rm -rf CVS )
tar cBf - emboss_doc | ( cd $(distdir); tar xBf - ; cd emboss_doc; rm -rf CVS; rm -rf master)
tar cBf - doc | ( cd $(distdir); tar xBf - ; cd doc; rm -rf CVS )
tar cBf - include | ( cd $(distdir); tar xBf - ; cd include; rm -rf CVS )
tar cBf - data | ( cd $(distdir); tar xBf - ; cd data; rm -rf CVS )
tar cBf - test | ( cd $(distdir); tar xBf - ; cd test; rm -rf CVS)
# Tell versions [3.59,3.63) of GNU make to not export all variables.
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.NOEXPORT:
PHYLIPNEW-3.69.650/NEWS 0000664 0001750 0001750 00000000000 07712253200 010751 0000000 0000000 PHYLIPNEW-3.69.650/configure 0000775 0001750 0001750 00002415307 12171071675 012220 0000000 0000000 #! /bin/sh
# From configure.in Revision: 1.39 .
# Guess values for system-dependent variables and create Makefiles.
# Generated by GNU Autoconf 2.69 for PHYLIPNEW 3.69.650.
#
# Report bugs to .
#
#
# Copyright (C) 1992-1996, 1998-2012 Free Software Foundation, Inc.
#
#
# This configure script is free software; the Free Software Foundation
# gives unlimited permission to copy, distribute and modify it.
## -------------------- ##
## M4sh Initialization. ##
## -------------------- ##
# Be more Bourne compatible
DUALCASE=1; export DUALCASE # for MKS sh
if test -n "${ZSH_VERSION+set}" && (emulate sh) >/dev/null 2>&1; then :
emulate sh
NULLCMD=:
# Pre-4.2 versions of Zsh do word splitting on ${1+"$@"}, which
# is contrary to our usage. Disable this feature.
alias -g '${1+"$@"}'='"$@"'
setopt NO_GLOB_SUBST
else
case `(set -o) 2>/dev/null` in #(
*posix*) :
set -o posix ;; #(
*) :
;;
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as_nl='
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export as_nl
# Printing a long string crashes Solaris 7 /usr/bin/printf.
as_echo='\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'
as_echo=$as_echo$as_echo$as_echo$as_echo$as_echo
as_echo=$as_echo$as_echo$as_echo$as_echo$as_echo$as_echo
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if test -z "$BASH_VERSION$ZSH_VERSION" \
&& (test "X`print -r -- $as_echo`" = "X$as_echo") 2>/dev/null; then
as_echo='print -r --'
as_echo_n='print -rn --'
elif (test "X`printf %s $as_echo`" = "X$as_echo") 2>/dev/null; then
as_echo='printf %s\n'
as_echo_n='printf %s'
else
if test "X`(/usr/ucb/echo -n -n $as_echo) 2>/dev/null`" = "X-n $as_echo"; then
as_echo_body='eval /usr/ucb/echo -n "$1$as_nl"'
as_echo_n='/usr/ucb/echo -n'
else
as_echo_body='eval expr "X$1" : "X\\(.*\\)"'
as_echo_n_body='eval
arg=$1;
case $arg in #(
*"$as_nl"*)
expr "X$arg" : "X\\(.*\\)$as_nl";
arg=`expr "X$arg" : ".*$as_nl\\(.*\\)"`;;
esac;
expr "X$arg" : "X\\(.*\\)" | tr -d "$as_nl"
'
export as_echo_n_body
as_echo_n='sh -c $as_echo_n_body as_echo'
fi
export as_echo_body
as_echo='sh -c $as_echo_body as_echo'
fi
# The user is always right.
if test "${PATH_SEPARATOR+set}" != set; then
PATH_SEPARATOR=:
(PATH='/bin;/bin'; FPATH=$PATH; sh -c :) >/dev/null 2>&1 && {
(PATH='/bin:/bin'; FPATH=$PATH; sh -c :) >/dev/null 2>&1 ||
PATH_SEPARATOR=';'
}
fi
# IFS
# We need space, tab and new line, in precisely that order. Quoting is
# there to prevent editors from complaining about space-tab.
# (If _AS_PATH_WALK were called with IFS unset, it would disable word
# splitting by setting IFS to empty value.)
IFS=" "" $as_nl"
# Find who we are. Look in the path if we contain no directory separator.
as_myself=
case $0 in #((
*[\\/]* ) as_myself=$0 ;;
*) as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
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test -z "$as_dir" && as_dir=.
test -r "$as_dir/$0" && as_myself=$as_dir/$0 && break
done
IFS=$as_save_IFS
;;
esac
# We did not find ourselves, most probably we were run as `sh COMMAND'
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if test "x$as_myself" = x; then
as_myself=$0
fi
if test ! -f "$as_myself"; then
$as_echo "$as_myself: error: cannot find myself; rerun with an absolute file name" >&2
exit 1
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# Unset variables that we do not need and which cause bugs (e.g. in
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for as_var in BASH_ENV ENV MAIL MAILPATH
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PS1='$ '
PS2='> '
PS4='+ '
# NLS nuisances.
LC_ALL=C
export LC_ALL
LANGUAGE=C
export LANGUAGE
# CDPATH.
(unset CDPATH) >/dev/null 2>&1 && unset CDPATH
# Use a proper internal environment variable to ensure we don't fall
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# We cannot yet assume a decent shell, so we have to provide a
# neutralization value for shells without unset; and this also
# works around shells that cannot unset nonexistent variables.
# Preserve -v and -x to the replacement shell.
BASH_ENV=/dev/null
ENV=/dev/null
(unset BASH_ENV) >/dev/null 2>&1 && unset BASH_ENV ENV
case $- in # ((((
*v*x* | *x*v* ) as_opts=-vx ;;
*v* ) as_opts=-v ;;
*x* ) as_opts=-x ;;
* ) as_opts= ;;
esac
exec $CONFIG_SHELL $as_opts "$as_myself" ${1+"$@"}
# Admittedly, this is quite paranoid, since all the known shells bail
# out after a failed `exec'.
$as_echo "$0: could not re-execute with $CONFIG_SHELL" >&2
as_fn_exit 255
fi
# We don't want this to propagate to other subprocesses.
{ _as_can_reexec=; unset _as_can_reexec;}
if test "x$CONFIG_SHELL" = x; then
as_bourne_compatible="if test -n \"\${ZSH_VERSION+set}\" && (emulate sh) >/dev/null 2>&1; then :
emulate sh
NULLCMD=:
# Pre-4.2 versions of Zsh do word splitting on \${1+\"\$@\"}, which
# is contrary to our usage. Disable this feature.
alias -g '\${1+\"\$@\"}'='\"\$@\"'
setopt NO_GLOB_SUBST
else
case \`(set -o) 2>/dev/null\` in #(
*posix*) :
set -o posix ;; #(
*) :
;;
esac
fi
"
as_required="as_fn_return () { (exit \$1); }
as_fn_success () { as_fn_return 0; }
as_fn_failure () { as_fn_return 1; }
as_fn_ret_success () { return 0; }
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as_fn_failure && { exitcode=1; echo as_fn_failure succeeded.; }
as_fn_ret_success || { exitcode=1; echo as_fn_ret_success failed.; }
as_fn_ret_failure && { exitcode=1; echo as_fn_ret_failure succeeded.; }
if ( set x; as_fn_ret_success y && test x = \"\$1\" ); then :
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exitcode=1; echo positional parameters were not saved.
fi
test x\$exitcode = x0 || exit 1
test -x / || exit 1"
as_suggested=" as_lineno_1=";as_suggested=$as_suggested$LINENO;as_suggested=$as_suggested" as_lineno_1a=\$LINENO
as_lineno_2=";as_suggested=$as_suggested$LINENO;as_suggested=$as_suggested" as_lineno_2a=\$LINENO
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test -n \"\${ZSH_VERSION+set}\${BASH_VERSION+set}\" || (
ECHO='\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\'
ECHO=\$ECHO\$ECHO\$ECHO\$ECHO\$ECHO
ECHO=\$ECHO\$ECHO\$ECHO\$ECHO\$ECHO\$ECHO
PATH=/empty FPATH=/empty; export PATH FPATH
test \"X\`printf %s \$ECHO\`\" = \"X\$ECHO\" \\
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test \$(( 1 + 1 )) = 2 || exit 1"
if (eval "$as_required") 2>/dev/null; then :
as_have_required=yes
else
as_have_required=no
fi
if test x$as_have_required = xyes && (eval "$as_suggested") 2>/dev/null; then :
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
as_found=false
for as_dir in /bin$PATH_SEPARATOR/usr/bin$PATH_SEPARATOR$PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
as_found=:
case $as_dir in #(
/*)
for as_base in sh bash ksh sh5; do
# Try only shells that exist, to save several forks.
as_shell=$as_dir/$as_base
if { test -f "$as_shell" || test -f "$as_shell.exe"; } &&
{ $as_echo "$as_bourne_compatible""$as_required" | as_run=a "$as_shell"; } 2>/dev/null; then :
CONFIG_SHELL=$as_shell as_have_required=yes
if { $as_echo "$as_bourne_compatible""$as_suggested" | as_run=a "$as_shell"; } 2>/dev/null; then :
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esac
as_found=false
done
$as_found || { if { test -f "$SHELL" || test -f "$SHELL.exe"; } &&
{ $as_echo "$as_bourne_compatible""$as_required" | as_run=a "$SHELL"; } 2>/dev/null; then :
CONFIG_SHELL=$SHELL as_have_required=yes
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IFS=$as_save_IFS
if test "x$CONFIG_SHELL" != x; then :
export CONFIG_SHELL
# We cannot yet assume a decent shell, so we have to provide a
# neutralization value for shells without unset; and this also
# works around shells that cannot unset nonexistent variables.
# Preserve -v and -x to the replacement shell.
BASH_ENV=/dev/null
ENV=/dev/null
(unset BASH_ENV) >/dev/null 2>&1 && unset BASH_ENV ENV
case $- in # ((((
*v*x* | *x*v* ) as_opts=-vx ;;
*v* ) as_opts=-v ;;
*x* ) as_opts=-x ;;
* ) as_opts= ;;
esac
exec $CONFIG_SHELL $as_opts "$as_myself" ${1+"$@"}
# Admittedly, this is quite paranoid, since all the known shells bail
# out after a failed `exec'.
$as_echo "$0: could not re-execute with $CONFIG_SHELL" >&2
exit 255
fi
if test x$as_have_required = xno; then :
$as_echo "$0: This script requires a shell more modern than all"
$as_echo "$0: the shells that I found on your system."
if test x${ZSH_VERSION+set} = xset ; then
$as_echo "$0: In particular, zsh $ZSH_VERSION has bugs and should"
$as_echo "$0: be upgraded to zsh 4.3.4 or later."
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$as_echo "$0: Please tell bug-autoconf@gnu.org and
$0: emboss-bug@emboss.open-bio.org about your system,
$0: including any error possibly output before this
$0: message. Then install a modern shell, or manually run
$0: the script under such a shell if you do have one."
fi
exit 1
fi
fi
fi
SHELL=${CONFIG_SHELL-/bin/sh}
export SHELL
# Unset more variables known to interfere with behavior of common tools.
CLICOLOR_FORCE= GREP_OPTIONS=
unset CLICOLOR_FORCE GREP_OPTIONS
## --------------------- ##
## M4sh Shell Functions. ##
## --------------------- ##
# as_fn_unset VAR
# ---------------
# Portably unset VAR.
as_fn_unset ()
{
{ eval $1=; unset $1;}
}
as_unset=as_fn_unset
# as_fn_set_status STATUS
# -----------------------
# Set $? to STATUS, without forking.
as_fn_set_status ()
{
return $1
} # as_fn_set_status
# as_fn_exit STATUS
# -----------------
# Exit the shell with STATUS, even in a "trap 0" or "set -e" context.
as_fn_exit ()
{
set +e
as_fn_set_status $1
exit $1
} # as_fn_exit
# as_fn_mkdir_p
# -------------
# Create "$as_dir" as a directory, including parents if necessary.
as_fn_mkdir_p ()
{
case $as_dir in #(
-*) as_dir=./$as_dir;;
esac
test -d "$as_dir" || eval $as_mkdir_p || {
as_dirs=
while :; do
case $as_dir in #(
*\'*) as_qdir=`$as_echo "$as_dir" | sed "s/'/'\\\\\\\\''/g"`;; #'(
*) as_qdir=$as_dir;;
esac
as_dirs="'$as_qdir' $as_dirs"
as_dir=`$as_dirname -- "$as_dir" ||
$as_expr X"$as_dir" : 'X\(.*[^/]\)//*[^/][^/]*/*$' \| \
X"$as_dir" : 'X\(//\)[^/]' \| \
X"$as_dir" : 'X\(//\)$' \| \
X"$as_dir" : 'X\(/\)' \| . 2>/dev/null ||
$as_echo X"$as_dir" |
sed '/^X\(.*[^/]\)\/\/*[^/][^/]*\/*$/{
s//\1/
q
}
/^X\(\/\/\)[^/].*/{
s//\1/
q
}
/^X\(\/\/\)$/{
s//\1/
q
}
/^X\(\/\).*/{
s//\1/
q
}
s/.*/./; q'`
test -d "$as_dir" && break
done
test -z "$as_dirs" || eval "mkdir $as_dirs"
} || test -d "$as_dir" || as_fn_error $? "cannot create directory $as_dir"
} # as_fn_mkdir_p
# as_fn_executable_p FILE
# -----------------------
# Test if FILE is an executable regular file.
as_fn_executable_p ()
{
test -f "$1" && test -x "$1"
} # as_fn_executable_p
# as_fn_append VAR VALUE
# ----------------------
# Append the text in VALUE to the end of the definition contained in VAR. Take
# advantage of any shell optimizations that allow amortized linear growth over
# repeated appends, instead of the typical quadratic growth present in naive
# implementations.
if (eval "as_var=1; as_var+=2; test x\$as_var = x12") 2>/dev/null; then :
eval 'as_fn_append ()
{
eval $1+=\$2
}'
else
as_fn_append ()
{
eval $1=\$$1\$2
}
fi # as_fn_append
# as_fn_arith ARG...
# ------------------
# Perform arithmetic evaluation on the ARGs, and store the result in the
# global $as_val. Take advantage of shells that can avoid forks. The arguments
# must be portable across $(()) and expr.
if (eval "test \$(( 1 + 1 )) = 2") 2>/dev/null; then :
eval 'as_fn_arith ()
{
as_val=$(( $* ))
}'
else
as_fn_arith ()
{
as_val=`expr "$@" || test $? -eq 1`
}
fi # as_fn_arith
# as_fn_error STATUS ERROR [LINENO LOG_FD]
# ----------------------------------------
# Output "`basename $0`: error: ERROR" to stderr. If LINENO and LOG_FD are
# provided, also output the error to LOG_FD, referencing LINENO. Then exit the
# script with STATUS, using 1 if that was 0.
as_fn_error ()
{
as_status=$1; test $as_status -eq 0 && as_status=1
if test "$4"; then
as_lineno=${as_lineno-"$3"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
$as_echo "$as_me:${as_lineno-$LINENO}: error: $2" >&$4
fi
$as_echo "$as_me: error: $2" >&2
as_fn_exit $as_status
} # as_fn_error
if expr a : '\(a\)' >/dev/null 2>&1 &&
test "X`expr 00001 : '.*\(...\)'`" = X001; then
as_expr=expr
else
as_expr=false
fi
if (basename -- /) >/dev/null 2>&1 && test "X`basename -- / 2>&1`" = "X/"; then
as_basename=basename
else
as_basename=false
fi
if (as_dir=`dirname -- /` && test "X$as_dir" = X/) >/dev/null 2>&1; then
as_dirname=dirname
else
as_dirname=false
fi
as_me=`$as_basename -- "$0" ||
$as_expr X/"$0" : '.*/\([^/][^/]*\)/*$' \| \
X"$0" : 'X\(//\)$' \| \
X"$0" : 'X\(/\)' \| . 2>/dev/null ||
$as_echo X/"$0" |
sed '/^.*\/\([^/][^/]*\)\/*$/{
s//\1/
q
}
/^X\/\(\/\/\)$/{
s//\1/
q
}
/^X\/\(\/\).*/{
s//\1/
q
}
s/.*/./; q'`
# Avoid depending upon Character Ranges.
as_cr_letters='abcdefghijklmnopqrstuvwxyz'
as_cr_LETTERS='ABCDEFGHIJKLMNOPQRSTUVWXYZ'
as_cr_Letters=$as_cr_letters$as_cr_LETTERS
as_cr_digits='0123456789'
as_cr_alnum=$as_cr_Letters$as_cr_digits
as_lineno_1=$LINENO as_lineno_1a=$LINENO
as_lineno_2=$LINENO as_lineno_2a=$LINENO
eval 'test "x$as_lineno_1'$as_run'" != "x$as_lineno_2'$as_run'" &&
test "x`expr $as_lineno_1'$as_run' + 1`" = "x$as_lineno_2'$as_run'"' || {
# Blame Lee E. McMahon (1931-1989) for sed's syntax. :-)
sed -n '
p
/[$]LINENO/=
' <$as_myself |
sed '
s/[$]LINENO.*/&-/
t lineno
b
:lineno
N
:loop
s/[$]LINENO\([^'$as_cr_alnum'_].*\n\)\(.*\)/\2\1\2/
t loop
s/-\n.*//
' >$as_me.lineno &&
chmod +x "$as_me.lineno" ||
{ $as_echo "$as_me: error: cannot create $as_me.lineno; rerun with a POSIX shell" >&2; as_fn_exit 1; }
# If we had to re-execute with $CONFIG_SHELL, we're ensured to have
# already done that, so ensure we don't try to do so again and fall
# in an infinite loop. This has already happened in practice.
_as_can_reexec=no; export _as_can_reexec
# Don't try to exec as it changes $[0], causing all sort of problems
# (the dirname of $[0] is not the place where we might find the
# original and so on. Autoconf is especially sensitive to this).
. "./$as_me.lineno"
# Exit status is that of the last command.
exit
}
ECHO_C= ECHO_N= ECHO_T=
case `echo -n x` in #(((((
-n*)
case `echo 'xy\c'` in
*c*) ECHO_T=' ';; # ECHO_T is single tab character.
xy) ECHO_C='\c';;
*) echo `echo ksh88 bug on AIX 6.1` > /dev/null
ECHO_T=' ';;
esac;;
*)
ECHO_N='-n';;
esac
rm -f conf$$ conf$$.exe conf$$.file
if test -d conf$$.dir; then
rm -f conf$$.dir/conf$$.file
else
rm -f conf$$.dir
mkdir conf$$.dir 2>/dev/null
fi
if (echo >conf$$.file) 2>/dev/null; then
if ln -s conf$$.file conf$$ 2>/dev/null; then
as_ln_s='ln -s'
# ... but there are two gotchas:
# 1) On MSYS, both `ln -s file dir' and `ln file dir' fail.
# 2) DJGPP < 2.04 has no symlinks; `ln -s' creates a wrapper executable.
# In both cases, we have to default to `cp -pR'.
ln -s conf$$.file conf$$.dir 2>/dev/null && test ! -f conf$$.exe ||
as_ln_s='cp -pR'
elif ln conf$$.file conf$$ 2>/dev/null; then
as_ln_s=ln
else
as_ln_s='cp -pR'
fi
else
as_ln_s='cp -pR'
fi
rm -f conf$$ conf$$.exe conf$$.dir/conf$$.file conf$$.file
rmdir conf$$.dir 2>/dev/null
if mkdir -p . 2>/dev/null; then
as_mkdir_p='mkdir -p "$as_dir"'
else
test -d ./-p && rmdir ./-p
as_mkdir_p=false
fi
as_test_x='test -x'
as_executable_p=as_fn_executable_p
# Sed expression to map a string onto a valid CPP name.
as_tr_cpp="eval sed 'y%*$as_cr_letters%P$as_cr_LETTERS%;s%[^_$as_cr_alnum]%_%g'"
# Sed expression to map a string onto a valid variable name.
as_tr_sh="eval sed 'y%*+%pp%;s%[^_$as_cr_alnum]%_%g'"
SHELL=${CONFIG_SHELL-/bin/sh}
test -n "$DJDIR" || exec 7<&0 &1
# Name of the host.
# hostname on some systems (SVR3.2, old GNU/Linux) returns a bogus exit status,
# so uname gets run too.
ac_hostname=`(hostname || uname -n) 2>/dev/null | sed 1q`
#
# Initializations.
#
ac_default_prefix=/usr/local
ac_clean_files=
ac_config_libobj_dir=.
LIBOBJS=
cross_compiling=no
subdirs=
MFLAGS=
MAKEFLAGS=
# Identity of this package.
PACKAGE_NAME='PHYLIPNEW'
PACKAGE_TARNAME='PHYLIPNEW'
PACKAGE_VERSION='3.69.650'
PACKAGE_STRING='PHYLIPNEW 3.69.650'
PACKAGE_BUGREPORT='emboss-bug@emboss.open-bio.org'
PACKAGE_URL='http://emboss.open-bio.org/'
ac_unique_file="src/dnadist.c"
# Factoring default headers for most tests.
ac_includes_default="\
#include
#ifdef HAVE_SYS_TYPES_H
# include
#endif
#ifdef HAVE_SYS_STAT_H
# include
#endif
#ifdef STDC_HEADERS
# include
# include
#else
# ifdef HAVE_STDLIB_H
# include
# endif
#endif
#ifdef HAVE_STRING_H
# if !defined STDC_HEADERS && defined HAVE_MEMORY_H
# include
# endif
# include
#endif
#ifdef HAVE_STRINGS_H
# include
#endif
#ifdef HAVE_INTTYPES_H
# include
#endif
#ifdef HAVE_STDINT_H
# include
#endif
#ifdef HAVE_UNISTD_H
# include
#endif"
ac_subst_vars='am__EXEEXT_FALSE
am__EXEEXT_TRUE
LTLIBOBJS
LIBOBJS
NEEDAJAX_FALSE
NEEDAJAX_TRUE
ISSHARED_FALSE
ISSHARED_TRUE
ISAIXIA64_FALSE
ISAIXIA64_TRUE
ISCYGWIN_FALSE
ISCYGWIN_TRUE
PURIFY_FALSE
PURIFY_TRUE
ESYSTEMLIBS_FALSE
ESYSTEMLIBS_TRUE
embprefix
LOCALLINK_FALSE
LOCALLINK_TRUE
POSIX_MALLOC_THRESHOLD
PCRE_POSIXLIB_VERSION
PCRE_LIB_VERSION
PCRE_VERSION
PCRE_DATE
PCRE_MINOR
PCRE_MAJOR
HAVE_STRERROR
HAVE_MEMMOVE
POSTGRESQL_VERSION
POSTGRESQL_LDFLAGS
POSTGRESQL_CPPFLAGS
POSTGRESQL_CFLAGS
POSTGRESQL_CONFIG
MYSQL_VERSION
MYSQL_LDFLAGS
MYSQL_CPPFLAGS
MYSQL_CFLAGS
MYSQL_CONFIG
JAVA_BUILD_FALSE
JAVA_BUILD_TRUE
JAVA_LDFLAGS
JAVA_CPPFLAGS
JAVA_CFLAGS
JAVAC
JAVA
JAR
ANT
AMPDF_FALSE
AMPDF_TRUE
AMPNG_FALSE
AMPNG_TRUE
XLIB
X_EXTRA_LIBS
X_LIBS
X_PRE_LIBS
X_CFLAGS
XMKMF
DEVWARN_CFLAGS
WARN_CFLAGS
CXXCPP
OTOOL64
OTOOL
LIPO
NMEDIT
DSYMUTIL
MANIFEST_TOOL
RANLIB
ac_ct_AR
AR
DLLTOOL
OBJDUMP
NM
ac_ct_DUMPBIN
DUMPBIN
LD
FGREP
EGREP
GREP
SED
host_os
host_vendor
host_cpu
host
build_os
build_vendor
build_cpu
build
LIBTOOL
am__fastdepCXX_FALSE
am__fastdepCXX_TRUE
CXXDEPMODE
am__fastdepCC_FALSE
am__fastdepCC_TRUE
CCDEPMODE
am__nodep
AMDEPBACKSLASH
AMDEP_FALSE
AMDEP_TRUE
am__quote
am__include
DEPDIR
am__untar
am__tar
AMTAR
am__leading_dot
mkdir_p
INSTALL_STRIP_PROGRAM
STRIP
install_sh
MAKEINFO
AUTOHEADER
AUTOMAKE
AUTOCONF
ACLOCAL
VERSION
PACKAGE
CYGPATH_W
am__isrc
MKDIR_P
SET_MAKE
LN_S
INSTALL_DATA
INSTALL_SCRIPT
INSTALL_PROGRAM
CPP
ac_ct_CXX
CXXFLAGS
CXX
OBJEXT
EXEEXT
ac_ct_CC
CPPFLAGS
LDFLAGS
CFLAGS
CC
AWK
target_alias
host_alias
build_alias
LIBS
ECHO_T
ECHO_N
ECHO_C
DEFS
mandir
localedir
libdir
psdir
pdfdir
dvidir
htmldir
infodir
docdir
oldincludedir
includedir
localstatedir
sharedstatedir
sysconfdir
datadir
datarootdir
libexecdir
sbindir
bindir
program_transform_name
prefix
exec_prefix
PACKAGE_URL
PACKAGE_BUGREPORT
PACKAGE_STRING
PACKAGE_VERSION
PACKAGE_TARNAME
PACKAGE_NAME
PATH_SEPARATOR
SHELL'
ac_subst_files=''
ac_user_opts='
enable_option_checking
enable_dependency_tracking
enable_shared
enable_static
with_pic
enable_fast_install
with_gnu_ld
with_sysroot
enable_libtool_lock
enable_64
with_optimisation
enable_warnings
enable_devwarnings
enable_devextrawarnings
enable_buildbookdeprecated
enable_buildalldeprecated
with_sgiabi
with_x
with_docroot
with_gccprofile
with_java
with_javaos
with_auth
with_thread
with_hpdf
with_pngdriver
with_mysql
with_postgresql
enable_localforce
enable_debug
enable_large
enable_systemlibs
enable_purify
enable_mcheck
enable_savestats
'
ac_precious_vars='build_alias
host_alias
target_alias
CC
CFLAGS
LDFLAGS
LIBS
CPPFLAGS
CXX
CXXFLAGS
CCC
CPP
CXXCPP
XMKMF
ANT
JAR
JAVA
JAVAC'
# Initialize some variables set by options.
ac_init_help=
ac_init_version=false
ac_unrecognized_opts=
ac_unrecognized_sep=
# The variables have the same names as the options, with
# dashes changed to underlines.
cache_file=/dev/null
exec_prefix=NONE
no_create=
no_recursion=
prefix=NONE
program_prefix=NONE
program_suffix=NONE
program_transform_name=s,x,x,
silent=
site=
srcdir=
verbose=
x_includes=NONE
x_libraries=NONE
# Installation directory options.
# These are left unexpanded so users can "make install exec_prefix=/foo"
# and all the variables that are supposed to be based on exec_prefix
# by default will actually change.
# Use braces instead of parens because sh, perl, etc. also accept them.
# (The list follows the same order as the GNU Coding Standards.)
bindir='${exec_prefix}/bin'
sbindir='${exec_prefix}/sbin'
libexecdir='${exec_prefix}/libexec'
datarootdir='${prefix}/share'
datadir='${datarootdir}'
sysconfdir='${prefix}/etc'
sharedstatedir='${prefix}/com'
localstatedir='${prefix}/var'
includedir='${prefix}/include'
oldincludedir='/usr/include'
docdir='${datarootdir}/doc/${PACKAGE_TARNAME}'
infodir='${datarootdir}/info'
htmldir='${docdir}'
dvidir='${docdir}'
pdfdir='${docdir}'
psdir='${docdir}'
libdir='${exec_prefix}/lib'
localedir='${datarootdir}/locale'
mandir='${datarootdir}/man'
ac_prev=
ac_dashdash=
for ac_option
do
# If the previous option needs an argument, assign it.
if test -n "$ac_prev"; then
eval $ac_prev=\$ac_option
ac_prev=
continue
fi
case $ac_option in
*=?*) ac_optarg=`expr "X$ac_option" : '[^=]*=\(.*\)'` ;;
*=) ac_optarg= ;;
*) ac_optarg=yes ;;
esac
# Accept the important Cygnus configure options, so we can diagnose typos.
case $ac_dashdash$ac_option in
--)
ac_dashdash=yes ;;
-bindir | --bindir | --bindi | --bind | --bin | --bi)
ac_prev=bindir ;;
-bindir=* | --bindir=* | --bindi=* | --bind=* | --bin=* | --bi=*)
bindir=$ac_optarg ;;
-build | --build | --buil | --bui | --bu)
ac_prev=build_alias ;;
-build=* | --build=* | --buil=* | --bui=* | --bu=*)
build_alias=$ac_optarg ;;
-cache-file | --cache-file | --cache-fil | --cache-fi \
| --cache-f | --cache- | --cache | --cach | --cac | --ca | --c)
ac_prev=cache_file ;;
-cache-file=* | --cache-file=* | --cache-fil=* | --cache-fi=* \
| --cache-f=* | --cache-=* | --cache=* | --cach=* | --cac=* | --ca=* | --c=*)
cache_file=$ac_optarg ;;
--config-cache | -C)
cache_file=config.cache ;;
-datadir | --datadir | --datadi | --datad)
ac_prev=datadir ;;
-datadir=* | --datadir=* | --datadi=* | --datad=*)
datadir=$ac_optarg ;;
-datarootdir | --datarootdir | --datarootdi | --datarootd | --dataroot \
| --dataroo | --dataro | --datar)
ac_prev=datarootdir ;;
-datarootdir=* | --datarootdir=* | --datarootdi=* | --datarootd=* \
| --dataroot=* | --dataroo=* | --dataro=* | --datar=*)
datarootdir=$ac_optarg ;;
-disable-* | --disable-*)
ac_useropt=`expr "x$ac_option" : 'x-*disable-\(.*\)'`
# Reject names that are not valid shell variable names.
expr "x$ac_useropt" : ".*[^-+._$as_cr_alnum]" >/dev/null &&
as_fn_error $? "invalid feature name: $ac_useropt"
ac_useropt_orig=$ac_useropt
ac_useropt=`$as_echo "$ac_useropt" | sed 's/[-+.]/_/g'`
case $ac_user_opts in
*"
"enable_$ac_useropt"
"*) ;;
*) ac_unrecognized_opts="$ac_unrecognized_opts$ac_unrecognized_sep--disable-$ac_useropt_orig"
ac_unrecognized_sep=', ';;
esac
eval enable_$ac_useropt=no ;;
-docdir | --docdir | --docdi | --doc | --do)
ac_prev=docdir ;;
-docdir=* | --docdir=* | --docdi=* | --doc=* | --do=*)
docdir=$ac_optarg ;;
-dvidir | --dvidir | --dvidi | --dvid | --dvi | --dv)
ac_prev=dvidir ;;
-dvidir=* | --dvidir=* | --dvidi=* | --dvid=* | --dvi=* | --dv=*)
dvidir=$ac_optarg ;;
-enable-* | --enable-*)
ac_useropt=`expr "x$ac_option" : 'x-*enable-\([^=]*\)'`
# Reject names that are not valid shell variable names.
expr "x$ac_useropt" : ".*[^-+._$as_cr_alnum]" >/dev/null &&
as_fn_error $? "invalid feature name: $ac_useropt"
ac_useropt_orig=$ac_useropt
ac_useropt=`$as_echo "$ac_useropt" | sed 's/[-+.]/_/g'`
case $ac_user_opts in
*"
"enable_$ac_useropt"
"*) ;;
*) ac_unrecognized_opts="$ac_unrecognized_opts$ac_unrecognized_sep--enable-$ac_useropt_orig"
ac_unrecognized_sep=', ';;
esac
eval enable_$ac_useropt=\$ac_optarg ;;
-exec-prefix | --exec_prefix | --exec-prefix | --exec-prefi \
| --exec-pref | --exec-pre | --exec-pr | --exec-p | --exec- \
| --exec | --exe | --ex)
ac_prev=exec_prefix ;;
-exec-prefix=* | --exec_prefix=* | --exec-prefix=* | --exec-prefi=* \
| --exec-pref=* | --exec-pre=* | --exec-pr=* | --exec-p=* | --exec-=* \
| --exec=* | --exe=* | --ex=*)
exec_prefix=$ac_optarg ;;
-gas | --gas | --ga | --g)
# Obsolete; use --with-gas.
with_gas=yes ;;
-help | --help | --hel | --he | -h)
ac_init_help=long ;;
-help=r* | --help=r* | --hel=r* | --he=r* | -hr*)
ac_init_help=recursive ;;
-help=s* | --help=s* | --hel=s* | --he=s* | -hs*)
ac_init_help=short ;;
-host | --host | --hos | --ho)
ac_prev=host_alias ;;
-host=* | --host=* | --hos=* | --ho=*)
host_alias=$ac_optarg ;;
-htmldir | --htmldir | --htmldi | --htmld | --html | --htm | --ht)
ac_prev=htmldir ;;
-htmldir=* | --htmldir=* | --htmldi=* | --htmld=* | --html=* | --htm=* \
| --ht=*)
htmldir=$ac_optarg ;;
-includedir | --includedir | --includedi | --included | --include \
| --includ | --inclu | --incl | --inc)
ac_prev=includedir ;;
-includedir=* | --includedir=* | --includedi=* | --included=* | --include=* \
| --includ=* | --inclu=* | --incl=* | --inc=*)
includedir=$ac_optarg ;;
-infodir | --infodir | --infodi | --infod | --info | --inf)
ac_prev=infodir ;;
-infodir=* | --infodir=* | --infodi=* | --infod=* | --info=* | --inf=*)
infodir=$ac_optarg ;;
-libdir | --libdir | --libdi | --libd)
ac_prev=libdir ;;
-libdir=* | --libdir=* | --libdi=* | --libd=*)
libdir=$ac_optarg ;;
-libexecdir | --libexecdir | --libexecdi | --libexecd | --libexec \
| --libexe | --libex | --libe)
ac_prev=libexecdir ;;
-libexecdir=* | --libexecdir=* | --libexecdi=* | --libexecd=* | --libexec=* \
| --libexe=* | --libex=* | --libe=*)
libexecdir=$ac_optarg ;;
-localedir | --localedir | --localedi | --localed | --locale)
ac_prev=localedir ;;
-localedir=* | --localedir=* | --localedi=* | --localed=* | --locale=*)
localedir=$ac_optarg ;;
-localstatedir | --localstatedir | --localstatedi | --localstated \
| --localstate | --localstat | --localsta | --localst | --locals)
ac_prev=localstatedir ;;
-localstatedir=* | --localstatedir=* | --localstatedi=* | --localstated=* \
| --localstate=* | --localstat=* | --localsta=* | --localst=* | --locals=*)
localstatedir=$ac_optarg ;;
-mandir | --mandir | --mandi | --mand | --man | --ma | --m)
ac_prev=mandir ;;
-mandir=* | --mandir=* | --mandi=* | --mand=* | --man=* | --ma=* | --m=*)
mandir=$ac_optarg ;;
-nfp | --nfp | --nf)
# Obsolete; use --without-fp.
with_fp=no ;;
-no-create | --no-create | --no-creat | --no-crea | --no-cre \
| --no-cr | --no-c | -n)
no_create=yes ;;
-no-recursion | --no-recursion | --no-recursio | --no-recursi \
| --no-recurs | --no-recur | --no-recu | --no-rec | --no-re | --no-r)
no_recursion=yes ;;
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\`configure' configures PHYLIPNEW 3.69.650 to adapt to many kinds of systems.
Usage: $0 [OPTION]... [VAR=VALUE]...
To assign environment variables (e.g., CC, CFLAGS...), specify them as
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LIBS libraries to pass to the linker, e.g. -l
CPPFLAGS (Objective) C/C++ preprocessor flags, e.g. -I if
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XMKMF Path to xmkmf, Makefile generator for X Window System
ANT Path to the Apache Ant make tool
JAR Path to the Java archive tool
JAVA Path to the Java application launcher
JAVAC Path to the Java compiler
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Report bugs to .
PHYLIPNEW home page: .
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PHYLIPNEW configure 3.69.650
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Copyright (C) 2012 Free Software Foundation, Inc.
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sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=1
fi
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
as_fn_set_status $ac_retval
} # ac_fn_cxx_try_compile
# ac_fn_c_try_cpp LINENO
# ----------------------
# Try to preprocess conftest.$ac_ext, and return whether this succeeded.
ac_fn_c_try_cpp ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
if { { ac_try="$ac_cpp conftest.$ac_ext"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_cpp conftest.$ac_ext") 2>conftest.err
ac_status=$?
if test -s conftest.err; then
grep -v '^ *+' conftest.err >conftest.er1
cat conftest.er1 >&5
mv -f conftest.er1 conftest.err
fi
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } > conftest.i && {
test -z "$ac_c_preproc_warn_flag$ac_c_werror_flag" ||
test ! -s conftest.err
}; then :
ac_retval=0
else
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=1
fi
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
as_fn_set_status $ac_retval
} # ac_fn_c_try_cpp
# ac_fn_c_try_link LINENO
# -----------------------
# Try to link conftest.$ac_ext, and return whether this succeeded.
ac_fn_c_try_link ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
rm -f conftest.$ac_objext conftest$ac_exeext
if { { ac_try="$ac_link"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_link") 2>conftest.err
ac_status=$?
if test -s conftest.err; then
grep -v '^ *+' conftest.err >conftest.er1
cat conftest.er1 >&5
mv -f conftest.er1 conftest.err
fi
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && {
test -z "$ac_c_werror_flag" ||
test ! -s conftest.err
} && test -s conftest$ac_exeext && {
test "$cross_compiling" = yes ||
test -x conftest$ac_exeext
}; then :
ac_retval=0
else
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=1
fi
# Delete the IPA/IPO (Inter Procedural Analysis/Optimization) information
# created by the PGI compiler (conftest_ipa8_conftest.oo), as it would
# interfere with the next link command; also delete a directory that is
# left behind by Apple's compiler. We do this before executing the actions.
rm -rf conftest.dSYM conftest_ipa8_conftest.oo
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
as_fn_set_status $ac_retval
} # ac_fn_c_try_link
# ac_fn_c_check_header_compile LINENO HEADER VAR INCLUDES
# -------------------------------------------------------
# Tests whether HEADER exists and can be compiled using the include files in
# INCLUDES, setting the cache variable VAR accordingly.
ac_fn_c_check_header_compile ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if eval \${$3+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
$4
#include <$2>
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
eval "$3=yes"
else
eval "$3=no"
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
} # ac_fn_c_check_header_compile
# ac_fn_c_try_run LINENO
# ----------------------
# Try to link conftest.$ac_ext, and return whether this succeeded. Assumes
# that executables *can* be run.
ac_fn_c_try_run ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
if { { ac_try="$ac_link"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_link") 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && { ac_try='./conftest$ac_exeext'
{ { case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_try") 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }; }; then :
ac_retval=0
else
$as_echo "$as_me: program exited with status $ac_status" >&5
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=$ac_status
fi
rm -rf conftest.dSYM conftest_ipa8_conftest.oo
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
as_fn_set_status $ac_retval
} # ac_fn_c_try_run
# ac_fn_c_check_func LINENO FUNC VAR
# ----------------------------------
# Tests whether FUNC exists, setting the cache variable VAR accordingly
ac_fn_c_check_func ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if eval \${$3+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
/* Define $2 to an innocuous variant, in case declares $2.
For example, HP-UX 11i declares gettimeofday. */
#define $2 innocuous_$2
/* System header to define __stub macros and hopefully few prototypes,
which can conflict with char $2 (); below.
Prefer to if __STDC__ is defined, since
exists even on freestanding compilers. */
#ifdef __STDC__
# include
#else
# include
#endif
#undef $2
/* Override any GCC internal prototype to avoid an error.
Use char because int might match the return type of a GCC
builtin and then its argument prototype would still apply. */
#ifdef __cplusplus
extern "C"
#endif
char $2 ();
/* The GNU C library defines this for functions which it implements
to always fail with ENOSYS. Some functions are actually named
something starting with __ and the normal name is an alias. */
#if defined __stub_$2 || defined __stub___$2
choke me
#endif
int
main ()
{
return $2 ();
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
eval "$3=yes"
else
eval "$3=no"
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
} # ac_fn_c_check_func
# ac_fn_cxx_try_cpp LINENO
# ------------------------
# Try to preprocess conftest.$ac_ext, and return whether this succeeded.
ac_fn_cxx_try_cpp ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
if { { ac_try="$ac_cpp conftest.$ac_ext"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_cpp conftest.$ac_ext") 2>conftest.err
ac_status=$?
if test -s conftest.err; then
grep -v '^ *+' conftest.err >conftest.er1
cat conftest.er1 >&5
mv -f conftest.er1 conftest.err
fi
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } > conftest.i && {
test -z "$ac_cxx_preproc_warn_flag$ac_cxx_werror_flag" ||
test ! -s conftest.err
}; then :
ac_retval=0
else
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=1
fi
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
as_fn_set_status $ac_retval
} # ac_fn_cxx_try_cpp
# ac_fn_cxx_try_link LINENO
# -------------------------
# Try to link conftest.$ac_ext, and return whether this succeeded.
ac_fn_cxx_try_link ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
rm -f conftest.$ac_objext conftest$ac_exeext
if { { ac_try="$ac_link"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_link") 2>conftest.err
ac_status=$?
if test -s conftest.err; then
grep -v '^ *+' conftest.err >conftest.er1
cat conftest.er1 >&5
mv -f conftest.er1 conftest.err
fi
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && {
test -z "$ac_cxx_werror_flag" ||
test ! -s conftest.err
} && test -s conftest$ac_exeext && {
test "$cross_compiling" = yes ||
test -x conftest$ac_exeext
}; then :
ac_retval=0
else
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
ac_retval=1
fi
# Delete the IPA/IPO (Inter Procedural Analysis/Optimization) information
# created by the PGI compiler (conftest_ipa8_conftest.oo), as it would
# interfere with the next link command; also delete a directory that is
# left behind by Apple's compiler. We do this before executing the actions.
rm -rf conftest.dSYM conftest_ipa8_conftest.oo
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
as_fn_set_status $ac_retval
} # ac_fn_cxx_try_link
# ac_fn_c_check_header_mongrel LINENO HEADER VAR INCLUDES
# -------------------------------------------------------
# Tests whether HEADER exists, giving a warning if it cannot be compiled using
# the include files in INCLUDES and setting the cache variable VAR
# accordingly.
ac_fn_c_check_header_mongrel ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
if eval \${$3+:} false; then :
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if eval \${$3+:} false; then :
$as_echo_n "(cached) " >&6
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
else
# Is the header compilable?
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking $2 usability" >&5
$as_echo_n "checking $2 usability... " >&6; }
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
$4
#include <$2>
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
ac_header_compiler=yes
else
ac_header_compiler=no
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_header_compiler" >&5
$as_echo "$ac_header_compiler" >&6; }
# Is the header present?
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking $2 presence" >&5
$as_echo_n "checking $2 presence... " >&6; }
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include <$2>
_ACEOF
if ac_fn_c_try_cpp "$LINENO"; then :
ac_header_preproc=yes
else
ac_header_preproc=no
fi
rm -f conftest.err conftest.i conftest.$ac_ext
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_header_preproc" >&5
$as_echo "$ac_header_preproc" >&6; }
# So? What about this header?
case $ac_header_compiler:$ac_header_preproc:$ac_c_preproc_warn_flag in #((
yes:no: )
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: accepted by the compiler, rejected by the preprocessor!" >&5
$as_echo "$as_me: WARNING: $2: accepted by the compiler, rejected by the preprocessor!" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: proceeding with the compiler's result" >&5
$as_echo "$as_me: WARNING: $2: proceeding with the compiler's result" >&2;}
;;
no:yes:* )
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: present but cannot be compiled" >&5
$as_echo "$as_me: WARNING: $2: present but cannot be compiled" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: check for missing prerequisite headers?" >&5
$as_echo "$as_me: WARNING: $2: check for missing prerequisite headers?" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: see the Autoconf documentation" >&5
$as_echo "$as_me: WARNING: $2: see the Autoconf documentation" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: section \"Present But Cannot Be Compiled\"" >&5
$as_echo "$as_me: WARNING: $2: section \"Present But Cannot Be Compiled\"" >&2;}
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: $2: proceeding with the compiler's result" >&5
$as_echo "$as_me: WARNING: $2: proceeding with the compiler's result" >&2;}
( $as_echo "## --------------------------------------------- ##
## Report this to emboss-bug@emboss.open-bio.org ##
## --------------------------------------------- ##"
) | sed "s/^/$as_me: WARNING: /" >&2
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if eval \${$3+:} false; then :
$as_echo_n "(cached) " >&6
else
eval "$3=\$ac_header_compiler"
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
fi
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
} # ac_fn_c_check_header_mongrel
# ac_fn_c_check_type LINENO TYPE VAR INCLUDES
# -------------------------------------------
# Tests whether TYPE exists after having included INCLUDES, setting cache
# variable VAR accordingly.
ac_fn_c_check_type ()
{
as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $2" >&5
$as_echo_n "checking for $2... " >&6; }
if eval \${$3+:} false; then :
$as_echo_n "(cached) " >&6
else
eval "$3=no"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
$4
int
main ()
{
if (sizeof ($2))
return 0;
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
$4
int
main ()
{
if (sizeof (($2)))
return 0;
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
else
eval "$3=yes"
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
eval ac_res=\$$3
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_res" >&5
$as_echo "$ac_res" >&6; }
eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno
} # ac_fn_c_check_type
cat >config.log <<_ACEOF
This file contains any messages produced by compilers while
running configure, to aid debugging if configure makes a mistake.
It was created by PHYLIPNEW $as_me 3.69.650, which was
generated by GNU Autoconf 2.69. Invocation command line was
$ $0 $@
_ACEOF
exec 5>>config.log
{
cat <<_ASUNAME
## --------- ##
## Platform. ##
## --------- ##
hostname = `(hostname || uname -n) 2>/dev/null | sed 1q`
uname -m = `(uname -m) 2>/dev/null || echo unknown`
uname -r = `(uname -r) 2>/dev/null || echo unknown`
uname -s = `(uname -s) 2>/dev/null || echo unknown`
uname -v = `(uname -v) 2>/dev/null || echo unknown`
/usr/bin/uname -p = `(/usr/bin/uname -p) 2>/dev/null || echo unknown`
/bin/uname -X = `(/bin/uname -X) 2>/dev/null || echo unknown`
/bin/arch = `(/bin/arch) 2>/dev/null || echo unknown`
/usr/bin/arch -k = `(/usr/bin/arch -k) 2>/dev/null || echo unknown`
/usr/convex/getsysinfo = `(/usr/convex/getsysinfo) 2>/dev/null || echo unknown`
/usr/bin/hostinfo = `(/usr/bin/hostinfo) 2>/dev/null || echo unknown`
/bin/machine = `(/bin/machine) 2>/dev/null || echo unknown`
/usr/bin/oslevel = `(/usr/bin/oslevel) 2>/dev/null || echo unknown`
/bin/universe = `(/bin/universe) 2>/dev/null || echo unknown`
_ASUNAME
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
$as_echo "PATH: $as_dir"
done
IFS=$as_save_IFS
} >&5
cat >&5 <<_ACEOF
## ----------- ##
## Core tests. ##
## ----------- ##
_ACEOF
# Keep a trace of the command line.
# Strip out --no-create and --no-recursion so they do not pile up.
# Strip out --silent because we don't want to record it for future runs.
# Also quote any args containing shell meta-characters.
# Make two passes to allow for proper duplicate-argument suppression.
ac_configure_args=
ac_configure_args0=
ac_configure_args1=
ac_must_keep_next=false
for ac_pass in 1 2
do
for ac_arg
do
case $ac_arg in
-no-create | --no-c* | -n | -no-recursion | --no-r*) continue ;;
-q | -quiet | --quiet | --quie | --qui | --qu | --q \
| -silent | --silent | --silen | --sile | --sil)
continue ;;
*\'*)
ac_arg=`$as_echo "$ac_arg" | sed "s/'/'\\\\\\\\''/g"` ;;
esac
case $ac_pass in
1) as_fn_append ac_configure_args0 " '$ac_arg'" ;;
2)
as_fn_append ac_configure_args1 " '$ac_arg'"
if test $ac_must_keep_next = true; then
ac_must_keep_next=false # Got value, back to normal.
else
case $ac_arg in
*=* | --config-cache | -C | -disable-* | --disable-* \
| -enable-* | --enable-* | -gas | --g* | -nfp | --nf* \
| -q | -quiet | --q* | -silent | --sil* | -v | -verb* \
| -with-* | --with-* | -without-* | --without-* | --x)
case "$ac_configure_args0 " in
"$ac_configure_args1"*" '$ac_arg' "* ) continue ;;
esac
;;
-* ) ac_must_keep_next=true ;;
esac
fi
as_fn_append ac_configure_args " '$ac_arg'"
;;
esac
done
done
{ ac_configure_args0=; unset ac_configure_args0;}
{ ac_configure_args1=; unset ac_configure_args1;}
# When interrupted or exit'd, cleanup temporary files, and complete
# config.log. We remove comments because anyway the quotes in there
# would cause problems or look ugly.
# WARNING: Use '\'' to represent an apostrophe within the trap.
# WARNING: Do not start the trap code with a newline, due to a FreeBSD 4.0 bug.
trap 'exit_status=$?
# Save into config.log some information that might help in debugging.
{
echo
$as_echo "## ---------------- ##
## Cache variables. ##
## ---------------- ##"
echo
# The following way of writing the cache mishandles newlines in values,
(
for ac_var in `(set) 2>&1 | sed -n '\''s/^\([a-zA-Z_][a-zA-Z0-9_]*\)=.*/\1/p'\''`; do
eval ac_val=\$$ac_var
case $ac_val in #(
*${as_nl}*)
case $ac_var in #(
*_cv_*) { $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: cache variable $ac_var contains a newline" >&5
$as_echo "$as_me: WARNING: cache variable $ac_var contains a newline" >&2;} ;;
esac
case $ac_var in #(
_ | IFS | as_nl) ;; #(
BASH_ARGV | BASH_SOURCE) eval $ac_var= ;; #(
*) { eval $ac_var=; unset $ac_var;} ;;
esac ;;
esac
done
(set) 2>&1 |
case $as_nl`(ac_space='\'' '\''; set) 2>&1` in #(
*${as_nl}ac_space=\ *)
sed -n \
"s/'\''/'\''\\\\'\'''\''/g;
s/^\\([_$as_cr_alnum]*_cv_[_$as_cr_alnum]*\\)=\\(.*\\)/\\1='\''\\2'\''/p"
;; #(
*)
sed -n "/^[_$as_cr_alnum]*_cv_[_$as_cr_alnum]*=/p"
;;
esac |
sort
)
echo
$as_echo "## ----------------- ##
## Output variables. ##
## ----------------- ##"
echo
for ac_var in $ac_subst_vars
do
eval ac_val=\$$ac_var
case $ac_val in
*\'\''*) ac_val=`$as_echo "$ac_val" | sed "s/'\''/'\''\\\\\\\\'\'''\''/g"`;;
esac
$as_echo "$ac_var='\''$ac_val'\''"
done | sort
echo
if test -n "$ac_subst_files"; then
$as_echo "## ------------------- ##
## File substitutions. ##
## ------------------- ##"
echo
for ac_var in $ac_subst_files
do
eval ac_val=\$$ac_var
case $ac_val in
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echo
fi
if test -s confdefs.h; then
$as_echo "## ----------- ##
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cat confdefs.h
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for ac_signal in 1 2 13 15; do
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ac_signal=0
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# Predefined preprocessor variables.
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#define PACKAGE_NAME "$PACKAGE_NAME"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_TARNAME "$PACKAGE_TARNAME"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_VERSION "$PACKAGE_VERSION"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_STRING "$PACKAGE_STRING"
_ACEOF
cat >>confdefs.h <<_ACEOF
#define PACKAGE_BUGREPORT "$PACKAGE_BUGREPORT"
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#define PACKAGE_URL "$PACKAGE_URL"
_ACEOF
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{ $as_echo "$as_me:${as_lineno-$LINENO}: loading site script $ac_site_file" >&5
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ac_cache_corrupted=: ;;
,set)
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eval $ac_var=\$ac_old_val
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{ $as_echo "$as_me:${as_lineno-$LINENO}: former value: \`$ac_old_val'" >&5
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## -------------------- ##
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ac_cpp='$CPP $CPPFLAGS'
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ac_cpp='$CPP $CPPFLAGS'
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ac_ct_CC=$ac_cv_prog_ac_ct_CC
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yes:)
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# Provide some information about the compiler.
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set X $ac_compile
ac_compiler=$2
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fi
rm -f conftest.er1 conftest.err
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cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
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{
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ac_clean_files_save=$ac_clean_files
ac_clean_files="$ac_clean_files a.out a.out.dSYM a.exe b.out"
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# of exeext.
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether the C compiler works" >&5
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ac_rmfiles=
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do
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rm -f $ac_rmfiles
if { { ac_try="$ac_link_default"
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[ab].out )
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ac_file=''
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{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_exeext" >&5
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cat confdefs.h - <<_ACEOF >conftest.$ac_ext
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{
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;
return 0;
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{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $cross_compiling" >&5
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cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
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rm -f conftest.o conftest.obj
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test -f "$ac_file" || continue;
case $ac_file in
*.$ac_ext | *.xcoff | *.tds | *.d | *.pdb | *.xSYM | *.bb | *.bbg | *.map | *.inf | *.dSYM ) ;;
*) ac_cv_objext=`expr "$ac_file" : '.*\.\(.*\)'`
break;;
esac
done
else
$as_echo "$as_me: failed program was:" >&5
sed 's/^/| /' conftest.$ac_ext >&5
{ { $as_echo "$as_me:${as_lineno-$LINENO}: error: in \`$ac_pwd':" >&5
$as_echo "$as_me: error: in \`$ac_pwd':" >&2;}
as_fn_error $? "cannot compute suffix of object files: cannot compile
See \`config.log' for more details" "$LINENO" 5; }
fi
rm -f conftest.$ac_cv_objext conftest.$ac_ext
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_objext" >&5
$as_echo "$ac_cv_objext" >&6; }
OBJEXT=$ac_cv_objext
ac_objext=$OBJEXT
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether we are using the GNU C compiler" >&5
$as_echo_n "checking whether we are using the GNU C compiler... " >&6; }
if ${ac_cv_c_compiler_gnu+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
#ifndef __GNUC__
choke me
#endif
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
ac_compiler_gnu=yes
else
ac_compiler_gnu=no
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
ac_cv_c_compiler_gnu=$ac_compiler_gnu
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_c_compiler_gnu" >&5
$as_echo "$ac_cv_c_compiler_gnu" >&6; }
if test $ac_compiler_gnu = yes; then
GCC=yes
else
GCC=
fi
ac_test_CFLAGS=${CFLAGS+set}
ac_save_CFLAGS=$CFLAGS
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether $CC accepts -g" >&5
$as_echo_n "checking whether $CC accepts -g... " >&6; }
if ${ac_cv_prog_cc_g+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_save_c_werror_flag=$ac_c_werror_flag
ac_c_werror_flag=yes
ac_cv_prog_cc_g=no
CFLAGS="-g"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
ac_cv_prog_cc_g=yes
else
CFLAGS=""
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
else
ac_c_werror_flag=$ac_save_c_werror_flag
CFLAGS="-g"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
ac_cv_prog_cc_g=yes
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
ac_c_werror_flag=$ac_save_c_werror_flag
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cc_g" >&5
$as_echo "$ac_cv_prog_cc_g" >&6; }
if test "$ac_test_CFLAGS" = set; then
CFLAGS=$ac_save_CFLAGS
elif test $ac_cv_prog_cc_g = yes; then
if test "$GCC" = yes; then
CFLAGS="-g -O2"
else
CFLAGS="-g"
fi
else
if test "$GCC" = yes; then
CFLAGS="-O2"
else
CFLAGS=
fi
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $CC option to accept ISO C89" >&5
$as_echo_n "checking for $CC option to accept ISO C89... " >&6; }
if ${ac_cv_prog_cc_c89+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_cv_prog_cc_c89=no
ac_save_CC=$CC
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
#include
struct stat;
/* Most of the following tests are stolen from RCS 5.7's src/conf.sh. */
struct buf { int x; };
FILE * (*rcsopen) (struct buf *, struct stat *, int);
static char *e (p, i)
char **p;
int i;
{
return p[i];
}
static char *f (char * (*g) (char **, int), char **p, ...)
{
char *s;
va_list v;
va_start (v,p);
s = g (p, va_arg (v,int));
va_end (v);
return s;
}
/* OSF 4.0 Compaq cc is some sort of almost-ANSI by default. It has
function prototypes and stuff, but not '\xHH' hex character constants.
These don't provoke an error unfortunately, instead are silently treated
as 'x'. The following induces an error, until -std is added to get
proper ANSI mode. Curiously '\x00'!='x' always comes out true, for an
array size at least. It's necessary to write '\x00'==0 to get something
that's true only with -std. */
int osf4_cc_array ['\x00' == 0 ? 1 : -1];
/* IBM C 6 for AIX is almost-ANSI by default, but it replaces macro parameters
inside strings and character constants. */
#define FOO(x) 'x'
int xlc6_cc_array[FOO(a) == 'x' ? 1 : -1];
int test (int i, double x);
struct s1 {int (*f) (int a);};
struct s2 {int (*f) (double a);};
int pairnames (int, char **, FILE *(*)(struct buf *, struct stat *, int), int, int);
int argc;
char **argv;
int
main ()
{
return f (e, argv, 0) != argv[0] || f (e, argv, 1) != argv[1];
;
return 0;
}
_ACEOF
for ac_arg in '' -qlanglvl=extc89 -qlanglvl=ansi -std \
-Ae "-Aa -D_HPUX_SOURCE" "-Xc -D__EXTENSIONS__"
do
CC="$ac_save_CC $ac_arg"
if ac_fn_c_try_compile "$LINENO"; then :
ac_cv_prog_cc_c89=$ac_arg
fi
rm -f core conftest.err conftest.$ac_objext
test "x$ac_cv_prog_cc_c89" != "xno" && break
done
rm -f conftest.$ac_ext
CC=$ac_save_CC
fi
# AC_CACHE_VAL
case "x$ac_cv_prog_cc_c89" in
x)
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: none needed" >&5
$as_echo "none needed" >&6; } ;;
xno)
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: unsupported" >&5
$as_echo "unsupported" >&6; } ;;
*)
CC="$CC $ac_cv_prog_cc_c89"
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cc_c89" >&5
$as_echo "$ac_cv_prog_cc_c89" >&6; } ;;
esac
if test "x$ac_cv_prog_cc_c89" != xno; then :
fi
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
ac_ext=cpp
ac_cpp='$CXXCPP $CPPFLAGS'
ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_cxx_compiler_gnu
if test -z "$CXX"; then
if test -n "$CCC"; then
CXX=$CCC
else
if test -n "$ac_tool_prefix"; then
for ac_prog in icpc g++
do
# Extract the first word of "$ac_tool_prefix$ac_prog", so it can be a program name with args.
set dummy $ac_tool_prefix$ac_prog; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$CXX"; then
ac_cv_prog_CXX="$CXX" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_CXX="$ac_tool_prefix$ac_prog"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
CXX=$ac_cv_prog_CXX
if test -n "$CXX"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $CXX" >&5
$as_echo "$CXX" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
test -n "$CXX" && break
done
fi
if test -z "$CXX"; then
ac_ct_CXX=$CXX
for ac_prog in icpc g++
do
# Extract the first word of "$ac_prog", so it can be a program name with args.
set dummy $ac_prog; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_CXX"; then
ac_cv_prog_ac_ct_CXX="$ac_ct_CXX" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_CXX="$ac_prog"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_CXX=$ac_cv_prog_ac_ct_CXX
if test -n "$ac_ct_CXX"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_CXX" >&5
$as_echo "$ac_ct_CXX" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
test -n "$ac_ct_CXX" && break
done
if test "x$ac_ct_CXX" = x; then
CXX="g++"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
CXX=$ac_ct_CXX
fi
fi
fi
fi
# Provide some information about the compiler.
$as_echo "$as_me:${as_lineno-$LINENO}: checking for C++ compiler version" >&5
set X $ac_compile
ac_compiler=$2
for ac_option in --version -v -V -qversion; do
{ { ac_try="$ac_compiler $ac_option >&5"
case "(($ac_try" in
*\"* | *\`* | *\\*) ac_try_echo=\$ac_try;;
*) ac_try_echo=$ac_try;;
esac
eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\""
$as_echo "$ac_try_echo"; } >&5
(eval "$ac_compiler $ac_option >&5") 2>conftest.err
ac_status=$?
if test -s conftest.err; then
sed '10a\
... rest of stderr output deleted ...
10q' conftest.err >conftest.er1
cat conftest.er1 >&5
fi
rm -f conftest.er1 conftest.err
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }
done
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether we are using the GNU C++ compiler" >&5
$as_echo_n "checking whether we are using the GNU C++ compiler... " >&6; }
if ${ac_cv_cxx_compiler_gnu+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
#ifndef __GNUC__
choke me
#endif
;
return 0;
}
_ACEOF
if ac_fn_cxx_try_compile "$LINENO"; then :
ac_compiler_gnu=yes
else
ac_compiler_gnu=no
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
ac_cv_cxx_compiler_gnu=$ac_compiler_gnu
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_cxx_compiler_gnu" >&5
$as_echo "$ac_cv_cxx_compiler_gnu" >&6; }
if test $ac_compiler_gnu = yes; then
GXX=yes
else
GXX=
fi
ac_test_CXXFLAGS=${CXXFLAGS+set}
ac_save_CXXFLAGS=$CXXFLAGS
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether $CXX accepts -g" >&5
$as_echo_n "checking whether $CXX accepts -g... " >&6; }
if ${ac_cv_prog_cxx_g+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_save_cxx_werror_flag=$ac_cxx_werror_flag
ac_cxx_werror_flag=yes
ac_cv_prog_cxx_g=no
CXXFLAGS="-g"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_cxx_try_compile "$LINENO"; then :
ac_cv_prog_cxx_g=yes
else
CXXFLAGS=""
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_cxx_try_compile "$LINENO"; then :
else
ac_cxx_werror_flag=$ac_save_cxx_werror_flag
CXXFLAGS="-g"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_cxx_try_compile "$LINENO"; then :
ac_cv_prog_cxx_g=yes
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
ac_cxx_werror_flag=$ac_save_cxx_werror_flag
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cxx_g" >&5
$as_echo "$ac_cv_prog_cxx_g" >&6; }
if test "$ac_test_CXXFLAGS" = set; then
CXXFLAGS=$ac_save_CXXFLAGS
elif test $ac_cv_prog_cxx_g = yes; then
if test "$GXX" = yes; then
CXXFLAGS="-g -O2"
else
CXXFLAGS="-g"
fi
else
if test "$GXX" = yes; then
CXXFLAGS="-O2"
else
CXXFLAGS=
fi
fi
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking how to run the C preprocessor" >&5
$as_echo_n "checking how to run the C preprocessor... " >&6; }
# On Suns, sometimes $CPP names a directory.
if test -n "$CPP" && test -d "$CPP"; then
CPP=
fi
if test -z "$CPP"; then
if ${ac_cv_prog_CPP+:} false; then :
$as_echo_n "(cached) " >&6
else
# Double quotes because CPP needs to be expanded
for CPP in "$CC -E" "$CC -E -traditional-cpp" "/lib/cpp"
do
ac_preproc_ok=false
for ac_c_preproc_warn_flag in '' yes
do
# Use a header file that comes with gcc, so configuring glibc
# with a fresh cross-compiler works.
# Prefer to if __STDC__ is defined, since
# exists even on freestanding compilers.
# On the NeXT, cc -E runs the code through the compiler's parser,
# not just through cpp. "Syntax error" is here to catch this case.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#ifdef __STDC__
# include
#else
# include
#endif
Syntax error
_ACEOF
if ac_fn_c_try_cpp "$LINENO"; then :
else
# Broken: fails on valid input.
continue
fi
rm -f conftest.err conftest.i conftest.$ac_ext
# OK, works on sane cases. Now check whether nonexistent headers
# can be detected and how.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
_ACEOF
if ac_fn_c_try_cpp "$LINENO"; then :
# Broken: success on invalid input.
continue
else
# Passes both tests.
ac_preproc_ok=:
break
fi
rm -f conftest.err conftest.i conftest.$ac_ext
done
# Because of `break', _AC_PREPROC_IFELSE's cleaning code was skipped.
rm -f conftest.i conftest.err conftest.$ac_ext
if $ac_preproc_ok; then :
break
fi
done
ac_cv_prog_CPP=$CPP
fi
CPP=$ac_cv_prog_CPP
else
ac_cv_prog_CPP=$CPP
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $CPP" >&5
$as_echo "$CPP" >&6; }
ac_preproc_ok=false
for ac_c_preproc_warn_flag in '' yes
do
# Use a header file that comes with gcc, so configuring glibc
# with a fresh cross-compiler works.
# Prefer to if __STDC__ is defined, since
# exists even on freestanding compilers.
# On the NeXT, cc -E runs the code through the compiler's parser,
# not just through cpp. "Syntax error" is here to catch this case.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#ifdef __STDC__
# include
#else
# include
#endif
Syntax error
_ACEOF
if ac_fn_c_try_cpp "$LINENO"; then :
else
# Broken: fails on valid input.
continue
fi
rm -f conftest.err conftest.i conftest.$ac_ext
# OK, works on sane cases. Now check whether nonexistent headers
# can be detected and how.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
_ACEOF
if ac_fn_c_try_cpp "$LINENO"; then :
# Broken: success on invalid input.
continue
else
# Passes both tests.
ac_preproc_ok=:
break
fi
rm -f conftest.err conftest.i conftest.$ac_ext
done
# Because of `break', _AC_PREPROC_IFELSE's cleaning code was skipped.
rm -f conftest.i conftest.err conftest.$ac_ext
if $ac_preproc_ok; then :
else
{ { $as_echo "$as_me:${as_lineno-$LINENO}: error: in \`$ac_pwd':" >&5
$as_echo "$as_me: error: in \`$ac_pwd':" >&2;}
as_fn_error $? "C preprocessor \"$CPP\" fails sanity check
See \`config.log' for more details" "$LINENO" 5; }
fi
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
ac_aux_dir=
for ac_dir in "$srcdir" "$srcdir/.." "$srcdir/../.."; do
if test -f "$ac_dir/install-sh"; then
ac_aux_dir=$ac_dir
ac_install_sh="$ac_aux_dir/install-sh -c"
break
elif test -f "$ac_dir/install.sh"; then
ac_aux_dir=$ac_dir
ac_install_sh="$ac_aux_dir/install.sh -c"
break
elif test -f "$ac_dir/shtool"; then
ac_aux_dir=$ac_dir
ac_install_sh="$ac_aux_dir/shtool install -c"
break
fi
done
if test -z "$ac_aux_dir"; then
as_fn_error $? "cannot find install-sh, install.sh, or shtool in \"$srcdir\" \"$srcdir/..\" \"$srcdir/../..\"" "$LINENO" 5
fi
# These three variables are undocumented and unsupported,
# and are intended to be withdrawn in a future Autoconf release.
# They can cause serious problems if a builder's source tree is in a directory
# whose full name contains unusual characters.
ac_config_guess="$SHELL $ac_aux_dir/config.guess" # Please don't use this var.
ac_config_sub="$SHELL $ac_aux_dir/config.sub" # Please don't use this var.
ac_configure="$SHELL $ac_aux_dir/configure" # Please don't use this var.
# Find a good install program. We prefer a C program (faster),
# so one script is as good as another. But avoid the broken or
# incompatible versions:
# SysV /etc/install, /usr/sbin/install
# SunOS /usr/etc/install
# IRIX /sbin/install
# AIX /bin/install
# AmigaOS /C/install, which installs bootblocks on floppy discs
# AIX 4 /usr/bin/installbsd, which doesn't work without a -g flag
# AFS /usr/afsws/bin/install, which mishandles nonexistent args
# SVR4 /usr/ucb/install, which tries to use the nonexistent group "staff"
# OS/2's system install, which has a completely different semantic
# ./install, which can be erroneously created by make from ./install.sh.
# Reject install programs that cannot install multiple files.
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for a BSD-compatible install" >&5
$as_echo_n "checking for a BSD-compatible install... " >&6; }
if test -z "$INSTALL"; then
if ${ac_cv_path_install+:} false; then :
$as_echo_n "(cached) " >&6
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
# Account for people who put trailing slashes in PATH elements.
case $as_dir/ in #((
./ | .// | /[cC]/* | \
/etc/* | /usr/sbin/* | /usr/etc/* | /sbin/* | /usr/afsws/bin/* | \
?:[\\/]os2[\\/]install[\\/]* | ?:[\\/]OS2[\\/]INSTALL[\\/]* | \
/usr/ucb/* ) ;;
*)
# OSF1 and SCO ODT 3.0 have their own names for install.
# Don't use installbsd from OSF since it installs stuff as root
# by default.
for ac_prog in ginstall scoinst install; do
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_prog$ac_exec_ext"; then
if test $ac_prog = install &&
grep dspmsg "$as_dir/$ac_prog$ac_exec_ext" >/dev/null 2>&1; then
# AIX install. It has an incompatible calling convention.
:
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continue
else
break
fi
;;
msvc7 | msvc7msys | msvisualcpp | msvcmsys)
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# When given -MP, icc 7.0 and 7.1 complain thusly:
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# Use this function as a fallback that always works.
func_fallback_echo ()
{
eval 'cat <<_LTECHO_EOF
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ECHO='func_fallback_echo'
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$ac_path_SED_found && break 3
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cp "conftest.in" "conftest.nl"
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ac_cv_path_GREP=$GREP
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cp "conftest.in" "conftest.nl"
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esac
$ac_path_EGREP_found && break 3
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ac_cv_path_EGREP=$EGREP
fi
fi
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_path_EGREP" >&5
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ac_cv_path_FGREP="$ac_path_FGREP" ac_path_FGREP_found=:;;
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ac_count=0
$as_echo_n 0123456789 >"conftest.in"
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cp "conftest.in" "conftest.nl"
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# 10*(2^10) chars as input seems more than enough
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$ac_path_FGREP_found && break 3
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ac_cv_path_FGREP=$FGREP
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lt_cv_path_NM="$tmp_nm -B"
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*)
lt_cv_path_NM=${lt_cv_path_NM="$tmp_nm"} # keep the first match, but
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;;
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;;
esac
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fi
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_path_NM" >&5
$as_echo "$lt_cv_path_NM" >&6; }
if test "$lt_cv_path_NM" != "no"; then
NM="$lt_cv_path_NM"
else
# Didn't find any BSD compatible name lister, look for dumpbin.
if test -n "$DUMPBIN"; then :
# Let the user override the test.
else
if test -n "$ac_tool_prefix"; then
for ac_prog in dumpbin "link -dump"
do
# Extract the first word of "$ac_tool_prefix$ac_prog", so it can be a program name with args.
set dummy $ac_tool_prefix$ac_prog; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_DUMPBIN+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$DUMPBIN"; then
ac_cv_prog_DUMPBIN="$DUMPBIN" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_DUMPBIN="$ac_tool_prefix$ac_prog"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
DUMPBIN=$ac_cv_prog_DUMPBIN
if test -n "$DUMPBIN"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $DUMPBIN" >&5
$as_echo "$DUMPBIN" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
test -n "$DUMPBIN" && break
done
fi
if test -z "$DUMPBIN"; then
ac_ct_DUMPBIN=$DUMPBIN
for ac_prog in dumpbin "link -dump"
do
# Extract the first word of "$ac_prog", so it can be a program name with args.
set dummy $ac_prog; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_DUMPBIN+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_DUMPBIN"; then
ac_cv_prog_ac_ct_DUMPBIN="$ac_ct_DUMPBIN" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_DUMPBIN="$ac_prog"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_DUMPBIN=$ac_cv_prog_ac_ct_DUMPBIN
if test -n "$ac_ct_DUMPBIN"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_DUMPBIN" >&5
$as_echo "$ac_ct_DUMPBIN" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
test -n "$ac_ct_DUMPBIN" && break
done
if test "x$ac_ct_DUMPBIN" = x; then
DUMPBIN=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
DUMPBIN=$ac_ct_DUMPBIN
fi
fi
case `$DUMPBIN -symbols /dev/null 2>&1 | sed '1q'` in
*COFF*)
DUMPBIN="$DUMPBIN -symbols"
;;
*)
DUMPBIN=:
;;
esac
fi
if test "$DUMPBIN" != ":"; then
NM="$DUMPBIN"
fi
fi
test -z "$NM" && NM=nm
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking the name lister ($NM) interface" >&5
$as_echo_n "checking the name lister ($NM) interface... " >&6; }
if ${lt_cv_nm_interface+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_nm_interface="BSD nm"
echo "int some_variable = 0;" > conftest.$ac_ext
(eval echo "\"\$as_me:$LINENO: $ac_compile\"" >&5)
(eval "$ac_compile" 2>conftest.err)
cat conftest.err >&5
(eval echo "\"\$as_me:$LINENO: $NM \\\"conftest.$ac_objext\\\"\"" >&5)
(eval "$NM \"conftest.$ac_objext\"" 2>conftest.err > conftest.out)
cat conftest.err >&5
(eval echo "\"\$as_me:$LINENO: output\"" >&5)
cat conftest.out >&5
if $GREP 'External.*some_variable' conftest.out > /dev/null; then
lt_cv_nm_interface="MS dumpbin"
fi
rm -f conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_nm_interface" >&5
$as_echo "$lt_cv_nm_interface" >&6; }
# find the maximum length of command line arguments
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking the maximum length of command line arguments" >&5
$as_echo_n "checking the maximum length of command line arguments... " >&6; }
if ${lt_cv_sys_max_cmd_len+:} false; then :
$as_echo_n "(cached) " >&6
else
i=0
teststring="ABCD"
case $build_os in
msdosdjgpp*)
# On DJGPP, this test can blow up pretty badly due to problems in libc
# (any single argument exceeding 2000 bytes causes a buffer overrun
# during glob expansion). Even if it were fixed, the result of this
# check would be larger than it should be.
lt_cv_sys_max_cmd_len=12288; # 12K is about right
;;
gnu*)
# Under GNU Hurd, this test is not required because there is
# no limit to the length of command line arguments.
# Libtool will interpret -1 as no limit whatsoever
lt_cv_sys_max_cmd_len=-1;
;;
cygwin* | mingw* | cegcc*)
# On Win9x/ME, this test blows up -- it succeeds, but takes
# about 5 minutes as the teststring grows exponentially.
# Worse, since 9x/ME are not pre-emptively multitasking,
# you end up with a "frozen" computer, even though with patience
# the test eventually succeeds (with a max line length of 256k).
# Instead, let's just punt: use the minimum linelength reported by
# all of the supported platforms: 8192 (on NT/2K/XP).
lt_cv_sys_max_cmd_len=8192;
;;
mint*)
# On MiNT this can take a long time and run out of memory.
lt_cv_sys_max_cmd_len=8192;
;;
amigaos*)
# On AmigaOS with pdksh, this test takes hours, literally.
# So we just punt and use a minimum line length of 8192.
lt_cv_sys_max_cmd_len=8192;
;;
netbsd* | freebsd* | openbsd* | darwin* | dragonfly*)
# This has been around since 386BSD, at least. Likely further.
if test -x /sbin/sysctl; then
lt_cv_sys_max_cmd_len=`/sbin/sysctl -n kern.argmax`
elif test -x /usr/sbin/sysctl; then
lt_cv_sys_max_cmd_len=`/usr/sbin/sysctl -n kern.argmax`
else
lt_cv_sys_max_cmd_len=65536 # usable default for all BSDs
fi
# And add a safety zone
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \/ 4`
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \* 3`
;;
interix*)
# We know the value 262144 and hardcode it with a safety zone (like BSD)
lt_cv_sys_max_cmd_len=196608
;;
os2*)
# The test takes a long time on OS/2.
lt_cv_sys_max_cmd_len=8192
;;
osf*)
# Dr. Hans Ekkehard Plesser reports seeing a kernel panic running configure
# due to this test when exec_disable_arg_limit is 1 on Tru64. It is not
# nice to cause kernel panics so lets avoid the loop below.
# First set a reasonable default.
lt_cv_sys_max_cmd_len=16384
#
if test -x /sbin/sysconfig; then
case `/sbin/sysconfig -q proc exec_disable_arg_limit` in
*1*) lt_cv_sys_max_cmd_len=-1 ;;
esac
fi
;;
sco3.2v5*)
lt_cv_sys_max_cmd_len=102400
;;
sysv5* | sco5v6* | sysv4.2uw2*)
kargmax=`grep ARG_MAX /etc/conf/cf.d/stune 2>/dev/null`
if test -n "$kargmax"; then
lt_cv_sys_max_cmd_len=`echo $kargmax | sed 's/.*[ ]//'`
else
lt_cv_sys_max_cmd_len=32768
fi
;;
*)
lt_cv_sys_max_cmd_len=`(getconf ARG_MAX) 2> /dev/null`
if test -n "$lt_cv_sys_max_cmd_len"; then
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \/ 4`
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \* 3`
else
# Make teststring a little bigger before we do anything with it.
# a 1K string should be a reasonable start.
for i in 1 2 3 4 5 6 7 8 ; do
teststring=$teststring$teststring
done
SHELL=${SHELL-${CONFIG_SHELL-/bin/sh}}
# If test is not a shell built-in, we'll probably end up computing a
# maximum length that is only half of the actual maximum length, but
# we can't tell.
while { test "X"`env echo "$teststring$teststring" 2>/dev/null` \
= "X$teststring$teststring"; } >/dev/null 2>&1 &&
test $i != 17 # 1/2 MB should be enough
do
i=`expr $i + 1`
teststring=$teststring$teststring
done
# Only check the string length outside the loop.
lt_cv_sys_max_cmd_len=`expr "X$teststring" : ".*" 2>&1`
teststring=
# Add a significant safety factor because C++ compilers can tack on
# massive amounts of additional arguments before passing them to the
# linker. It appears as though 1/2 is a usable value.
lt_cv_sys_max_cmd_len=`expr $lt_cv_sys_max_cmd_len \/ 2`
fi
;;
esac
fi
if test -n $lt_cv_sys_max_cmd_len ; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_sys_max_cmd_len" >&5
$as_echo "$lt_cv_sys_max_cmd_len" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: none" >&5
$as_echo "none" >&6; }
fi
max_cmd_len=$lt_cv_sys_max_cmd_len
: ${CP="cp -f"}
: ${MV="mv -f"}
: ${RM="rm -f"}
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether the shell understands some XSI constructs" >&5
$as_echo_n "checking whether the shell understands some XSI constructs... " >&6; }
# Try some XSI features
xsi_shell=no
( _lt_dummy="a/b/c"
test "${_lt_dummy##*/},${_lt_dummy%/*},${_lt_dummy#??}"${_lt_dummy%"$_lt_dummy"}, \
= c,a/b,b/c, \
&& eval 'test $(( 1 + 1 )) -eq 2 \
&& test "${#_lt_dummy}" -eq 5' ) >/dev/null 2>&1 \
&& xsi_shell=yes
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $xsi_shell" >&5
$as_echo "$xsi_shell" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether the shell understands \"+=\"" >&5
$as_echo_n "checking whether the shell understands \"+=\"... " >&6; }
lt_shell_append=no
( foo=bar; set foo baz; eval "$1+=\$2" && test "$foo" = barbaz ) \
>/dev/null 2>&1 \
&& lt_shell_append=yes
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_shell_append" >&5
$as_echo "$lt_shell_append" >&6; }
if ( (MAIL=60; unset MAIL) || exit) >/dev/null 2>&1; then
lt_unset=unset
else
lt_unset=false
fi
# test EBCDIC or ASCII
case `echo X|tr X '\101'` in
A) # ASCII based system
# \n is not interpreted correctly by Solaris 8 /usr/ucb/tr
lt_SP2NL='tr \040 \012'
lt_NL2SP='tr \015\012 \040\040'
;;
*) # EBCDIC based system
lt_SP2NL='tr \100 \n'
lt_NL2SP='tr \r\n \100\100'
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking how to convert $build file names to $host format" >&5
$as_echo_n "checking how to convert $build file names to $host format... " >&6; }
if ${lt_cv_to_host_file_cmd+:} false; then :
$as_echo_n "(cached) " >&6
else
case $host in
*-*-mingw* )
case $build in
*-*-mingw* ) # actually msys
lt_cv_to_host_file_cmd=func_convert_file_msys_to_w32
;;
*-*-cygwin* )
lt_cv_to_host_file_cmd=func_convert_file_cygwin_to_w32
;;
* ) # otherwise, assume *nix
lt_cv_to_host_file_cmd=func_convert_file_nix_to_w32
;;
esac
;;
*-*-cygwin* )
case $build in
*-*-mingw* ) # actually msys
lt_cv_to_host_file_cmd=func_convert_file_msys_to_cygwin
;;
*-*-cygwin* )
lt_cv_to_host_file_cmd=func_convert_file_noop
;;
* ) # otherwise, assume *nix
lt_cv_to_host_file_cmd=func_convert_file_nix_to_cygwin
;;
esac
;;
* ) # unhandled hosts (and "normal" native builds)
lt_cv_to_host_file_cmd=func_convert_file_noop
;;
esac
fi
to_host_file_cmd=$lt_cv_to_host_file_cmd
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_to_host_file_cmd" >&5
$as_echo "$lt_cv_to_host_file_cmd" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking how to convert $build file names to toolchain format" >&5
$as_echo_n "checking how to convert $build file names to toolchain format... " >&6; }
if ${lt_cv_to_tool_file_cmd+:} false; then :
$as_echo_n "(cached) " >&6
else
#assume ordinary cross tools, or native build.
lt_cv_to_tool_file_cmd=func_convert_file_noop
case $host in
*-*-mingw* )
case $build in
*-*-mingw* ) # actually msys
lt_cv_to_tool_file_cmd=func_convert_file_msys_to_w32
;;
esac
;;
esac
fi
to_tool_file_cmd=$lt_cv_to_tool_file_cmd
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_to_tool_file_cmd" >&5
$as_echo "$lt_cv_to_tool_file_cmd" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $LD option to reload object files" >&5
$as_echo_n "checking for $LD option to reload object files... " >&6; }
if ${lt_cv_ld_reload_flag+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_ld_reload_flag='-r'
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_ld_reload_flag" >&5
$as_echo "$lt_cv_ld_reload_flag" >&6; }
reload_flag=$lt_cv_ld_reload_flag
case $reload_flag in
"" | " "*) ;;
*) reload_flag=" $reload_flag" ;;
esac
reload_cmds='$LD$reload_flag -o $output$reload_objs'
case $host_os in
cygwin* | mingw* | pw32* | cegcc*)
if test "$GCC" != yes; then
reload_cmds=false
fi
;;
darwin*)
if test "$GCC" = yes; then
reload_cmds='$LTCC $LTCFLAGS -nostdlib ${wl}-r -o $output$reload_objs'
else
reload_cmds='$LD$reload_flag -o $output$reload_objs'
fi
;;
esac
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}objdump", so it can be a program name with args.
set dummy ${ac_tool_prefix}objdump; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_OBJDUMP+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$OBJDUMP"; then
ac_cv_prog_OBJDUMP="$OBJDUMP" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_OBJDUMP="${ac_tool_prefix}objdump"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
OBJDUMP=$ac_cv_prog_OBJDUMP
if test -n "$OBJDUMP"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $OBJDUMP" >&5
$as_echo "$OBJDUMP" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_OBJDUMP"; then
ac_ct_OBJDUMP=$OBJDUMP
# Extract the first word of "objdump", so it can be a program name with args.
set dummy objdump; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_OBJDUMP+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_OBJDUMP"; then
ac_cv_prog_ac_ct_OBJDUMP="$ac_ct_OBJDUMP" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_OBJDUMP="objdump"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_OBJDUMP=$ac_cv_prog_ac_ct_OBJDUMP
if test -n "$ac_ct_OBJDUMP"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_OBJDUMP" >&5
$as_echo "$ac_ct_OBJDUMP" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_OBJDUMP" = x; then
OBJDUMP="false"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
OBJDUMP=$ac_ct_OBJDUMP
fi
else
OBJDUMP="$ac_cv_prog_OBJDUMP"
fi
test -z "$OBJDUMP" && OBJDUMP=objdump
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking how to recognize dependent libraries" >&5
$as_echo_n "checking how to recognize dependent libraries... " >&6; }
if ${lt_cv_deplibs_check_method+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_file_magic_cmd='$MAGIC_CMD'
lt_cv_file_magic_test_file=
lt_cv_deplibs_check_method='unknown'
# Need to set the preceding variable on all platforms that support
# interlibrary dependencies.
# 'none' -- dependencies not supported.
# `unknown' -- same as none, but documents that we really don't know.
# 'pass_all' -- all dependencies passed with no checks.
# 'test_compile' -- check by making test program.
# 'file_magic [[regex]]' -- check by looking for files in library path
# which responds to the $file_magic_cmd with a given extended regex.
# If you have `file' or equivalent on your system and you're not sure
# whether `pass_all' will *always* work, you probably want this one.
case $host_os in
aix[4-9]*)
lt_cv_deplibs_check_method=pass_all
;;
beos*)
lt_cv_deplibs_check_method=pass_all
;;
bsdi[45]*)
lt_cv_deplibs_check_method='file_magic ELF [0-9][0-9]*-bit [ML]SB (shared object|dynamic lib)'
lt_cv_file_magic_cmd='/usr/bin/file -L'
lt_cv_file_magic_test_file=/shlib/libc.so
;;
cygwin*)
# func_win32_libid is a shell function defined in ltmain.sh
lt_cv_deplibs_check_method='file_magic ^x86 archive import|^x86 DLL'
lt_cv_file_magic_cmd='func_win32_libid'
;;
mingw* | pw32*)
# Base MSYS/MinGW do not provide the 'file' command needed by
# func_win32_libid shell function, so use a weaker test based on 'objdump',
# unless we find 'file', for example because we are cross-compiling.
# func_win32_libid assumes BSD nm, so disallow it if using MS dumpbin.
if ( test "$lt_cv_nm_interface" = "BSD nm" && file / ) >/dev/null 2>&1; then
lt_cv_deplibs_check_method='file_magic ^x86 archive import|^x86 DLL'
lt_cv_file_magic_cmd='func_win32_libid'
else
# Keep this pattern in sync with the one in func_win32_libid.
lt_cv_deplibs_check_method='file_magic file format (pei*-i386(.*architecture: i386)?|pe-arm-wince|pe-x86-64)'
lt_cv_file_magic_cmd='$OBJDUMP -f'
fi
;;
cegcc*)
# use the weaker test based on 'objdump'. See mingw*.
lt_cv_deplibs_check_method='file_magic file format pe-arm-.*little(.*architecture: arm)?'
lt_cv_file_magic_cmd='$OBJDUMP -f'
;;
darwin* | rhapsody*)
lt_cv_deplibs_check_method=pass_all
;;
freebsd* | dragonfly*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ > /dev/null; then
case $host_cpu in
i*86 )
# Not sure whether the presence of OpenBSD here was a mistake.
# Let's accept both of them until this is cleared up.
lt_cv_deplibs_check_method='file_magic (FreeBSD|OpenBSD|DragonFly)/i[3-9]86 (compact )?demand paged shared library'
lt_cv_file_magic_cmd=/usr/bin/file
lt_cv_file_magic_test_file=`echo /usr/lib/libc.so.*`
;;
esac
else
lt_cv_deplibs_check_method=pass_all
fi
;;
gnu*)
lt_cv_deplibs_check_method=pass_all
;;
haiku*)
lt_cv_deplibs_check_method=pass_all
;;
hpux10.20* | hpux11*)
lt_cv_file_magic_cmd=/usr/bin/file
case $host_cpu in
ia64*)
lt_cv_deplibs_check_method='file_magic (s[0-9][0-9][0-9]|ELF-[0-9][0-9]) shared object file - IA64'
lt_cv_file_magic_test_file=/usr/lib/hpux32/libc.so
;;
hppa*64*)
lt_cv_deplibs_check_method='file_magic (s[0-9][0-9][0-9]|ELF[ -][0-9][0-9])(-bit)?( [LM]SB)? shared object( file)?[, -]* PA-RISC [0-9]\.[0-9]'
lt_cv_file_magic_test_file=/usr/lib/pa20_64/libc.sl
;;
*)
lt_cv_deplibs_check_method='file_magic (s[0-9][0-9][0-9]|PA-RISC[0-9]\.[0-9]) shared library'
lt_cv_file_magic_test_file=/usr/lib/libc.sl
;;
esac
;;
interix[3-9]*)
# PIC code is broken on Interix 3.x, that's why |\.a not |_pic\.a here
lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so|\.a)$'
;;
irix5* | irix6* | nonstopux*)
case $LD in
*-32|*"-32 ") libmagic=32-bit;;
*-n32|*"-n32 ") libmagic=N32;;
*-64|*"-64 ") libmagic=64-bit;;
*) libmagic=never-match;;
esac
lt_cv_deplibs_check_method=pass_all
;;
# This must be glibc/ELF.
linux* | k*bsd*-gnu | kopensolaris*-gnu)
lt_cv_deplibs_check_method=pass_all
;;
netbsd*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ > /dev/null; then
lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so\.[0-9]+\.[0-9]+|_pic\.a)$'
else
lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so|_pic\.a)$'
fi
;;
newos6*)
lt_cv_deplibs_check_method='file_magic ELF [0-9][0-9]*-bit [ML]SB (executable|dynamic lib)'
lt_cv_file_magic_cmd=/usr/bin/file
lt_cv_file_magic_test_file=/usr/lib/libnls.so
;;
*nto* | *qnx*)
lt_cv_deplibs_check_method=pass_all
;;
openbsd*)
if test -z "`echo __ELF__ | $CC -E - | $GREP __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so\.[0-9]+\.[0-9]+|\.so|_pic\.a)$'
else
lt_cv_deplibs_check_method='match_pattern /lib[^/]+(\.so\.[0-9]+\.[0-9]+|_pic\.a)$'
fi
;;
osf3* | osf4* | osf5*)
lt_cv_deplibs_check_method=pass_all
;;
rdos*)
lt_cv_deplibs_check_method=pass_all
;;
solaris*)
lt_cv_deplibs_check_method=pass_all
;;
sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX* | sysv4*uw2*)
lt_cv_deplibs_check_method=pass_all
;;
sysv4 | sysv4.3*)
case $host_vendor in
motorola)
lt_cv_deplibs_check_method='file_magic ELF [0-9][0-9]*-bit [ML]SB (shared object|dynamic lib) M[0-9][0-9]* Version [0-9]'
lt_cv_file_magic_test_file=`echo /usr/lib/libc.so*`
;;
ncr)
lt_cv_deplibs_check_method=pass_all
;;
sequent)
lt_cv_file_magic_cmd='/bin/file'
lt_cv_deplibs_check_method='file_magic ELF [0-9][0-9]*-bit [LM]SB (shared object|dynamic lib )'
;;
sni)
lt_cv_file_magic_cmd='/bin/file'
lt_cv_deplibs_check_method="file_magic ELF [0-9][0-9]*-bit [LM]SB dynamic lib"
lt_cv_file_magic_test_file=/lib/libc.so
;;
siemens)
lt_cv_deplibs_check_method=pass_all
;;
pc)
lt_cv_deplibs_check_method=pass_all
;;
esac
;;
tpf*)
lt_cv_deplibs_check_method=pass_all
;;
esac
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_deplibs_check_method" >&5
$as_echo "$lt_cv_deplibs_check_method" >&6; }
file_magic_glob=
want_nocaseglob=no
if test "$build" = "$host"; then
case $host_os in
mingw* | pw32*)
if ( shopt | grep nocaseglob ) >/dev/null 2>&1; then
want_nocaseglob=yes
else
file_magic_glob=`echo aAbBcCdDeEfFgGhHiIjJkKlLmMnNoOpPqQrRsStTuUvVwWxXyYzZ | $SED -e "s/\(..\)/s\/[\1]\/[\1]\/g;/g"`
fi
;;
esac
fi
file_magic_cmd=$lt_cv_file_magic_cmd
deplibs_check_method=$lt_cv_deplibs_check_method
test -z "$deplibs_check_method" && deplibs_check_method=unknown
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}dlltool", so it can be a program name with args.
set dummy ${ac_tool_prefix}dlltool; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_DLLTOOL+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$DLLTOOL"; then
ac_cv_prog_DLLTOOL="$DLLTOOL" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_DLLTOOL="${ac_tool_prefix}dlltool"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
DLLTOOL=$ac_cv_prog_DLLTOOL
if test -n "$DLLTOOL"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $DLLTOOL" >&5
$as_echo "$DLLTOOL" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_DLLTOOL"; then
ac_ct_DLLTOOL=$DLLTOOL
# Extract the first word of "dlltool", so it can be a program name with args.
set dummy dlltool; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_DLLTOOL+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_DLLTOOL"; then
ac_cv_prog_ac_ct_DLLTOOL="$ac_ct_DLLTOOL" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_DLLTOOL="dlltool"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_DLLTOOL=$ac_cv_prog_ac_ct_DLLTOOL
if test -n "$ac_ct_DLLTOOL"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_DLLTOOL" >&5
$as_echo "$ac_ct_DLLTOOL" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_DLLTOOL" = x; then
DLLTOOL="false"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
DLLTOOL=$ac_ct_DLLTOOL
fi
else
DLLTOOL="$ac_cv_prog_DLLTOOL"
fi
test -z "$DLLTOOL" && DLLTOOL=dlltool
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking how to associate runtime and link libraries" >&5
$as_echo_n "checking how to associate runtime and link libraries... " >&6; }
if ${lt_cv_sharedlib_from_linklib_cmd+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_sharedlib_from_linklib_cmd='unknown'
case $host_os in
cygwin* | mingw* | pw32* | cegcc*)
# two different shell functions defined in ltmain.sh
# decide which to use based on capabilities of $DLLTOOL
case `$DLLTOOL --help 2>&1` in
*--identify-strict*)
lt_cv_sharedlib_from_linklib_cmd=func_cygming_dll_for_implib
;;
*)
lt_cv_sharedlib_from_linklib_cmd=func_cygming_dll_for_implib_fallback
;;
esac
;;
*)
# fallback: assume linklib IS sharedlib
lt_cv_sharedlib_from_linklib_cmd="$ECHO"
;;
esac
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_sharedlib_from_linklib_cmd" >&5
$as_echo "$lt_cv_sharedlib_from_linklib_cmd" >&6; }
sharedlib_from_linklib_cmd=$lt_cv_sharedlib_from_linklib_cmd
test -z "$sharedlib_from_linklib_cmd" && sharedlib_from_linklib_cmd=$ECHO
if test -n "$ac_tool_prefix"; then
for ac_prog in ar
do
# Extract the first word of "$ac_tool_prefix$ac_prog", so it can be a program name with args.
set dummy $ac_tool_prefix$ac_prog; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_AR+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$AR"; then
ac_cv_prog_AR="$AR" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_AR="$ac_tool_prefix$ac_prog"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
AR=$ac_cv_prog_AR
if test -n "$AR"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $AR" >&5
$as_echo "$AR" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
test -n "$AR" && break
done
fi
if test -z "$AR"; then
ac_ct_AR=$AR
for ac_prog in ar
do
# Extract the first word of "$ac_prog", so it can be a program name with args.
set dummy $ac_prog; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_AR+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_AR"; then
ac_cv_prog_ac_ct_AR="$ac_ct_AR" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_AR="$ac_prog"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_AR=$ac_cv_prog_ac_ct_AR
if test -n "$ac_ct_AR"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_AR" >&5
$as_echo "$ac_ct_AR" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
test -n "$ac_ct_AR" && break
done
if test "x$ac_ct_AR" = x; then
AR="false"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
AR=$ac_ct_AR
fi
fi
: ${AR=ar}
: ${AR_FLAGS=cru}
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for archiver @FILE support" >&5
$as_echo_n "checking for archiver @FILE support... " >&6; }
if ${lt_cv_ar_at_file+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_ar_at_file=no
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
echo conftest.$ac_objext > conftest.lst
lt_ar_try='$AR $AR_FLAGS libconftest.a @conftest.lst >&5'
{ { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$lt_ar_try\""; } >&5
(eval $lt_ar_try) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }
if test "$ac_status" -eq 0; then
# Ensure the archiver fails upon bogus file names.
rm -f conftest.$ac_objext libconftest.a
{ { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$lt_ar_try\""; } >&5
(eval $lt_ar_try) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }
if test "$ac_status" -ne 0; then
lt_cv_ar_at_file=@
fi
fi
rm -f conftest.* libconftest.a
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_ar_at_file" >&5
$as_echo "$lt_cv_ar_at_file" >&6; }
if test "x$lt_cv_ar_at_file" = xno; then
archiver_list_spec=
else
archiver_list_spec=$lt_cv_ar_at_file
fi
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}strip", so it can be a program name with args.
set dummy ${ac_tool_prefix}strip; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_STRIP+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$STRIP"; then
ac_cv_prog_STRIP="$STRIP" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_STRIP="${ac_tool_prefix}strip"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
STRIP=$ac_cv_prog_STRIP
if test -n "$STRIP"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $STRIP" >&5
$as_echo "$STRIP" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_STRIP"; then
ac_ct_STRIP=$STRIP
# Extract the first word of "strip", so it can be a program name with args.
set dummy strip; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_STRIP+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_STRIP"; then
ac_cv_prog_ac_ct_STRIP="$ac_ct_STRIP" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_STRIP="strip"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_STRIP=$ac_cv_prog_ac_ct_STRIP
if test -n "$ac_ct_STRIP"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_STRIP" >&5
$as_echo "$ac_ct_STRIP" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_STRIP" = x; then
STRIP=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
STRIP=$ac_ct_STRIP
fi
else
STRIP="$ac_cv_prog_STRIP"
fi
test -z "$STRIP" && STRIP=:
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}ranlib", so it can be a program name with args.
set dummy ${ac_tool_prefix}ranlib; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_RANLIB+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$RANLIB"; then
ac_cv_prog_RANLIB="$RANLIB" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_RANLIB="${ac_tool_prefix}ranlib"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
RANLIB=$ac_cv_prog_RANLIB
if test -n "$RANLIB"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $RANLIB" >&5
$as_echo "$RANLIB" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_RANLIB"; then
ac_ct_RANLIB=$RANLIB
# Extract the first word of "ranlib", so it can be a program name with args.
set dummy ranlib; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_RANLIB+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_RANLIB"; then
ac_cv_prog_ac_ct_RANLIB="$ac_ct_RANLIB" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_RANLIB="ranlib"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_RANLIB=$ac_cv_prog_ac_ct_RANLIB
if test -n "$ac_ct_RANLIB"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_RANLIB" >&5
$as_echo "$ac_ct_RANLIB" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_RANLIB" = x; then
RANLIB=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
RANLIB=$ac_ct_RANLIB
fi
else
RANLIB="$ac_cv_prog_RANLIB"
fi
test -z "$RANLIB" && RANLIB=:
# Determine commands to create old-style static archives.
old_archive_cmds='$AR $AR_FLAGS $oldlib$oldobjs'
old_postinstall_cmds='chmod 644 $oldlib'
old_postuninstall_cmds=
if test -n "$RANLIB"; then
case $host_os in
openbsd*)
old_postinstall_cmds="$old_postinstall_cmds~\$RANLIB -t \$tool_oldlib"
;;
*)
old_postinstall_cmds="$old_postinstall_cmds~\$RANLIB \$tool_oldlib"
;;
esac
old_archive_cmds="$old_archive_cmds~\$RANLIB \$tool_oldlib"
fi
case $host_os in
darwin*)
lock_old_archive_extraction=yes ;;
*)
lock_old_archive_extraction=no ;;
esac
# If no C compiler was specified, use CC.
LTCC=${LTCC-"$CC"}
# If no C compiler flags were specified, use CFLAGS.
LTCFLAGS=${LTCFLAGS-"$CFLAGS"}
# Allow CC to be a program name with arguments.
compiler=$CC
# Check for command to grab the raw symbol name followed by C symbol from nm.
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking command to parse $NM output from $compiler object" >&5
$as_echo_n "checking command to parse $NM output from $compiler object... " >&6; }
if ${lt_cv_sys_global_symbol_pipe+:} false; then :
$as_echo_n "(cached) " >&6
else
# These are sane defaults that work on at least a few old systems.
# [They come from Ultrix. What could be older than Ultrix?!! ;)]
# Character class describing NM global symbol codes.
symcode='[BCDEGRST]'
# Regexp to match symbols that can be accessed directly from C.
sympat='\([_A-Za-z][_A-Za-z0-9]*\)'
# Define system-specific variables.
case $host_os in
aix*)
symcode='[BCDT]'
;;
cygwin* | mingw* | pw32* | cegcc*)
symcode='[ABCDGISTW]'
;;
hpux*)
if test "$host_cpu" = ia64; then
symcode='[ABCDEGRST]'
fi
;;
irix* | nonstopux*)
symcode='[BCDEGRST]'
;;
osf*)
symcode='[BCDEGQRST]'
;;
solaris*)
symcode='[BDRT]'
;;
sco3.2v5*)
symcode='[DT]'
;;
sysv4.2uw2*)
symcode='[DT]'
;;
sysv5* | sco5v6* | unixware* | OpenUNIX*)
symcode='[ABDT]'
;;
sysv4)
symcode='[DFNSTU]'
;;
esac
# If we're using GNU nm, then use its standard symbol codes.
case `$NM -V 2>&1` in
*GNU* | *'with BFD'*)
symcode='[ABCDGIRSTW]' ;;
esac
# Transform an extracted symbol line into a proper C declaration.
# Some systems (esp. on ia64) link data and code symbols differently,
# so use this general approach.
lt_cv_sys_global_symbol_to_cdecl="sed -n -e 's/^T .* \(.*\)$/extern int \1();/p' -e 's/^$symcode* .* \(.*\)$/extern char \1;/p'"
# Transform an extracted symbol line into symbol name and symbol address
lt_cv_sys_global_symbol_to_c_name_address="sed -n -e 's/^: \([^ ]*\)[ ]*$/ {\\\"\1\\\", (void *) 0},/p' -e 's/^$symcode* \([^ ]*\) \([^ ]*\)$/ {\"\2\", (void *) \&\2},/p'"
lt_cv_sys_global_symbol_to_c_name_address_lib_prefix="sed -n -e 's/^: \([^ ]*\)[ ]*$/ {\\\"\1\\\", (void *) 0},/p' -e 's/^$symcode* \([^ ]*\) \(lib[^ ]*\)$/ {\"\2\", (void *) \&\2},/p' -e 's/^$symcode* \([^ ]*\) \([^ ]*\)$/ {\"lib\2\", (void *) \&\2},/p'"
# Handle CRLF in mingw tool chain
opt_cr=
case $build_os in
mingw*)
opt_cr=`$ECHO 'x\{0,1\}' | tr x '\015'` # option cr in regexp
;;
esac
# Try without a prefix underscore, then with it.
for ac_symprfx in "" "_"; do
# Transform symcode, sympat, and symprfx into a raw symbol and a C symbol.
symxfrm="\\1 $ac_symprfx\\2 \\2"
# Write the raw and C identifiers.
if test "$lt_cv_nm_interface" = "MS dumpbin"; then
# Fake it for dumpbin and say T for any non-static function
# and D for any global variable.
# Also find C++ and __fastcall symbols from MSVC++,
# which start with @ or ?.
lt_cv_sys_global_symbol_pipe="$AWK '"\
" {last_section=section; section=\$ 3};"\
" /^COFF SYMBOL TABLE/{for(i in hide) delete hide[i]};"\
" /Section length .*#relocs.*(pick any)/{hide[last_section]=1};"\
" \$ 0!~/External *\|/{next};"\
" / 0+ UNDEF /{next}; / UNDEF \([^|]\)*()/{next};"\
" {if(hide[section]) next};"\
" {f=0}; \$ 0~/\(\).*\|/{f=1}; {printf f ? \"T \" : \"D \"};"\
" {split(\$ 0, a, /\||\r/); split(a[2], s)};"\
" s[1]~/^[@?]/{print s[1], s[1]; next};"\
" s[1]~prfx {split(s[1],t,\"@\"); print t[1], substr(t[1],length(prfx))}"\
" ' prfx=^$ac_symprfx"
else
lt_cv_sys_global_symbol_pipe="sed -n -e 's/^.*[ ]\($symcode$symcode*\)[ ][ ]*$ac_symprfx$sympat$opt_cr$/$symxfrm/p'"
fi
lt_cv_sys_global_symbol_pipe="$lt_cv_sys_global_symbol_pipe | sed '/ __gnu_lto/d'"
# Check to see that the pipe works correctly.
pipe_works=no
rm -f conftest*
cat > conftest.$ac_ext <<_LT_EOF
#ifdef __cplusplus
extern "C" {
#endif
char nm_test_var;
void nm_test_func(void);
void nm_test_func(void){}
#ifdef __cplusplus
}
#endif
int main(){nm_test_var='a';nm_test_func();return(0);}
_LT_EOF
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_compile\""; } >&5
(eval $ac_compile) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }; then
# Now try to grab the symbols.
nlist=conftest.nm
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$NM conftest.$ac_objext \| "$lt_cv_sys_global_symbol_pipe" \> $nlist\""; } >&5
(eval $NM conftest.$ac_objext \| "$lt_cv_sys_global_symbol_pipe" \> $nlist) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && test -s "$nlist"; then
# Try sorting and uniquifying the output.
if sort "$nlist" | uniq > "$nlist"T; then
mv -f "$nlist"T "$nlist"
else
rm -f "$nlist"T
fi
# Make sure that we snagged all the symbols we need.
if $GREP ' nm_test_var$' "$nlist" >/dev/null; then
if $GREP ' nm_test_func$' "$nlist" >/dev/null; then
cat <<_LT_EOF > conftest.$ac_ext
/* Keep this code in sync between libtool.m4, ltmain, lt_system.h, and tests. */
#if defined(_WIN32) || defined(__CYGWIN__) || defined(_WIN32_WCE)
/* DATA imports from DLLs on WIN32 con't be const, because runtime
relocations are performed -- see ld's documentation on pseudo-relocs. */
# define LT_DLSYM_CONST
#elif defined(__osf__)
/* This system does not cope well with relocations in const data. */
# define LT_DLSYM_CONST
#else
# define LT_DLSYM_CONST const
#endif
#ifdef __cplusplus
extern "C" {
#endif
_LT_EOF
# Now generate the symbol file.
eval "$lt_cv_sys_global_symbol_to_cdecl"' < "$nlist" | $GREP -v main >> conftest.$ac_ext'
cat <<_LT_EOF >> conftest.$ac_ext
/* The mapping between symbol names and symbols. */
LT_DLSYM_CONST struct {
const char *name;
void *address;
}
lt__PROGRAM__LTX_preloaded_symbols[] =
{
{ "@PROGRAM@", (void *) 0 },
_LT_EOF
$SED "s/^$symcode$symcode* \(.*\) \(.*\)$/ {\"\2\", (void *) \&\2},/" < "$nlist" | $GREP -v main >> conftest.$ac_ext
cat <<\_LT_EOF >> conftest.$ac_ext
{0, (void *) 0}
};
/* This works around a problem in FreeBSD linker */
#ifdef FREEBSD_WORKAROUND
static const void *lt_preloaded_setup() {
return lt__PROGRAM__LTX_preloaded_symbols;
}
#endif
#ifdef __cplusplus
}
#endif
_LT_EOF
# Now try linking the two files.
mv conftest.$ac_objext conftstm.$ac_objext
lt_globsym_save_LIBS=$LIBS
lt_globsym_save_CFLAGS=$CFLAGS
LIBS="conftstm.$ac_objext"
CFLAGS="$CFLAGS$lt_prog_compiler_no_builtin_flag"
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_link\""; } >&5
(eval $ac_link) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && test -s conftest${ac_exeext}; then
pipe_works=yes
fi
LIBS=$lt_globsym_save_LIBS
CFLAGS=$lt_globsym_save_CFLAGS
else
echo "cannot find nm_test_func in $nlist" >&5
fi
else
echo "cannot find nm_test_var in $nlist" >&5
fi
else
echo "cannot run $lt_cv_sys_global_symbol_pipe" >&5
fi
else
echo "$progname: failed program was:" >&5
cat conftest.$ac_ext >&5
fi
rm -rf conftest* conftst*
# Do not use the global_symbol_pipe unless it works.
if test "$pipe_works" = yes; then
break
else
lt_cv_sys_global_symbol_pipe=
fi
done
fi
if test -z "$lt_cv_sys_global_symbol_pipe"; then
lt_cv_sys_global_symbol_to_cdecl=
fi
if test -z "$lt_cv_sys_global_symbol_pipe$lt_cv_sys_global_symbol_to_cdecl"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: failed" >&5
$as_echo "failed" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: ok" >&5
$as_echo "ok" >&6; }
fi
# Response file support.
if test "$lt_cv_nm_interface" = "MS dumpbin"; then
nm_file_list_spec='@'
elif $NM --help 2>/dev/null | grep '[@]FILE' >/dev/null; then
nm_file_list_spec='@'
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for sysroot" >&5
$as_echo_n "checking for sysroot... " >&6; }
# Check whether --with-sysroot was given.
if test "${with_sysroot+set}" = set; then :
withval=$with_sysroot;
else
with_sysroot=no
fi
lt_sysroot=
case ${with_sysroot} in #(
yes)
if test "$GCC" = yes; then
lt_sysroot=`$CC --print-sysroot 2>/dev/null`
fi
;; #(
/*)
lt_sysroot=`echo "$with_sysroot" | sed -e "$sed_quote_subst"`
;; #(
no|'')
;; #(
*)
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: ${with_sysroot}" >&5
$as_echo "${with_sysroot}" >&6; }
as_fn_error $? "The sysroot must be an absolute path." "$LINENO" 5
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: ${lt_sysroot:-no}" >&5
$as_echo "${lt_sysroot:-no}" >&6; }
# Check whether --enable-libtool-lock was given.
if test "${enable_libtool_lock+set}" = set; then :
enableval=$enable_libtool_lock;
fi
test "x$enable_libtool_lock" != xno && enable_libtool_lock=yes
# Some flags need to be propagated to the compiler or linker for good
# libtool support.
case $host in
ia64-*-hpux*)
# Find out which ABI we are using.
echo 'int i;' > conftest.$ac_ext
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_compile\""; } >&5
(eval $ac_compile) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }; then
case `/usr/bin/file conftest.$ac_objext` in
*ELF-32*)
HPUX_IA64_MODE="32"
;;
*ELF-64*)
HPUX_IA64_MODE="64"
;;
esac
fi
rm -rf conftest*
;;
*-*-irix6*)
# Find out which ABI we are using.
echo '#line '$LINENO' "configure"' > conftest.$ac_ext
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_compile\""; } >&5
(eval $ac_compile) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }; then
if test "$lt_cv_prog_gnu_ld" = yes; then
case `/usr/bin/file conftest.$ac_objext` in
*32-bit*)
LD="${LD-ld} -melf32bsmip"
;;
*N32*)
LD="${LD-ld} -melf32bmipn32"
;;
*64-bit*)
LD="${LD-ld} -melf64bmip"
;;
esac
else
case `/usr/bin/file conftest.$ac_objext` in
*32-bit*)
LD="${LD-ld} -32"
;;
*N32*)
LD="${LD-ld} -n32"
;;
*64-bit*)
LD="${LD-ld} -64"
;;
esac
fi
fi
rm -rf conftest*
;;
x86_64-*kfreebsd*-gnu|x86_64-*linux*|ppc*-*linux*|powerpc*-*linux*| \
s390*-*linux*|s390*-*tpf*|sparc*-*linux*)
# Find out which ABI we are using.
echo 'int i;' > conftest.$ac_ext
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_compile\""; } >&5
(eval $ac_compile) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }; then
case `/usr/bin/file conftest.o` in
*32-bit*)
case $host in
x86_64-*kfreebsd*-gnu)
LD="${LD-ld} -m elf_i386_fbsd"
;;
x86_64-*linux*)
LD="${LD-ld} -m elf_i386"
;;
ppc64-*linux*|powerpc64-*linux*)
LD="${LD-ld} -m elf32ppclinux"
;;
s390x-*linux*)
LD="${LD-ld} -m elf_s390"
;;
sparc64-*linux*)
LD="${LD-ld} -m elf32_sparc"
;;
esac
;;
*64-bit*)
case $host in
x86_64-*kfreebsd*-gnu)
LD="${LD-ld} -m elf_x86_64_fbsd"
;;
x86_64-*linux*)
LD="${LD-ld} -m elf_x86_64"
;;
ppc*-*linux*|powerpc*-*linux*)
LD="${LD-ld} -m elf64ppc"
;;
s390*-*linux*|s390*-*tpf*)
LD="${LD-ld} -m elf64_s390"
;;
sparc*-*linux*)
LD="${LD-ld} -m elf64_sparc"
;;
esac
;;
esac
fi
rm -rf conftest*
;;
*-*-sco3.2v5*)
# On SCO OpenServer 5, we need -belf to get full-featured binaries.
SAVE_CFLAGS="$CFLAGS"
CFLAGS="$CFLAGS -belf"
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether the C compiler needs -belf" >&5
$as_echo_n "checking whether the C compiler needs -belf... " >&6; }
if ${lt_cv_cc_needs_belf+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
lt_cv_cc_needs_belf=yes
else
lt_cv_cc_needs_belf=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_cc_needs_belf" >&5
$as_echo "$lt_cv_cc_needs_belf" >&6; }
if test x"$lt_cv_cc_needs_belf" != x"yes"; then
# this is probably gcc 2.8.0, egcs 1.0 or newer; no need for -belf
CFLAGS="$SAVE_CFLAGS"
fi
;;
*-*solaris*)
# Find out which ABI we are using.
echo 'int i;' > conftest.$ac_ext
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_compile\""; } >&5
(eval $ac_compile) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }; then
case `/usr/bin/file conftest.o` in
*64-bit*)
case $lt_cv_prog_gnu_ld in
yes*)
case $host in
i?86-*-solaris*)
LD="${LD-ld} -m elf_x86_64"
;;
sparc*-*-solaris*)
LD="${LD-ld} -m elf64_sparc"
;;
esac
# GNU ld 2.21 introduced _sol2 emulations. Use them if available.
if ${LD-ld} -V | grep _sol2 >/dev/null 2>&1; then
LD="${LD-ld}_sol2"
fi
;;
*)
if ${LD-ld} -64 -r -o conftest2.o conftest.o >/dev/null 2>&1; then
LD="${LD-ld} -64"
fi
;;
esac
;;
esac
fi
rm -rf conftest*
;;
esac
need_locks="$enable_libtool_lock"
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}mt", so it can be a program name with args.
set dummy ${ac_tool_prefix}mt; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_MANIFEST_TOOL+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$MANIFEST_TOOL"; then
ac_cv_prog_MANIFEST_TOOL="$MANIFEST_TOOL" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_MANIFEST_TOOL="${ac_tool_prefix}mt"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
MANIFEST_TOOL=$ac_cv_prog_MANIFEST_TOOL
if test -n "$MANIFEST_TOOL"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $MANIFEST_TOOL" >&5
$as_echo "$MANIFEST_TOOL" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_MANIFEST_TOOL"; then
ac_ct_MANIFEST_TOOL=$MANIFEST_TOOL
# Extract the first word of "mt", so it can be a program name with args.
set dummy mt; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_MANIFEST_TOOL+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_MANIFEST_TOOL"; then
ac_cv_prog_ac_ct_MANIFEST_TOOL="$ac_ct_MANIFEST_TOOL" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_MANIFEST_TOOL="mt"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_MANIFEST_TOOL=$ac_cv_prog_ac_ct_MANIFEST_TOOL
if test -n "$ac_ct_MANIFEST_TOOL"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_MANIFEST_TOOL" >&5
$as_echo "$ac_ct_MANIFEST_TOOL" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_MANIFEST_TOOL" = x; then
MANIFEST_TOOL=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
MANIFEST_TOOL=$ac_ct_MANIFEST_TOOL
fi
else
MANIFEST_TOOL="$ac_cv_prog_MANIFEST_TOOL"
fi
test -z "$MANIFEST_TOOL" && MANIFEST_TOOL=mt
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $MANIFEST_TOOL is a manifest tool" >&5
$as_echo_n "checking if $MANIFEST_TOOL is a manifest tool... " >&6; }
if ${lt_cv_path_mainfest_tool+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_path_mainfest_tool=no
echo "$as_me:$LINENO: $MANIFEST_TOOL '-?'" >&5
$MANIFEST_TOOL '-?' 2>conftest.err > conftest.out
cat conftest.err >&5
if $GREP 'Manifest Tool' conftest.out > /dev/null; then
lt_cv_path_mainfest_tool=yes
fi
rm -f conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_path_mainfest_tool" >&5
$as_echo "$lt_cv_path_mainfest_tool" >&6; }
if test "x$lt_cv_path_mainfest_tool" != xyes; then
MANIFEST_TOOL=:
fi
case $host_os in
rhapsody* | darwin*)
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}dsymutil", so it can be a program name with args.
set dummy ${ac_tool_prefix}dsymutil; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_DSYMUTIL+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$DSYMUTIL"; then
ac_cv_prog_DSYMUTIL="$DSYMUTIL" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_DSYMUTIL="${ac_tool_prefix}dsymutil"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
DSYMUTIL=$ac_cv_prog_DSYMUTIL
if test -n "$DSYMUTIL"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $DSYMUTIL" >&5
$as_echo "$DSYMUTIL" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_DSYMUTIL"; then
ac_ct_DSYMUTIL=$DSYMUTIL
# Extract the first word of "dsymutil", so it can be a program name with args.
set dummy dsymutil; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_DSYMUTIL+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_DSYMUTIL"; then
ac_cv_prog_ac_ct_DSYMUTIL="$ac_ct_DSYMUTIL" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_DSYMUTIL="dsymutil"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_DSYMUTIL=$ac_cv_prog_ac_ct_DSYMUTIL
if test -n "$ac_ct_DSYMUTIL"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_DSYMUTIL" >&5
$as_echo "$ac_ct_DSYMUTIL" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_DSYMUTIL" = x; then
DSYMUTIL=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
DSYMUTIL=$ac_ct_DSYMUTIL
fi
else
DSYMUTIL="$ac_cv_prog_DSYMUTIL"
fi
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}nmedit", so it can be a program name with args.
set dummy ${ac_tool_prefix}nmedit; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_NMEDIT+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$NMEDIT"; then
ac_cv_prog_NMEDIT="$NMEDIT" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_NMEDIT="${ac_tool_prefix}nmedit"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
NMEDIT=$ac_cv_prog_NMEDIT
if test -n "$NMEDIT"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $NMEDIT" >&5
$as_echo "$NMEDIT" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_NMEDIT"; then
ac_ct_NMEDIT=$NMEDIT
# Extract the first word of "nmedit", so it can be a program name with args.
set dummy nmedit; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_NMEDIT+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_NMEDIT"; then
ac_cv_prog_ac_ct_NMEDIT="$ac_ct_NMEDIT" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_NMEDIT="nmedit"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_NMEDIT=$ac_cv_prog_ac_ct_NMEDIT
if test -n "$ac_ct_NMEDIT"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_NMEDIT" >&5
$as_echo "$ac_ct_NMEDIT" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_NMEDIT" = x; then
NMEDIT=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
NMEDIT=$ac_ct_NMEDIT
fi
else
NMEDIT="$ac_cv_prog_NMEDIT"
fi
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}lipo", so it can be a program name with args.
set dummy ${ac_tool_prefix}lipo; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_LIPO+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$LIPO"; then
ac_cv_prog_LIPO="$LIPO" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_LIPO="${ac_tool_prefix}lipo"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
LIPO=$ac_cv_prog_LIPO
if test -n "$LIPO"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $LIPO" >&5
$as_echo "$LIPO" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_LIPO"; then
ac_ct_LIPO=$LIPO
# Extract the first word of "lipo", so it can be a program name with args.
set dummy lipo; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_LIPO+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_LIPO"; then
ac_cv_prog_ac_ct_LIPO="$ac_ct_LIPO" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_LIPO="lipo"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_LIPO=$ac_cv_prog_ac_ct_LIPO
if test -n "$ac_ct_LIPO"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_LIPO" >&5
$as_echo "$ac_ct_LIPO" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_LIPO" = x; then
LIPO=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
LIPO=$ac_ct_LIPO
fi
else
LIPO="$ac_cv_prog_LIPO"
fi
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}otool", so it can be a program name with args.
set dummy ${ac_tool_prefix}otool; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_OTOOL+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$OTOOL"; then
ac_cv_prog_OTOOL="$OTOOL" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_OTOOL="${ac_tool_prefix}otool"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
OTOOL=$ac_cv_prog_OTOOL
if test -n "$OTOOL"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $OTOOL" >&5
$as_echo "$OTOOL" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_OTOOL"; then
ac_ct_OTOOL=$OTOOL
# Extract the first word of "otool", so it can be a program name with args.
set dummy otool; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_OTOOL+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_OTOOL"; then
ac_cv_prog_ac_ct_OTOOL="$ac_ct_OTOOL" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_OTOOL="otool"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_OTOOL=$ac_cv_prog_ac_ct_OTOOL
if test -n "$ac_ct_OTOOL"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_OTOOL" >&5
$as_echo "$ac_ct_OTOOL" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_OTOOL" = x; then
OTOOL=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
OTOOL=$ac_ct_OTOOL
fi
else
OTOOL="$ac_cv_prog_OTOOL"
fi
if test -n "$ac_tool_prefix"; then
# Extract the first word of "${ac_tool_prefix}otool64", so it can be a program name with args.
set dummy ${ac_tool_prefix}otool64; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_OTOOL64+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$OTOOL64"; then
ac_cv_prog_OTOOL64="$OTOOL64" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_OTOOL64="${ac_tool_prefix}otool64"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
OTOOL64=$ac_cv_prog_OTOOL64
if test -n "$OTOOL64"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $OTOOL64" >&5
$as_echo "$OTOOL64" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
fi
if test -z "$ac_cv_prog_OTOOL64"; then
ac_ct_OTOOL64=$OTOOL64
# Extract the first word of "otool64", so it can be a program name with args.
set dummy otool64; ac_word=$2
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5
$as_echo_n "checking for $ac_word... " >&6; }
if ${ac_cv_prog_ac_ct_OTOOL64+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -n "$ac_ct_OTOOL64"; then
ac_cv_prog_ac_ct_OTOOL64="$ac_ct_OTOOL64" # Let the user override the test.
else
as_save_IFS=$IFS; IFS=$PATH_SEPARATOR
for as_dir in $PATH
do
IFS=$as_save_IFS
test -z "$as_dir" && as_dir=.
for ac_exec_ext in '' $ac_executable_extensions; do
if as_fn_executable_p "$as_dir/$ac_word$ac_exec_ext"; then
ac_cv_prog_ac_ct_OTOOL64="otool64"
$as_echo "$as_me:${as_lineno-$LINENO}: found $as_dir/$ac_word$ac_exec_ext" >&5
break 2
fi
done
done
IFS=$as_save_IFS
fi
fi
ac_ct_OTOOL64=$ac_cv_prog_ac_ct_OTOOL64
if test -n "$ac_ct_OTOOL64"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_ct_OTOOL64" >&5
$as_echo "$ac_ct_OTOOL64" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test "x$ac_ct_OTOOL64" = x; then
OTOOL64=":"
else
case $cross_compiling:$ac_tool_warned in
yes:)
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5
$as_echo "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;}
ac_tool_warned=yes ;;
esac
OTOOL64=$ac_ct_OTOOL64
fi
else
OTOOL64="$ac_cv_prog_OTOOL64"
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for -single_module linker flag" >&5
$as_echo_n "checking for -single_module linker flag... " >&6; }
if ${lt_cv_apple_cc_single_mod+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_apple_cc_single_mod=no
if test -z "${LT_MULTI_MODULE}"; then
# By default we will add the -single_module flag. You can override
# by either setting the environment variable LT_MULTI_MODULE
# non-empty at configure time, or by adding -multi_module to the
# link flags.
rm -rf libconftest.dylib*
echo "int foo(void){return 1;}" > conftest.c
echo "$LTCC $LTCFLAGS $LDFLAGS -o libconftest.dylib \
-dynamiclib -Wl,-single_module conftest.c" >&5
$LTCC $LTCFLAGS $LDFLAGS -o libconftest.dylib \
-dynamiclib -Wl,-single_module conftest.c 2>conftest.err
_lt_result=$?
# If there is a non-empty error log, and "single_module"
# appears in it, assume the flag caused a linker warning
if test -s conftest.err && $GREP single_module conftest.err; then
cat conftest.err >&5
# Otherwise, if the output was created with a 0 exit code from
# the compiler, it worked.
elif test -f libconftest.dylib && test $_lt_result -eq 0; then
lt_cv_apple_cc_single_mod=yes
else
cat conftest.err >&5
fi
rm -rf libconftest.dylib*
rm -f conftest.*
fi
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_apple_cc_single_mod" >&5
$as_echo "$lt_cv_apple_cc_single_mod" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for -exported_symbols_list linker flag" >&5
$as_echo_n "checking for -exported_symbols_list linker flag... " >&6; }
if ${lt_cv_ld_exported_symbols_list+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_ld_exported_symbols_list=no
save_LDFLAGS=$LDFLAGS
echo "_main" > conftest.sym
LDFLAGS="$LDFLAGS -Wl,-exported_symbols_list,conftest.sym"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
lt_cv_ld_exported_symbols_list=yes
else
lt_cv_ld_exported_symbols_list=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LDFLAGS="$save_LDFLAGS"
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_ld_exported_symbols_list" >&5
$as_echo "$lt_cv_ld_exported_symbols_list" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for -force_load linker flag" >&5
$as_echo_n "checking for -force_load linker flag... " >&6; }
if ${lt_cv_ld_force_load+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_ld_force_load=no
cat > conftest.c << _LT_EOF
int forced_loaded() { return 2;}
_LT_EOF
echo "$LTCC $LTCFLAGS -c -o conftest.o conftest.c" >&5
$LTCC $LTCFLAGS -c -o conftest.o conftest.c 2>&5
echo "$AR cru libconftest.a conftest.o" >&5
$AR cru libconftest.a conftest.o 2>&5
echo "$RANLIB libconftest.a" >&5
$RANLIB libconftest.a 2>&5
cat > conftest.c << _LT_EOF
int main() { return 0;}
_LT_EOF
echo "$LTCC $LTCFLAGS $LDFLAGS -o conftest conftest.c -Wl,-force_load,./libconftest.a" >&5
$LTCC $LTCFLAGS $LDFLAGS -o conftest conftest.c -Wl,-force_load,./libconftest.a 2>conftest.err
_lt_result=$?
if test -s conftest.err && $GREP force_load conftest.err; then
cat conftest.err >&5
elif test -f conftest && test $_lt_result -eq 0 && $GREP forced_load conftest >/dev/null 2>&1 ; then
lt_cv_ld_force_load=yes
else
cat conftest.err >&5
fi
rm -f conftest.err libconftest.a conftest conftest.c
rm -rf conftest.dSYM
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_ld_force_load" >&5
$as_echo "$lt_cv_ld_force_load" >&6; }
case $host_os in
rhapsody* | darwin1.[012])
_lt_dar_allow_undefined='${wl}-undefined ${wl}suppress' ;;
darwin1.*)
_lt_dar_allow_undefined='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;;
darwin*) # darwin 5.x on
# if running on 10.5 or later, the deployment target defaults
# to the OS version, if on x86, and 10.4, the deployment
# target defaults to 10.4. Don't you love it?
case ${MACOSX_DEPLOYMENT_TARGET-10.0},$host in
10.0,*86*-darwin8*|10.0,*-darwin[91]*)
_lt_dar_allow_undefined='${wl}-undefined ${wl}dynamic_lookup' ;;
10.[012]*)
_lt_dar_allow_undefined='${wl}-flat_namespace ${wl}-undefined ${wl}suppress' ;;
10.*)
_lt_dar_allow_undefined='${wl}-undefined ${wl}dynamic_lookup' ;;
esac
;;
esac
if test "$lt_cv_apple_cc_single_mod" = "yes"; then
_lt_dar_single_mod='$single_module'
fi
if test "$lt_cv_ld_exported_symbols_list" = "yes"; then
_lt_dar_export_syms=' ${wl}-exported_symbols_list,$output_objdir/${libname}-symbols.expsym'
else
_lt_dar_export_syms='~$NMEDIT -s $output_objdir/${libname}-symbols.expsym ${lib}'
fi
if test "$DSYMUTIL" != ":" && test "$lt_cv_ld_force_load" = "no"; then
_lt_dsymutil='~$DSYMUTIL $lib || :'
else
_lt_dsymutil=
fi
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for ANSI C header files" >&5
$as_echo_n "checking for ANSI C header files... " >&6; }
if ${ac_cv_header_stdc+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
#include
#include
#include
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_compile "$LINENO"; then :
ac_cv_header_stdc=yes
else
ac_cv_header_stdc=no
fi
rm -f core conftest.err conftest.$ac_objext conftest.$ac_ext
if test $ac_cv_header_stdc = yes; then
# SunOS 4.x string.h does not declare mem*, contrary to ANSI.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
_ACEOF
if (eval "$ac_cpp conftest.$ac_ext") 2>&5 |
$EGREP "memchr" >/dev/null 2>&1; then :
else
ac_cv_header_stdc=no
fi
rm -f conftest*
fi
if test $ac_cv_header_stdc = yes; then
# ISC 2.0.2 stdlib.h does not declare free, contrary to ANSI.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
_ACEOF
if (eval "$ac_cpp conftest.$ac_ext") 2>&5 |
$EGREP "free" >/dev/null 2>&1; then :
else
ac_cv_header_stdc=no
fi
rm -f conftest*
fi
if test $ac_cv_header_stdc = yes; then
# /bin/cc in Irix-4.0.5 gets non-ANSI ctype macros unless using -ansi.
if test "$cross_compiling" = yes; then :
:
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
#include
#if ((' ' & 0x0FF) == 0x020)
# define ISLOWER(c) ('a' <= (c) && (c) <= 'z')
# define TOUPPER(c) (ISLOWER(c) ? 'A' + ((c) - 'a') : (c))
#else
# define ISLOWER(c) \
(('a' <= (c) && (c) <= 'i') \
|| ('j' <= (c) && (c) <= 'r') \
|| ('s' <= (c) && (c) <= 'z'))
# define TOUPPER(c) (ISLOWER(c) ? ((c) | 0x40) : (c))
#endif
#define XOR(e, f) (((e) && !(f)) || (!(e) && (f)))
int
main ()
{
int i;
for (i = 0; i < 256; i++)
if (XOR (islower (i), ISLOWER (i))
|| toupper (i) != TOUPPER (i))
return 2;
return 0;
}
_ACEOF
if ac_fn_c_try_run "$LINENO"; then :
else
ac_cv_header_stdc=no
fi
rm -f core *.core core.conftest.* gmon.out bb.out conftest$ac_exeext \
conftest.$ac_objext conftest.beam conftest.$ac_ext
fi
fi
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_header_stdc" >&5
$as_echo "$ac_cv_header_stdc" >&6; }
if test $ac_cv_header_stdc = yes; then
$as_echo "#define STDC_HEADERS 1" >>confdefs.h
fi
# On IRIX 5.3, sys/types and inttypes.h are conflicting.
for ac_header in sys/types.h sys/stat.h stdlib.h string.h memory.h strings.h \
inttypes.h stdint.h unistd.h
do :
as_ac_Header=`$as_echo "ac_cv_header_$ac_header" | $as_tr_sh`
ac_fn_c_check_header_compile "$LINENO" "$ac_header" "$as_ac_Header" "$ac_includes_default
"
if eval test \"x\$"$as_ac_Header"\" = x"yes"; then :
cat >>confdefs.h <<_ACEOF
#define `$as_echo "HAVE_$ac_header" | $as_tr_cpp` 1
_ACEOF
fi
done
for ac_header in dlfcn.h
do :
ac_fn_c_check_header_compile "$LINENO" "dlfcn.h" "ac_cv_header_dlfcn_h" "$ac_includes_default
"
if test "x$ac_cv_header_dlfcn_h" = xyes; then :
cat >>confdefs.h <<_ACEOF
#define HAVE_DLFCN_H 1
_ACEOF
fi
done
func_stripname_cnf ()
{
case ${2} in
.*) func_stripname_result=`$ECHO "${3}" | $SED "s%^${1}%%; s%\\\\${2}\$%%"`;;
*) func_stripname_result=`$ECHO "${3}" | $SED "s%^${1}%%; s%${2}\$%%"`;;
esac
} # func_stripname_cnf
# Set options
enable_dlopen=no
enable_win32_dll=no
# Check whether --enable-shared was given.
if test "${enable_shared+set}" = set; then :
enableval=$enable_shared; p=${PACKAGE-default}
case $enableval in
yes) enable_shared=yes ;;
no) enable_shared=no ;;
*)
enable_shared=no
# Look at the argument we got. We use all the common list separators.
lt_save_ifs="$IFS"; IFS="${IFS}$PATH_SEPARATOR,"
for pkg in $enableval; do
IFS="$lt_save_ifs"
if test "X$pkg" = "X$p"; then
enable_shared=yes
fi
done
IFS="$lt_save_ifs"
;;
esac
else
enable_shared=yes
fi
# Check whether --enable-static was given.
if test "${enable_static+set}" = set; then :
enableval=$enable_static; p=${PACKAGE-default}
case $enableval in
yes) enable_static=yes ;;
no) enable_static=no ;;
*)
enable_static=no
# Look at the argument we got. We use all the common list separators.
lt_save_ifs="$IFS"; IFS="${IFS}$PATH_SEPARATOR,"
for pkg in $enableval; do
IFS="$lt_save_ifs"
if test "X$pkg" = "X$p"; then
enable_static=yes
fi
done
IFS="$lt_save_ifs"
;;
esac
else
enable_static=yes
fi
# Check whether --with-pic was given.
if test "${with_pic+set}" = set; then :
withval=$with_pic; lt_p=${PACKAGE-default}
case $withval in
yes|no) pic_mode=$withval ;;
*)
pic_mode=default
# Look at the argument we got. We use all the common list separators.
lt_save_ifs="$IFS"; IFS="${IFS}$PATH_SEPARATOR,"
for lt_pkg in $withval; do
IFS="$lt_save_ifs"
if test "X$lt_pkg" = "X$lt_p"; then
pic_mode=yes
fi
done
IFS="$lt_save_ifs"
;;
esac
else
pic_mode=default
fi
test -z "$pic_mode" && pic_mode=default
# Check whether --enable-fast-install was given.
if test "${enable_fast_install+set}" = set; then :
enableval=$enable_fast_install; p=${PACKAGE-default}
case $enableval in
yes) enable_fast_install=yes ;;
no) enable_fast_install=no ;;
*)
enable_fast_install=no
# Look at the argument we got. We use all the common list separators.
lt_save_ifs="$IFS"; IFS="${IFS}$PATH_SEPARATOR,"
for pkg in $enableval; do
IFS="$lt_save_ifs"
if test "X$pkg" = "X$p"; then
enable_fast_install=yes
fi
done
IFS="$lt_save_ifs"
;;
esac
else
enable_fast_install=yes
fi
# This can be used to rebuild libtool when needed
LIBTOOL_DEPS="$ltmain"
# Always use our own libtool.
LIBTOOL='$(SHELL) $(top_builddir)/libtool'
test -z "$LN_S" && LN_S="ln -s"
if test -n "${ZSH_VERSION+set}" ; then
setopt NO_GLOB_SUBST
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for objdir" >&5
$as_echo_n "checking for objdir... " >&6; }
if ${lt_cv_objdir+:} false; then :
$as_echo_n "(cached) " >&6
else
rm -f .libs 2>/dev/null
mkdir .libs 2>/dev/null
if test -d .libs; then
lt_cv_objdir=.libs
else
# MS-DOS does not allow filenames that begin with a dot.
lt_cv_objdir=_libs
fi
rmdir .libs 2>/dev/null
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_objdir" >&5
$as_echo "$lt_cv_objdir" >&6; }
objdir=$lt_cv_objdir
cat >>confdefs.h <<_ACEOF
#define LT_OBJDIR "$lt_cv_objdir/"
_ACEOF
case $host_os in
aix3*)
# AIX sometimes has problems with the GCC collect2 program. For some
# reason, if we set the COLLECT_NAMES environment variable, the problems
# vanish in a puff of smoke.
if test "X${COLLECT_NAMES+set}" != Xset; then
COLLECT_NAMES=
export COLLECT_NAMES
fi
;;
esac
# Global variables:
ofile=libtool
can_build_shared=yes
# All known linkers require a `.a' archive for static linking (except MSVC,
# which needs '.lib').
libext=a
with_gnu_ld="$lt_cv_prog_gnu_ld"
old_CC="$CC"
old_CFLAGS="$CFLAGS"
# Set sane defaults for various variables
test -z "$CC" && CC=cc
test -z "$LTCC" && LTCC=$CC
test -z "$LTCFLAGS" && LTCFLAGS=$CFLAGS
test -z "$LD" && LD=ld
test -z "$ac_objext" && ac_objext=o
for cc_temp in $compiler""; do
case $cc_temp in
compile | *[\\/]compile | ccache | *[\\/]ccache ) ;;
distcc | *[\\/]distcc | purify | *[\\/]purify ) ;;
\-*) ;;
*) break;;
esac
done
cc_basename=`$ECHO "$cc_temp" | $SED "s%.*/%%; s%^$host_alias-%%"`
# Only perform the check for file, if the check method requires it
test -z "$MAGIC_CMD" && MAGIC_CMD=file
case $deplibs_check_method in
file_magic*)
if test "$file_magic_cmd" = '$MAGIC_CMD'; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for ${ac_tool_prefix}file" >&5
$as_echo_n "checking for ${ac_tool_prefix}file... " >&6; }
if ${lt_cv_path_MAGIC_CMD+:} false; then :
$as_echo_n "(cached) " >&6
else
case $MAGIC_CMD in
[\\/*] | ?:[\\/]*)
lt_cv_path_MAGIC_CMD="$MAGIC_CMD" # Let the user override the test with a path.
;;
*)
lt_save_MAGIC_CMD="$MAGIC_CMD"
lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR
ac_dummy="/usr/bin$PATH_SEPARATOR$PATH"
for ac_dir in $ac_dummy; do
IFS="$lt_save_ifs"
test -z "$ac_dir" && ac_dir=.
if test -f $ac_dir/${ac_tool_prefix}file; then
lt_cv_path_MAGIC_CMD="$ac_dir/${ac_tool_prefix}file"
if test -n "$file_magic_test_file"; then
case $deplibs_check_method in
"file_magic "*)
file_magic_regex=`expr "$deplibs_check_method" : "file_magic \(.*\)"`
MAGIC_CMD="$lt_cv_path_MAGIC_CMD"
if eval $file_magic_cmd \$file_magic_test_file 2> /dev/null |
$EGREP "$file_magic_regex" > /dev/null; then
:
else
cat <<_LT_EOF 1>&2
*** Warning: the command libtool uses to detect shared libraries,
*** $file_magic_cmd, produces output that libtool cannot recognize.
*** The result is that libtool may fail to recognize shared libraries
*** as such. This will affect the creation of libtool libraries that
*** depend on shared libraries, but programs linked with such libtool
*** libraries will work regardless of this problem. Nevertheless, you
*** may want to report the problem to your system manager and/or to
*** bug-libtool@gnu.org
_LT_EOF
fi ;;
esac
fi
break
fi
done
IFS="$lt_save_ifs"
MAGIC_CMD="$lt_save_MAGIC_CMD"
;;
esac
fi
MAGIC_CMD="$lt_cv_path_MAGIC_CMD"
if test -n "$MAGIC_CMD"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $MAGIC_CMD" >&5
$as_echo "$MAGIC_CMD" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
if test -z "$lt_cv_path_MAGIC_CMD"; then
if test -n "$ac_tool_prefix"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for file" >&5
$as_echo_n "checking for file... " >&6; }
if ${lt_cv_path_MAGIC_CMD+:} false; then :
$as_echo_n "(cached) " >&6
else
case $MAGIC_CMD in
[\\/*] | ?:[\\/]*)
lt_cv_path_MAGIC_CMD="$MAGIC_CMD" # Let the user override the test with a path.
;;
*)
lt_save_MAGIC_CMD="$MAGIC_CMD"
lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR
ac_dummy="/usr/bin$PATH_SEPARATOR$PATH"
for ac_dir in $ac_dummy; do
IFS="$lt_save_ifs"
test -z "$ac_dir" && ac_dir=.
if test -f $ac_dir/file; then
lt_cv_path_MAGIC_CMD="$ac_dir/file"
if test -n "$file_magic_test_file"; then
case $deplibs_check_method in
"file_magic "*)
file_magic_regex=`expr "$deplibs_check_method" : "file_magic \(.*\)"`
MAGIC_CMD="$lt_cv_path_MAGIC_CMD"
if eval $file_magic_cmd \$file_magic_test_file 2> /dev/null |
$EGREP "$file_magic_regex" > /dev/null; then
:
else
cat <<_LT_EOF 1>&2
*** Warning: the command libtool uses to detect shared libraries,
*** $file_magic_cmd, produces output that libtool cannot recognize.
*** The result is that libtool may fail to recognize shared libraries
*** as such. This will affect the creation of libtool libraries that
*** depend on shared libraries, but programs linked with such libtool
*** libraries will work regardless of this problem. Nevertheless, you
*** may want to report the problem to your system manager and/or to
*** bug-libtool@gnu.org
_LT_EOF
fi ;;
esac
fi
break
fi
done
IFS="$lt_save_ifs"
MAGIC_CMD="$lt_save_MAGIC_CMD"
;;
esac
fi
MAGIC_CMD="$lt_cv_path_MAGIC_CMD"
if test -n "$MAGIC_CMD"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $MAGIC_CMD" >&5
$as_echo "$MAGIC_CMD" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
else
MAGIC_CMD=:
fi
fi
fi
;;
esac
# Use C for the default configuration in the libtool script
lt_save_CC="$CC"
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
# Source file extension for C test sources.
ac_ext=c
# Object file extension for compiled C test sources.
objext=o
objext=$objext
# Code to be used in simple compile tests
lt_simple_compile_test_code="int some_variable = 0;"
# Code to be used in simple link tests
lt_simple_link_test_code='int main(){return(0);}'
# If no C compiler was specified, use CC.
LTCC=${LTCC-"$CC"}
# If no C compiler flags were specified, use CFLAGS.
LTCFLAGS=${LTCFLAGS-"$CFLAGS"}
# Allow CC to be a program name with arguments.
compiler=$CC
# Save the default compiler, since it gets overwritten when the other
# tags are being tested, and _LT_TAGVAR(compiler, []) is a NOP.
compiler_DEFAULT=$CC
# save warnings/boilerplate of simple test code
ac_outfile=conftest.$ac_objext
echo "$lt_simple_compile_test_code" >conftest.$ac_ext
eval "$ac_compile" 2>&1 >/dev/null | $SED '/^$/d; /^ *+/d' >conftest.err
_lt_compiler_boilerplate=`cat conftest.err`
$RM conftest*
ac_outfile=conftest.$ac_objext
echo "$lt_simple_link_test_code" >conftest.$ac_ext
eval "$ac_link" 2>&1 >/dev/null | $SED '/^$/d; /^ *+/d' >conftest.err
_lt_linker_boilerplate=`cat conftest.err`
$RM -r conftest*
## CAVEAT EMPTOR:
## There is no encapsulation within the following macros, do not change
## the running order or otherwise move them around unless you know exactly
## what you are doing...
if test -n "$compiler"; then
lt_prog_compiler_no_builtin_flag=
if test "$GCC" = yes; then
case $cc_basename in
nvcc*)
lt_prog_compiler_no_builtin_flag=' -Xcompiler -fno-builtin' ;;
*)
lt_prog_compiler_no_builtin_flag=' -fno-builtin' ;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler supports -fno-rtti -fno-exceptions" >&5
$as_echo_n "checking if $compiler supports -fno-rtti -fno-exceptions... " >&6; }
if ${lt_cv_prog_compiler_rtti_exceptions+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_rtti_exceptions=no
ac_outfile=conftest.$ac_objext
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="-fno-rtti -fno-exceptions"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
# The option is referenced via a variable to avoid confusing sed.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [^ ]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&5)
(eval "$lt_compile" 2>conftest.err)
ac_status=$?
cat conftest.err >&5
echo "$as_me:$LINENO: \$? = $ac_status" >&5
if (exit $ac_status) && test -s "$ac_outfile"; then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings other than the usual output.
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' >conftest.exp
$SED '/^$/d; /^ *+/d' conftest.err >conftest.er2
if test ! -s conftest.er2 || diff conftest.exp conftest.er2 >/dev/null; then
lt_cv_prog_compiler_rtti_exceptions=yes
fi
fi
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_rtti_exceptions" >&5
$as_echo "$lt_cv_prog_compiler_rtti_exceptions" >&6; }
if test x"$lt_cv_prog_compiler_rtti_exceptions" = xyes; then
lt_prog_compiler_no_builtin_flag="$lt_prog_compiler_no_builtin_flag -fno-rtti -fno-exceptions"
else
:
fi
fi
lt_prog_compiler_wl=
lt_prog_compiler_pic=
lt_prog_compiler_static=
if test "$GCC" = yes; then
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_static='-static'
case $host_os in
aix*)
# All AIX code is PIC.
if test "$host_cpu" = ia64; then
# AIX 5 now supports IA64 processor
lt_prog_compiler_static='-Bstatic'
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# see comment about AmigaOS4 .so support
lt_prog_compiler_pic='-fPIC'
;;
m68k)
# FIXME: we need at least 68020 code to build shared libraries, but
# adding the `-m68020' flag to GCC prevents building anything better,
# like `-m68040'.
lt_prog_compiler_pic='-m68020 -resident32 -malways-restore-a4'
;;
esac
;;
beos* | irix5* | irix6* | nonstopux* | osf3* | osf4* | osf5*)
# PIC is the default for these OSes.
;;
mingw* | cygwin* | pw32* | os2* | cegcc*)
# This hack is so that the source file can tell whether it is being
# built for inclusion in a dll (and should export symbols for example).
# Although the cygwin gcc ignores -fPIC, still need this for old-style
# (--disable-auto-import) libraries
lt_prog_compiler_pic='-DDLL_EXPORT'
;;
darwin* | rhapsody*)
# PIC is the default on this platform
# Common symbols not allowed in MH_DYLIB files
lt_prog_compiler_pic='-fno-common'
;;
haiku*)
# PIC is the default for Haiku.
# The "-static" flag exists, but is broken.
lt_prog_compiler_static=
;;
hpux*)
# PIC is the default for 64-bit PA HP-UX, but not for 32-bit
# PA HP-UX. On IA64 HP-UX, PIC is the default but the pic flag
# sets the default TLS model and affects inlining.
case $host_cpu in
hppa*64*)
# +Z the default
;;
*)
lt_prog_compiler_pic='-fPIC'
;;
esac
;;
interix[3-9]*)
# Interix 3.x gcc -fpic/-fPIC options generate broken code.
# Instead, we relocate shared libraries at runtime.
;;
msdosdjgpp*)
# Just because we use GCC doesn't mean we suddenly get shared libraries
# on systems that don't support them.
lt_prog_compiler_can_build_shared=no
enable_shared=no
;;
*nto* | *qnx*)
# QNX uses GNU C++, but need to define -shared option too, otherwise
# it will coredump.
lt_prog_compiler_pic='-fPIC -shared'
;;
sysv4*MP*)
if test -d /usr/nec; then
lt_prog_compiler_pic=-Kconform_pic
fi
;;
*)
lt_prog_compiler_pic='-fPIC'
;;
esac
case $cc_basename in
nvcc*) # Cuda Compiler Driver 2.2
lt_prog_compiler_wl='-Xlinker '
if test -n "$lt_prog_compiler_pic"; then
lt_prog_compiler_pic="-Xcompiler $lt_prog_compiler_pic"
fi
;;
esac
else
# PORTME Check for flag to pass linker flags through the system compiler.
case $host_os in
aix*)
lt_prog_compiler_wl='-Wl,'
if test "$host_cpu" = ia64; then
# AIX 5 now supports IA64 processor
lt_prog_compiler_static='-Bstatic'
else
lt_prog_compiler_static='-bnso -bI:/lib/syscalls.exp'
fi
;;
mingw* | cygwin* | pw32* | os2* | cegcc*)
# This hack is so that the source file can tell whether it is being
# built for inclusion in a dll (and should export symbols for example).
lt_prog_compiler_pic='-DDLL_EXPORT'
;;
hpux9* | hpux10* | hpux11*)
lt_prog_compiler_wl='-Wl,'
# PIC is the default for IA64 HP-UX and 64-bit HP-UX, but
# not for PA HP-UX.
case $host_cpu in
hppa*64*|ia64*)
# +Z the default
;;
*)
lt_prog_compiler_pic='+Z'
;;
esac
# Is there a better lt_prog_compiler_static that works with the bundled CC?
lt_prog_compiler_static='${wl}-a ${wl}archive'
;;
irix5* | irix6* | nonstopux*)
lt_prog_compiler_wl='-Wl,'
# PIC (with -KPIC) is the default.
lt_prog_compiler_static='-non_shared'
;;
linux* | k*bsd*-gnu | kopensolaris*-gnu)
case $cc_basename in
# old Intel for x86_64 which still supported -KPIC.
ecc*)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='-KPIC'
lt_prog_compiler_static='-static'
;;
# icc used to be incompatible with GCC.
# ICC 10 doesn't accept -KPIC any more.
icc* | ifort*)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='-fPIC'
lt_prog_compiler_static='-static'
;;
# Lahey Fortran 8.1.
lf95*)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='--shared'
lt_prog_compiler_static='--static'
;;
nagfor*)
# NAG Fortran compiler
lt_prog_compiler_wl='-Wl,-Wl,,'
lt_prog_compiler_pic='-PIC'
lt_prog_compiler_static='-Bstatic'
;;
pgcc* | pgf77* | pgf90* | pgf95* | pgfortran*)
# Portland Group compilers (*not* the Pentium gcc compiler,
# which looks to be a dead project)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='-fpic'
lt_prog_compiler_static='-Bstatic'
;;
ccc*)
lt_prog_compiler_wl='-Wl,'
# All Alpha code is PIC.
lt_prog_compiler_static='-non_shared'
;;
xl* | bgxl* | bgf* | mpixl*)
# IBM XL C 8.0/Fortran 10.1, 11.1 on PPC and BlueGene
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='-qpic'
lt_prog_compiler_static='-qstaticlink'
;;
*)
case `$CC -V 2>&1 | sed 5q` in
*Sun\ Ceres\ Fortran* | *Sun*Fortran*\ [1-7].* | *Sun*Fortran*\ 8.[0-3]*)
# Sun Fortran 8.3 passes all unrecognized flags to the linker
lt_prog_compiler_pic='-KPIC'
lt_prog_compiler_static='-Bstatic'
lt_prog_compiler_wl=''
;;
*Sun\ F* | *Sun*Fortran*)
lt_prog_compiler_pic='-KPIC'
lt_prog_compiler_static='-Bstatic'
lt_prog_compiler_wl='-Qoption ld '
;;
*Sun\ C*)
# Sun C 5.9
lt_prog_compiler_pic='-KPIC'
lt_prog_compiler_static='-Bstatic'
lt_prog_compiler_wl='-Wl,'
;;
*Intel*\ [CF]*Compiler*)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='-fPIC'
lt_prog_compiler_static='-static'
;;
*Portland\ Group*)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='-fpic'
lt_prog_compiler_static='-Bstatic'
;;
esac
;;
esac
;;
newsos6)
lt_prog_compiler_pic='-KPIC'
lt_prog_compiler_static='-Bstatic'
;;
*nto* | *qnx*)
# QNX uses GNU C++, but need to define -shared option too, otherwise
# it will coredump.
lt_prog_compiler_pic='-fPIC -shared'
;;
osf3* | osf4* | osf5*)
lt_prog_compiler_wl='-Wl,'
# All OSF/1 code is PIC.
lt_prog_compiler_static='-non_shared'
;;
rdos*)
lt_prog_compiler_static='-non_shared'
;;
solaris*)
lt_prog_compiler_pic='-KPIC'
lt_prog_compiler_static='-Bstatic'
case $cc_basename in
f77* | f90* | f95* | sunf77* | sunf90* | sunf95*)
lt_prog_compiler_wl='-Qoption ld ';;
*)
lt_prog_compiler_wl='-Wl,';;
esac
;;
sunos4*)
lt_prog_compiler_wl='-Qoption ld '
lt_prog_compiler_pic='-PIC'
lt_prog_compiler_static='-Bstatic'
;;
sysv4 | sysv4.2uw2* | sysv4.3*)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='-KPIC'
lt_prog_compiler_static='-Bstatic'
;;
sysv4*MP*)
if test -d /usr/nec ;then
lt_prog_compiler_pic='-Kconform_pic'
lt_prog_compiler_static='-Bstatic'
fi
;;
sysv5* | unixware* | sco3.2v5* | sco5v6* | OpenUNIX*)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_pic='-KPIC'
lt_prog_compiler_static='-Bstatic'
;;
unicos*)
lt_prog_compiler_wl='-Wl,'
lt_prog_compiler_can_build_shared=no
;;
uts4*)
lt_prog_compiler_pic='-pic'
lt_prog_compiler_static='-Bstatic'
;;
*)
lt_prog_compiler_can_build_shared=no
;;
esac
fi
case $host_os in
# For platforms which do not support PIC, -DPIC is meaningless:
*djgpp*)
lt_prog_compiler_pic=
;;
*)
lt_prog_compiler_pic="$lt_prog_compiler_pic -DPIC"
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $compiler option to produce PIC" >&5
$as_echo_n "checking for $compiler option to produce PIC... " >&6; }
if ${lt_cv_prog_compiler_pic+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_pic=$lt_prog_compiler_pic
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_pic" >&5
$as_echo "$lt_cv_prog_compiler_pic" >&6; }
lt_prog_compiler_pic=$lt_cv_prog_compiler_pic
#
# Check to make sure the PIC flag actually works.
#
if test -n "$lt_prog_compiler_pic"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler PIC flag $lt_prog_compiler_pic works" >&5
$as_echo_n "checking if $compiler PIC flag $lt_prog_compiler_pic works... " >&6; }
if ${lt_cv_prog_compiler_pic_works+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_pic_works=no
ac_outfile=conftest.$ac_objext
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="$lt_prog_compiler_pic -DPIC"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
# The option is referenced via a variable to avoid confusing sed.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [^ ]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&5)
(eval "$lt_compile" 2>conftest.err)
ac_status=$?
cat conftest.err >&5
echo "$as_me:$LINENO: \$? = $ac_status" >&5
if (exit $ac_status) && test -s "$ac_outfile"; then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings other than the usual output.
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' >conftest.exp
$SED '/^$/d; /^ *+/d' conftest.err >conftest.er2
if test ! -s conftest.er2 || diff conftest.exp conftest.er2 >/dev/null; then
lt_cv_prog_compiler_pic_works=yes
fi
fi
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_pic_works" >&5
$as_echo "$lt_cv_prog_compiler_pic_works" >&6; }
if test x"$lt_cv_prog_compiler_pic_works" = xyes; then
case $lt_prog_compiler_pic in
"" | " "*) ;;
*) lt_prog_compiler_pic=" $lt_prog_compiler_pic" ;;
esac
else
lt_prog_compiler_pic=
lt_prog_compiler_can_build_shared=no
fi
fi
#
# Check to make sure the static flag actually works.
#
wl=$lt_prog_compiler_wl eval lt_tmp_static_flag=\"$lt_prog_compiler_static\"
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler static flag $lt_tmp_static_flag works" >&5
$as_echo_n "checking if $compiler static flag $lt_tmp_static_flag works... " >&6; }
if ${lt_cv_prog_compiler_static_works+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_static_works=no
save_LDFLAGS="$LDFLAGS"
LDFLAGS="$LDFLAGS $lt_tmp_static_flag"
echo "$lt_simple_link_test_code" > conftest.$ac_ext
if (eval $ac_link 2>conftest.err) && test -s conftest$ac_exeext; then
# The linker can only warn and ignore the option if not recognized
# So say no if there are warnings
if test -s conftest.err; then
# Append any errors to the config.log.
cat conftest.err 1>&5
$ECHO "$_lt_linker_boilerplate" | $SED '/^$/d' > conftest.exp
$SED '/^$/d; /^ *+/d' conftest.err >conftest.er2
if diff conftest.exp conftest.er2 >/dev/null; then
lt_cv_prog_compiler_static_works=yes
fi
else
lt_cv_prog_compiler_static_works=yes
fi
fi
$RM -r conftest*
LDFLAGS="$save_LDFLAGS"
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_static_works" >&5
$as_echo "$lt_cv_prog_compiler_static_works" >&6; }
if test x"$lt_cv_prog_compiler_static_works" = xyes; then
:
else
lt_prog_compiler_static=
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler supports -c -o file.$ac_objext" >&5
$as_echo_n "checking if $compiler supports -c -o file.$ac_objext... " >&6; }
if ${lt_cv_prog_compiler_c_o+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_c_o=no
$RM -r conftest 2>/dev/null
mkdir conftest
cd conftest
mkdir out
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="-o out/conftest2.$ac_objext"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [^ ]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&5)
(eval "$lt_compile" 2>out/conftest.err)
ac_status=$?
cat out/conftest.err >&5
echo "$as_me:$LINENO: \$? = $ac_status" >&5
if (exit $ac_status) && test -s out/conftest2.$ac_objext
then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' > out/conftest.exp
$SED '/^$/d; /^ *+/d' out/conftest.err >out/conftest.er2
if test ! -s out/conftest.er2 || diff out/conftest.exp out/conftest.er2 >/dev/null; then
lt_cv_prog_compiler_c_o=yes
fi
fi
chmod u+w . 2>&5
$RM conftest*
# SGI C++ compiler will create directory out/ii_files/ for
# template instantiation
test -d out/ii_files && $RM out/ii_files/* && rmdir out/ii_files
$RM out/* && rmdir out
cd ..
$RM -r conftest
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_c_o" >&5
$as_echo "$lt_cv_prog_compiler_c_o" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler supports -c -o file.$ac_objext" >&5
$as_echo_n "checking if $compiler supports -c -o file.$ac_objext... " >&6; }
if ${lt_cv_prog_compiler_c_o+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_c_o=no
$RM -r conftest 2>/dev/null
mkdir conftest
cd conftest
mkdir out
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="-o out/conftest2.$ac_objext"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [^ ]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&5)
(eval "$lt_compile" 2>out/conftest.err)
ac_status=$?
cat out/conftest.err >&5
echo "$as_me:$LINENO: \$? = $ac_status" >&5
if (exit $ac_status) && test -s out/conftest2.$ac_objext
then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' > out/conftest.exp
$SED '/^$/d; /^ *+/d' out/conftest.err >out/conftest.er2
if test ! -s out/conftest.er2 || diff out/conftest.exp out/conftest.er2 >/dev/null; then
lt_cv_prog_compiler_c_o=yes
fi
fi
chmod u+w . 2>&5
$RM conftest*
# SGI C++ compiler will create directory out/ii_files/ for
# template instantiation
test -d out/ii_files && $RM out/ii_files/* && rmdir out/ii_files
$RM out/* && rmdir out
cd ..
$RM -r conftest
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_c_o" >&5
$as_echo "$lt_cv_prog_compiler_c_o" >&6; }
hard_links="nottested"
if test "$lt_cv_prog_compiler_c_o" = no && test "$need_locks" != no; then
# do not overwrite the value of need_locks provided by the user
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if we can lock with hard links" >&5
$as_echo_n "checking if we can lock with hard links... " >&6; }
hard_links=yes
$RM conftest*
ln conftest.a conftest.b 2>/dev/null && hard_links=no
touch conftest.a
ln conftest.a conftest.b 2>&5 || hard_links=no
ln conftest.a conftest.b 2>/dev/null && hard_links=no
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $hard_links" >&5
$as_echo "$hard_links" >&6; }
if test "$hard_links" = no; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: \`$CC' does not support \`-c -o', so \`make -j' may be unsafe" >&5
$as_echo "$as_me: WARNING: \`$CC' does not support \`-c -o', so \`make -j' may be unsafe" >&2;}
need_locks=warn
fi
else
need_locks=no
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether the $compiler linker ($LD) supports shared libraries" >&5
$as_echo_n "checking whether the $compiler linker ($LD) supports shared libraries... " >&6; }
runpath_var=
allow_undefined_flag=
always_export_symbols=no
archive_cmds=
archive_expsym_cmds=
compiler_needs_object=no
enable_shared_with_static_runtimes=no
export_dynamic_flag_spec=
export_symbols_cmds='$NM $libobjs $convenience | $global_symbol_pipe | $SED '\''s/.* //'\'' | sort | uniq > $export_symbols'
hardcode_automatic=no
hardcode_direct=no
hardcode_direct_absolute=no
hardcode_libdir_flag_spec=
hardcode_libdir_separator=
hardcode_minus_L=no
hardcode_shlibpath_var=unsupported
inherit_rpath=no
link_all_deplibs=unknown
module_cmds=
module_expsym_cmds=
old_archive_from_new_cmds=
old_archive_from_expsyms_cmds=
thread_safe_flag_spec=
whole_archive_flag_spec=
# include_expsyms should be a list of space-separated symbols to be *always*
# included in the symbol list
include_expsyms=
# exclude_expsyms can be an extended regexp of symbols to exclude
# it will be wrapped by ` (' and `)$', so one must not match beginning or
# end of line. Example: `a|bc|.*d.*' will exclude the symbols `a' and `bc',
# as well as any symbol that contains `d'.
exclude_expsyms='_GLOBAL_OFFSET_TABLE_|_GLOBAL__F[ID]_.*'
# Although _GLOBAL_OFFSET_TABLE_ is a valid symbol C name, most a.out
# platforms (ab)use it in PIC code, but their linkers get confused if
# the symbol is explicitly referenced. Since portable code cannot
# rely on this symbol name, it's probably fine to never include it in
# preloaded symbol tables.
# Exclude shared library initialization/finalization symbols.
extract_expsyms_cmds=
case $host_os in
cygwin* | mingw* | pw32* | cegcc*)
# FIXME: the MSVC++ port hasn't been tested in a loooong time
# When not using gcc, we currently assume that we are using
# Microsoft Visual C++.
if test "$GCC" != yes; then
with_gnu_ld=no
fi
;;
interix*)
# we just hope/assume this is gcc and not c89 (= MSVC++)
with_gnu_ld=yes
;;
openbsd*)
with_gnu_ld=no
;;
esac
ld_shlibs=yes
# On some targets, GNU ld is compatible enough with the native linker
# that we're better off using the native interface for both.
lt_use_gnu_ld_interface=no
if test "$with_gnu_ld" = yes; then
case $host_os in
aix*)
# The AIX port of GNU ld has always aspired to compatibility
# with the native linker. However, as the warning in the GNU ld
# block says, versions before 2.19.5* couldn't really create working
# shared libraries, regardless of the interface used.
case `$LD -v 2>&1` in
*\ \(GNU\ Binutils\)\ 2.19.5*) ;;
*\ \(GNU\ Binutils\)\ 2.[2-9]*) ;;
*\ \(GNU\ Binutils\)\ [3-9]*) ;;
*)
lt_use_gnu_ld_interface=yes
;;
esac
;;
*)
lt_use_gnu_ld_interface=yes
;;
esac
fi
if test "$lt_use_gnu_ld_interface" = yes; then
# If archive_cmds runs LD, not CC, wlarc should be empty
wlarc='${wl}'
# Set some defaults for GNU ld with shared library support. These
# are reset later if shared libraries are not supported. Putting them
# here allows them to be overridden if necessary.
runpath_var=LD_RUN_PATH
hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir'
export_dynamic_flag_spec='${wl}--export-dynamic'
# ancient GNU ld didn't support --whole-archive et. al.
if $LD --help 2>&1 | $GREP 'no-whole-archive' > /dev/null; then
whole_archive_flag_spec="$wlarc"'--whole-archive$convenience '"$wlarc"'--no-whole-archive'
else
whole_archive_flag_spec=
fi
supports_anon_versioning=no
case `$LD -v 2>&1` in
*GNU\ gold*) supports_anon_versioning=yes ;;
*\ [01].* | *\ 2.[0-9].* | *\ 2.10.*) ;; # catch versions < 2.11
*\ 2.11.93.0.2\ *) supports_anon_versioning=yes ;; # RH7.3 ...
*\ 2.11.92.0.12\ *) supports_anon_versioning=yes ;; # Mandrake 8.2 ...
*\ 2.11.*) ;; # other 2.11 versions
*) supports_anon_versioning=yes ;;
esac
# See if GNU ld supports shared libraries.
case $host_os in
aix[3-9]*)
# On AIX/PPC, the GNU linker is very broken
if test "$host_cpu" != ia64; then
ld_shlibs=no
cat <<_LT_EOF 1>&2
*** Warning: the GNU linker, at least up to release 2.19, is reported
*** to be unable to reliably create shared libraries on AIX.
*** Therefore, libtool is disabling shared libraries support. If you
*** really care for shared libraries, you may want to install binutils
*** 2.20 or above, or modify your PATH so that a non-GNU linker is found.
*** You will then need to restart the configuration process.
_LT_EOF
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# see comment about AmigaOS4 .so support
archive_cmds='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds=''
;;
m68k)
archive_cmds='$RM $output_objdir/a2ixlibrary.data~$ECHO "#define NAME $libname" > $output_objdir/a2ixlibrary.data~$ECHO "#define LIBRARY_ID 1" >> $output_objdir/a2ixlibrary.data~$ECHO "#define VERSION $major" >> $output_objdir/a2ixlibrary.data~$ECHO "#define REVISION $revision" >> $output_objdir/a2ixlibrary.data~$AR $AR_FLAGS $lib $libobjs~$RANLIB $lib~(cd $output_objdir && a2ixlibrary -32)'
hardcode_libdir_flag_spec='-L$libdir'
hardcode_minus_L=yes
;;
esac
;;
beos*)
if $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
allow_undefined_flag=unsupported
# Joseph Beckenbach says some releases of gcc
# support --undefined. This deserves some investigation. FIXME
archive_cmds='$CC -nostart $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
else
ld_shlibs=no
fi
;;
cygwin* | mingw* | pw32* | cegcc*)
# _LT_TAGVAR(hardcode_libdir_flag_spec, ) is actually meaningless,
# as there is no search path for DLLs.
hardcode_libdir_flag_spec='-L$libdir'
export_dynamic_flag_spec='${wl}--export-all-symbols'
allow_undefined_flag=unsupported
always_export_symbols=no
enable_shared_with_static_runtimes=yes
export_symbols_cmds='$NM $libobjs $convenience | $global_symbol_pipe | $SED -e '\''/^[BCDGRS][ ]/s/.*[ ]\([^ ]*\)/\1 DATA/;s/^.*[ ]__nm__\([^ ]*\)[ ][^ ]*/\1 DATA/;/^I[ ]/d;/^[AITW][ ]/s/.* //'\'' | sort | uniq > $export_symbols'
exclude_expsyms='[_]+GLOBAL_OFFSET_TABLE_|[_]+GLOBAL__[FID]_.*|[_]+head_[A-Za-z0-9_]+_dll|[A-Za-z0-9_]+_dll_iname'
if $LD --help 2>&1 | $GREP 'auto-import' > /dev/null; then
archive_cmds='$CC -shared $libobjs $deplibs $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib'
# If the export-symbols file already is a .def file (1st line
# is EXPORTS), use it as is; otherwise, prepend...
archive_expsym_cmds='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then
cp $export_symbols $output_objdir/$soname.def;
else
echo EXPORTS > $output_objdir/$soname.def;
cat $export_symbols >> $output_objdir/$soname.def;
fi~
$CC -shared $output_objdir/$soname.def $libobjs $deplibs $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib'
else
ld_shlibs=no
fi
;;
haiku*)
archive_cmds='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
link_all_deplibs=yes
;;
interix[3-9]*)
hardcode_direct=no
hardcode_shlibpath_var=no
hardcode_libdir_flag_spec='${wl}-rpath,$libdir'
export_dynamic_flag_spec='${wl}-E'
# Hack: On Interix 3.x, we cannot compile PIC because of a broken gcc.
# Instead, shared libraries are loaded at an image base (0x10000000 by
# default) and relocated if they conflict, which is a slow very memory
# consuming and fragmenting process. To avoid this, we pick a random,
# 256 KiB-aligned image base between 0x50000000 and 0x6FFC0000 at link
# time. Moving up from 0x10000000 also allows more sbrk(2) space.
archive_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib'
archive_expsym_cmds='sed "s,^,_," $export_symbols >$output_objdir/$soname.expsym~$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--retain-symbols-file,$output_objdir/$soname.expsym ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib'
;;
gnu* | linux* | tpf* | k*bsd*-gnu | kopensolaris*-gnu)
tmp_diet=no
if test "$host_os" = linux-dietlibc; then
case $cc_basename in
diet\ *) tmp_diet=yes;; # linux-dietlibc with static linking (!diet-dyn)
esac
fi
if $LD --help 2>&1 | $EGREP ': supported targets:.* elf' > /dev/null \
&& test "$tmp_diet" = no
then
tmp_addflag=' $pic_flag'
tmp_sharedflag='-shared'
case $cc_basename,$host_cpu in
pgcc*) # Portland Group C compiler
whole_archive_flag_spec='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
tmp_addflag=' $pic_flag'
;;
pgf77* | pgf90* | pgf95* | pgfortran*)
# Portland Group f77 and f90 compilers
whole_archive_flag_spec='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
tmp_addflag=' $pic_flag -Mnomain' ;;
ecc*,ia64* | icc*,ia64*) # Intel C compiler on ia64
tmp_addflag=' -i_dynamic' ;;
efc*,ia64* | ifort*,ia64*) # Intel Fortran compiler on ia64
tmp_addflag=' -i_dynamic -nofor_main' ;;
ifc* | ifort*) # Intel Fortran compiler
tmp_addflag=' -nofor_main' ;;
lf95*) # Lahey Fortran 8.1
whole_archive_flag_spec=
tmp_sharedflag='--shared' ;;
xl[cC]* | bgxl[cC]* | mpixl[cC]*) # IBM XL C 8.0 on PPC (deal with xlf below)
tmp_sharedflag='-qmkshrobj'
tmp_addflag= ;;
nvcc*) # Cuda Compiler Driver 2.2
whole_archive_flag_spec='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
compiler_needs_object=yes
;;
esac
case `$CC -V 2>&1 | sed 5q` in
*Sun\ C*) # Sun C 5.9
whole_archive_flag_spec='${wl}--whole-archive`new_convenience=; for conv in $convenience\"\"; do test -z \"$conv\" || new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
compiler_needs_object=yes
tmp_sharedflag='-G' ;;
*Sun\ F*) # Sun Fortran 8.3
tmp_sharedflag='-G' ;;
esac
archive_cmds='$CC '"$tmp_sharedflag""$tmp_addflag"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
if test "x$supports_anon_versioning" = xyes; then
archive_expsym_cmds='echo "{ global:" > $output_objdir/$libname.ver~
cat $export_symbols | sed -e "s/\(.*\)/\1;/" >> $output_objdir/$libname.ver~
echo "local: *; };" >> $output_objdir/$libname.ver~
$CC '"$tmp_sharedflag""$tmp_addflag"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-version-script ${wl}$output_objdir/$libname.ver -o $lib'
fi
case $cc_basename in
xlf* | bgf* | bgxlf* | mpixlf*)
# IBM XL Fortran 10.1 on PPC cannot create shared libs itself
whole_archive_flag_spec='--whole-archive$convenience --no-whole-archive'
hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir'
archive_cmds='$LD -shared $libobjs $deplibs $linker_flags -soname $soname -o $lib'
if test "x$supports_anon_versioning" = xyes; then
archive_expsym_cmds='echo "{ global:" > $output_objdir/$libname.ver~
cat $export_symbols | sed -e "s/\(.*\)/\1;/" >> $output_objdir/$libname.ver~
echo "local: *; };" >> $output_objdir/$libname.ver~
$LD -shared $libobjs $deplibs $linker_flags -soname $soname -version-script $output_objdir/$libname.ver -o $lib'
fi
;;
esac
else
ld_shlibs=no
fi
;;
netbsd*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
archive_cmds='$LD -Bshareable $libobjs $deplibs $linker_flags -o $lib'
wlarc=
else
archive_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
fi
;;
solaris*)
if $LD -v 2>&1 | $GREP 'BFD 2\.8' > /dev/null; then
ld_shlibs=no
cat <<_LT_EOF 1>&2
*** Warning: The releases 2.8.* of the GNU linker cannot reliably
*** create shared libraries on Solaris systems. Therefore, libtool
*** is disabling shared libraries support. We urge you to upgrade GNU
*** binutils to release 2.9.1 or newer. Another option is to modify
*** your PATH or compiler configuration so that the native linker is
*** used, and then restart.
_LT_EOF
elif $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
archive_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
else
ld_shlibs=no
fi
;;
sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX*)
case `$LD -v 2>&1` in
*\ [01].* | *\ 2.[0-9].* | *\ 2.1[0-5].*)
ld_shlibs=no
cat <<_LT_EOF 1>&2
*** Warning: Releases of the GNU linker prior to 2.16.91.0.3 can not
*** reliably create shared libraries on SCO systems. Therefore, libtool
*** is disabling shared libraries support. We urge you to upgrade GNU
*** binutils to release 2.16.91.0.3 or newer. Another option is to modify
*** your PATH or compiler configuration so that the native linker is
*** used, and then restart.
_LT_EOF
;;
*)
# For security reasons, it is highly recommended that you always
# use absolute paths for naming shared libraries, and exclude the
# DT_RUNPATH tag from executables and libraries. But doing so
# requires that you compile everything twice, which is a pain.
if $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir'
archive_cmds='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
else
ld_shlibs=no
fi
;;
esac
;;
sunos4*)
archive_cmds='$LD -assert pure-text -Bshareable -o $lib $libobjs $deplibs $linker_flags'
wlarc=
hardcode_direct=yes
hardcode_shlibpath_var=no
;;
*)
if $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
archive_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
else
ld_shlibs=no
fi
;;
esac
if test "$ld_shlibs" = no; then
runpath_var=
hardcode_libdir_flag_spec=
export_dynamic_flag_spec=
whole_archive_flag_spec=
fi
else
# PORTME fill in a description of your system's linker (not GNU ld)
case $host_os in
aix3*)
allow_undefined_flag=unsupported
always_export_symbols=yes
archive_expsym_cmds='$LD -o $output_objdir/$soname $libobjs $deplibs $linker_flags -bE:$export_symbols -T512 -H512 -bM:SRE~$AR $AR_FLAGS $lib $output_objdir/$soname'
# Note: this linker hardcodes the directories in LIBPATH if there
# are no directories specified by -L.
hardcode_minus_L=yes
if test "$GCC" = yes && test -z "$lt_prog_compiler_static"; then
# Neither direct hardcoding nor static linking is supported with a
# broken collect2.
hardcode_direct=unsupported
fi
;;
aix[4-9]*)
if test "$host_cpu" = ia64; then
# On IA64, the linker does run time linking by default, so we don't
# have to do anything special.
aix_use_runtimelinking=no
exp_sym_flag='-Bexport'
no_entry_flag=""
else
# If we're using GNU nm, then we don't want the "-C" option.
# -C means demangle to AIX nm, but means don't demangle with GNU nm
# Also, AIX nm treats weak defined symbols like other global
# defined symbols, whereas GNU nm marks them as "W".
if $NM -V 2>&1 | $GREP 'GNU' > /dev/null; then
export_symbols_cmds='$NM -Bpg $libobjs $convenience | awk '\''{ if (((\$ 2 == "T") || (\$ 2 == "D") || (\$ 2 == "B") || (\$ 2 == "W")) && (substr(\$ 3,1,1) != ".")) { print \$ 3 } }'\'' | sort -u > $export_symbols'
else
export_symbols_cmds='$NM -BCpg $libobjs $convenience | awk '\''{ if (((\$ 2 == "T") || (\$ 2 == "D") || (\$ 2 == "B")) && (substr(\$ 3,1,1) != ".")) { print \$ 3 } }'\'' | sort -u > $export_symbols'
fi
aix_use_runtimelinking=no
# Test if we are trying to use run time linking or normal
# AIX style linking. If -brtl is somewhere in LDFLAGS, we
# need to do runtime linking.
case $host_os in aix4.[23]|aix4.[23].*|aix[5-9]*)
for ld_flag in $LDFLAGS; do
if (test $ld_flag = "-brtl" || test $ld_flag = "-Wl,-brtl"); then
aix_use_runtimelinking=yes
break
fi
done
;;
esac
exp_sym_flag='-bexport'
no_entry_flag='-bnoentry'
fi
# When large executables or shared objects are built, AIX ld can
# have problems creating the table of contents. If linking a library
# or program results in "error TOC overflow" add -mminimal-toc to
# CXXFLAGS/CFLAGS for g++/gcc. In the cases where that is not
# enough to fix the problem, add -Wl,-bbigtoc to LDFLAGS.
archive_cmds=''
hardcode_direct=yes
hardcode_direct_absolute=yes
hardcode_libdir_separator=':'
link_all_deplibs=yes
file_list_spec='${wl}-f,'
if test "$GCC" = yes; then
case $host_os in aix4.[012]|aix4.[012].*)
# We only want to do this on AIX 4.2 and lower, the check
# below for broken collect2 doesn't work under 4.3+
collect2name=`${CC} -print-prog-name=collect2`
if test -f "$collect2name" &&
strings "$collect2name" | $GREP resolve_lib_name >/dev/null
then
# We have reworked collect2
:
else
# We have old collect2
hardcode_direct=unsupported
# It fails to find uninstalled libraries when the uninstalled
# path is not listed in the libpath. Setting hardcode_minus_L
# to unsupported forces relinking
hardcode_minus_L=yes
hardcode_libdir_flag_spec='-L$libdir'
hardcode_libdir_separator=
fi
;;
esac
shared_flag='-shared'
if test "$aix_use_runtimelinking" = yes; then
shared_flag="$shared_flag "'${wl}-G'
fi
else
# not using gcc
if test "$host_cpu" = ia64; then
# VisualAge C++, Version 5.5 for AIX 5L for IA-64, Beta 3 Release
# chokes on -Wl,-G. The following line is correct:
shared_flag='-G'
else
if test "$aix_use_runtimelinking" = yes; then
shared_flag='${wl}-G'
else
shared_flag='${wl}-bM:SRE'
fi
fi
fi
export_dynamic_flag_spec='${wl}-bexpall'
# It seems that -bexpall does not export symbols beginning with
# underscore (_), so it is better to generate a list of symbols to export.
always_export_symbols=yes
if test "$aix_use_runtimelinking" = yes; then
# Warning - without using the other runtime loading flags (-brtl),
# -berok will link without error, but may produce a broken library.
allow_undefined_flag='-berok'
# Determine the default libpath from the value encoded in an
# empty executable.
if test "${lt_cv_aix_libpath+set}" = set; then
aix_libpath=$lt_cv_aix_libpath
else
if ${lt_cv_aix_libpath_+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
lt_aix_libpath_sed='
/Import File Strings/,/^$/ {
/^0/ {
s/^0 *\([^ ]*\) *$/\1/
p
}
}'
lt_cv_aix_libpath_=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
# Check for a 64-bit object if we didn't find anything.
if test -z "$lt_cv_aix_libpath_"; then
lt_cv_aix_libpath_=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
fi
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
if test -z "$lt_cv_aix_libpath_"; then
lt_cv_aix_libpath_="/usr/lib:/lib"
fi
fi
aix_libpath=$lt_cv_aix_libpath_
fi
hardcode_libdir_flag_spec='${wl}-blibpath:$libdir:'"$aix_libpath"
archive_expsym_cmds='$CC -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags `if test "x${allow_undefined_flag}" != "x"; then func_echo_all "${wl}${allow_undefined_flag}"; else :; fi` '"\${wl}$exp_sym_flag:\$export_symbols $shared_flag"
else
if test "$host_cpu" = ia64; then
hardcode_libdir_flag_spec='${wl}-R $libdir:/usr/lib:/lib'
allow_undefined_flag="-z nodefs"
archive_expsym_cmds="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags ${wl}${allow_undefined_flag} '"\${wl}$exp_sym_flag:\$export_symbols"
else
# Determine the default libpath from the value encoded in an
# empty executable.
if test "${lt_cv_aix_libpath+set}" = set; then
aix_libpath=$lt_cv_aix_libpath
else
if ${lt_cv_aix_libpath_+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
lt_aix_libpath_sed='
/Import File Strings/,/^$/ {
/^0/ {
s/^0 *\([^ ]*\) *$/\1/
p
}
}'
lt_cv_aix_libpath_=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
# Check for a 64-bit object if we didn't find anything.
if test -z "$lt_cv_aix_libpath_"; then
lt_cv_aix_libpath_=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
fi
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
if test -z "$lt_cv_aix_libpath_"; then
lt_cv_aix_libpath_="/usr/lib:/lib"
fi
fi
aix_libpath=$lt_cv_aix_libpath_
fi
hardcode_libdir_flag_spec='${wl}-blibpath:$libdir:'"$aix_libpath"
# Warning - without using the other run time loading flags,
# -berok will link without error, but may produce a broken library.
no_undefined_flag=' ${wl}-bernotok'
allow_undefined_flag=' ${wl}-berok'
if test "$with_gnu_ld" = yes; then
# We only use this code for GNU lds that support --whole-archive.
whole_archive_flag_spec='${wl}--whole-archive$convenience ${wl}--no-whole-archive'
else
# Exported symbols can be pulled into shared objects from archives
whole_archive_flag_spec='$convenience'
fi
archive_cmds_need_lc=yes
# This is similar to how AIX traditionally builds its shared libraries.
archive_expsym_cmds="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs ${wl}-bnoentry $compiler_flags ${wl}-bE:$export_symbols${allow_undefined_flag}~$AR $AR_FLAGS $output_objdir/$libname$release.a $output_objdir/$soname'
fi
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# see comment about AmigaOS4 .so support
archive_cmds='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds=''
;;
m68k)
archive_cmds='$RM $output_objdir/a2ixlibrary.data~$ECHO "#define NAME $libname" > $output_objdir/a2ixlibrary.data~$ECHO "#define LIBRARY_ID 1" >> $output_objdir/a2ixlibrary.data~$ECHO "#define VERSION $major" >> $output_objdir/a2ixlibrary.data~$ECHO "#define REVISION $revision" >> $output_objdir/a2ixlibrary.data~$AR $AR_FLAGS $lib $libobjs~$RANLIB $lib~(cd $output_objdir && a2ixlibrary -32)'
hardcode_libdir_flag_spec='-L$libdir'
hardcode_minus_L=yes
;;
esac
;;
bsdi[45]*)
export_dynamic_flag_spec=-rdynamic
;;
cygwin* | mingw* | pw32* | cegcc*)
# When not using gcc, we currently assume that we are using
# Microsoft Visual C++.
# hardcode_libdir_flag_spec is actually meaningless, as there is
# no search path for DLLs.
case $cc_basename in
cl*)
# Native MSVC
hardcode_libdir_flag_spec=' '
allow_undefined_flag=unsupported
always_export_symbols=yes
file_list_spec='@'
# Tell ltmain to make .lib files, not .a files.
libext=lib
# Tell ltmain to make .dll files, not .so files.
shrext_cmds=".dll"
# FIXME: Setting linknames here is a bad hack.
archive_cmds='$CC -o $output_objdir/$soname $libobjs $compiler_flags $deplibs -Wl,-dll~linknames='
archive_expsym_cmds='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then
sed -n -e 's/\\\\\\\(.*\\\\\\\)/-link\\\ -EXPORT:\\\\\\\1/' -e '1\\\!p' < $export_symbols > $output_objdir/$soname.exp;
else
sed -e 's/\\\\\\\(.*\\\\\\\)/-link\\\ -EXPORT:\\\\\\\1/' < $export_symbols > $output_objdir/$soname.exp;
fi~
$CC -o $tool_output_objdir$soname $libobjs $compiler_flags $deplibs "@$tool_output_objdir$soname.exp" -Wl,-DLL,-IMPLIB:"$tool_output_objdir$libname.dll.lib"~
linknames='
# The linker will not automatically build a static lib if we build a DLL.
# _LT_TAGVAR(old_archive_from_new_cmds, )='true'
enable_shared_with_static_runtimes=yes
exclude_expsyms='_NULL_IMPORT_DESCRIPTOR|_IMPORT_DESCRIPTOR_.*'
export_symbols_cmds='$NM $libobjs $convenience | $global_symbol_pipe | $SED -e '\''/^[BCDGRS][ ]/s/.*[ ]\([^ ]*\)/\1,DATA/'\'' | $SED -e '\''/^[AITW][ ]/s/.*[ ]//'\'' | sort | uniq > $export_symbols'
# Don't use ranlib
old_postinstall_cmds='chmod 644 $oldlib'
postlink_cmds='lt_outputfile="@OUTPUT@"~
lt_tool_outputfile="@TOOL_OUTPUT@"~
case $lt_outputfile in
*.exe|*.EXE) ;;
*)
lt_outputfile="$lt_outputfile.exe"
lt_tool_outputfile="$lt_tool_outputfile.exe"
;;
esac~
if test "$MANIFEST_TOOL" != ":" && test -f "$lt_outputfile.manifest"; then
$MANIFEST_TOOL -manifest "$lt_tool_outputfile.manifest" -outputresource:"$lt_tool_outputfile" || exit 1;
$RM "$lt_outputfile.manifest";
fi'
;;
*)
# Assume MSVC wrapper
hardcode_libdir_flag_spec=' '
allow_undefined_flag=unsupported
# Tell ltmain to make .lib files, not .a files.
libext=lib
# Tell ltmain to make .dll files, not .so files.
shrext_cmds=".dll"
# FIXME: Setting linknames here is a bad hack.
archive_cmds='$CC -o $lib $libobjs $compiler_flags `func_echo_all "$deplibs" | $SED '\''s/ -lc$//'\''` -link -dll~linknames='
# The linker will automatically build a .lib file if we build a DLL.
old_archive_from_new_cmds='true'
# FIXME: Should let the user specify the lib program.
old_archive_cmds='lib -OUT:$oldlib$oldobjs$old_deplibs'
enable_shared_with_static_runtimes=yes
;;
esac
;;
darwin* | rhapsody*)
archive_cmds_need_lc=no
hardcode_direct=no
hardcode_automatic=yes
hardcode_shlibpath_var=unsupported
if test "$lt_cv_ld_force_load" = "yes"; then
whole_archive_flag_spec='`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience ${wl}-force_load,$conv\"; done; func_echo_all \"$new_convenience\"`'
else
whole_archive_flag_spec=''
fi
link_all_deplibs=yes
allow_undefined_flag="$_lt_dar_allow_undefined"
case $cc_basename in
ifort*) _lt_dar_can_shared=yes ;;
*) _lt_dar_can_shared=$GCC ;;
esac
if test "$_lt_dar_can_shared" = "yes"; then
output_verbose_link_cmd=func_echo_all
archive_cmds="\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring $_lt_dar_single_mod${_lt_dsymutil}"
module_cmds="\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dsymutil}"
archive_expsym_cmds="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring ${_lt_dar_single_mod}${_lt_dar_export_syms}${_lt_dsymutil}"
module_expsym_cmds="sed -e 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dar_export_syms}${_lt_dsymutil}"
else
ld_shlibs=no
fi
;;
dgux*)
archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
hardcode_libdir_flag_spec='-L$libdir'
hardcode_shlibpath_var=no
;;
# FreeBSD 2.2.[012] allows us to include c++rt0.o to get C++ constructor
# support. Future versions do this automatically, but an explicit c++rt0.o
# does not break anything, and helps significantly (at the cost of a little
# extra space).
freebsd2.2*)
archive_cmds='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags /usr/lib/c++rt0.o'
hardcode_libdir_flag_spec='-R$libdir'
hardcode_direct=yes
hardcode_shlibpath_var=no
;;
# Unfortunately, older versions of FreeBSD 2 do not have this feature.
freebsd2.*)
archive_cmds='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags'
hardcode_direct=yes
hardcode_minus_L=yes
hardcode_shlibpath_var=no
;;
# FreeBSD 3 and greater uses gcc -shared to do shared libraries.
freebsd* | dragonfly*)
archive_cmds='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags'
hardcode_libdir_flag_spec='-R$libdir'
hardcode_direct=yes
hardcode_shlibpath_var=no
;;
hpux9*)
if test "$GCC" = yes; then
archive_cmds='$RM $output_objdir/$soname~$CC -shared $pic_flag ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $libobjs $deplibs $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib'
else
archive_cmds='$RM $output_objdir/$soname~$LD -b +b $install_libdir -o $output_objdir/$soname $libobjs $deplibs $linker_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib'
fi
hardcode_libdir_flag_spec='${wl}+b ${wl}$libdir'
hardcode_libdir_separator=:
hardcode_direct=yes
# hardcode_minus_L: Not really in the search PATH,
# but as the default location of the library.
hardcode_minus_L=yes
export_dynamic_flag_spec='${wl}-E'
;;
hpux10*)
if test "$GCC" = yes && test "$with_gnu_ld" = no; then
archive_cmds='$CC -shared $pic_flag ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags'
else
archive_cmds='$LD -b +h $soname +b $install_libdir -o $lib $libobjs $deplibs $linker_flags'
fi
if test "$with_gnu_ld" = no; then
hardcode_libdir_flag_spec='${wl}+b ${wl}$libdir'
hardcode_libdir_separator=:
hardcode_direct=yes
hardcode_direct_absolute=yes
export_dynamic_flag_spec='${wl}-E'
# hardcode_minus_L: Not really in the search PATH,
# but as the default location of the library.
hardcode_minus_L=yes
fi
;;
hpux11*)
if test "$GCC" = yes && test "$with_gnu_ld" = no; then
case $host_cpu in
hppa*64*)
archive_cmds='$CC -shared ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
ia64*)
archive_cmds='$CC -shared $pic_flag ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags'
;;
*)
archive_cmds='$CC -shared $pic_flag ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags'
;;
esac
else
case $host_cpu in
hppa*64*)
archive_cmds='$CC -b ${wl}+h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
ia64*)
archive_cmds='$CC -b ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $libobjs $deplibs $compiler_flags'
;;
*)
# Older versions of the 11.00 compiler do not understand -b yet
# (HP92453-01 A.11.01.20 doesn't, HP92453-01 B.11.X.35175-35176.GP does)
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $CC understands -b" >&5
$as_echo_n "checking if $CC understands -b... " >&6; }
if ${lt_cv_prog_compiler__b+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler__b=no
save_LDFLAGS="$LDFLAGS"
LDFLAGS="$LDFLAGS -b"
echo "$lt_simple_link_test_code" > conftest.$ac_ext
if (eval $ac_link 2>conftest.err) && test -s conftest$ac_exeext; then
# The linker can only warn and ignore the option if not recognized
# So say no if there are warnings
if test -s conftest.err; then
# Append any errors to the config.log.
cat conftest.err 1>&5
$ECHO "$_lt_linker_boilerplate" | $SED '/^$/d' > conftest.exp
$SED '/^$/d; /^ *+/d' conftest.err >conftest.er2
if diff conftest.exp conftest.er2 >/dev/null; then
lt_cv_prog_compiler__b=yes
fi
else
lt_cv_prog_compiler__b=yes
fi
fi
$RM -r conftest*
LDFLAGS="$save_LDFLAGS"
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler__b" >&5
$as_echo "$lt_cv_prog_compiler__b" >&6; }
if test x"$lt_cv_prog_compiler__b" = xyes; then
archive_cmds='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $libobjs $deplibs $compiler_flags'
else
archive_cmds='$LD -b +h $soname +b $install_libdir -o $lib $libobjs $deplibs $linker_flags'
fi
;;
esac
fi
if test "$with_gnu_ld" = no; then
hardcode_libdir_flag_spec='${wl}+b ${wl}$libdir'
hardcode_libdir_separator=:
case $host_cpu in
hppa*64*|ia64*)
hardcode_direct=no
hardcode_shlibpath_var=no
;;
*)
hardcode_direct=yes
hardcode_direct_absolute=yes
export_dynamic_flag_spec='${wl}-E'
# hardcode_minus_L: Not really in the search PATH,
# but as the default location of the library.
hardcode_minus_L=yes
;;
esac
fi
;;
irix5* | irix6* | nonstopux*)
if test "$GCC" = yes; then
archive_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
# Try to use the -exported_symbol ld option, if it does not
# work, assume that -exports_file does not work either and
# implicitly export all symbols.
# This should be the same for all languages, so no per-tag cache variable.
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether the $host_os linker accepts -exported_symbol" >&5
$as_echo_n "checking whether the $host_os linker accepts -exported_symbol... " >&6; }
if ${lt_cv_irix_exported_symbol+:} false; then :
$as_echo_n "(cached) " >&6
else
save_LDFLAGS="$LDFLAGS"
LDFLAGS="$LDFLAGS -shared ${wl}-exported_symbol ${wl}foo ${wl}-update_registry ${wl}/dev/null"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int foo (void) { return 0; }
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
lt_cv_irix_exported_symbol=yes
else
lt_cv_irix_exported_symbol=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LDFLAGS="$save_LDFLAGS"
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_irix_exported_symbol" >&5
$as_echo "$lt_cv_irix_exported_symbol" >&6; }
if test "$lt_cv_irix_exported_symbol" = yes; then
archive_expsym_cmds='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations ${wl}-exports_file ${wl}$export_symbols -o $lib'
fi
else
archive_cmds='$CC -shared $libobjs $deplibs $compiler_flags -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
archive_expsym_cmds='$CC -shared $libobjs $deplibs $compiler_flags -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -exports_file $export_symbols -o $lib'
fi
archive_cmds_need_lc='no'
hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir'
hardcode_libdir_separator=:
inherit_rpath=yes
link_all_deplibs=yes
;;
netbsd*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
archive_cmds='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags' # a.out
else
archive_cmds='$LD -shared -o $lib $libobjs $deplibs $linker_flags' # ELF
fi
hardcode_libdir_flag_spec='-R$libdir'
hardcode_direct=yes
hardcode_shlibpath_var=no
;;
newsos6)
archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
hardcode_direct=yes
hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir'
hardcode_libdir_separator=:
hardcode_shlibpath_var=no
;;
*nto* | *qnx*)
;;
openbsd*)
if test -f /usr/libexec/ld.so; then
hardcode_direct=yes
hardcode_shlibpath_var=no
hardcode_direct_absolute=yes
if test -z "`echo __ELF__ | $CC -E - | $GREP __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
archive_cmds='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags ${wl}-retain-symbols-file,$export_symbols'
hardcode_libdir_flag_spec='${wl}-rpath,$libdir'
export_dynamic_flag_spec='${wl}-E'
else
case $host_os in
openbsd[01].* | openbsd2.[0-7] | openbsd2.[0-7].*)
archive_cmds='$LD -Bshareable -o $lib $libobjs $deplibs $linker_flags'
hardcode_libdir_flag_spec='-R$libdir'
;;
*)
archive_cmds='$CC -shared $pic_flag -o $lib $libobjs $deplibs $compiler_flags'
hardcode_libdir_flag_spec='${wl}-rpath,$libdir'
;;
esac
fi
else
ld_shlibs=no
fi
;;
os2*)
hardcode_libdir_flag_spec='-L$libdir'
hardcode_minus_L=yes
allow_undefined_flag=unsupported
archive_cmds='$ECHO "LIBRARY $libname INITINSTANCE" > $output_objdir/$libname.def~$ECHO "DESCRIPTION \"$libname\"" >> $output_objdir/$libname.def~echo DATA >> $output_objdir/$libname.def~echo " SINGLE NONSHARED" >> $output_objdir/$libname.def~echo EXPORTS >> $output_objdir/$libname.def~emxexp $libobjs >> $output_objdir/$libname.def~$CC -Zdll -Zcrtdll -o $lib $libobjs $deplibs $compiler_flags $output_objdir/$libname.def'
old_archive_from_new_cmds='emximp -o $output_objdir/$libname.a $output_objdir/$libname.def'
;;
osf3*)
if test "$GCC" = yes; then
allow_undefined_flag=' ${wl}-expect_unresolved ${wl}\*'
archive_cmds='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
else
allow_undefined_flag=' -expect_unresolved \*'
archive_cmds='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
fi
archive_cmds_need_lc='no'
hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir'
hardcode_libdir_separator=:
;;
osf4* | osf5*) # as osf3* with the addition of -msym flag
if test "$GCC" = yes; then
allow_undefined_flag=' ${wl}-expect_unresolved ${wl}\*'
archive_cmds='$CC -shared${allow_undefined_flag} $pic_flag $libobjs $deplibs $compiler_flags ${wl}-msym ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
hardcode_libdir_flag_spec='${wl}-rpath ${wl}$libdir'
else
allow_undefined_flag=' -expect_unresolved \*'
archive_cmds='$CC -shared${allow_undefined_flag} $libobjs $deplibs $compiler_flags -msym -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
archive_expsym_cmds='for i in `cat $export_symbols`; do printf "%s %s\\n" -exported_symbol "\$i" >> $lib.exp; done; printf "%s\\n" "-hidden">> $lib.exp~
$CC -shared${allow_undefined_flag} ${wl}-input ${wl}$lib.exp $compiler_flags $libobjs $deplibs -soname $soname `test -n "$verstring" && $ECHO "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib~$RM $lib.exp'
# Both c and cxx compiler support -rpath directly
hardcode_libdir_flag_spec='-rpath $libdir'
fi
archive_cmds_need_lc='no'
hardcode_libdir_separator=:
;;
solaris*)
no_undefined_flag=' -z defs'
if test "$GCC" = yes; then
wlarc='${wl}'
archive_cmds='$CC -shared $pic_flag ${wl}-z ${wl}text ${wl}-h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -shared $pic_flag ${wl}-z ${wl}text ${wl}-M ${wl}$lib.exp ${wl}-h ${wl}$soname -o $lib $libobjs $deplibs $compiler_flags~$RM $lib.exp'
else
case `$CC -V 2>&1` in
*"Compilers 5.0"*)
wlarc=''
archive_cmds='$LD -G${allow_undefined_flag} -h $soname -o $lib $libobjs $deplibs $linker_flags'
archive_expsym_cmds='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$LD -G${allow_undefined_flag} -M $lib.exp -h $soname -o $lib $libobjs $deplibs $linker_flags~$RM $lib.exp'
;;
*)
wlarc='${wl}'
archive_cmds='$CC -G${allow_undefined_flag} -h $soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -G${allow_undefined_flag} -M $lib.exp -h $soname -o $lib $libobjs $deplibs $compiler_flags~$RM $lib.exp'
;;
esac
fi
hardcode_libdir_flag_spec='-R$libdir'
hardcode_shlibpath_var=no
case $host_os in
solaris2.[0-5] | solaris2.[0-5].*) ;;
*)
# The compiler driver will combine and reorder linker options,
# but understands `-z linker_flag'. GCC discards it without `$wl',
# but is careful enough not to reorder.
# Supported since Solaris 2.6 (maybe 2.5.1?)
if test "$GCC" = yes; then
whole_archive_flag_spec='${wl}-z ${wl}allextract$convenience ${wl}-z ${wl}defaultextract'
else
whole_archive_flag_spec='-z allextract$convenience -z defaultextract'
fi
;;
esac
link_all_deplibs=yes
;;
sunos4*)
if test "x$host_vendor" = xsequent; then
# Use $CC to link under sequent, because it throws in some extra .o
# files that make .init and .fini sections work.
archive_cmds='$CC -G ${wl}-h $soname -o $lib $libobjs $deplibs $compiler_flags'
else
archive_cmds='$LD -assert pure-text -Bstatic -o $lib $libobjs $deplibs $linker_flags'
fi
hardcode_libdir_flag_spec='-L$libdir'
hardcode_direct=yes
hardcode_minus_L=yes
hardcode_shlibpath_var=no
;;
sysv4)
case $host_vendor in
sni)
archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
hardcode_direct=yes # is this really true???
;;
siemens)
## LD is ld it makes a PLAMLIB
## CC just makes a GrossModule.
archive_cmds='$LD -G -o $lib $libobjs $deplibs $linker_flags'
reload_cmds='$CC -r -o $output$reload_objs'
hardcode_direct=no
;;
motorola)
archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
hardcode_direct=no #Motorola manual says yes, but my tests say they lie
;;
esac
runpath_var='LD_RUN_PATH'
hardcode_shlibpath_var=no
;;
sysv4.3*)
archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
hardcode_shlibpath_var=no
export_dynamic_flag_spec='-Bexport'
;;
sysv4*MP*)
if test -d /usr/nec; then
archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
hardcode_shlibpath_var=no
runpath_var=LD_RUN_PATH
hardcode_runpath_var=yes
ld_shlibs=yes
fi
;;
sysv4*uw2* | sysv5OpenUNIX* | sysv5UnixWare7.[01].[10]* | unixware7* | sco3.2v5.0.[024]*)
no_undefined_flag='${wl}-z,text'
archive_cmds_need_lc=no
hardcode_shlibpath_var=no
runpath_var='LD_RUN_PATH'
if test "$GCC" = yes; then
archive_cmds='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
else
archive_cmds='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
fi
;;
sysv5* | sco3.2v5* | sco5v6*)
# Note: We can NOT use -z defs as we might desire, because we do not
# link with -lc, and that would cause any symbols used from libc to
# always be unresolved, which means just about no library would
# ever link correctly. If we're not using GNU ld we use -z text
# though, which does catch some bad symbols but isn't as heavy-handed
# as -z defs.
no_undefined_flag='${wl}-z,text'
allow_undefined_flag='${wl}-z,nodefs'
archive_cmds_need_lc=no
hardcode_shlibpath_var=no
hardcode_libdir_flag_spec='${wl}-R,$libdir'
hardcode_libdir_separator=':'
link_all_deplibs=yes
export_dynamic_flag_spec='${wl}-Bexport'
runpath_var='LD_RUN_PATH'
if test "$GCC" = yes; then
archive_cmds='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
else
archive_cmds='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
fi
;;
uts4*)
archive_cmds='$LD -G -h $soname -o $lib $libobjs $deplibs $linker_flags'
hardcode_libdir_flag_spec='-L$libdir'
hardcode_shlibpath_var=no
;;
*)
ld_shlibs=no
;;
esac
if test x$host_vendor = xsni; then
case $host in
sysv4 | sysv4.2uw2* | sysv4.3* | sysv5*)
export_dynamic_flag_spec='${wl}-Blargedynsym'
;;
esac
fi
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ld_shlibs" >&5
$as_echo "$ld_shlibs" >&6; }
test "$ld_shlibs" = no && can_build_shared=no
with_gnu_ld=$with_gnu_ld
#
# Do we need to explicitly link libc?
#
case "x$archive_cmds_need_lc" in
x|xyes)
# Assume -lc should be added
archive_cmds_need_lc=yes
if test "$enable_shared" = yes && test "$GCC" = yes; then
case $archive_cmds in
*'~'*)
# FIXME: we may have to deal with multi-command sequences.
;;
'$CC '*)
# Test whether the compiler implicitly links with -lc since on some
# systems, -lgcc has to come before -lc. If gcc already passes -lc
# to ld, don't add -lc before -lgcc.
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether -lc should be explicitly linked in" >&5
$as_echo_n "checking whether -lc should be explicitly linked in... " >&6; }
if ${lt_cv_archive_cmds_need_lc+:} false; then :
$as_echo_n "(cached) " >&6
else
$RM conftest*
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_compile\""; } >&5
(eval $ac_compile) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } 2>conftest.err; then
soname=conftest
lib=conftest
libobjs=conftest.$ac_objext
deplibs=
wl=$lt_prog_compiler_wl
pic_flag=$lt_prog_compiler_pic
compiler_flags=-v
linker_flags=-v
verstring=
output_objdir=.
libname=conftest
lt_save_allow_undefined_flag=$allow_undefined_flag
allow_undefined_flag=
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$archive_cmds 2\>\&1 \| $GREP \" -lc \" \>/dev/null 2\>\&1\""; } >&5
(eval $archive_cmds 2\>\&1 \| $GREP \" -lc \" \>/dev/null 2\>\&1) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }
then
lt_cv_archive_cmds_need_lc=no
else
lt_cv_archive_cmds_need_lc=yes
fi
allow_undefined_flag=$lt_save_allow_undefined_flag
else
cat conftest.err 1>&5
fi
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_archive_cmds_need_lc" >&5
$as_echo "$lt_cv_archive_cmds_need_lc" >&6; }
archive_cmds_need_lc=$lt_cv_archive_cmds_need_lc
;;
esac
fi
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking dynamic linker characteristics" >&5
$as_echo_n "checking dynamic linker characteristics... " >&6; }
if test "$GCC" = yes; then
case $host_os in
darwin*) lt_awk_arg="/^libraries:/,/LR/" ;;
*) lt_awk_arg="/^libraries:/" ;;
esac
case $host_os in
mingw* | cegcc*) lt_sed_strip_eq="s,=\([A-Za-z]:\),\1,g" ;;
*) lt_sed_strip_eq="s,=/,/,g" ;;
esac
lt_search_path_spec=`$CC -print-search-dirs | awk $lt_awk_arg | $SED -e "s/^libraries://" -e $lt_sed_strip_eq`
case $lt_search_path_spec in
*\;*)
# if the path contains ";" then we assume it to be the separator
# otherwise default to the standard path separator (i.e. ":") - it is
# assumed that no part of a normal pathname contains ";" but that should
# okay in the real world where ";" in dirpaths is itself problematic.
lt_search_path_spec=`$ECHO "$lt_search_path_spec" | $SED 's/;/ /g'`
;;
*)
lt_search_path_spec=`$ECHO "$lt_search_path_spec" | $SED "s/$PATH_SEPARATOR/ /g"`
;;
esac
# Ok, now we have the path, separated by spaces, we can step through it
# and add multilib dir if necessary.
lt_tmp_lt_search_path_spec=
lt_multi_os_dir=`$CC $CPPFLAGS $CFLAGS $LDFLAGS -print-multi-os-directory 2>/dev/null`
for lt_sys_path in $lt_search_path_spec; do
if test -d "$lt_sys_path/$lt_multi_os_dir"; then
lt_tmp_lt_search_path_spec="$lt_tmp_lt_search_path_spec $lt_sys_path/$lt_multi_os_dir"
else
test -d "$lt_sys_path" && \
lt_tmp_lt_search_path_spec="$lt_tmp_lt_search_path_spec $lt_sys_path"
fi
done
lt_search_path_spec=`$ECHO "$lt_tmp_lt_search_path_spec" | awk '
BEGIN {RS=" "; FS="/|\n";} {
lt_foo="";
lt_count=0;
for (lt_i = NF; lt_i > 0; lt_i--) {
if ($lt_i != "" && $lt_i != ".") {
if ($lt_i == "..") {
lt_count++;
} else {
if (lt_count == 0) {
lt_foo="/" $lt_i lt_foo;
} else {
lt_count--;
}
}
}
}
if (lt_foo != "") { lt_freq[lt_foo]++; }
if (lt_freq[lt_foo] == 1) { print lt_foo; }
}'`
# AWK program above erroneously prepends '/' to C:/dos/paths
# for these hosts.
case $host_os in
mingw* | cegcc*) lt_search_path_spec=`$ECHO "$lt_search_path_spec" |\
$SED 's,/\([A-Za-z]:\),\1,g'` ;;
esac
sys_lib_search_path_spec=`$ECHO "$lt_search_path_spec" | $lt_NL2SP`
else
sys_lib_search_path_spec="/lib /usr/lib /usr/local/lib"
fi
library_names_spec=
libname_spec='lib$name'
soname_spec=
shrext_cmds=".so"
postinstall_cmds=
postuninstall_cmds=
finish_cmds=
finish_eval=
shlibpath_var=
shlibpath_overrides_runpath=unknown
version_type=none
dynamic_linker="$host_os ld.so"
sys_lib_dlsearch_path_spec="/lib /usr/lib"
need_lib_prefix=unknown
hardcode_into_libs=no
# when you set need_version to no, make sure it does not cause -set_version
# flags to be left without arguments
need_version=unknown
case $host_os in
aix3*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix $libname.a'
shlibpath_var=LIBPATH
# AIX 3 has no versioning support, so we append a major version to the name.
soname_spec='${libname}${release}${shared_ext}$major'
;;
aix[4-9]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
hardcode_into_libs=yes
if test "$host_cpu" = ia64; then
# AIX 5 supports IA64
library_names_spec='${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext}$versuffix $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
else
# With GCC up to 2.95.x, collect2 would create an import file
# for dependence libraries. The import file would start with
# the line `#! .'. This would cause the generated library to
# depend on `.', always an invalid library. This was fixed in
# development snapshots of GCC prior to 3.0.
case $host_os in
aix4 | aix4.[01] | aix4.[01].*)
if { echo '#if __GNUC__ > 2 || (__GNUC__ == 2 && __GNUC_MINOR__ >= 97)'
echo ' yes '
echo '#endif'; } | ${CC} -E - | $GREP yes > /dev/null; then
:
else
can_build_shared=no
fi
;;
esac
# AIX (on Power*) has no versioning support, so currently we can not hardcode correct
# soname into executable. Probably we can add versioning support to
# collect2, so additional links can be useful in future.
if test "$aix_use_runtimelinking" = yes; then
# If using run time linking (on AIX 4.2 or later) use lib.so
# instead of lib.a to let people know that these are not
# typical AIX shared libraries.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
else
# We preserve .a as extension for shared libraries through AIX4.2
# and later when we are not doing run time linking.
library_names_spec='${libname}${release}.a $libname.a'
soname_spec='${libname}${release}${shared_ext}$major'
fi
shlibpath_var=LIBPATH
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# Since July 2007 AmigaOS4 officially supports .so libraries.
# When compiling the executable, add -use-dynld -Lsobjs: to the compileline.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
;;
m68k)
library_names_spec='$libname.ixlibrary $libname.a'
# Create ${libname}_ixlibrary.a entries in /sys/libs.
finish_eval='for lib in `ls $libdir/*.ixlibrary 2>/dev/null`; do libname=`func_echo_all "$lib" | $SED '\''s%^.*/\([^/]*\)\.ixlibrary$%\1%'\''`; test $RM /sys/libs/${libname}_ixlibrary.a; $show "cd /sys/libs && $LN_S $lib ${libname}_ixlibrary.a"; cd /sys/libs && $LN_S $lib ${libname}_ixlibrary.a || exit 1; done'
;;
esac
;;
beos*)
library_names_spec='${libname}${shared_ext}'
dynamic_linker="$host_os ld.so"
shlibpath_var=LIBRARY_PATH
;;
bsdi[45]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
finish_cmds='PATH="\$PATH:/sbin" ldconfig $libdir'
shlibpath_var=LD_LIBRARY_PATH
sys_lib_search_path_spec="/shlib /usr/lib /usr/X11/lib /usr/contrib/lib /lib /usr/local/lib"
sys_lib_dlsearch_path_spec="/shlib /usr/lib /usr/local/lib"
# the default ld.so.conf also contains /usr/contrib/lib and
# /usr/X11R6/lib (/usr/X11 is a link to /usr/X11R6), but let us allow
# libtool to hard-code these into programs
;;
cygwin* | mingw* | pw32* | cegcc*)
version_type=windows
shrext_cmds=".dll"
need_version=no
need_lib_prefix=no
case $GCC,$cc_basename in
yes,*)
# gcc
library_names_spec='$libname.dll.a'
# DLL is installed to $(libdir)/../bin by postinstall_cmds
postinstall_cmds='base_file=`basename \${file}`~
dlpath=`$SHELL 2>&1 -c '\''. $dir/'\''\${base_file}'\''i; echo \$dlname'\''`~
dldir=$destdir/`dirname \$dlpath`~
test -d \$dldir || mkdir -p \$dldir~
$install_prog $dir/$dlname \$dldir/$dlname~
chmod a+x \$dldir/$dlname~
if test -n '\''$stripme'\'' && test -n '\''$striplib'\''; then
eval '\''$striplib \$dldir/$dlname'\'' || exit \$?;
fi'
postuninstall_cmds='dldll=`$SHELL 2>&1 -c '\''. $file; echo \$dlname'\''`~
dlpath=$dir/\$dldll~
$RM \$dlpath'
shlibpath_overrides_runpath=yes
case $host_os in
cygwin*)
# Cygwin DLLs use 'cyg' prefix rather than 'lib'
soname_spec='`echo ${libname} | sed -e 's/^lib/cyg/'``echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}'
sys_lib_search_path_spec="$sys_lib_search_path_spec /usr/lib/w32api"
;;
mingw* | cegcc*)
# MinGW DLLs use traditional 'lib' prefix
soname_spec='${libname}`echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}'
;;
pw32*)
# pw32 DLLs use 'pw' prefix rather than 'lib'
library_names_spec='`echo ${libname} | sed -e 's/^lib/pw/'``echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}'
;;
esac
dynamic_linker='Win32 ld.exe'
;;
*,cl*)
# Native MSVC
libname_spec='$name'
soname_spec='${libname}`echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}'
library_names_spec='${libname}.dll.lib'
case $build_os in
mingw*)
sys_lib_search_path_spec=
lt_save_ifs=$IFS
IFS=';'
for lt_path in $LIB
do
IFS=$lt_save_ifs
# Let DOS variable expansion print the short 8.3 style file name.
lt_path=`cd "$lt_path" 2>/dev/null && cmd //C "for %i in (".") do @echo %~si"`
sys_lib_search_path_spec="$sys_lib_search_path_spec $lt_path"
done
IFS=$lt_save_ifs
# Convert to MSYS style.
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | sed -e 's|\\\\|/|g' -e 's| \\([a-zA-Z]\\):| /\\1|g' -e 's|^ ||'`
;;
cygwin*)
# Convert to unix form, then to dos form, then back to unix form
# but this time dos style (no spaces!) so that the unix form looks
# like /cygdrive/c/PROGRA~1:/cygdr...
sys_lib_search_path_spec=`cygpath --path --unix "$LIB"`
sys_lib_search_path_spec=`cygpath --path --dos "$sys_lib_search_path_spec" 2>/dev/null`
sys_lib_search_path_spec=`cygpath --path --unix "$sys_lib_search_path_spec" | $SED -e "s/$PATH_SEPARATOR/ /g"`
;;
*)
sys_lib_search_path_spec="$LIB"
if $ECHO "$sys_lib_search_path_spec" | $GREP ';[c-zC-Z]:/' >/dev/null; then
# It is most probably a Windows format PATH.
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | $SED -e 's/;/ /g'`
else
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | $SED -e "s/$PATH_SEPARATOR/ /g"`
fi
# FIXME: find the short name or the path components, as spaces are
# common. (e.g. "Program Files" -> "PROGRA~1")
;;
esac
# DLL is installed to $(libdir)/../bin by postinstall_cmds
postinstall_cmds='base_file=`basename \${file}`~
dlpath=`$SHELL 2>&1 -c '\''. $dir/'\''\${base_file}'\''i; echo \$dlname'\''`~
dldir=$destdir/`dirname \$dlpath`~
test -d \$dldir || mkdir -p \$dldir~
$install_prog $dir/$dlname \$dldir/$dlname'
postuninstall_cmds='dldll=`$SHELL 2>&1 -c '\''. $file; echo \$dlname'\''`~
dlpath=$dir/\$dldll~
$RM \$dlpath'
shlibpath_overrides_runpath=yes
dynamic_linker='Win32 link.exe'
;;
*)
# Assume MSVC wrapper
library_names_spec='${libname}`echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext} $libname.lib'
dynamic_linker='Win32 ld.exe'
;;
esac
# FIXME: first we should search . and the directory the executable is in
shlibpath_var=PATH
;;
darwin* | rhapsody*)
dynamic_linker="$host_os dyld"
version_type=darwin
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${major}$shared_ext ${libname}$shared_ext'
soname_spec='${libname}${release}${major}$shared_ext'
shlibpath_overrides_runpath=yes
shlibpath_var=DYLD_LIBRARY_PATH
shrext_cmds='`test .$module = .yes && echo .so || echo .dylib`'
sys_lib_search_path_spec="$sys_lib_search_path_spec /usr/local/lib"
sys_lib_dlsearch_path_spec='/usr/local/lib /lib /usr/lib'
;;
dgux*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname$shared_ext'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
;;
freebsd* | dragonfly*)
# DragonFly does not have aout. When/if they implement a new
# versioning mechanism, adjust this.
if test -x /usr/bin/objformat; then
objformat=`/usr/bin/objformat`
else
case $host_os in
freebsd[23].*) objformat=aout ;;
*) objformat=elf ;;
esac
fi
version_type=freebsd-$objformat
case $version_type in
freebsd-elf*)
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext} $libname${shared_ext}'
need_version=no
need_lib_prefix=no
;;
freebsd-*)
library_names_spec='${libname}${release}${shared_ext}$versuffix $libname${shared_ext}$versuffix'
need_version=yes
;;
esac
shlibpath_var=LD_LIBRARY_PATH
case $host_os in
freebsd2.*)
shlibpath_overrides_runpath=yes
;;
freebsd3.[01]* | freebsdelf3.[01]*)
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
freebsd3.[2-9]* | freebsdelf3.[2-9]* | \
freebsd4.[0-5] | freebsdelf4.[0-5] | freebsd4.1.1 | freebsdelf4.1.1)
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
*) # from 4.6 on, and DragonFly
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
esac
;;
gnu*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
haiku*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
dynamic_linker="$host_os runtime_loader"
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LIBRARY_PATH
shlibpath_overrides_runpath=yes
sys_lib_dlsearch_path_spec='/boot/home/config/lib /boot/common/lib /boot/system/lib'
hardcode_into_libs=yes
;;
hpux9* | hpux10* | hpux11*)
# Give a soname corresponding to the major version so that dld.sl refuses to
# link against other versions.
version_type=sunos
need_lib_prefix=no
need_version=no
case $host_cpu in
ia64*)
shrext_cmds='.so'
hardcode_into_libs=yes
dynamic_linker="$host_os dld.so"
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes # Unless +noenvvar is specified.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
if test "X$HPUX_IA64_MODE" = X32; then
sys_lib_search_path_spec="/usr/lib/hpux32 /usr/local/lib/hpux32 /usr/local/lib"
else
sys_lib_search_path_spec="/usr/lib/hpux64 /usr/local/lib/hpux64"
fi
sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec
;;
hppa*64*)
shrext_cmds='.sl'
hardcode_into_libs=yes
dynamic_linker="$host_os dld.sl"
shlibpath_var=LD_LIBRARY_PATH # How should we handle SHLIB_PATH
shlibpath_overrides_runpath=yes # Unless +noenvvar is specified.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
sys_lib_search_path_spec="/usr/lib/pa20_64 /usr/ccs/lib/pa20_64"
sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec
;;
*)
shrext_cmds='.sl'
dynamic_linker="$host_os dld.sl"
shlibpath_var=SHLIB_PATH
shlibpath_overrides_runpath=no # +s is required to enable SHLIB_PATH
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
;;
esac
# HP-UX runs *really* slowly unless shared libraries are mode 555, ...
postinstall_cmds='chmod 555 $lib'
# or fails outright, so override atomically:
install_override_mode=555
;;
interix[3-9]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
dynamic_linker='Interix 3.x ld.so.1 (PE, like ELF)'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
irix5* | irix6* | nonstopux*)
case $host_os in
nonstopux*) version_type=nonstopux ;;
*)
if test "$lt_cv_prog_gnu_ld" = yes; then
version_type=linux # correct to gnu/linux during the next big refactor
else
version_type=irix
fi ;;
esac
need_lib_prefix=no
need_version=no
soname_spec='${libname}${release}${shared_ext}$major'
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext} $libname${shared_ext}'
case $host_os in
irix5* | nonstopux*)
libsuff= shlibsuff=
;;
*)
case $LD in # libtool.m4 will add one of these switches to LD
*-32|*"-32 "|*-melf32bsmip|*"-melf32bsmip ")
libsuff= shlibsuff= libmagic=32-bit;;
*-n32|*"-n32 "|*-melf32bmipn32|*"-melf32bmipn32 ")
libsuff=32 shlibsuff=N32 libmagic=N32;;
*-64|*"-64 "|*-melf64bmip|*"-melf64bmip ")
libsuff=64 shlibsuff=64 libmagic=64-bit;;
*) libsuff= shlibsuff= libmagic=never-match;;
esac
;;
esac
shlibpath_var=LD_LIBRARY${shlibsuff}_PATH
shlibpath_overrides_runpath=no
sys_lib_search_path_spec="/usr/lib${libsuff} /lib${libsuff} /usr/local/lib${libsuff}"
sys_lib_dlsearch_path_spec="/usr/lib${libsuff} /lib${libsuff}"
hardcode_into_libs=yes
;;
# No shared lib support for Linux oldld, aout, or coff.
linux*oldld* | linux*aout* | linux*coff*)
dynamic_linker=no
;;
# This must be glibc/ELF.
linux* | k*bsd*-gnu | kopensolaris*-gnu)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -n $libdir'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
# Some binutils ld are patched to set DT_RUNPATH
if ${lt_cv_shlibpath_overrides_runpath+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_shlibpath_overrides_runpath=no
save_LDFLAGS=$LDFLAGS
save_libdir=$libdir
eval "libdir=/foo; wl=\"$lt_prog_compiler_wl\"; \
LDFLAGS=\"\$LDFLAGS $hardcode_libdir_flag_spec\""
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
if ($OBJDUMP -p conftest$ac_exeext) 2>/dev/null | grep "RUNPATH.*$libdir" >/dev/null; then :
lt_cv_shlibpath_overrides_runpath=yes
fi
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LDFLAGS=$save_LDFLAGS
libdir=$save_libdir
fi
shlibpath_overrides_runpath=$lt_cv_shlibpath_overrides_runpath
# This implies no fast_install, which is unacceptable.
# Some rework will be needed to allow for fast_install
# before this can be enabled.
hardcode_into_libs=yes
# Add ABI-specific directories to the system library path.
sys_lib_dlsearch_path_spec="/lib64 /usr/lib64 /lib /usr/lib"
# Append ld.so.conf contents to the search path
if test -f /etc/ld.so.conf; then
lt_ld_extra=`awk '/^include / { system(sprintf("cd /etc; cat %s 2>/dev/null", \$2)); skip = 1; } { if (!skip) print \$0; skip = 0; }' < /etc/ld.so.conf | $SED -e 's/#.*//;/^[ ]*hwcap[ ]/d;s/[:, ]/ /g;s/=[^=]*$//;s/=[^= ]* / /g;s/"//g;/^$/d' | tr '\n' ' '`
sys_lib_dlsearch_path_spec="$sys_lib_dlsearch_path_spec $lt_ld_extra"
fi
# We used to test for /lib/ld.so.1 and disable shared libraries on
# powerpc, because MkLinux only supported shared libraries with the
# GNU dynamic linker. Since this was broken with cross compilers,
# most powerpc-linux boxes support dynamic linking these days and
# people can always --disable-shared, the test was removed, and we
# assume the GNU/Linux dynamic linker is in use.
dynamic_linker='GNU/Linux ld.so'
;;
netbsd*)
version_type=sunos
need_lib_prefix=no
need_version=no
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -m $libdir'
dynamic_linker='NetBSD (a.out) ld.so'
else
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
dynamic_linker='NetBSD ld.elf_so'
fi
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
newsos6)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
;;
*nto* | *qnx*)
version_type=qnx
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
dynamic_linker='ldqnx.so'
;;
openbsd*)
version_type=sunos
sys_lib_dlsearch_path_spec="/usr/lib"
need_lib_prefix=no
# Some older versions of OpenBSD (3.3 at least) *do* need versioned libs.
case $host_os in
openbsd3.3 | openbsd3.3.*) need_version=yes ;;
*) need_version=no ;;
esac
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -m $libdir'
shlibpath_var=LD_LIBRARY_PATH
if test -z "`echo __ELF__ | $CC -E - | $GREP __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
case $host_os in
openbsd2.[89] | openbsd2.[89].*)
shlibpath_overrides_runpath=no
;;
*)
shlibpath_overrides_runpath=yes
;;
esac
else
shlibpath_overrides_runpath=yes
fi
;;
os2*)
libname_spec='$name'
shrext_cmds=".dll"
need_lib_prefix=no
library_names_spec='$libname${shared_ext} $libname.a'
dynamic_linker='OS/2 ld.exe'
shlibpath_var=LIBPATH
;;
osf3* | osf4* | osf5*)
version_type=osf
need_lib_prefix=no
need_version=no
soname_spec='${libname}${release}${shared_ext}$major'
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
sys_lib_search_path_spec="/usr/shlib /usr/ccs/lib /usr/lib/cmplrs/cc /usr/lib /usr/local/lib /var/shlib"
sys_lib_dlsearch_path_spec="$sys_lib_search_path_spec"
;;
rdos*)
dynamic_linker=no
;;
solaris*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
# ldd complains unless libraries are executable
postinstall_cmds='chmod +x $lib'
;;
sunos4*)
version_type=sunos
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/usr/etc" ldconfig $libdir'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
if test "$with_gnu_ld" = yes; then
need_lib_prefix=no
fi
need_version=yes
;;
sysv4 | sysv4.3*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
case $host_vendor in
sni)
shlibpath_overrides_runpath=no
need_lib_prefix=no
runpath_var=LD_RUN_PATH
;;
siemens)
need_lib_prefix=no
;;
motorola)
need_lib_prefix=no
need_version=no
shlibpath_overrides_runpath=no
sys_lib_search_path_spec='/lib /usr/lib /usr/ccs/lib'
;;
esac
;;
sysv4*MP*)
if test -d /usr/nec ;then
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='$libname${shared_ext}.$versuffix $libname${shared_ext}.$major $libname${shared_ext}'
soname_spec='$libname${shared_ext}.$major'
shlibpath_var=LD_LIBRARY_PATH
fi
;;
sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX* | sysv4*uw2*)
version_type=freebsd-elf
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext} $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
if test "$with_gnu_ld" = yes; then
sys_lib_search_path_spec='/usr/local/lib /usr/gnu/lib /usr/ccs/lib /usr/lib /lib'
else
sys_lib_search_path_spec='/usr/ccs/lib /usr/lib'
case $host_os in
sco3.2v5*)
sys_lib_search_path_spec="$sys_lib_search_path_spec /lib"
;;
esac
fi
sys_lib_dlsearch_path_spec='/usr/lib'
;;
tpf*)
# TPF is a cross-target only. Preferred cross-host = GNU/Linux.
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
uts4*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
;;
*)
dynamic_linker=no
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $dynamic_linker" >&5
$as_echo "$dynamic_linker" >&6; }
test "$dynamic_linker" = no && can_build_shared=no
variables_saved_for_relink="PATH $shlibpath_var $runpath_var"
if test "$GCC" = yes; then
variables_saved_for_relink="$variables_saved_for_relink GCC_EXEC_PREFIX COMPILER_PATH LIBRARY_PATH"
fi
if test "${lt_cv_sys_lib_search_path_spec+set}" = set; then
sys_lib_search_path_spec="$lt_cv_sys_lib_search_path_spec"
fi
if test "${lt_cv_sys_lib_dlsearch_path_spec+set}" = set; then
sys_lib_dlsearch_path_spec="$lt_cv_sys_lib_dlsearch_path_spec"
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking how to hardcode library paths into programs" >&5
$as_echo_n "checking how to hardcode library paths into programs... " >&6; }
hardcode_action=
if test -n "$hardcode_libdir_flag_spec" ||
test -n "$runpath_var" ||
test "X$hardcode_automatic" = "Xyes" ; then
# We can hardcode non-existent directories.
if test "$hardcode_direct" != no &&
# If the only mechanism to avoid hardcoding is shlibpath_var, we
# have to relink, otherwise we might link with an installed library
# when we should be linking with a yet-to-be-installed one
## test "$_LT_TAGVAR(hardcode_shlibpath_var, )" != no &&
test "$hardcode_minus_L" != no; then
# Linking always hardcodes the temporary library directory.
hardcode_action=relink
else
# We can link without hardcoding, and we can hardcode nonexisting dirs.
hardcode_action=immediate
fi
else
# We cannot hardcode anything, or else we can only hardcode existing
# directories.
hardcode_action=unsupported
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $hardcode_action" >&5
$as_echo "$hardcode_action" >&6; }
if test "$hardcode_action" = relink ||
test "$inherit_rpath" = yes; then
# Fast installation is not supported
enable_fast_install=no
elif test "$shlibpath_overrides_runpath" = yes ||
test "$enable_shared" = no; then
# Fast installation is not necessary
enable_fast_install=needless
fi
if test "x$enable_dlopen" != xyes; then
enable_dlopen=unknown
enable_dlopen_self=unknown
enable_dlopen_self_static=unknown
else
lt_cv_dlopen=no
lt_cv_dlopen_libs=
case $host_os in
beos*)
lt_cv_dlopen="load_add_on"
lt_cv_dlopen_libs=
lt_cv_dlopen_self=yes
;;
mingw* | pw32* | cegcc*)
lt_cv_dlopen="LoadLibrary"
lt_cv_dlopen_libs=
;;
cygwin*)
lt_cv_dlopen="dlopen"
lt_cv_dlopen_libs=
;;
darwin*)
# if libdl is installed we need to link against it
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for dlopen in -ldl" >&5
$as_echo_n "checking for dlopen in -ldl... " >&6; }
if ${ac_cv_lib_dl_dlopen+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_check_lib_save_LIBS=$LIBS
LIBS="-ldl $LIBS"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
/* Override any GCC internal prototype to avoid an error.
Use char because int might match the return type of a GCC
builtin and then its argument prototype would still apply. */
#ifdef __cplusplus
extern "C"
#endif
char dlopen ();
int
main ()
{
return dlopen ();
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
ac_cv_lib_dl_dlopen=yes
else
ac_cv_lib_dl_dlopen=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LIBS=$ac_check_lib_save_LIBS
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_lib_dl_dlopen" >&5
$as_echo "$ac_cv_lib_dl_dlopen" >&6; }
if test "x$ac_cv_lib_dl_dlopen" = xyes; then :
lt_cv_dlopen="dlopen" lt_cv_dlopen_libs="-ldl"
else
lt_cv_dlopen="dyld"
lt_cv_dlopen_libs=
lt_cv_dlopen_self=yes
fi
;;
*)
ac_fn_c_check_func "$LINENO" "shl_load" "ac_cv_func_shl_load"
if test "x$ac_cv_func_shl_load" = xyes; then :
lt_cv_dlopen="shl_load"
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for shl_load in -ldld" >&5
$as_echo_n "checking for shl_load in -ldld... " >&6; }
if ${ac_cv_lib_dld_shl_load+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_check_lib_save_LIBS=$LIBS
LIBS="-ldld $LIBS"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
/* Override any GCC internal prototype to avoid an error.
Use char because int might match the return type of a GCC
builtin and then its argument prototype would still apply. */
#ifdef __cplusplus
extern "C"
#endif
char shl_load ();
int
main ()
{
return shl_load ();
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
ac_cv_lib_dld_shl_load=yes
else
ac_cv_lib_dld_shl_load=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LIBS=$ac_check_lib_save_LIBS
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_lib_dld_shl_load" >&5
$as_echo "$ac_cv_lib_dld_shl_load" >&6; }
if test "x$ac_cv_lib_dld_shl_load" = xyes; then :
lt_cv_dlopen="shl_load" lt_cv_dlopen_libs="-ldld"
else
ac_fn_c_check_func "$LINENO" "dlopen" "ac_cv_func_dlopen"
if test "x$ac_cv_func_dlopen" = xyes; then :
lt_cv_dlopen="dlopen"
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for dlopen in -ldl" >&5
$as_echo_n "checking for dlopen in -ldl... " >&6; }
if ${ac_cv_lib_dl_dlopen+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_check_lib_save_LIBS=$LIBS
LIBS="-ldl $LIBS"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
/* Override any GCC internal prototype to avoid an error.
Use char because int might match the return type of a GCC
builtin and then its argument prototype would still apply. */
#ifdef __cplusplus
extern "C"
#endif
char dlopen ();
int
main ()
{
return dlopen ();
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
ac_cv_lib_dl_dlopen=yes
else
ac_cv_lib_dl_dlopen=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LIBS=$ac_check_lib_save_LIBS
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_lib_dl_dlopen" >&5
$as_echo "$ac_cv_lib_dl_dlopen" >&6; }
if test "x$ac_cv_lib_dl_dlopen" = xyes; then :
lt_cv_dlopen="dlopen" lt_cv_dlopen_libs="-ldl"
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for dlopen in -lsvld" >&5
$as_echo_n "checking for dlopen in -lsvld... " >&6; }
if ${ac_cv_lib_svld_dlopen+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_check_lib_save_LIBS=$LIBS
LIBS="-lsvld $LIBS"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
/* Override any GCC internal prototype to avoid an error.
Use char because int might match the return type of a GCC
builtin and then its argument prototype would still apply. */
#ifdef __cplusplus
extern "C"
#endif
char dlopen ();
int
main ()
{
return dlopen ();
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
ac_cv_lib_svld_dlopen=yes
else
ac_cv_lib_svld_dlopen=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LIBS=$ac_check_lib_save_LIBS
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_lib_svld_dlopen" >&5
$as_echo "$ac_cv_lib_svld_dlopen" >&6; }
if test "x$ac_cv_lib_svld_dlopen" = xyes; then :
lt_cv_dlopen="dlopen" lt_cv_dlopen_libs="-lsvld"
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for dld_link in -ldld" >&5
$as_echo_n "checking for dld_link in -ldld... " >&6; }
if ${ac_cv_lib_dld_dld_link+:} false; then :
$as_echo_n "(cached) " >&6
else
ac_check_lib_save_LIBS=$LIBS
LIBS="-ldld $LIBS"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
/* Override any GCC internal prototype to avoid an error.
Use char because int might match the return type of a GCC
builtin and then its argument prototype would still apply. */
#ifdef __cplusplus
extern "C"
#endif
char dld_link ();
int
main ()
{
return dld_link ();
;
return 0;
}
_ACEOF
if ac_fn_c_try_link "$LINENO"; then :
ac_cv_lib_dld_dld_link=yes
else
ac_cv_lib_dld_dld_link=no
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LIBS=$ac_check_lib_save_LIBS
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ac_cv_lib_dld_dld_link" >&5
$as_echo "$ac_cv_lib_dld_dld_link" >&6; }
if test "x$ac_cv_lib_dld_dld_link" = xyes; then :
lt_cv_dlopen="dld_link" lt_cv_dlopen_libs="-ldld"
fi
fi
fi
fi
fi
fi
;;
esac
if test "x$lt_cv_dlopen" != xno; then
enable_dlopen=yes
else
enable_dlopen=no
fi
case $lt_cv_dlopen in
dlopen)
save_CPPFLAGS="$CPPFLAGS"
test "x$ac_cv_header_dlfcn_h" = xyes && CPPFLAGS="$CPPFLAGS -DHAVE_DLFCN_H"
save_LDFLAGS="$LDFLAGS"
wl=$lt_prog_compiler_wl eval LDFLAGS=\"\$LDFLAGS $export_dynamic_flag_spec\"
save_LIBS="$LIBS"
LIBS="$lt_cv_dlopen_libs $LIBS"
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether a program can dlopen itself" >&5
$as_echo_n "checking whether a program can dlopen itself... " >&6; }
if ${lt_cv_dlopen_self+:} false; then :
$as_echo_n "(cached) " >&6
else
if test "$cross_compiling" = yes; then :
lt_cv_dlopen_self=cross
else
lt_dlunknown=0; lt_dlno_uscore=1; lt_dlneed_uscore=2
lt_status=$lt_dlunknown
cat > conftest.$ac_ext <<_LT_EOF
#line $LINENO "configure"
#include "confdefs.h"
#if HAVE_DLFCN_H
#include
#endif
#include
#ifdef RTLD_GLOBAL
# define LT_DLGLOBAL RTLD_GLOBAL
#else
# ifdef DL_GLOBAL
# define LT_DLGLOBAL DL_GLOBAL
# else
# define LT_DLGLOBAL 0
# endif
#endif
/* We may have to define LT_DLLAZY_OR_NOW in the command line if we
find out it does not work in some platform. */
#ifndef LT_DLLAZY_OR_NOW
# ifdef RTLD_LAZY
# define LT_DLLAZY_OR_NOW RTLD_LAZY
# else
# ifdef DL_LAZY
# define LT_DLLAZY_OR_NOW DL_LAZY
# else
# ifdef RTLD_NOW
# define LT_DLLAZY_OR_NOW RTLD_NOW
# else
# ifdef DL_NOW
# define LT_DLLAZY_OR_NOW DL_NOW
# else
# define LT_DLLAZY_OR_NOW 0
# endif
# endif
# endif
# endif
#endif
/* When -fvisbility=hidden is used, assume the code has been annotated
correspondingly for the symbols needed. */
#if defined(__GNUC__) && (((__GNUC__ == 3) && (__GNUC_MINOR__ >= 3)) || (__GNUC__ > 3))
int fnord () __attribute__((visibility("default")));
#endif
int fnord () { return 42; }
int main ()
{
void *self = dlopen (0, LT_DLGLOBAL|LT_DLLAZY_OR_NOW);
int status = $lt_dlunknown;
if (self)
{
if (dlsym (self,"fnord")) status = $lt_dlno_uscore;
else
{
if (dlsym( self,"_fnord")) status = $lt_dlneed_uscore;
else puts (dlerror ());
}
/* dlclose (self); */
}
else
puts (dlerror ());
return status;
}
_LT_EOF
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_link\""; } >&5
(eval $ac_link) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && test -s conftest${ac_exeext} 2>/dev/null; then
(./conftest; exit; ) >&5 2>/dev/null
lt_status=$?
case x$lt_status in
x$lt_dlno_uscore) lt_cv_dlopen_self=yes ;;
x$lt_dlneed_uscore) lt_cv_dlopen_self=yes ;;
x$lt_dlunknown|x*) lt_cv_dlopen_self=no ;;
esac
else :
# compilation failed
lt_cv_dlopen_self=no
fi
fi
rm -fr conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_dlopen_self" >&5
$as_echo "$lt_cv_dlopen_self" >&6; }
if test "x$lt_cv_dlopen_self" = xyes; then
wl=$lt_prog_compiler_wl eval LDFLAGS=\"\$LDFLAGS $lt_prog_compiler_static\"
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether a statically linked program can dlopen itself" >&5
$as_echo_n "checking whether a statically linked program can dlopen itself... " >&6; }
if ${lt_cv_dlopen_self_static+:} false; then :
$as_echo_n "(cached) " >&6
else
if test "$cross_compiling" = yes; then :
lt_cv_dlopen_self_static=cross
else
lt_dlunknown=0; lt_dlno_uscore=1; lt_dlneed_uscore=2
lt_status=$lt_dlunknown
cat > conftest.$ac_ext <<_LT_EOF
#line $LINENO "configure"
#include "confdefs.h"
#if HAVE_DLFCN_H
#include
#endif
#include
#ifdef RTLD_GLOBAL
# define LT_DLGLOBAL RTLD_GLOBAL
#else
# ifdef DL_GLOBAL
# define LT_DLGLOBAL DL_GLOBAL
# else
# define LT_DLGLOBAL 0
# endif
#endif
/* We may have to define LT_DLLAZY_OR_NOW in the command line if we
find out it does not work in some platform. */
#ifndef LT_DLLAZY_OR_NOW
# ifdef RTLD_LAZY
# define LT_DLLAZY_OR_NOW RTLD_LAZY
# else
# ifdef DL_LAZY
# define LT_DLLAZY_OR_NOW DL_LAZY
# else
# ifdef RTLD_NOW
# define LT_DLLAZY_OR_NOW RTLD_NOW
# else
# ifdef DL_NOW
# define LT_DLLAZY_OR_NOW DL_NOW
# else
# define LT_DLLAZY_OR_NOW 0
# endif
# endif
# endif
# endif
#endif
/* When -fvisbility=hidden is used, assume the code has been annotated
correspondingly for the symbols needed. */
#if defined(__GNUC__) && (((__GNUC__ == 3) && (__GNUC_MINOR__ >= 3)) || (__GNUC__ > 3))
int fnord () __attribute__((visibility("default")));
#endif
int fnord () { return 42; }
int main ()
{
void *self = dlopen (0, LT_DLGLOBAL|LT_DLLAZY_OR_NOW);
int status = $lt_dlunknown;
if (self)
{
if (dlsym (self,"fnord")) status = $lt_dlno_uscore;
else
{
if (dlsym( self,"_fnord")) status = $lt_dlneed_uscore;
else puts (dlerror ());
}
/* dlclose (self); */
}
else
puts (dlerror ());
return status;
}
_LT_EOF
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_link\""; } >&5
(eval $ac_link) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } && test -s conftest${ac_exeext} 2>/dev/null; then
(./conftest; exit; ) >&5 2>/dev/null
lt_status=$?
case x$lt_status in
x$lt_dlno_uscore) lt_cv_dlopen_self_static=yes ;;
x$lt_dlneed_uscore) lt_cv_dlopen_self_static=yes ;;
x$lt_dlunknown|x*) lt_cv_dlopen_self_static=no ;;
esac
else :
# compilation failed
lt_cv_dlopen_self_static=no
fi
fi
rm -fr conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_dlopen_self_static" >&5
$as_echo "$lt_cv_dlopen_self_static" >&6; }
fi
CPPFLAGS="$save_CPPFLAGS"
LDFLAGS="$save_LDFLAGS"
LIBS="$save_LIBS"
;;
esac
case $lt_cv_dlopen_self in
yes|no) enable_dlopen_self=$lt_cv_dlopen_self ;;
*) enable_dlopen_self=unknown ;;
esac
case $lt_cv_dlopen_self_static in
yes|no) enable_dlopen_self_static=$lt_cv_dlopen_self_static ;;
*) enable_dlopen_self_static=unknown ;;
esac
fi
striplib=
old_striplib=
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether stripping libraries is possible" >&5
$as_echo_n "checking whether stripping libraries is possible... " >&6; }
if test -n "$STRIP" && $STRIP -V 2>&1 | $GREP "GNU strip" >/dev/null; then
test -z "$old_striplib" && old_striplib="$STRIP --strip-debug"
test -z "$striplib" && striplib="$STRIP --strip-unneeded"
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: yes" >&5
$as_echo "yes" >&6; }
else
# FIXME - insert some real tests, host_os isn't really good enough
case $host_os in
darwin*)
if test -n "$STRIP" ; then
striplib="$STRIP -x"
old_striplib="$STRIP -S"
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: yes" >&5
$as_echo "yes" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
;;
*)
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
;;
esac
fi
# Report which library types will actually be built
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if libtool supports shared libraries" >&5
$as_echo_n "checking if libtool supports shared libraries... " >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $can_build_shared" >&5
$as_echo "$can_build_shared" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether to build shared libraries" >&5
$as_echo_n "checking whether to build shared libraries... " >&6; }
test "$can_build_shared" = "no" && enable_shared=no
# On AIX, shared libraries and static libraries use the same namespace, and
# are all built from PIC.
case $host_os in
aix3*)
test "$enable_shared" = yes && enable_static=no
if test -n "$RANLIB"; then
archive_cmds="$archive_cmds~\$RANLIB \$lib"
postinstall_cmds='$RANLIB $lib'
fi
;;
aix[4-9]*)
if test "$host_cpu" != ia64 && test "$aix_use_runtimelinking" = no ; then
test "$enable_shared" = yes && enable_static=no
fi
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $enable_shared" >&5
$as_echo "$enable_shared" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether to build static libraries" >&5
$as_echo_n "checking whether to build static libraries... " >&6; }
# Make sure either enable_shared or enable_static is yes.
test "$enable_shared" = yes || enable_static=yes
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $enable_static" >&5
$as_echo "$enable_static" >&6; }
fi
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
CC="$lt_save_CC"
if test -n "$CXX" && ( test "X$CXX" != "Xno" &&
( (test "X$CXX" = "Xg++" && `g++ -v >/dev/null 2>&1` ) ||
(test "X$CXX" != "Xg++"))) ; then
ac_ext=cpp
ac_cpp='$CXXCPP $CPPFLAGS'
ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_cxx_compiler_gnu
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking how to run the C++ preprocessor" >&5
$as_echo_n "checking how to run the C++ preprocessor... " >&6; }
if test -z "$CXXCPP"; then
if ${ac_cv_prog_CXXCPP+:} false; then :
$as_echo_n "(cached) " >&6
else
# Double quotes because CXXCPP needs to be expanded
for CXXCPP in "$CXX -E" "/lib/cpp"
do
ac_preproc_ok=false
for ac_cxx_preproc_warn_flag in '' yes
do
# Use a header file that comes with gcc, so configuring glibc
# with a fresh cross-compiler works.
# Prefer to if __STDC__ is defined, since
# exists even on freestanding compilers.
# On the NeXT, cc -E runs the code through the compiler's parser,
# not just through cpp. "Syntax error" is here to catch this case.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#ifdef __STDC__
# include
#else
# include
#endif
Syntax error
_ACEOF
if ac_fn_cxx_try_cpp "$LINENO"; then :
else
# Broken: fails on valid input.
continue
fi
rm -f conftest.err conftest.i conftest.$ac_ext
# OK, works on sane cases. Now check whether nonexistent headers
# can be detected and how.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
_ACEOF
if ac_fn_cxx_try_cpp "$LINENO"; then :
# Broken: success on invalid input.
continue
else
# Passes both tests.
ac_preproc_ok=:
break
fi
rm -f conftest.err conftest.i conftest.$ac_ext
done
# Because of `break', _AC_PREPROC_IFELSE's cleaning code was skipped.
rm -f conftest.i conftest.err conftest.$ac_ext
if $ac_preproc_ok; then :
break
fi
done
ac_cv_prog_CXXCPP=$CXXCPP
fi
CXXCPP=$ac_cv_prog_CXXCPP
else
ac_cv_prog_CXXCPP=$CXXCPP
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $CXXCPP" >&5
$as_echo "$CXXCPP" >&6; }
ac_preproc_ok=false
for ac_cxx_preproc_warn_flag in '' yes
do
# Use a header file that comes with gcc, so configuring glibc
# with a fresh cross-compiler works.
# Prefer to if __STDC__ is defined, since
# exists even on freestanding compilers.
# On the NeXT, cc -E runs the code through the compiler's parser,
# not just through cpp. "Syntax error" is here to catch this case.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#ifdef __STDC__
# include
#else
# include
#endif
Syntax error
_ACEOF
if ac_fn_cxx_try_cpp "$LINENO"; then :
else
# Broken: fails on valid input.
continue
fi
rm -f conftest.err conftest.i conftest.$ac_ext
# OK, works on sane cases. Now check whether nonexistent headers
# can be detected and how.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
_ACEOF
if ac_fn_cxx_try_cpp "$LINENO"; then :
# Broken: success on invalid input.
continue
else
# Passes both tests.
ac_preproc_ok=:
break
fi
rm -f conftest.err conftest.i conftest.$ac_ext
done
# Because of `break', _AC_PREPROC_IFELSE's cleaning code was skipped.
rm -f conftest.i conftest.err conftest.$ac_ext
if $ac_preproc_ok; then :
else
{ { $as_echo "$as_me:${as_lineno-$LINENO}: error: in \`$ac_pwd':" >&5
$as_echo "$as_me: error: in \`$ac_pwd':" >&2;}
as_fn_error $? "C++ preprocessor \"$CXXCPP\" fails sanity check
See \`config.log' for more details" "$LINENO" 5; }
fi
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
else
_lt_caught_CXX_error=yes
fi
ac_ext=cpp
ac_cpp='$CXXCPP $CPPFLAGS'
ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_cxx_compiler_gnu
archive_cmds_need_lc_CXX=no
allow_undefined_flag_CXX=
always_export_symbols_CXX=no
archive_expsym_cmds_CXX=
compiler_needs_object_CXX=no
export_dynamic_flag_spec_CXX=
hardcode_direct_CXX=no
hardcode_direct_absolute_CXX=no
hardcode_libdir_flag_spec_CXX=
hardcode_libdir_separator_CXX=
hardcode_minus_L_CXX=no
hardcode_shlibpath_var_CXX=unsupported
hardcode_automatic_CXX=no
inherit_rpath_CXX=no
module_cmds_CXX=
module_expsym_cmds_CXX=
link_all_deplibs_CXX=unknown
old_archive_cmds_CXX=$old_archive_cmds
reload_flag_CXX=$reload_flag
reload_cmds_CXX=$reload_cmds
no_undefined_flag_CXX=
whole_archive_flag_spec_CXX=
enable_shared_with_static_runtimes_CXX=no
# Source file extension for C++ test sources.
ac_ext=cpp
# Object file extension for compiled C++ test sources.
objext=o
objext_CXX=$objext
# No sense in running all these tests if we already determined that
# the CXX compiler isn't working. Some variables (like enable_shared)
# are currently assumed to apply to all compilers on this platform,
# and will be corrupted by setting them based on a non-working compiler.
if test "$_lt_caught_CXX_error" != yes; then
# Code to be used in simple compile tests
lt_simple_compile_test_code="int some_variable = 0;"
# Code to be used in simple link tests
lt_simple_link_test_code='int main(int, char *[]) { return(0); }'
# ltmain only uses $CC for tagged configurations so make sure $CC is set.
# If no C compiler was specified, use CC.
LTCC=${LTCC-"$CC"}
# If no C compiler flags were specified, use CFLAGS.
LTCFLAGS=${LTCFLAGS-"$CFLAGS"}
# Allow CC to be a program name with arguments.
compiler=$CC
# save warnings/boilerplate of simple test code
ac_outfile=conftest.$ac_objext
echo "$lt_simple_compile_test_code" >conftest.$ac_ext
eval "$ac_compile" 2>&1 >/dev/null | $SED '/^$/d; /^ *+/d' >conftest.err
_lt_compiler_boilerplate=`cat conftest.err`
$RM conftest*
ac_outfile=conftest.$ac_objext
echo "$lt_simple_link_test_code" >conftest.$ac_ext
eval "$ac_link" 2>&1 >/dev/null | $SED '/^$/d; /^ *+/d' >conftest.err
_lt_linker_boilerplate=`cat conftest.err`
$RM -r conftest*
# Allow CC to be a program name with arguments.
lt_save_CC=$CC
lt_save_CFLAGS=$CFLAGS
lt_save_LD=$LD
lt_save_GCC=$GCC
GCC=$GXX
lt_save_with_gnu_ld=$with_gnu_ld
lt_save_path_LD=$lt_cv_path_LD
if test -n "${lt_cv_prog_gnu_ldcxx+set}"; then
lt_cv_prog_gnu_ld=$lt_cv_prog_gnu_ldcxx
else
$as_unset lt_cv_prog_gnu_ld
fi
if test -n "${lt_cv_path_LDCXX+set}"; then
lt_cv_path_LD=$lt_cv_path_LDCXX
else
$as_unset lt_cv_path_LD
fi
test -z "${LDCXX+set}" || LD=$LDCXX
CC=${CXX-"c++"}
CFLAGS=$CXXFLAGS
compiler=$CC
compiler_CXX=$CC
for cc_temp in $compiler""; do
case $cc_temp in
compile | *[\\/]compile | ccache | *[\\/]ccache ) ;;
distcc | *[\\/]distcc | purify | *[\\/]purify ) ;;
\-*) ;;
*) break;;
esac
done
cc_basename=`$ECHO "$cc_temp" | $SED "s%.*/%%; s%^$host_alias-%%"`
if test -n "$compiler"; then
# We don't want -fno-exception when compiling C++ code, so set the
# no_builtin_flag separately
if test "$GXX" = yes; then
lt_prog_compiler_no_builtin_flag_CXX=' -fno-builtin'
else
lt_prog_compiler_no_builtin_flag_CXX=
fi
if test "$GXX" = yes; then
# Set up default GNU C++ configuration
# Check whether --with-gnu-ld was given.
if test "${with_gnu_ld+set}" = set; then :
withval=$with_gnu_ld; test "$withval" = no || with_gnu_ld=yes
else
with_gnu_ld=no
fi
ac_prog=ld
if test "$GCC" = yes; then
# Check if gcc -print-prog-name=ld gives a path.
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for ld used by $CC" >&5
$as_echo_n "checking for ld used by $CC... " >&6; }
case $host in
*-*-mingw*)
# gcc leaves a trailing carriage return which upsets mingw
ac_prog=`($CC -print-prog-name=ld) 2>&5 | tr -d '\015'` ;;
*)
ac_prog=`($CC -print-prog-name=ld) 2>&5` ;;
esac
case $ac_prog in
# Accept absolute paths.
[\\/]* | ?:[\\/]*)
re_direlt='/[^/][^/]*/\.\./'
# Canonicalize the pathname of ld
ac_prog=`$ECHO "$ac_prog"| $SED 's%\\\\%/%g'`
while $ECHO "$ac_prog" | $GREP "$re_direlt" > /dev/null 2>&1; do
ac_prog=`$ECHO $ac_prog| $SED "s%$re_direlt%/%"`
done
test -z "$LD" && LD="$ac_prog"
;;
"")
# If it fails, then pretend we aren't using GCC.
ac_prog=ld
;;
*)
# If it is relative, then search for the first ld in PATH.
with_gnu_ld=unknown
;;
esac
elif test "$with_gnu_ld" = yes; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for GNU ld" >&5
$as_echo_n "checking for GNU ld... " >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for non-GNU ld" >&5
$as_echo_n "checking for non-GNU ld... " >&6; }
fi
if ${lt_cv_path_LD+:} false; then :
$as_echo_n "(cached) " >&6
else
if test -z "$LD"; then
lt_save_ifs="$IFS"; IFS=$PATH_SEPARATOR
for ac_dir in $PATH; do
IFS="$lt_save_ifs"
test -z "$ac_dir" && ac_dir=.
if test -f "$ac_dir/$ac_prog" || test -f "$ac_dir/$ac_prog$ac_exeext"; then
lt_cv_path_LD="$ac_dir/$ac_prog"
# Check to see if the program is GNU ld. I'd rather use --version,
# but apparently some variants of GNU ld only accept -v.
# Break only if it was the GNU/non-GNU ld that we prefer.
case `"$lt_cv_path_LD" -v 2>&1 &5
$as_echo "$LD" >&6; }
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
test -z "$LD" && as_fn_error $? "no acceptable ld found in \$PATH" "$LINENO" 5
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if the linker ($LD) is GNU ld" >&5
$as_echo_n "checking if the linker ($LD) is GNU ld... " >&6; }
if ${lt_cv_prog_gnu_ld+:} false; then :
$as_echo_n "(cached) " >&6
else
# I'd rather use --version here, but apparently some GNU lds only accept -v.
case `$LD -v 2>&1 &5
$as_echo "$lt_cv_prog_gnu_ld" >&6; }
with_gnu_ld=$lt_cv_prog_gnu_ld
# Check if GNU C++ uses GNU ld as the underlying linker, since the
# archiving commands below assume that GNU ld is being used.
if test "$with_gnu_ld" = yes; then
archive_cmds_CXX='$CC $pic_flag -shared -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds_CXX='$CC $pic_flag -shared -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
hardcode_libdir_flag_spec_CXX='${wl}-rpath ${wl}$libdir'
export_dynamic_flag_spec_CXX='${wl}--export-dynamic'
# If archive_cmds runs LD, not CC, wlarc should be empty
# XXX I think wlarc can be eliminated in ltcf-cxx, but I need to
# investigate it a little bit more. (MM)
wlarc='${wl}'
# ancient GNU ld didn't support --whole-archive et. al.
if eval "`$CC -print-prog-name=ld` --help 2>&1" |
$GREP 'no-whole-archive' > /dev/null; then
whole_archive_flag_spec_CXX="$wlarc"'--whole-archive$convenience '"$wlarc"'--no-whole-archive'
else
whole_archive_flag_spec_CXX=
fi
else
with_gnu_ld=no
wlarc=
# A generic and very simple default shared library creation
# command for GNU C++ for the case where it uses the native
# linker, instead of GNU ld. If possible, this setting should
# overridden to take advantage of the native linker features on
# the platform it is being used on.
archive_cmds_CXX='$CC -shared -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $lib'
fi
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
output_verbose_link_cmd='$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP -v "^Configured with:" | $GREP "\-L"'
else
GXX=no
with_gnu_ld=no
wlarc=
fi
# PORTME: fill in a description of your system's C++ link characteristics
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether the $compiler linker ($LD) supports shared libraries" >&5
$as_echo_n "checking whether the $compiler linker ($LD) supports shared libraries... " >&6; }
ld_shlibs_CXX=yes
case $host_os in
aix3*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
aix[4-9]*)
if test "$host_cpu" = ia64; then
# On IA64, the linker does run time linking by default, so we don't
# have to do anything special.
aix_use_runtimelinking=no
exp_sym_flag='-Bexport'
no_entry_flag=""
else
aix_use_runtimelinking=no
# Test if we are trying to use run time linking or normal
# AIX style linking. If -brtl is somewhere in LDFLAGS, we
# need to do runtime linking.
case $host_os in aix4.[23]|aix4.[23].*|aix[5-9]*)
for ld_flag in $LDFLAGS; do
case $ld_flag in
*-brtl*)
aix_use_runtimelinking=yes
break
;;
esac
done
;;
esac
exp_sym_flag='-bexport'
no_entry_flag='-bnoentry'
fi
# When large executables or shared objects are built, AIX ld can
# have problems creating the table of contents. If linking a library
# or program results in "error TOC overflow" add -mminimal-toc to
# CXXFLAGS/CFLAGS for g++/gcc. In the cases where that is not
# enough to fix the problem, add -Wl,-bbigtoc to LDFLAGS.
archive_cmds_CXX=''
hardcode_direct_CXX=yes
hardcode_direct_absolute_CXX=yes
hardcode_libdir_separator_CXX=':'
link_all_deplibs_CXX=yes
file_list_spec_CXX='${wl}-f,'
if test "$GXX" = yes; then
case $host_os in aix4.[012]|aix4.[012].*)
# We only want to do this on AIX 4.2 and lower, the check
# below for broken collect2 doesn't work under 4.3+
collect2name=`${CC} -print-prog-name=collect2`
if test -f "$collect2name" &&
strings "$collect2name" | $GREP resolve_lib_name >/dev/null
then
# We have reworked collect2
:
else
# We have old collect2
hardcode_direct_CXX=unsupported
# It fails to find uninstalled libraries when the uninstalled
# path is not listed in the libpath. Setting hardcode_minus_L
# to unsupported forces relinking
hardcode_minus_L_CXX=yes
hardcode_libdir_flag_spec_CXX='-L$libdir'
hardcode_libdir_separator_CXX=
fi
esac
shared_flag='-shared'
if test "$aix_use_runtimelinking" = yes; then
shared_flag="$shared_flag "'${wl}-G'
fi
else
# not using gcc
if test "$host_cpu" = ia64; then
# VisualAge C++, Version 5.5 for AIX 5L for IA-64, Beta 3 Release
# chokes on -Wl,-G. The following line is correct:
shared_flag='-G'
else
if test "$aix_use_runtimelinking" = yes; then
shared_flag='${wl}-G'
else
shared_flag='${wl}-bM:SRE'
fi
fi
fi
export_dynamic_flag_spec_CXX='${wl}-bexpall'
# It seems that -bexpall does not export symbols beginning with
# underscore (_), so it is better to generate a list of symbols to
# export.
always_export_symbols_CXX=yes
if test "$aix_use_runtimelinking" = yes; then
# Warning - without using the other runtime loading flags (-brtl),
# -berok will link without error, but may produce a broken library.
allow_undefined_flag_CXX='-berok'
# Determine the default libpath from the value encoded in an empty
# executable.
if test "${lt_cv_aix_libpath+set}" = set; then
aix_libpath=$lt_cv_aix_libpath
else
if ${lt_cv_aix_libpath__CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_cxx_try_link "$LINENO"; then :
lt_aix_libpath_sed='
/Import File Strings/,/^$/ {
/^0/ {
s/^0 *\([^ ]*\) *$/\1/
p
}
}'
lt_cv_aix_libpath__CXX=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
# Check for a 64-bit object if we didn't find anything.
if test -z "$lt_cv_aix_libpath__CXX"; then
lt_cv_aix_libpath__CXX=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
fi
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
if test -z "$lt_cv_aix_libpath__CXX"; then
lt_cv_aix_libpath__CXX="/usr/lib:/lib"
fi
fi
aix_libpath=$lt_cv_aix_libpath__CXX
fi
hardcode_libdir_flag_spec_CXX='${wl}-blibpath:$libdir:'"$aix_libpath"
archive_expsym_cmds_CXX='$CC -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags `if test "x${allow_undefined_flag}" != "x"; then func_echo_all "${wl}${allow_undefined_flag}"; else :; fi` '"\${wl}$exp_sym_flag:\$export_symbols $shared_flag"
else
if test "$host_cpu" = ia64; then
hardcode_libdir_flag_spec_CXX='${wl}-R $libdir:/usr/lib:/lib'
allow_undefined_flag_CXX="-z nodefs"
archive_expsym_cmds_CXX="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs '"\${wl}$no_entry_flag"' $compiler_flags ${wl}${allow_undefined_flag} '"\${wl}$exp_sym_flag:\$export_symbols"
else
# Determine the default libpath from the value encoded in an
# empty executable.
if test "${lt_cv_aix_libpath+set}" = set; then
aix_libpath=$lt_cv_aix_libpath
else
if ${lt_cv_aix_libpath__CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_cxx_try_link "$LINENO"; then :
lt_aix_libpath_sed='
/Import File Strings/,/^$/ {
/^0/ {
s/^0 *\([^ ]*\) *$/\1/
p
}
}'
lt_cv_aix_libpath__CXX=`dump -H conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
# Check for a 64-bit object if we didn't find anything.
if test -z "$lt_cv_aix_libpath__CXX"; then
lt_cv_aix_libpath__CXX=`dump -HX64 conftest$ac_exeext 2>/dev/null | $SED -n -e "$lt_aix_libpath_sed"`
fi
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
if test -z "$lt_cv_aix_libpath__CXX"; then
lt_cv_aix_libpath__CXX="/usr/lib:/lib"
fi
fi
aix_libpath=$lt_cv_aix_libpath__CXX
fi
hardcode_libdir_flag_spec_CXX='${wl}-blibpath:$libdir:'"$aix_libpath"
# Warning - without using the other run time loading flags,
# -berok will link without error, but may produce a broken library.
no_undefined_flag_CXX=' ${wl}-bernotok'
allow_undefined_flag_CXX=' ${wl}-berok'
if test "$with_gnu_ld" = yes; then
# We only use this code for GNU lds that support --whole-archive.
whole_archive_flag_spec_CXX='${wl}--whole-archive$convenience ${wl}--no-whole-archive'
else
# Exported symbols can be pulled into shared objects from archives
whole_archive_flag_spec_CXX='$convenience'
fi
archive_cmds_need_lc_CXX=yes
# This is similar to how AIX traditionally builds its shared
# libraries.
archive_expsym_cmds_CXX="\$CC $shared_flag"' -o $output_objdir/$soname $libobjs $deplibs ${wl}-bnoentry $compiler_flags ${wl}-bE:$export_symbols${allow_undefined_flag}~$AR $AR_FLAGS $output_objdir/$libname$release.a $output_objdir/$soname'
fi
fi
;;
beos*)
if $LD --help 2>&1 | $GREP ': supported targets:.* elf' > /dev/null; then
allow_undefined_flag_CXX=unsupported
# Joseph Beckenbach says some releases of gcc
# support --undefined. This deserves some investigation. FIXME
archive_cmds_CXX='$CC -nostart $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
else
ld_shlibs_CXX=no
fi
;;
chorus*)
case $cc_basename in
*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
esac
;;
cygwin* | mingw* | pw32* | cegcc*)
case $GXX,$cc_basename in
,cl* | no,cl*)
# Native MSVC
# hardcode_libdir_flag_spec is actually meaningless, as there is
# no search path for DLLs.
hardcode_libdir_flag_spec_CXX=' '
allow_undefined_flag_CXX=unsupported
always_export_symbols_CXX=yes
file_list_spec_CXX='@'
# Tell ltmain to make .lib files, not .a files.
libext=lib
# Tell ltmain to make .dll files, not .so files.
shrext_cmds=".dll"
# FIXME: Setting linknames here is a bad hack.
archive_cmds_CXX='$CC -o $output_objdir/$soname $libobjs $compiler_flags $deplibs -Wl,-dll~linknames='
archive_expsym_cmds_CXX='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then
$SED -n -e 's/\\\\\\\(.*\\\\\\\)/-link\\\ -EXPORT:\\\\\\\1/' -e '1\\\!p' < $export_symbols > $output_objdir/$soname.exp;
else
$SED -e 's/\\\\\\\(.*\\\\\\\)/-link\\\ -EXPORT:\\\\\\\1/' < $export_symbols > $output_objdir/$soname.exp;
fi~
$CC -o $tool_output_objdir$soname $libobjs $compiler_flags $deplibs "@$tool_output_objdir$soname.exp" -Wl,-DLL,-IMPLIB:"$tool_output_objdir$libname.dll.lib"~
linknames='
# The linker will not automatically build a static lib if we build a DLL.
# _LT_TAGVAR(old_archive_from_new_cmds, CXX)='true'
enable_shared_with_static_runtimes_CXX=yes
# Don't use ranlib
old_postinstall_cmds_CXX='chmod 644 $oldlib'
postlink_cmds_CXX='lt_outputfile="@OUTPUT@"~
lt_tool_outputfile="@TOOL_OUTPUT@"~
case $lt_outputfile in
*.exe|*.EXE) ;;
*)
lt_outputfile="$lt_outputfile.exe"
lt_tool_outputfile="$lt_tool_outputfile.exe"
;;
esac~
func_to_tool_file "$lt_outputfile"~
if test "$MANIFEST_TOOL" != ":" && test -f "$lt_outputfile.manifest"; then
$MANIFEST_TOOL -manifest "$lt_tool_outputfile.manifest" -outputresource:"$lt_tool_outputfile" || exit 1;
$RM "$lt_outputfile.manifest";
fi'
;;
*)
# g++
# _LT_TAGVAR(hardcode_libdir_flag_spec, CXX) is actually meaningless,
# as there is no search path for DLLs.
hardcode_libdir_flag_spec_CXX='-L$libdir'
export_dynamic_flag_spec_CXX='${wl}--export-all-symbols'
allow_undefined_flag_CXX=unsupported
always_export_symbols_CXX=no
enable_shared_with_static_runtimes_CXX=yes
if $LD --help 2>&1 | $GREP 'auto-import' > /dev/null; then
archive_cmds_CXX='$CC -shared -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib'
# If the export-symbols file already is a .def file (1st line
# is EXPORTS), use it as is; otherwise, prepend...
archive_expsym_cmds_CXX='if test "x`$SED 1q $export_symbols`" = xEXPORTS; then
cp $export_symbols $output_objdir/$soname.def;
else
echo EXPORTS > $output_objdir/$soname.def;
cat $export_symbols >> $output_objdir/$soname.def;
fi~
$CC -shared -nostdlib $output_objdir/$soname.def $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $output_objdir/$soname ${wl}--enable-auto-image-base -Xlinker --out-implib -Xlinker $lib'
else
ld_shlibs_CXX=no
fi
;;
esac
;;
darwin* | rhapsody*)
archive_cmds_need_lc_CXX=no
hardcode_direct_CXX=no
hardcode_automatic_CXX=yes
hardcode_shlibpath_var_CXX=unsupported
if test "$lt_cv_ld_force_load" = "yes"; then
whole_archive_flag_spec_CXX='`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience ${wl}-force_load,$conv\"; done; func_echo_all \"$new_convenience\"`'
else
whole_archive_flag_spec_CXX=''
fi
link_all_deplibs_CXX=yes
allow_undefined_flag_CXX="$_lt_dar_allow_undefined"
case $cc_basename in
ifort*) _lt_dar_can_shared=yes ;;
*) _lt_dar_can_shared=$GCC ;;
esac
if test "$_lt_dar_can_shared" = "yes"; then
output_verbose_link_cmd=func_echo_all
archive_cmds_CXX="\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring $_lt_dar_single_mod${_lt_dsymutil}"
module_cmds_CXX="\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dsymutil}"
archive_expsym_cmds_CXX="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \$libobjs \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring ${_lt_dar_single_mod}${_lt_dar_export_syms}${_lt_dsymutil}"
module_expsym_cmds_CXX="sed -e 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC \$allow_undefined_flag -o \$lib -bundle \$libobjs \$deplibs \$compiler_flags${_lt_dar_export_syms}${_lt_dsymutil}"
if test "$lt_cv_apple_cc_single_mod" != "yes"; then
archive_cmds_CXX="\$CC -r -keep_private_externs -nostdlib -o \${lib}-master.o \$libobjs~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \${lib}-master.o \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring${_lt_dsymutil}"
archive_expsym_cmds_CXX="sed 's,^,_,' < \$export_symbols > \$output_objdir/\${libname}-symbols.expsym~\$CC -r -keep_private_externs -nostdlib -o \${lib}-master.o \$libobjs~\$CC -dynamiclib \$allow_undefined_flag -o \$lib \${lib}-master.o \$deplibs \$compiler_flags -install_name \$rpath/\$soname \$verstring${_lt_dar_export_syms}${_lt_dsymutil}"
fi
else
ld_shlibs_CXX=no
fi
;;
dgux*)
case $cc_basename in
ec++*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
ghcx*)
# Green Hills C++ Compiler
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
esac
;;
freebsd2.*)
# C++ shared libraries reported to be fairly broken before
# switch to ELF
ld_shlibs_CXX=no
;;
freebsd-elf*)
archive_cmds_need_lc_CXX=no
;;
freebsd* | dragonfly*)
# FreeBSD 3 and later use GNU C++ and GNU ld with standard ELF
# conventions
ld_shlibs_CXX=yes
;;
gnu*)
;;
haiku*)
archive_cmds_CXX='$CC -shared $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
link_all_deplibs_CXX=yes
;;
hpux9*)
hardcode_libdir_flag_spec_CXX='${wl}+b ${wl}$libdir'
hardcode_libdir_separator_CXX=:
export_dynamic_flag_spec_CXX='${wl}-E'
hardcode_direct_CXX=yes
hardcode_minus_L_CXX=yes # Not in the search PATH,
# but as the default
# location of the library.
case $cc_basename in
CC*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
aCC*)
archive_cmds_CXX='$RM $output_objdir/$soname~$CC -b ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib'
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`($CC -b $CFLAGS -v conftest.$objext 2>&1) | $EGREP "\-L"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "$list"'
;;
*)
if test "$GXX" = yes; then
archive_cmds_CXX='$RM $output_objdir/$soname~$CC -shared -nostdlib $pic_flag ${wl}+b ${wl}$install_libdir -o $output_objdir/$soname $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~test $output_objdir/$soname = $lib || mv $output_objdir/$soname $lib'
else
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
fi
;;
esac
;;
hpux10*|hpux11*)
if test $with_gnu_ld = no; then
hardcode_libdir_flag_spec_CXX='${wl}+b ${wl}$libdir'
hardcode_libdir_separator_CXX=:
case $host_cpu in
hppa*64*|ia64*)
;;
*)
export_dynamic_flag_spec_CXX='${wl}-E'
;;
esac
fi
case $host_cpu in
hppa*64*|ia64*)
hardcode_direct_CXX=no
hardcode_shlibpath_var_CXX=no
;;
*)
hardcode_direct_CXX=yes
hardcode_direct_absolute_CXX=yes
hardcode_minus_L_CXX=yes # Not in the search PATH,
# but as the default
# location of the library.
;;
esac
case $cc_basename in
CC*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
aCC*)
case $host_cpu in
hppa*64*)
archive_cmds_CXX='$CC -b ${wl}+h ${wl}$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
ia64*)
archive_cmds_CXX='$CC -b ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
*)
archive_cmds_CXX='$CC -b ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
esac
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`($CC -b $CFLAGS -v conftest.$objext 2>&1) | $GREP "\-L"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "$list"'
;;
*)
if test "$GXX" = yes; then
if test $with_gnu_ld = no; then
case $host_cpu in
hppa*64*)
archive_cmds_CXX='$CC -shared -nostdlib -fPIC ${wl}+h ${wl}$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
ia64*)
archive_cmds_CXX='$CC -shared -nostdlib $pic_flag ${wl}+h ${wl}$soname ${wl}+nodefaultrpath -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
*)
archive_cmds_CXX='$CC -shared -nostdlib $pic_flag ${wl}+h ${wl}$soname ${wl}+b ${wl}$install_libdir -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
;;
esac
fi
else
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
fi
;;
esac
;;
interix[3-9]*)
hardcode_direct_CXX=no
hardcode_shlibpath_var_CXX=no
hardcode_libdir_flag_spec_CXX='${wl}-rpath,$libdir'
export_dynamic_flag_spec_CXX='${wl}-E'
# Hack: On Interix 3.x, we cannot compile PIC because of a broken gcc.
# Instead, shared libraries are loaded at an image base (0x10000000 by
# default) and relocated if they conflict, which is a slow very memory
# consuming and fragmenting process. To avoid this, we pick a random,
# 256 KiB-aligned image base between 0x50000000 and 0x6FFC0000 at link
# time. Moving up from 0x10000000 also allows more sbrk(2) space.
archive_cmds_CXX='$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib'
archive_expsym_cmds_CXX='sed "s,^,_," $export_symbols >$output_objdir/$soname.expsym~$CC -shared $pic_flag $libobjs $deplibs $compiler_flags ${wl}-h,$soname ${wl}--retain-symbols-file,$output_objdir/$soname.expsym ${wl}--image-base,`expr ${RANDOM-$$} % 4096 / 2 \* 262144 + 1342177280` -o $lib'
;;
irix5* | irix6*)
case $cc_basename in
CC*)
# SGI C++
archive_cmds_CXX='$CC -shared -all -multigot $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
# Archives containing C++ object files must be created using
# "CC -ar", where "CC" is the IRIX C++ compiler. This is
# necessary to make sure instantiated templates are included
# in the archive.
old_archive_cmds_CXX='$CC -ar -WR,-u -o $oldlib $oldobjs'
;;
*)
if test "$GXX" = yes; then
if test "$with_gnu_ld" = no; then
archive_cmds_CXX='$CC -shared $pic_flag -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
else
archive_cmds_CXX='$CC -shared $pic_flag -nostdlib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` -o $lib'
fi
fi
link_all_deplibs_CXX=yes
;;
esac
hardcode_libdir_flag_spec_CXX='${wl}-rpath ${wl}$libdir'
hardcode_libdir_separator_CXX=:
inherit_rpath_CXX=yes
;;
linux* | k*bsd*-gnu | kopensolaris*-gnu)
case $cc_basename in
KCC*)
# Kuck and Associates, Inc. (KAI) C++ Compiler
# KCC will only create a shared library if the output file
# ends with ".so" (or ".sl" for HP-UX), so rename the library
# to its proper name (with version) after linking.
archive_cmds_CXX='tempext=`echo $shared_ext | $SED -e '\''s/\([^()0-9A-Za-z{}]\)/\\\\\1/g'\''`; templib=`echo $lib | $SED -e "s/\${tempext}\..*/.so/"`; $CC $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags --soname $soname -o \$templib; mv \$templib $lib'
archive_expsym_cmds_CXX='tempext=`echo $shared_ext | $SED -e '\''s/\([^()0-9A-Za-z{}]\)/\\\\\1/g'\''`; templib=`echo $lib | $SED -e "s/\${tempext}\..*/.so/"`; $CC $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags --soname $soname -o \$templib ${wl}-retain-symbols-file,$export_symbols; mv \$templib $lib'
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`$CC $CFLAGS -v conftest.$objext -o libconftest$shared_ext 2>&1 | $GREP "ld"`; rm -f libconftest$shared_ext; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "$list"'
hardcode_libdir_flag_spec_CXX='${wl}-rpath,$libdir'
export_dynamic_flag_spec_CXX='${wl}--export-dynamic'
# Archives containing C++ object files must be created using
# "CC -Bstatic", where "CC" is the KAI C++ compiler.
old_archive_cmds_CXX='$CC -Bstatic -o $oldlib $oldobjs'
;;
icpc* | ecpc* )
# Intel C++
with_gnu_ld=yes
# version 8.0 and above of icpc choke on multiply defined symbols
# if we add $predep_objects and $postdep_objects, however 7.1 and
# earlier do not add the objects themselves.
case `$CC -V 2>&1` in
*"Version 7."*)
archive_cmds_CXX='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds_CXX='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
;;
*) # Version 8.0 or newer
tmp_idyn=
case $host_cpu in
ia64*) tmp_idyn=' -i_dynamic';;
esac
archive_cmds_CXX='$CC -shared'"$tmp_idyn"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds_CXX='$CC -shared'"$tmp_idyn"' $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-retain-symbols-file $wl$export_symbols -o $lib'
;;
esac
archive_cmds_need_lc_CXX=no
hardcode_libdir_flag_spec_CXX='${wl}-rpath,$libdir'
export_dynamic_flag_spec_CXX='${wl}--export-dynamic'
whole_archive_flag_spec_CXX='${wl}--whole-archive$convenience ${wl}--no-whole-archive'
;;
pgCC* | pgcpp*)
# Portland Group C++ compiler
case `$CC -V` in
*pgCC\ [1-5].* | *pgcpp\ [1-5].*)
prelink_cmds_CXX='tpldir=Template.dir~
rm -rf $tpldir~
$CC --prelink_objects --instantiation_dir $tpldir $objs $libobjs $compile_deplibs~
compile_command="$compile_command `find $tpldir -name \*.o | sort | $NL2SP`"'
old_archive_cmds_CXX='tpldir=Template.dir~
rm -rf $tpldir~
$CC --prelink_objects --instantiation_dir $tpldir $oldobjs$old_deplibs~
$AR $AR_FLAGS $oldlib$oldobjs$old_deplibs `find $tpldir -name \*.o | sort | $NL2SP`~
$RANLIB $oldlib'
archive_cmds_CXX='tpldir=Template.dir~
rm -rf $tpldir~
$CC --prelink_objects --instantiation_dir $tpldir $predep_objects $libobjs $deplibs $convenience $postdep_objects~
$CC -shared $pic_flag $predep_objects $libobjs $deplibs `find $tpldir -name \*.o | sort | $NL2SP` $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname -o $lib'
archive_expsym_cmds_CXX='tpldir=Template.dir~
rm -rf $tpldir~
$CC --prelink_objects --instantiation_dir $tpldir $predep_objects $libobjs $deplibs $convenience $postdep_objects~
$CC -shared $pic_flag $predep_objects $libobjs $deplibs `find $tpldir -name \*.o | sort | $NL2SP` $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname ${wl}-retain-symbols-file ${wl}$export_symbols -o $lib'
;;
*) # Version 6 and above use weak symbols
archive_cmds_CXX='$CC -shared $pic_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname -o $lib'
archive_expsym_cmds_CXX='$CC -shared $pic_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname ${wl}-retain-symbols-file ${wl}$export_symbols -o $lib'
;;
esac
hardcode_libdir_flag_spec_CXX='${wl}--rpath ${wl}$libdir'
export_dynamic_flag_spec_CXX='${wl}--export-dynamic'
whole_archive_flag_spec_CXX='${wl}--whole-archive`for conv in $convenience\"\"; do test -n \"$conv\" && new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
;;
cxx*)
# Compaq C++
archive_cmds_CXX='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib'
archive_expsym_cmds_CXX='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $wl$soname -o $lib ${wl}-retain-symbols-file $wl$export_symbols'
runpath_var=LD_RUN_PATH
hardcode_libdir_flag_spec_CXX='-rpath $libdir'
hardcode_libdir_separator_CXX=:
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP "ld"`; templist=`func_echo_all "$templist" | $SED "s/\(^.*ld.*\)\( .*ld .*$\)/\1/"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "X$list" | $Xsed'
;;
xl* | mpixl* | bgxl*)
# IBM XL 8.0 on PPC, with GNU ld
hardcode_libdir_flag_spec_CXX='${wl}-rpath ${wl}$libdir'
export_dynamic_flag_spec_CXX='${wl}--export-dynamic'
archive_cmds_CXX='$CC -qmkshrobj $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname -o $lib'
if test "x$supports_anon_versioning" = xyes; then
archive_expsym_cmds_CXX='echo "{ global:" > $output_objdir/$libname.ver~
cat $export_symbols | sed -e "s/\(.*\)/\1;/" >> $output_objdir/$libname.ver~
echo "local: *; };" >> $output_objdir/$libname.ver~
$CC -qmkshrobj $libobjs $deplibs $compiler_flags ${wl}-soname $wl$soname ${wl}-version-script ${wl}$output_objdir/$libname.ver -o $lib'
fi
;;
*)
case `$CC -V 2>&1 | sed 5q` in
*Sun\ C*)
# Sun C++ 5.9
no_undefined_flag_CXX=' -zdefs'
archive_cmds_CXX='$CC -G${allow_undefined_flag} -h$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
archive_expsym_cmds_CXX='$CC -G${allow_undefined_flag} -h$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-retain-symbols-file ${wl}$export_symbols'
hardcode_libdir_flag_spec_CXX='-R$libdir'
whole_archive_flag_spec_CXX='${wl}--whole-archive`new_convenience=; for conv in $convenience\"\"; do test -z \"$conv\" || new_convenience=\"$new_convenience,$conv\"; done; func_echo_all \"$new_convenience\"` ${wl}--no-whole-archive'
compiler_needs_object_CXX=yes
# Not sure whether something based on
# $CC $CFLAGS -v conftest.$objext -o libconftest$shared_ext 2>&1
# would be better.
output_verbose_link_cmd='func_echo_all'
# Archives containing C++ object files must be created using
# "CC -xar", where "CC" is the Sun C++ compiler. This is
# necessary to make sure instantiated templates are included
# in the archive.
old_archive_cmds_CXX='$CC -xar -o $oldlib $oldobjs'
;;
esac
;;
esac
;;
lynxos*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
m88k*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
mvs*)
case $cc_basename in
cxx*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
esac
;;
netbsd*)
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
archive_cmds_CXX='$LD -Bshareable -o $lib $predep_objects $libobjs $deplibs $postdep_objects $linker_flags'
wlarc=
hardcode_libdir_flag_spec_CXX='-R$libdir'
hardcode_direct_CXX=yes
hardcode_shlibpath_var_CXX=no
fi
# Workaround some broken pre-1.5 toolchains
output_verbose_link_cmd='$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP conftest.$objext | $SED -e "s:-lgcc -lc -lgcc::"'
;;
*nto* | *qnx*)
ld_shlibs_CXX=yes
;;
openbsd2*)
# C++ shared libraries are fairly broken
ld_shlibs_CXX=no
;;
openbsd*)
if test -f /usr/libexec/ld.so; then
hardcode_direct_CXX=yes
hardcode_shlibpath_var_CXX=no
hardcode_direct_absolute_CXX=yes
archive_cmds_CXX='$CC -shared $pic_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -o $lib'
hardcode_libdir_flag_spec_CXX='${wl}-rpath,$libdir'
if test -z "`echo __ELF__ | $CC -E - | grep __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
archive_expsym_cmds_CXX='$CC -shared $pic_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-retain-symbols-file,$export_symbols -o $lib'
export_dynamic_flag_spec_CXX='${wl}-E'
whole_archive_flag_spec_CXX="$wlarc"'--whole-archive$convenience '"$wlarc"'--no-whole-archive'
fi
output_verbose_link_cmd=func_echo_all
else
ld_shlibs_CXX=no
fi
;;
osf3* | osf4* | osf5*)
case $cc_basename in
KCC*)
# Kuck and Associates, Inc. (KAI) C++ Compiler
# KCC will only create a shared library if the output file
# ends with ".so" (or ".sl" for HP-UX), so rename the library
# to its proper name (with version) after linking.
archive_cmds_CXX='tempext=`echo $shared_ext | $SED -e '\''s/\([^()0-9A-Za-z{}]\)/\\\\\1/g'\''`; templib=`echo "$lib" | $SED -e "s/\${tempext}\..*/.so/"`; $CC $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags --soname $soname -o \$templib; mv \$templib $lib'
hardcode_libdir_flag_spec_CXX='${wl}-rpath,$libdir'
hardcode_libdir_separator_CXX=:
# Archives containing C++ object files must be created using
# the KAI C++ compiler.
case $host in
osf3*) old_archive_cmds_CXX='$CC -Bstatic -o $oldlib $oldobjs' ;;
*) old_archive_cmds_CXX='$CC -o $oldlib $oldobjs' ;;
esac
;;
RCC*)
# Rational C++ 2.4.1
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
cxx*)
case $host in
osf3*)
allow_undefined_flag_CXX=' ${wl}-expect_unresolved ${wl}\*'
archive_cmds_CXX='$CC -shared${allow_undefined_flag} $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname $soname `test -n "$verstring" && func_echo_all "${wl}-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
hardcode_libdir_flag_spec_CXX='${wl}-rpath ${wl}$libdir'
;;
*)
allow_undefined_flag_CXX=' -expect_unresolved \*'
archive_cmds_CXX='$CC -shared${allow_undefined_flag} $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -msym -soname $soname `test -n "$verstring" && func_echo_all "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib'
archive_expsym_cmds_CXX='for i in `cat $export_symbols`; do printf "%s %s\\n" -exported_symbol "\$i" >> $lib.exp; done~
echo "-hidden">> $lib.exp~
$CC -shared$allow_undefined_flag $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags -msym -soname $soname ${wl}-input ${wl}$lib.exp `test -n "$verstring" && $ECHO "-set_version $verstring"` -update_registry ${output_objdir}/so_locations -o $lib~
$RM $lib.exp'
hardcode_libdir_flag_spec_CXX='-rpath $libdir'
;;
esac
hardcode_libdir_separator_CXX=:
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
#
# There doesn't appear to be a way to prevent this compiler from
# explicitly linking system object files so we need to strip them
# from the output so that they don't get included in the library
# dependencies.
output_verbose_link_cmd='templist=`$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP "ld" | $GREP -v "ld:"`; templist=`func_echo_all "$templist" | $SED "s/\(^.*ld.*\)\( .*ld.*$\)/\1/"`; list=""; for z in $templist; do case $z in conftest.$objext) list="$list $z";; *.$objext);; *) list="$list $z";;esac; done; func_echo_all "$list"'
;;
*)
if test "$GXX" = yes && test "$with_gnu_ld" = no; then
allow_undefined_flag_CXX=' ${wl}-expect_unresolved ${wl}\*'
case $host in
osf3*)
archive_cmds_CXX='$CC -shared -nostdlib ${allow_undefined_flag} $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
;;
*)
archive_cmds_CXX='$CC -shared $pic_flag -nostdlib ${allow_undefined_flag} $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-msym ${wl}-soname ${wl}$soname `test -n "$verstring" && func_echo_all "${wl}-set_version ${wl}$verstring"` ${wl}-update_registry ${wl}${output_objdir}/so_locations -o $lib'
;;
esac
hardcode_libdir_flag_spec_CXX='${wl}-rpath ${wl}$libdir'
hardcode_libdir_separator_CXX=:
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
output_verbose_link_cmd='$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP -v "^Configured with:" | $GREP "\-L"'
else
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
fi
;;
esac
;;
psos*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
sunos4*)
case $cc_basename in
CC*)
# Sun C++ 4.x
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
lcc*)
# Lucid
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
esac
;;
solaris*)
case $cc_basename in
CC* | sunCC*)
# Sun C++ 4.2, 5.x and Centerline C++
archive_cmds_need_lc_CXX=yes
no_undefined_flag_CXX=' -zdefs'
archive_cmds_CXX='$CC -G${allow_undefined_flag} -h$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags'
archive_expsym_cmds_CXX='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -G${allow_undefined_flag} ${wl}-M ${wl}$lib.exp -h$soname -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~$RM $lib.exp'
hardcode_libdir_flag_spec_CXX='-R$libdir'
hardcode_shlibpath_var_CXX=no
case $host_os in
solaris2.[0-5] | solaris2.[0-5].*) ;;
*)
# The compiler driver will combine and reorder linker options,
# but understands `-z linker_flag'.
# Supported since Solaris 2.6 (maybe 2.5.1?)
whole_archive_flag_spec_CXX='-z allextract$convenience -z defaultextract'
;;
esac
link_all_deplibs_CXX=yes
output_verbose_link_cmd='func_echo_all'
# Archives containing C++ object files must be created using
# "CC -xar", where "CC" is the Sun C++ compiler. This is
# necessary to make sure instantiated templates are included
# in the archive.
old_archive_cmds_CXX='$CC -xar -o $oldlib $oldobjs'
;;
gcx*)
# Green Hills C++ Compiler
archive_cmds_CXX='$CC -shared $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-h $wl$soname -o $lib'
# The C++ compiler must be used to create the archive.
old_archive_cmds_CXX='$CC $LDFLAGS -archive -o $oldlib $oldobjs'
;;
*)
# GNU C++ compiler with Solaris linker
if test "$GXX" = yes && test "$with_gnu_ld" = no; then
no_undefined_flag_CXX=' ${wl}-z ${wl}defs'
if $CC --version | $GREP -v '^2\.7' > /dev/null; then
archive_cmds_CXX='$CC -shared $pic_flag -nostdlib $LDFLAGS $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-h $wl$soname -o $lib'
archive_expsym_cmds_CXX='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -shared $pic_flag -nostdlib ${wl}-M $wl$lib.exp -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~$RM $lib.exp'
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
output_verbose_link_cmd='$CC -shared $CFLAGS -v conftest.$objext 2>&1 | $GREP -v "^Configured with:" | $GREP "\-L"'
else
# g++ 2.7 appears to require `-G' NOT `-shared' on this
# platform.
archive_cmds_CXX='$CC -G -nostdlib $LDFLAGS $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags ${wl}-h $wl$soname -o $lib'
archive_expsym_cmds_CXX='echo "{ global:" > $lib.exp~cat $export_symbols | $SED -e "s/\(.*\)/\1;/" >> $lib.exp~echo "local: *; };" >> $lib.exp~
$CC -G -nostdlib ${wl}-M $wl$lib.exp -o $lib $predep_objects $libobjs $deplibs $postdep_objects $compiler_flags~$RM $lib.exp'
# Commands to make compiler produce verbose output that lists
# what "hidden" libraries, object files and flags are used when
# linking a shared library.
output_verbose_link_cmd='$CC -G $CFLAGS -v conftest.$objext 2>&1 | $GREP -v "^Configured with:" | $GREP "\-L"'
fi
hardcode_libdir_flag_spec_CXX='${wl}-R $wl$libdir'
case $host_os in
solaris2.[0-5] | solaris2.[0-5].*) ;;
*)
whole_archive_flag_spec_CXX='${wl}-z ${wl}allextract$convenience ${wl}-z ${wl}defaultextract'
;;
esac
fi
;;
esac
;;
sysv4*uw2* | sysv5OpenUNIX* | sysv5UnixWare7.[01].[10]* | unixware7* | sco3.2v5.0.[024]*)
no_undefined_flag_CXX='${wl}-z,text'
archive_cmds_need_lc_CXX=no
hardcode_shlibpath_var_CXX=no
runpath_var='LD_RUN_PATH'
case $cc_basename in
CC*)
archive_cmds_CXX='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds_CXX='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
*)
archive_cmds_CXX='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds_CXX='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
esac
;;
sysv5* | sco3.2v5* | sco5v6*)
# Note: We can NOT use -z defs as we might desire, because we do not
# link with -lc, and that would cause any symbols used from libc to
# always be unresolved, which means just about no library would
# ever link correctly. If we're not using GNU ld we use -z text
# though, which does catch some bad symbols but isn't as heavy-handed
# as -z defs.
no_undefined_flag_CXX='${wl}-z,text'
allow_undefined_flag_CXX='${wl}-z,nodefs'
archive_cmds_need_lc_CXX=no
hardcode_shlibpath_var_CXX=no
hardcode_libdir_flag_spec_CXX='${wl}-R,$libdir'
hardcode_libdir_separator_CXX=':'
link_all_deplibs_CXX=yes
export_dynamic_flag_spec_CXX='${wl}-Bexport'
runpath_var='LD_RUN_PATH'
case $cc_basename in
CC*)
archive_cmds_CXX='$CC -G ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds_CXX='$CC -G ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
old_archive_cmds_CXX='$CC -Tprelink_objects $oldobjs~
'"$old_archive_cmds_CXX"
reload_cmds_CXX='$CC -Tprelink_objects $reload_objs~
'"$reload_cmds_CXX"
;;
*)
archive_cmds_CXX='$CC -shared ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
archive_expsym_cmds_CXX='$CC -shared ${wl}-Bexport:$export_symbols ${wl}-h,$soname -o $lib $libobjs $deplibs $compiler_flags'
;;
esac
;;
tandem*)
case $cc_basename in
NCC*)
# NonStop-UX NCC 3.20
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
esac
;;
vxworks*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
*)
# FIXME: insert proper C++ library support
ld_shlibs_CXX=no
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ld_shlibs_CXX" >&5
$as_echo "$ld_shlibs_CXX" >&6; }
test "$ld_shlibs_CXX" = no && can_build_shared=no
GCC_CXX="$GXX"
LD_CXX="$LD"
## CAVEAT EMPTOR:
## There is no encapsulation within the following macros, do not change
## the running order or otherwise move them around unless you know exactly
## what you are doing...
# Dependencies to place before and after the object being linked:
predep_objects_CXX=
postdep_objects_CXX=
predeps_CXX=
postdeps_CXX=
compiler_lib_search_path_CXX=
cat > conftest.$ac_ext <<_LT_EOF
class Foo
{
public:
Foo (void) { a = 0; }
private:
int a;
};
_LT_EOF
_lt_libdeps_save_CFLAGS=$CFLAGS
case "$CC $CFLAGS " in #(
*\ -flto*\ *) CFLAGS="$CFLAGS -fno-lto" ;;
*\ -fwhopr*\ *) CFLAGS="$CFLAGS -fno-whopr" ;;
*\ -fuse-linker-plugin*\ *) CFLAGS="$CFLAGS -fno-use-linker-plugin" ;;
esac
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_compile\""; } >&5
(eval $ac_compile) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }; then
# Parse the compiler output and extract the necessary
# objects, libraries and library flags.
# Sentinel used to keep track of whether or not we are before
# the conftest object file.
pre_test_object_deps_done=no
for p in `eval "$output_verbose_link_cmd"`; do
case ${prev}${p} in
-L* | -R* | -l*)
# Some compilers place space between "-{L,R}" and the path.
# Remove the space.
if test $p = "-L" ||
test $p = "-R"; then
prev=$p
continue
fi
# Expand the sysroot to ease extracting the directories later.
if test -z "$prev"; then
case $p in
-L*) func_stripname_cnf '-L' '' "$p"; prev=-L; p=$func_stripname_result ;;
-R*) func_stripname_cnf '-R' '' "$p"; prev=-R; p=$func_stripname_result ;;
-l*) func_stripname_cnf '-l' '' "$p"; prev=-l; p=$func_stripname_result ;;
esac
fi
case $p in
=*) func_stripname_cnf '=' '' "$p"; p=$lt_sysroot$func_stripname_result ;;
esac
if test "$pre_test_object_deps_done" = no; then
case ${prev} in
-L | -R)
# Internal compiler library paths should come after those
# provided the user. The postdeps already come after the
# user supplied libs so there is no need to process them.
if test -z "$compiler_lib_search_path_CXX"; then
compiler_lib_search_path_CXX="${prev}${p}"
else
compiler_lib_search_path_CXX="${compiler_lib_search_path_CXX} ${prev}${p}"
fi
;;
# The "-l" case would never come before the object being
# linked, so don't bother handling this case.
esac
else
if test -z "$postdeps_CXX"; then
postdeps_CXX="${prev}${p}"
else
postdeps_CXX="${postdeps_CXX} ${prev}${p}"
fi
fi
prev=
;;
*.lto.$objext) ;; # Ignore GCC LTO objects
*.$objext)
# This assumes that the test object file only shows up
# once in the compiler output.
if test "$p" = "conftest.$objext"; then
pre_test_object_deps_done=yes
continue
fi
if test "$pre_test_object_deps_done" = no; then
if test -z "$predep_objects_CXX"; then
predep_objects_CXX="$p"
else
predep_objects_CXX="$predep_objects_CXX $p"
fi
else
if test -z "$postdep_objects_CXX"; then
postdep_objects_CXX="$p"
else
postdep_objects_CXX="$postdep_objects_CXX $p"
fi
fi
;;
*) ;; # Ignore the rest.
esac
done
# Clean up.
rm -f a.out a.exe
else
echo "libtool.m4: error: problem compiling CXX test program"
fi
$RM -f confest.$objext
CFLAGS=$_lt_libdeps_save_CFLAGS
# PORTME: override above test on systems where it is broken
case $host_os in
interix[3-9]*)
# Interix 3.5 installs completely hosed .la files for C++, so rather than
# hack all around it, let's just trust "g++" to DTRT.
predep_objects_CXX=
postdep_objects_CXX=
postdeps_CXX=
;;
linux*)
case `$CC -V 2>&1 | sed 5q` in
*Sun\ C*)
# Sun C++ 5.9
# The more standards-conforming stlport4 library is
# incompatible with the Cstd library. Avoid specifying
# it if it's in CXXFLAGS. Ignore libCrun as
# -library=stlport4 depends on it.
case " $CXX $CXXFLAGS " in
*" -library=stlport4 "*)
solaris_use_stlport4=yes
;;
esac
if test "$solaris_use_stlport4" != yes; then
postdeps_CXX='-library=Cstd -library=Crun'
fi
;;
esac
;;
solaris*)
case $cc_basename in
CC* | sunCC*)
# The more standards-conforming stlport4 library is
# incompatible with the Cstd library. Avoid specifying
# it if it's in CXXFLAGS. Ignore libCrun as
# -library=stlport4 depends on it.
case " $CXX $CXXFLAGS " in
*" -library=stlport4 "*)
solaris_use_stlport4=yes
;;
esac
# Adding this requires a known-good setup of shared libraries for
# Sun compiler versions before 5.6, else PIC objects from an old
# archive will be linked into the output, leading to subtle bugs.
if test "$solaris_use_stlport4" != yes; then
postdeps_CXX='-library=Cstd -library=Crun'
fi
;;
esac
;;
esac
case " $postdeps_CXX " in
*" -lc "*) archive_cmds_need_lc_CXX=no ;;
esac
compiler_lib_search_dirs_CXX=
if test -n "${compiler_lib_search_path_CXX}"; then
compiler_lib_search_dirs_CXX=`echo " ${compiler_lib_search_path_CXX}" | ${SED} -e 's! -L! !g' -e 's!^ !!'`
fi
lt_prog_compiler_wl_CXX=
lt_prog_compiler_pic_CXX=
lt_prog_compiler_static_CXX=
# C++ specific cases for pic, static, wl, etc.
if test "$GXX" = yes; then
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_static_CXX='-static'
case $host_os in
aix*)
# All AIX code is PIC.
if test "$host_cpu" = ia64; then
# AIX 5 now supports IA64 processor
lt_prog_compiler_static_CXX='-Bstatic'
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# see comment about AmigaOS4 .so support
lt_prog_compiler_pic_CXX='-fPIC'
;;
m68k)
# FIXME: we need at least 68020 code to build shared libraries, but
# adding the `-m68020' flag to GCC prevents building anything better,
# like `-m68040'.
lt_prog_compiler_pic_CXX='-m68020 -resident32 -malways-restore-a4'
;;
esac
;;
beos* | irix5* | irix6* | nonstopux* | osf3* | osf4* | osf5*)
# PIC is the default for these OSes.
;;
mingw* | cygwin* | os2* | pw32* | cegcc*)
# This hack is so that the source file can tell whether it is being
# built for inclusion in a dll (and should export symbols for example).
# Although the cygwin gcc ignores -fPIC, still need this for old-style
# (--disable-auto-import) libraries
lt_prog_compiler_pic_CXX='-DDLL_EXPORT'
;;
darwin* | rhapsody*)
# PIC is the default on this platform
# Common symbols not allowed in MH_DYLIB files
lt_prog_compiler_pic_CXX='-fno-common'
;;
*djgpp*)
# DJGPP does not support shared libraries at all
lt_prog_compiler_pic_CXX=
;;
haiku*)
# PIC is the default for Haiku.
# The "-static" flag exists, but is broken.
lt_prog_compiler_static_CXX=
;;
interix[3-9]*)
# Interix 3.x gcc -fpic/-fPIC options generate broken code.
# Instead, we relocate shared libraries at runtime.
;;
sysv4*MP*)
if test -d /usr/nec; then
lt_prog_compiler_pic_CXX=-Kconform_pic
fi
;;
hpux*)
# PIC is the default for 64-bit PA HP-UX, but not for 32-bit
# PA HP-UX. On IA64 HP-UX, PIC is the default but the pic flag
# sets the default TLS model and affects inlining.
case $host_cpu in
hppa*64*)
;;
*)
lt_prog_compiler_pic_CXX='-fPIC'
;;
esac
;;
*qnx* | *nto*)
# QNX uses GNU C++, but need to define -shared option too, otherwise
# it will coredump.
lt_prog_compiler_pic_CXX='-fPIC -shared'
;;
*)
lt_prog_compiler_pic_CXX='-fPIC'
;;
esac
else
case $host_os in
aix[4-9]*)
# All AIX code is PIC.
if test "$host_cpu" = ia64; then
# AIX 5 now supports IA64 processor
lt_prog_compiler_static_CXX='-Bstatic'
else
lt_prog_compiler_static_CXX='-bnso -bI:/lib/syscalls.exp'
fi
;;
chorus*)
case $cc_basename in
cxch68*)
# Green Hills C++ Compiler
# _LT_TAGVAR(lt_prog_compiler_static, CXX)="--no_auto_instantiation -u __main -u __premain -u _abort -r $COOL_DIR/lib/libOrb.a $MVME_DIR/lib/CC/libC.a $MVME_DIR/lib/classix/libcx.s.a"
;;
esac
;;
mingw* | cygwin* | os2* | pw32* | cegcc*)
# This hack is so that the source file can tell whether it is being
# built for inclusion in a dll (and should export symbols for example).
lt_prog_compiler_pic_CXX='-DDLL_EXPORT'
;;
dgux*)
case $cc_basename in
ec++*)
lt_prog_compiler_pic_CXX='-KPIC'
;;
ghcx*)
# Green Hills C++ Compiler
lt_prog_compiler_pic_CXX='-pic'
;;
*)
;;
esac
;;
freebsd* | dragonfly*)
# FreeBSD uses GNU C++
;;
hpux9* | hpux10* | hpux11*)
case $cc_basename in
CC*)
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_static_CXX='${wl}-a ${wl}archive'
if test "$host_cpu" != ia64; then
lt_prog_compiler_pic_CXX='+Z'
fi
;;
aCC*)
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_static_CXX='${wl}-a ${wl}archive'
case $host_cpu in
hppa*64*|ia64*)
# +Z the default
;;
*)
lt_prog_compiler_pic_CXX='+Z'
;;
esac
;;
*)
;;
esac
;;
interix*)
# This is c89, which is MS Visual C++ (no shared libs)
# Anyone wants to do a port?
;;
irix5* | irix6* | nonstopux*)
case $cc_basename in
CC*)
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_static_CXX='-non_shared'
# CC pic flag -KPIC is the default.
;;
*)
;;
esac
;;
linux* | k*bsd*-gnu | kopensolaris*-gnu)
case $cc_basename in
KCC*)
# KAI C++ Compiler
lt_prog_compiler_wl_CXX='--backend -Wl,'
lt_prog_compiler_pic_CXX='-fPIC'
;;
ecpc* )
# old Intel C++ for x86_64 which still supported -KPIC.
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_pic_CXX='-KPIC'
lt_prog_compiler_static_CXX='-static'
;;
icpc* )
# Intel C++, used to be incompatible with GCC.
# ICC 10 doesn't accept -KPIC any more.
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_pic_CXX='-fPIC'
lt_prog_compiler_static_CXX='-static'
;;
pgCC* | pgcpp*)
# Portland Group C++ compiler
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_pic_CXX='-fpic'
lt_prog_compiler_static_CXX='-Bstatic'
;;
cxx*)
# Compaq C++
# Make sure the PIC flag is empty. It appears that all Alpha
# Linux and Compaq Tru64 Unix objects are PIC.
lt_prog_compiler_pic_CXX=
lt_prog_compiler_static_CXX='-non_shared'
;;
xlc* | xlC* | bgxl[cC]* | mpixl[cC]*)
# IBM XL 8.0, 9.0 on PPC and BlueGene
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_pic_CXX='-qpic'
lt_prog_compiler_static_CXX='-qstaticlink'
;;
*)
case `$CC -V 2>&1 | sed 5q` in
*Sun\ C*)
# Sun C++ 5.9
lt_prog_compiler_pic_CXX='-KPIC'
lt_prog_compiler_static_CXX='-Bstatic'
lt_prog_compiler_wl_CXX='-Qoption ld '
;;
esac
;;
esac
;;
lynxos*)
;;
m88k*)
;;
mvs*)
case $cc_basename in
cxx*)
lt_prog_compiler_pic_CXX='-W c,exportall'
;;
*)
;;
esac
;;
netbsd*)
;;
*qnx* | *nto*)
# QNX uses GNU C++, but need to define -shared option too, otherwise
# it will coredump.
lt_prog_compiler_pic_CXX='-fPIC -shared'
;;
osf3* | osf4* | osf5*)
case $cc_basename in
KCC*)
lt_prog_compiler_wl_CXX='--backend -Wl,'
;;
RCC*)
# Rational C++ 2.4.1
lt_prog_compiler_pic_CXX='-pic'
;;
cxx*)
# Digital/Compaq C++
lt_prog_compiler_wl_CXX='-Wl,'
# Make sure the PIC flag is empty. It appears that all Alpha
# Linux and Compaq Tru64 Unix objects are PIC.
lt_prog_compiler_pic_CXX=
lt_prog_compiler_static_CXX='-non_shared'
;;
*)
;;
esac
;;
psos*)
;;
solaris*)
case $cc_basename in
CC* | sunCC*)
# Sun C++ 4.2, 5.x and Centerline C++
lt_prog_compiler_pic_CXX='-KPIC'
lt_prog_compiler_static_CXX='-Bstatic'
lt_prog_compiler_wl_CXX='-Qoption ld '
;;
gcx*)
# Green Hills C++ Compiler
lt_prog_compiler_pic_CXX='-PIC'
;;
*)
;;
esac
;;
sunos4*)
case $cc_basename in
CC*)
# Sun C++ 4.x
lt_prog_compiler_pic_CXX='-pic'
lt_prog_compiler_static_CXX='-Bstatic'
;;
lcc*)
# Lucid
lt_prog_compiler_pic_CXX='-pic'
;;
*)
;;
esac
;;
sysv5* | unixware* | sco3.2v5* | sco5v6* | OpenUNIX*)
case $cc_basename in
CC*)
lt_prog_compiler_wl_CXX='-Wl,'
lt_prog_compiler_pic_CXX='-KPIC'
lt_prog_compiler_static_CXX='-Bstatic'
;;
esac
;;
tandem*)
case $cc_basename in
NCC*)
# NonStop-UX NCC 3.20
lt_prog_compiler_pic_CXX='-KPIC'
;;
*)
;;
esac
;;
vxworks*)
;;
*)
lt_prog_compiler_can_build_shared_CXX=no
;;
esac
fi
case $host_os in
# For platforms which do not support PIC, -DPIC is meaningless:
*djgpp*)
lt_prog_compiler_pic_CXX=
;;
*)
lt_prog_compiler_pic_CXX="$lt_prog_compiler_pic_CXX -DPIC"
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for $compiler option to produce PIC" >&5
$as_echo_n "checking for $compiler option to produce PIC... " >&6; }
if ${lt_cv_prog_compiler_pic_CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_pic_CXX=$lt_prog_compiler_pic_CXX
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_pic_CXX" >&5
$as_echo "$lt_cv_prog_compiler_pic_CXX" >&6; }
lt_prog_compiler_pic_CXX=$lt_cv_prog_compiler_pic_CXX
#
# Check to make sure the PIC flag actually works.
#
if test -n "$lt_prog_compiler_pic_CXX"; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler PIC flag $lt_prog_compiler_pic_CXX works" >&5
$as_echo_n "checking if $compiler PIC flag $lt_prog_compiler_pic_CXX works... " >&6; }
if ${lt_cv_prog_compiler_pic_works_CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_pic_works_CXX=no
ac_outfile=conftest.$ac_objext
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="$lt_prog_compiler_pic_CXX -DPIC"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
# The option is referenced via a variable to avoid confusing sed.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [^ ]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&5)
(eval "$lt_compile" 2>conftest.err)
ac_status=$?
cat conftest.err >&5
echo "$as_me:$LINENO: \$? = $ac_status" >&5
if (exit $ac_status) && test -s "$ac_outfile"; then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings other than the usual output.
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' >conftest.exp
$SED '/^$/d; /^ *+/d' conftest.err >conftest.er2
if test ! -s conftest.er2 || diff conftest.exp conftest.er2 >/dev/null; then
lt_cv_prog_compiler_pic_works_CXX=yes
fi
fi
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_pic_works_CXX" >&5
$as_echo "$lt_cv_prog_compiler_pic_works_CXX" >&6; }
if test x"$lt_cv_prog_compiler_pic_works_CXX" = xyes; then
case $lt_prog_compiler_pic_CXX in
"" | " "*) ;;
*) lt_prog_compiler_pic_CXX=" $lt_prog_compiler_pic_CXX" ;;
esac
else
lt_prog_compiler_pic_CXX=
lt_prog_compiler_can_build_shared_CXX=no
fi
fi
#
# Check to make sure the static flag actually works.
#
wl=$lt_prog_compiler_wl_CXX eval lt_tmp_static_flag=\"$lt_prog_compiler_static_CXX\"
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler static flag $lt_tmp_static_flag works" >&5
$as_echo_n "checking if $compiler static flag $lt_tmp_static_flag works... " >&6; }
if ${lt_cv_prog_compiler_static_works_CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_static_works_CXX=no
save_LDFLAGS="$LDFLAGS"
LDFLAGS="$LDFLAGS $lt_tmp_static_flag"
echo "$lt_simple_link_test_code" > conftest.$ac_ext
if (eval $ac_link 2>conftest.err) && test -s conftest$ac_exeext; then
# The linker can only warn and ignore the option if not recognized
# So say no if there are warnings
if test -s conftest.err; then
# Append any errors to the config.log.
cat conftest.err 1>&5
$ECHO "$_lt_linker_boilerplate" | $SED '/^$/d' > conftest.exp
$SED '/^$/d; /^ *+/d' conftest.err >conftest.er2
if diff conftest.exp conftest.er2 >/dev/null; then
lt_cv_prog_compiler_static_works_CXX=yes
fi
else
lt_cv_prog_compiler_static_works_CXX=yes
fi
fi
$RM -r conftest*
LDFLAGS="$save_LDFLAGS"
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_static_works_CXX" >&5
$as_echo "$lt_cv_prog_compiler_static_works_CXX" >&6; }
if test x"$lt_cv_prog_compiler_static_works_CXX" = xyes; then
:
else
lt_prog_compiler_static_CXX=
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler supports -c -o file.$ac_objext" >&5
$as_echo_n "checking if $compiler supports -c -o file.$ac_objext... " >&6; }
if ${lt_cv_prog_compiler_c_o_CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_c_o_CXX=no
$RM -r conftest 2>/dev/null
mkdir conftest
cd conftest
mkdir out
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="-o out/conftest2.$ac_objext"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [^ ]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&5)
(eval "$lt_compile" 2>out/conftest.err)
ac_status=$?
cat out/conftest.err >&5
echo "$as_me:$LINENO: \$? = $ac_status" >&5
if (exit $ac_status) && test -s out/conftest2.$ac_objext
then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' > out/conftest.exp
$SED '/^$/d; /^ *+/d' out/conftest.err >out/conftest.er2
if test ! -s out/conftest.er2 || diff out/conftest.exp out/conftest.er2 >/dev/null; then
lt_cv_prog_compiler_c_o_CXX=yes
fi
fi
chmod u+w . 2>&5
$RM conftest*
# SGI C++ compiler will create directory out/ii_files/ for
# template instantiation
test -d out/ii_files && $RM out/ii_files/* && rmdir out/ii_files
$RM out/* && rmdir out
cd ..
$RM -r conftest
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_c_o_CXX" >&5
$as_echo "$lt_cv_prog_compiler_c_o_CXX" >&6; }
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if $compiler supports -c -o file.$ac_objext" >&5
$as_echo_n "checking if $compiler supports -c -o file.$ac_objext... " >&6; }
if ${lt_cv_prog_compiler_c_o_CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_prog_compiler_c_o_CXX=no
$RM -r conftest 2>/dev/null
mkdir conftest
cd conftest
mkdir out
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
lt_compiler_flag="-o out/conftest2.$ac_objext"
# Insert the option either (1) after the last *FLAGS variable, or
# (2) before a word containing "conftest.", or (3) at the end.
# Note that $ac_compile itself does not contain backslashes and begins
# with a dollar sign (not a hyphen), so the echo should work correctly.
lt_compile=`echo "$ac_compile" | $SED \
-e 's:.*FLAGS}\{0,1\} :&$lt_compiler_flag :; t' \
-e 's: [^ ]*conftest\.: $lt_compiler_flag&:; t' \
-e 's:$: $lt_compiler_flag:'`
(eval echo "\"\$as_me:$LINENO: $lt_compile\"" >&5)
(eval "$lt_compile" 2>out/conftest.err)
ac_status=$?
cat out/conftest.err >&5
echo "$as_me:$LINENO: \$? = $ac_status" >&5
if (exit $ac_status) && test -s out/conftest2.$ac_objext
then
# The compiler can only warn and ignore the option if not recognized
# So say no if there are warnings
$ECHO "$_lt_compiler_boilerplate" | $SED '/^$/d' > out/conftest.exp
$SED '/^$/d; /^ *+/d' out/conftest.err >out/conftest.er2
if test ! -s out/conftest.er2 || diff out/conftest.exp out/conftest.er2 >/dev/null; then
lt_cv_prog_compiler_c_o_CXX=yes
fi
fi
chmod u+w . 2>&5
$RM conftest*
# SGI C++ compiler will create directory out/ii_files/ for
# template instantiation
test -d out/ii_files && $RM out/ii_files/* && rmdir out/ii_files
$RM out/* && rmdir out
cd ..
$RM -r conftest
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_prog_compiler_c_o_CXX" >&5
$as_echo "$lt_cv_prog_compiler_c_o_CXX" >&6; }
hard_links="nottested"
if test "$lt_cv_prog_compiler_c_o_CXX" = no && test "$need_locks" != no; then
# do not overwrite the value of need_locks provided by the user
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking if we can lock with hard links" >&5
$as_echo_n "checking if we can lock with hard links... " >&6; }
hard_links=yes
$RM conftest*
ln conftest.a conftest.b 2>/dev/null && hard_links=no
touch conftest.a
ln conftest.a conftest.b 2>&5 || hard_links=no
ln conftest.a conftest.b 2>/dev/null && hard_links=no
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $hard_links" >&5
$as_echo "$hard_links" >&6; }
if test "$hard_links" = no; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: WARNING: \`$CC' does not support \`-c -o', so \`make -j' may be unsafe" >&5
$as_echo "$as_me: WARNING: \`$CC' does not support \`-c -o', so \`make -j' may be unsafe" >&2;}
need_locks=warn
fi
else
need_locks=no
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether the $compiler linker ($LD) supports shared libraries" >&5
$as_echo_n "checking whether the $compiler linker ($LD) supports shared libraries... " >&6; }
export_symbols_cmds_CXX='$NM $libobjs $convenience | $global_symbol_pipe | $SED '\''s/.* //'\'' | sort | uniq > $export_symbols'
exclude_expsyms_CXX='_GLOBAL_OFFSET_TABLE_|_GLOBAL__F[ID]_.*'
case $host_os in
aix[4-9]*)
# If we're using GNU nm, then we don't want the "-C" option.
# -C means demangle to AIX nm, but means don't demangle with GNU nm
# Also, AIX nm treats weak defined symbols like other global defined
# symbols, whereas GNU nm marks them as "W".
if $NM -V 2>&1 | $GREP 'GNU' > /dev/null; then
export_symbols_cmds_CXX='$NM -Bpg $libobjs $convenience | awk '\''{ if (((\$ 2 == "T") || (\$ 2 == "D") || (\$ 2 == "B") || (\$ 2 == "W")) && (substr(\$ 3,1,1) != ".")) { print \$ 3 } }'\'' | sort -u > $export_symbols'
else
export_symbols_cmds_CXX='$NM -BCpg $libobjs $convenience | awk '\''{ if (((\$ 2 == "T") || (\$ 2 == "D") || (\$ 2 == "B")) && (substr(\$ 3,1,1) != ".")) { print \$ 3 } }'\'' | sort -u > $export_symbols'
fi
;;
pw32*)
export_symbols_cmds_CXX="$ltdll_cmds"
;;
cygwin* | mingw* | cegcc*)
case $cc_basename in
cl*)
exclude_expsyms_CXX='_NULL_IMPORT_DESCRIPTOR|_IMPORT_DESCRIPTOR_.*'
;;
*)
export_symbols_cmds_CXX='$NM $libobjs $convenience | $global_symbol_pipe | $SED -e '\''/^[BCDGRS][ ]/s/.*[ ]\([^ ]*\)/\1 DATA/;s/^.*[ ]__nm__\([^ ]*\)[ ][^ ]*/\1 DATA/;/^I[ ]/d;/^[AITW][ ]/s/.* //'\'' | sort | uniq > $export_symbols'
exclude_expsyms_CXX='[_]+GLOBAL_OFFSET_TABLE_|[_]+GLOBAL__[FID]_.*|[_]+head_[A-Za-z0-9_]+_dll|[A-Za-z0-9_]+_dll_iname'
;;
esac
;;
*)
export_symbols_cmds_CXX='$NM $libobjs $convenience | $global_symbol_pipe | $SED '\''s/.* //'\'' | sort | uniq > $export_symbols'
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $ld_shlibs_CXX" >&5
$as_echo "$ld_shlibs_CXX" >&6; }
test "$ld_shlibs_CXX" = no && can_build_shared=no
with_gnu_ld_CXX=$with_gnu_ld
#
# Do we need to explicitly link libc?
#
case "x$archive_cmds_need_lc_CXX" in
x|xyes)
# Assume -lc should be added
archive_cmds_need_lc_CXX=yes
if test "$enable_shared" = yes && test "$GCC" = yes; then
case $archive_cmds_CXX in
*'~'*)
# FIXME: we may have to deal with multi-command sequences.
;;
'$CC '*)
# Test whether the compiler implicitly links with -lc since on some
# systems, -lgcc has to come before -lc. If gcc already passes -lc
# to ld, don't add -lc before -lgcc.
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking whether -lc should be explicitly linked in" >&5
$as_echo_n "checking whether -lc should be explicitly linked in... " >&6; }
if ${lt_cv_archive_cmds_need_lc_CXX+:} false; then :
$as_echo_n "(cached) " >&6
else
$RM conftest*
echo "$lt_simple_compile_test_code" > conftest.$ac_ext
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$ac_compile\""; } >&5
(eval $ac_compile) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; } 2>conftest.err; then
soname=conftest
lib=conftest
libobjs=conftest.$ac_objext
deplibs=
wl=$lt_prog_compiler_wl_CXX
pic_flag=$lt_prog_compiler_pic_CXX
compiler_flags=-v
linker_flags=-v
verstring=
output_objdir=.
libname=conftest
lt_save_allow_undefined_flag=$allow_undefined_flag_CXX
allow_undefined_flag_CXX=
if { { eval echo "\"\$as_me\":${as_lineno-$LINENO}: \"$archive_cmds_CXX 2\>\&1 \| $GREP \" -lc \" \>/dev/null 2\>\&1\""; } >&5
(eval $archive_cmds_CXX 2\>\&1 \| $GREP \" -lc \" \>/dev/null 2\>\&1) 2>&5
ac_status=$?
$as_echo "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5
test $ac_status = 0; }
then
lt_cv_archive_cmds_need_lc_CXX=no
else
lt_cv_archive_cmds_need_lc_CXX=yes
fi
allow_undefined_flag_CXX=$lt_save_allow_undefined_flag
else
cat conftest.err 1>&5
fi
$RM conftest*
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $lt_cv_archive_cmds_need_lc_CXX" >&5
$as_echo "$lt_cv_archive_cmds_need_lc_CXX" >&6; }
archive_cmds_need_lc_CXX=$lt_cv_archive_cmds_need_lc_CXX
;;
esac
fi
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking dynamic linker characteristics" >&5
$as_echo_n "checking dynamic linker characteristics... " >&6; }
library_names_spec=
libname_spec='lib$name'
soname_spec=
shrext_cmds=".so"
postinstall_cmds=
postuninstall_cmds=
finish_cmds=
finish_eval=
shlibpath_var=
shlibpath_overrides_runpath=unknown
version_type=none
dynamic_linker="$host_os ld.so"
sys_lib_dlsearch_path_spec="/lib /usr/lib"
need_lib_prefix=unknown
hardcode_into_libs=no
# when you set need_version to no, make sure it does not cause -set_version
# flags to be left without arguments
need_version=unknown
case $host_os in
aix3*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix $libname.a'
shlibpath_var=LIBPATH
# AIX 3 has no versioning support, so we append a major version to the name.
soname_spec='${libname}${release}${shared_ext}$major'
;;
aix[4-9]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
hardcode_into_libs=yes
if test "$host_cpu" = ia64; then
# AIX 5 supports IA64
library_names_spec='${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext}$versuffix $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
else
# With GCC up to 2.95.x, collect2 would create an import file
# for dependence libraries. The import file would start with
# the line `#! .'. This would cause the generated library to
# depend on `.', always an invalid library. This was fixed in
# development snapshots of GCC prior to 3.0.
case $host_os in
aix4 | aix4.[01] | aix4.[01].*)
if { echo '#if __GNUC__ > 2 || (__GNUC__ == 2 && __GNUC_MINOR__ >= 97)'
echo ' yes '
echo '#endif'; } | ${CC} -E - | $GREP yes > /dev/null; then
:
else
can_build_shared=no
fi
;;
esac
# AIX (on Power*) has no versioning support, so currently we can not hardcode correct
# soname into executable. Probably we can add versioning support to
# collect2, so additional links can be useful in future.
if test "$aix_use_runtimelinking" = yes; then
# If using run time linking (on AIX 4.2 or later) use lib.so
# instead of lib.a to let people know that these are not
# typical AIX shared libraries.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
else
# We preserve .a as extension for shared libraries through AIX4.2
# and later when we are not doing run time linking.
library_names_spec='${libname}${release}.a $libname.a'
soname_spec='${libname}${release}${shared_ext}$major'
fi
shlibpath_var=LIBPATH
fi
;;
amigaos*)
case $host_cpu in
powerpc)
# Since July 2007 AmigaOS4 officially supports .so libraries.
# When compiling the executable, add -use-dynld -Lsobjs: to the compileline.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
;;
m68k)
library_names_spec='$libname.ixlibrary $libname.a'
# Create ${libname}_ixlibrary.a entries in /sys/libs.
finish_eval='for lib in `ls $libdir/*.ixlibrary 2>/dev/null`; do libname=`func_echo_all "$lib" | $SED '\''s%^.*/\([^/]*\)\.ixlibrary$%\1%'\''`; test $RM /sys/libs/${libname}_ixlibrary.a; $show "cd /sys/libs && $LN_S $lib ${libname}_ixlibrary.a"; cd /sys/libs && $LN_S $lib ${libname}_ixlibrary.a || exit 1; done'
;;
esac
;;
beos*)
library_names_spec='${libname}${shared_ext}'
dynamic_linker="$host_os ld.so"
shlibpath_var=LIBRARY_PATH
;;
bsdi[45]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
finish_cmds='PATH="\$PATH:/sbin" ldconfig $libdir'
shlibpath_var=LD_LIBRARY_PATH
sys_lib_search_path_spec="/shlib /usr/lib /usr/X11/lib /usr/contrib/lib /lib /usr/local/lib"
sys_lib_dlsearch_path_spec="/shlib /usr/lib /usr/local/lib"
# the default ld.so.conf also contains /usr/contrib/lib and
# /usr/X11R6/lib (/usr/X11 is a link to /usr/X11R6), but let us allow
# libtool to hard-code these into programs
;;
cygwin* | mingw* | pw32* | cegcc*)
version_type=windows
shrext_cmds=".dll"
need_version=no
need_lib_prefix=no
case $GCC,$cc_basename in
yes,*)
# gcc
library_names_spec='$libname.dll.a'
# DLL is installed to $(libdir)/../bin by postinstall_cmds
postinstall_cmds='base_file=`basename \${file}`~
dlpath=`$SHELL 2>&1 -c '\''. $dir/'\''\${base_file}'\''i; echo \$dlname'\''`~
dldir=$destdir/`dirname \$dlpath`~
test -d \$dldir || mkdir -p \$dldir~
$install_prog $dir/$dlname \$dldir/$dlname~
chmod a+x \$dldir/$dlname~
if test -n '\''$stripme'\'' && test -n '\''$striplib'\''; then
eval '\''$striplib \$dldir/$dlname'\'' || exit \$?;
fi'
postuninstall_cmds='dldll=`$SHELL 2>&1 -c '\''. $file; echo \$dlname'\''`~
dlpath=$dir/\$dldll~
$RM \$dlpath'
shlibpath_overrides_runpath=yes
case $host_os in
cygwin*)
# Cygwin DLLs use 'cyg' prefix rather than 'lib'
soname_spec='`echo ${libname} | sed -e 's/^lib/cyg/'``echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}'
;;
mingw* | cegcc*)
# MinGW DLLs use traditional 'lib' prefix
soname_spec='${libname}`echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}'
;;
pw32*)
# pw32 DLLs use 'pw' prefix rather than 'lib'
library_names_spec='`echo ${libname} | sed -e 's/^lib/pw/'``echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}'
;;
esac
dynamic_linker='Win32 ld.exe'
;;
*,cl*)
# Native MSVC
libname_spec='$name'
soname_spec='${libname}`echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext}'
library_names_spec='${libname}.dll.lib'
case $build_os in
mingw*)
sys_lib_search_path_spec=
lt_save_ifs=$IFS
IFS=';'
for lt_path in $LIB
do
IFS=$lt_save_ifs
# Let DOS variable expansion print the short 8.3 style file name.
lt_path=`cd "$lt_path" 2>/dev/null && cmd //C "for %i in (".") do @echo %~si"`
sys_lib_search_path_spec="$sys_lib_search_path_spec $lt_path"
done
IFS=$lt_save_ifs
# Convert to MSYS style.
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | sed -e 's|\\\\|/|g' -e 's| \\([a-zA-Z]\\):| /\\1|g' -e 's|^ ||'`
;;
cygwin*)
# Convert to unix form, then to dos form, then back to unix form
# but this time dos style (no spaces!) so that the unix form looks
# like /cygdrive/c/PROGRA~1:/cygdr...
sys_lib_search_path_spec=`cygpath --path --unix "$LIB"`
sys_lib_search_path_spec=`cygpath --path --dos "$sys_lib_search_path_spec" 2>/dev/null`
sys_lib_search_path_spec=`cygpath --path --unix "$sys_lib_search_path_spec" | $SED -e "s/$PATH_SEPARATOR/ /g"`
;;
*)
sys_lib_search_path_spec="$LIB"
if $ECHO "$sys_lib_search_path_spec" | $GREP ';[c-zC-Z]:/' >/dev/null; then
# It is most probably a Windows format PATH.
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | $SED -e 's/;/ /g'`
else
sys_lib_search_path_spec=`$ECHO "$sys_lib_search_path_spec" | $SED -e "s/$PATH_SEPARATOR/ /g"`
fi
# FIXME: find the short name or the path components, as spaces are
# common. (e.g. "Program Files" -> "PROGRA~1")
;;
esac
# DLL is installed to $(libdir)/../bin by postinstall_cmds
postinstall_cmds='base_file=`basename \${file}`~
dlpath=`$SHELL 2>&1 -c '\''. $dir/'\''\${base_file}'\''i; echo \$dlname'\''`~
dldir=$destdir/`dirname \$dlpath`~
test -d \$dldir || mkdir -p \$dldir~
$install_prog $dir/$dlname \$dldir/$dlname'
postuninstall_cmds='dldll=`$SHELL 2>&1 -c '\''. $file; echo \$dlname'\''`~
dlpath=$dir/\$dldll~
$RM \$dlpath'
shlibpath_overrides_runpath=yes
dynamic_linker='Win32 link.exe'
;;
*)
# Assume MSVC wrapper
library_names_spec='${libname}`echo ${release} | $SED -e 's/[.]/-/g'`${versuffix}${shared_ext} $libname.lib'
dynamic_linker='Win32 ld.exe'
;;
esac
# FIXME: first we should search . and the directory the executable is in
shlibpath_var=PATH
;;
darwin* | rhapsody*)
dynamic_linker="$host_os dyld"
version_type=darwin
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${major}$shared_ext ${libname}$shared_ext'
soname_spec='${libname}${release}${major}$shared_ext'
shlibpath_overrides_runpath=yes
shlibpath_var=DYLD_LIBRARY_PATH
shrext_cmds='`test .$module = .yes && echo .so || echo .dylib`'
sys_lib_dlsearch_path_spec='/usr/local/lib /lib /usr/lib'
;;
dgux*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname$shared_ext'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
;;
freebsd* | dragonfly*)
# DragonFly does not have aout. When/if they implement a new
# versioning mechanism, adjust this.
if test -x /usr/bin/objformat; then
objformat=`/usr/bin/objformat`
else
case $host_os in
freebsd[23].*) objformat=aout ;;
*) objformat=elf ;;
esac
fi
version_type=freebsd-$objformat
case $version_type in
freebsd-elf*)
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext} $libname${shared_ext}'
need_version=no
need_lib_prefix=no
;;
freebsd-*)
library_names_spec='${libname}${release}${shared_ext}$versuffix $libname${shared_ext}$versuffix'
need_version=yes
;;
esac
shlibpath_var=LD_LIBRARY_PATH
case $host_os in
freebsd2.*)
shlibpath_overrides_runpath=yes
;;
freebsd3.[01]* | freebsdelf3.[01]*)
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
freebsd3.[2-9]* | freebsdelf3.[2-9]* | \
freebsd4.[0-5] | freebsdelf4.[0-5] | freebsd4.1.1 | freebsdelf4.1.1)
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
*) # from 4.6 on, and DragonFly
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
esac
;;
gnu*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
haiku*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
dynamic_linker="$host_os runtime_loader"
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}${major} ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LIBRARY_PATH
shlibpath_overrides_runpath=yes
sys_lib_dlsearch_path_spec='/boot/home/config/lib /boot/common/lib /boot/system/lib'
hardcode_into_libs=yes
;;
hpux9* | hpux10* | hpux11*)
# Give a soname corresponding to the major version so that dld.sl refuses to
# link against other versions.
version_type=sunos
need_lib_prefix=no
need_version=no
case $host_cpu in
ia64*)
shrext_cmds='.so'
hardcode_into_libs=yes
dynamic_linker="$host_os dld.so"
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes # Unless +noenvvar is specified.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
if test "X$HPUX_IA64_MODE" = X32; then
sys_lib_search_path_spec="/usr/lib/hpux32 /usr/local/lib/hpux32 /usr/local/lib"
else
sys_lib_search_path_spec="/usr/lib/hpux64 /usr/local/lib/hpux64"
fi
sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec
;;
hppa*64*)
shrext_cmds='.sl'
hardcode_into_libs=yes
dynamic_linker="$host_os dld.sl"
shlibpath_var=LD_LIBRARY_PATH # How should we handle SHLIB_PATH
shlibpath_overrides_runpath=yes # Unless +noenvvar is specified.
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
sys_lib_search_path_spec="/usr/lib/pa20_64 /usr/ccs/lib/pa20_64"
sys_lib_dlsearch_path_spec=$sys_lib_search_path_spec
;;
*)
shrext_cmds='.sl'
dynamic_linker="$host_os dld.sl"
shlibpath_var=SHLIB_PATH
shlibpath_overrides_runpath=no # +s is required to enable SHLIB_PATH
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
;;
esac
# HP-UX runs *really* slowly unless shared libraries are mode 555, ...
postinstall_cmds='chmod 555 $lib'
# or fails outright, so override atomically:
install_override_mode=555
;;
interix[3-9]*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
dynamic_linker='Interix 3.x ld.so.1 (PE, like ELF)'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
irix5* | irix6* | nonstopux*)
case $host_os in
nonstopux*) version_type=nonstopux ;;
*)
if test "$lt_cv_prog_gnu_ld" = yes; then
version_type=linux # correct to gnu/linux during the next big refactor
else
version_type=irix
fi ;;
esac
need_lib_prefix=no
need_version=no
soname_spec='${libname}${release}${shared_ext}$major'
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${release}${shared_ext} $libname${shared_ext}'
case $host_os in
irix5* | nonstopux*)
libsuff= shlibsuff=
;;
*)
case $LD in # libtool.m4 will add one of these switches to LD
*-32|*"-32 "|*-melf32bsmip|*"-melf32bsmip ")
libsuff= shlibsuff= libmagic=32-bit;;
*-n32|*"-n32 "|*-melf32bmipn32|*"-melf32bmipn32 ")
libsuff=32 shlibsuff=N32 libmagic=N32;;
*-64|*"-64 "|*-melf64bmip|*"-melf64bmip ")
libsuff=64 shlibsuff=64 libmagic=64-bit;;
*) libsuff= shlibsuff= libmagic=never-match;;
esac
;;
esac
shlibpath_var=LD_LIBRARY${shlibsuff}_PATH
shlibpath_overrides_runpath=no
sys_lib_search_path_spec="/usr/lib${libsuff} /lib${libsuff} /usr/local/lib${libsuff}"
sys_lib_dlsearch_path_spec="/usr/lib${libsuff} /lib${libsuff}"
hardcode_into_libs=yes
;;
# No shared lib support for Linux oldld, aout, or coff.
linux*oldld* | linux*aout* | linux*coff*)
dynamic_linker=no
;;
# This must be glibc/ELF.
linux* | k*bsd*-gnu | kopensolaris*-gnu)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -n $libdir'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
# Some binutils ld are patched to set DT_RUNPATH
if ${lt_cv_shlibpath_overrides_runpath+:} false; then :
$as_echo_n "(cached) " >&6
else
lt_cv_shlibpath_overrides_runpath=no
save_LDFLAGS=$LDFLAGS
save_libdir=$libdir
eval "libdir=/foo; wl=\"$lt_prog_compiler_wl_CXX\"; \
LDFLAGS=\"\$LDFLAGS $hardcode_libdir_flag_spec_CXX\""
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
int
main ()
{
;
return 0;
}
_ACEOF
if ac_fn_cxx_try_link "$LINENO"; then :
if ($OBJDUMP -p conftest$ac_exeext) 2>/dev/null | grep "RUNPATH.*$libdir" >/dev/null; then :
lt_cv_shlibpath_overrides_runpath=yes
fi
fi
rm -f core conftest.err conftest.$ac_objext \
conftest$ac_exeext conftest.$ac_ext
LDFLAGS=$save_LDFLAGS
libdir=$save_libdir
fi
shlibpath_overrides_runpath=$lt_cv_shlibpath_overrides_runpath
# This implies no fast_install, which is unacceptable.
# Some rework will be needed to allow for fast_install
# before this can be enabled.
hardcode_into_libs=yes
# Add ABI-specific directories to the system library path.
sys_lib_dlsearch_path_spec="/lib64 /usr/lib64 /lib /usr/lib"
# Append ld.so.conf contents to the search path
if test -f /etc/ld.so.conf; then
lt_ld_extra=`awk '/^include / { system(sprintf("cd /etc; cat %s 2>/dev/null", \$2)); skip = 1; } { if (!skip) print \$0; skip = 0; }' < /etc/ld.so.conf | $SED -e 's/#.*//;/^[ ]*hwcap[ ]/d;s/[:, ]/ /g;s/=[^=]*$//;s/=[^= ]* / /g;s/"//g;/^$/d' | tr '\n' ' '`
sys_lib_dlsearch_path_spec="$sys_lib_dlsearch_path_spec $lt_ld_extra"
fi
# We used to test for /lib/ld.so.1 and disable shared libraries on
# powerpc, because MkLinux only supported shared libraries with the
# GNU dynamic linker. Since this was broken with cross compilers,
# most powerpc-linux boxes support dynamic linking these days and
# people can always --disable-shared, the test was removed, and we
# assume the GNU/Linux dynamic linker is in use.
dynamic_linker='GNU/Linux ld.so'
;;
netbsd*)
version_type=sunos
need_lib_prefix=no
need_version=no
if echo __ELF__ | $CC -E - | $GREP __ELF__ >/dev/null; then
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -m $libdir'
dynamic_linker='NetBSD (a.out) ld.so'
else
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major ${libname}${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
dynamic_linker='NetBSD ld.elf_so'
fi
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
;;
newsos6)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
;;
*nto* | *qnx*)
version_type=qnx
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
dynamic_linker='ldqnx.so'
;;
openbsd*)
version_type=sunos
sys_lib_dlsearch_path_spec="/usr/lib"
need_lib_prefix=no
# Some older versions of OpenBSD (3.3 at least) *do* need versioned libs.
case $host_os in
openbsd3.3 | openbsd3.3.*) need_version=yes ;;
*) need_version=no ;;
esac
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/sbin" ldconfig -m $libdir'
shlibpath_var=LD_LIBRARY_PATH
if test -z "`echo __ELF__ | $CC -E - | $GREP __ELF__`" || test "$host_os-$host_cpu" = "openbsd2.8-powerpc"; then
case $host_os in
openbsd2.[89] | openbsd2.[89].*)
shlibpath_overrides_runpath=no
;;
*)
shlibpath_overrides_runpath=yes
;;
esac
else
shlibpath_overrides_runpath=yes
fi
;;
os2*)
libname_spec='$name'
shrext_cmds=".dll"
need_lib_prefix=no
library_names_spec='$libname${shared_ext} $libname.a'
dynamic_linker='OS/2 ld.exe'
shlibpath_var=LIBPATH
;;
osf3* | osf4* | osf5*)
version_type=osf
need_lib_prefix=no
need_version=no
soname_spec='${libname}${release}${shared_ext}$major'
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
sys_lib_search_path_spec="/usr/shlib /usr/ccs/lib /usr/lib/cmplrs/cc /usr/lib /usr/local/lib /var/shlib"
sys_lib_dlsearch_path_spec="$sys_lib_search_path_spec"
;;
rdos*)
dynamic_linker=no
;;
solaris*)
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
# ldd complains unless libraries are executable
postinstall_cmds='chmod +x $lib'
;;
sunos4*)
version_type=sunos
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${shared_ext}$versuffix'
finish_cmds='PATH="\$PATH:/usr/etc" ldconfig $libdir'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
if test "$with_gnu_ld" = yes; then
need_lib_prefix=no
fi
need_version=yes
;;
sysv4 | sysv4.3*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
case $host_vendor in
sni)
shlibpath_overrides_runpath=no
need_lib_prefix=no
runpath_var=LD_RUN_PATH
;;
siemens)
need_lib_prefix=no
;;
motorola)
need_lib_prefix=no
need_version=no
shlibpath_overrides_runpath=no
sys_lib_search_path_spec='/lib /usr/lib /usr/ccs/lib'
;;
esac
;;
sysv4*MP*)
if test -d /usr/nec ;then
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='$libname${shared_ext}.$versuffix $libname${shared_ext}.$major $libname${shared_ext}'
soname_spec='$libname${shared_ext}.$major'
shlibpath_var=LD_LIBRARY_PATH
fi
;;
sysv5* | sco3.2v5* | sco5v6* | unixware* | OpenUNIX* | sysv4*uw2*)
version_type=freebsd-elf
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext} $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=yes
hardcode_into_libs=yes
if test "$with_gnu_ld" = yes; then
sys_lib_search_path_spec='/usr/local/lib /usr/gnu/lib /usr/ccs/lib /usr/lib /lib'
else
sys_lib_search_path_spec='/usr/ccs/lib /usr/lib'
case $host_os in
sco3.2v5*)
sys_lib_search_path_spec="$sys_lib_search_path_spec /lib"
;;
esac
fi
sys_lib_dlsearch_path_spec='/usr/lib'
;;
tpf*)
# TPF is a cross-target only. Preferred cross-host = GNU/Linux.
version_type=linux # correct to gnu/linux during the next big refactor
need_lib_prefix=no
need_version=no
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
shlibpath_var=LD_LIBRARY_PATH
shlibpath_overrides_runpath=no
hardcode_into_libs=yes
;;
uts4*)
version_type=linux # correct to gnu/linux during the next big refactor
library_names_spec='${libname}${release}${shared_ext}$versuffix ${libname}${release}${shared_ext}$major $libname${shared_ext}'
soname_spec='${libname}${release}${shared_ext}$major'
shlibpath_var=LD_LIBRARY_PATH
;;
*)
dynamic_linker=no
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $dynamic_linker" >&5
$as_echo "$dynamic_linker" >&6; }
test "$dynamic_linker" = no && can_build_shared=no
variables_saved_for_relink="PATH $shlibpath_var $runpath_var"
if test "$GCC" = yes; then
variables_saved_for_relink="$variables_saved_for_relink GCC_EXEC_PREFIX COMPILER_PATH LIBRARY_PATH"
fi
if test "${lt_cv_sys_lib_search_path_spec+set}" = set; then
sys_lib_search_path_spec="$lt_cv_sys_lib_search_path_spec"
fi
if test "${lt_cv_sys_lib_dlsearch_path_spec+set}" = set; then
sys_lib_dlsearch_path_spec="$lt_cv_sys_lib_dlsearch_path_spec"
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking how to hardcode library paths into programs" >&5
$as_echo_n "checking how to hardcode library paths into programs... " >&6; }
hardcode_action_CXX=
if test -n "$hardcode_libdir_flag_spec_CXX" ||
test -n "$runpath_var_CXX" ||
test "X$hardcode_automatic_CXX" = "Xyes" ; then
# We can hardcode non-existent directories.
if test "$hardcode_direct_CXX" != no &&
# If the only mechanism to avoid hardcoding is shlibpath_var, we
# have to relink, otherwise we might link with an installed library
# when we should be linking with a yet-to-be-installed one
## test "$_LT_TAGVAR(hardcode_shlibpath_var, CXX)" != no &&
test "$hardcode_minus_L_CXX" != no; then
# Linking always hardcodes the temporary library directory.
hardcode_action_CXX=relink
else
# We can link without hardcoding, and we can hardcode nonexisting dirs.
hardcode_action_CXX=immediate
fi
else
# We cannot hardcode anything, or else we can only hardcode existing
# directories.
hardcode_action_CXX=unsupported
fi
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: $hardcode_action_CXX" >&5
$as_echo "$hardcode_action_CXX" >&6; }
if test "$hardcode_action_CXX" = relink ||
test "$inherit_rpath_CXX" = yes; then
# Fast installation is not supported
enable_fast_install=no
elif test "$shlibpath_overrides_runpath" = yes ||
test "$enable_shared" = no; then
# Fast installation is not necessary
enable_fast_install=needless
fi
fi # test -n "$compiler"
CC=$lt_save_CC
CFLAGS=$lt_save_CFLAGS
LDCXX=$LD
LD=$lt_save_LD
GCC=$lt_save_GCC
with_gnu_ld=$lt_save_with_gnu_ld
lt_cv_path_LDCXX=$lt_cv_path_LD
lt_cv_path_LD=$lt_save_path_LD
lt_cv_prog_gnu_ldcxx=$lt_cv_prog_gnu_ld
lt_cv_prog_gnu_ld=$lt_save_with_gnu_ld
fi # test "$_lt_caught_CXX_error" != yes
ac_ext=c
ac_cpp='$CPP $CPPFLAGS'
ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5'
ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5'
ac_compiler_gnu=$ac_cv_c_compiler_gnu
ac_config_commands="$ac_config_commands libtool"
# Only expand once:
# Check if 64 bit pointer support is required on 32 bit machines
# Disabled by default
# Check whether --enable-64 was given.
if test "${enable_64+set}" = set; then :
enableval=$enable_64;
fi
if test "x${enable_64}" = "xyes"; then :
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for 64bit compilation support" >&5
$as_echo_n "checking for 64bit compilation support... " >&6; }
case ${host_os} in #(
aix*) :
CPPFLAGS="-DAJ_AIX64 ${CPPFLAGS}"
case ${CC} in #(
gcc) :
;; #(
*) :
as_fn_append CC " -q64"
;;
esac
NM="nm -B -X 64"
AR="ar -X 64"
;; #(
hpux*) :
case ${CC} in #(
gcc) :
;; #(
*) :
as_fn_append CC " +DD64"
;;
esac
$as_echo "#define HPUX64PTRS 1" >>confdefs.h
;; #(
*) :
;;
esac
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: done" >&5
$as_echo "done" >&6; }
fi
# Compiler optimisations
# The Solaris 64bit ptr check has to be done here owing to param order
# Check whether --with-optimisation was given.
if test "${with_optimisation+set}" = set; then :
withval=$with_optimisation;
fi
if test "x${with_optimisation}" != "xno"; then :
case ${CC} in #(
gcc) :
# Intel MacOSX requires reduced optimisation for PCRE code
# other OSs just use -O2
case ${host_os} in #(
darwin*) :
if test "x${host_cpu}" = "xi386"; then :
as_fn_append CFLAGS " -O1"
else
as_fn_append CFLAGS " -O2"
fi
;; #(
*) :
as_fn_append CFLAGS " -O2"
;;
esac
;; #(
*) :
case ${host_os} in #(
aix*) :
as_fn_append CFLAGS " -O3 -qstrict -qarch=auto -qtune=auto"
;; #(
irix*) :
LD="/usr/bin/ld -IPA"
as_fn_append CFLAGS " -O3"
;; #(
hpux*) :
as_fn_append CFLAGS " -fast"
;; #(
osf*) :
as_fn_append CFLAGS " -fast -U_FASTMATH"
;; #(
solaris*) :
as_fn_append CFLAGS " -O"
# test for 64 bit ptr here (see Solaris 64bit above)
if test "x${enable_64}" = "xyes"; then :
as_fn_append CFLAGS " -xtarget=ultra -xarch=v9"
fi
;; #(
linux*) :
# Default optimisation for non-gcc compilers under Linux
as_fn_append CFLAGS " -O2"
;; #(
freebsd*) :
as_fn_append CFLAGS " -O2"
;; #(
*) :
;;
esac
;;
esac
fi
# Compiler warning settings: --enable-warnings, defines WARN_CFLAGS
# Check whether --enable-warnings was given.
if test "${enable_warnings+set}" = set; then :
enableval=$enable_warnings;
fi
if test "x${enable_warnings}" = "xyes"; then :
case ${CC} in #(
gcc) :
# -Wall priovides:
# -Waddress
# -Warray-bounds (only with -O2)
# -Wc++0x-compat
# -Wchar-subscripts
# -Wenum-compare (in C/Objc; this is on by default in C++)
# -Wimplicit-int (C and Objective-C only)
# -Wimplicit-function-declaration (C and Objective-C only)
# -Wcomment
# -Wformat
# -Wmain (only for C/ObjC and unless -ffreestanding)
# -Wmissing-braces
# -Wnonnull
# -Wparentheses
# -Wpointer-sign
# -Wreorder
# -Wreturn-type
# -Wsequence-point
# -Wsign-compare (only in C++)
# -Wstrict-aliasing
# -Wstrict-overflow=1
# -Wswitch
# -Wtrigraphs
# -Wuninitialized
# -Wunknown-pragmas
# -Wunused-function
# -Wunused-label
# -Wunused-value
# -Wunused-variable
# -Wvolatile-register-var
WARN_CFLAGS="-Wall -fno-strict-aliasing"
;; #(
*) :
;;
esac
fi
# Compiler developer warning settings: --enable-devwarnings,
# sets DEVWARN_CFLAGS
# Check whether --enable-devwarnings was given.
if test "${enable_devwarnings+set}" = set; then :
enableval=$enable_devwarnings;
fi
if test "x${enable_devwarnings}" = "xyes"; then :
case ${CC} in #(
gcc) :
# Only -Wstrict-prototypes and -Wmissing-prototypes are set in this
# EMBASSY module.
DEVWARN_CFLAGS="-Wstrict-prototypes -Wmissing-prototypes"
# Diagnostic options for the GNU GCC compiler version 4.6.1.
# http://gcc.gnu.org/onlinedocs/gcc-4.6.1/gcc/Warning-Options.html
#
# -Wextra: more warnings beyond what -Wall provides
# -Wclobbered
# -Wempty-body
# -Wignored-qualifiers
# -Wmissing-field-initializers
# -Wmissing-parameter-type (C only)
# -Wold-style-declaration (C only)
# -Woverride-init
# -Wsign-compare
# -Wtype-limits
# -Wuninitialized
# -Wunused-parameter (only with -Wunused or -Wall)
# -Wunused-but-set-parameter (only with -Wunused or -Wall)
# AS_VAR_SET([DEVWARN_CFLAGS], ["-Wextra"])
# Warn if a function is declared or defined without specifying the
# argument types.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wstrict-prototypes"])
# Warn if a global function is defined without a previous prototype
# declaration.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wmissing-prototypes"])
# Warn for obsolescent usages, according to the C Standard,
# in a declaration.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wold-style-definition"])
# Warn if a global function is defined without a previous declaration.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wmissing-declarations"])
# When compiling C, give string constants the type const char[length]
# so that copying the address of one into a non-const char * pointer
# will get a warning.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wwrite-strings"])
# Warn whenever a local variable or type declaration shadows another
# variable, parameter, type, or class member (in C++), or whenever a
# built-in function is shadowed.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wshadow"])
# Warn when a declaration is found after a statement in a block.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wdeclaration-after-statement"])
# Warn if an undefined identifier is evaluated in an `#if' directive.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wundef"])
# Warn about anything that depends on the "size of" a function type
# or of void.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wpointer-arith"])
# Warn whenever a pointer is cast so as to remove a type qualifier
# from the target type.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wcast-qual"])
# Warn whenever a pointer is cast such that the required alignment
# of the target is increased.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wcast-align"])
# Warn whenever a function call is cast to a non-matching type.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wbad-function-cast"])
# Warn when a comparison between signed and unsigned values could
# produce an incorrect result when the signed value is converted to
# unsigned.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wsign-compare"])
# Warn if a structure's initializer has some fields missing.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wmissing-field-initializers"])
# An alias of the new option -Wsuggest-attribute=noreturn
# Warn for cases where adding an attribute may be beneficial.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wmissing-noreturn"])
# Warn if an extern declaration is encountered within a function.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wnested-externs"])
# Warn if anything is declared more than once in the same scope,
# even in cases where multiple declaration is valid and changes
# nothing.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wredundant-decls"])
# Warn if the loop cannot be optimized because the compiler could not
# assume anything on the bounds of the loop indices.
# -Wunsafe-loop-optimizations objects to loops with increments more
# than 1 because if the end is at INT_MAX it could run forever ...
# rarely
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wunsafe-loop-optimizations"])
# Warn for implicit conversions that may alter a value.
# -Wconversion is brain-damaged - complains about char arguments
# every time
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wconversion"])
# Warn about certain constructs that behave differently in traditional
# and ISO C.
# -Wtraditional gives #elif and #error msgs
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wtraditional"])
# Warn if floating point values are used in equality comparisons.
# -Wfloat-equal will not allow tests for values still 0.0
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wfloat-equal"])
# This option is only active when -ftree-vrp is active
# (default for -O2 and above). It warns about subscripts to arrays
# that are always out of bounds.
# -Warray-bounds gives false positives in gcc 4.6.0
# Disable rather than use a non-portable pragma
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wno-array-bounds"])
;; #(
icc) :
# Diagnostic options for the Intel(R) C++ compiler version 11.1.
# http://software.intel.com/en-us/articles/intel-c-compiler-professional-edition-for-linux-documentation/
# This option specifies the level of diagnostic messages to be
# generated by the compiler.
DEVWARN_CFLAGS="-w2"
# This option determines whether a warning is issued if generated
# code is not C++ ABI compliant.
as_fn_append DEVWARN_CFLAGS " -Wabi"
# This option tells the compiler to display errors, warnings, and
# remarks.
as_fn_append DEVWARN_CFLAGS " -Wall"
# This option tells the compiler to display a shorter form of
# diagnostic output.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wbrief"])
# This option warns if cast is used to override pointer type
# qualifier
as_fn_append DEVWARN_CFLAGS " -Wcast-qual"
# This option tells the compiler to perform compile-time code
# checking for certain code.
as_fn_append DEVWARN_CFLAGS " -Wcheck"
# This option determines whether a warning is issued when /*
# appears in the middle of a /* */ comment.
as_fn_append DEVWARN_CFLAGS " -Wcomment"
# Set maximum number of template instantiation contexts shown in
# diagnostic.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wcontext-limit=n"])
# This option enables warnings for implicit conversions that may
# alter a value.
as_fn_append DEVWARN_CFLAGS " -Wconversion"
# This option determines whether warnings are issued for deprecated
# features.
as_fn_append DEVWARN_CFLAGS " -Wdeprecated"
# This option enables warnings based on certain C++ programming
# guidelines.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Weffc++"])
# This option changes all warnings to errors.
# Alternate: -diag-error warn
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Werror"])
# This option changes all warnings and remarks to errors.
# Alternate: -diag-error warn, remark
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Werror-all"])
# This option determines whether warnings are issued about extra
# tokens at the end of preprocessor directives.
as_fn_append DEVWARN_CFLAGS " -Wextra-tokens"
# This option determines whether argument checking is enabled for
# calls to printf, scanf, and so forth.
as_fn_append DEVWARN_CFLAGS " -Wformat"
# This option determines whether the compiler issues a warning when
# the use of format functions may cause security problems.
as_fn_append DEVWARN_CFLAGS " -Wformat-security"
# This option enables diagnostics about what is inlined and what is
# not inlined.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Winline"])
# This option determines whether a warning is issued if the return
# type of main is not expected.
as_fn_append DEVWARN_CFLAGS " -Wmain"
# This option determines whether warnings are issued for global
# functions and variables without prior declaration.
as_fn_append DEVWARN_CFLAGS " -Wmissing-declarations"
# Determines whether warnings are issued for missing prototypes.
as_fn_append DEVWARN_CFLAGS " -Wmissing-prototypes"
# This option enables warnings if a multicharacter constant
# ('ABC') is used.
as_fn_append DEVWARN_CFLAGS " -Wmultichar"
# Issue a warning when a class appears to be polymorphic,
# yet it declares a non-virtual one.
# This option is supported in C++ only.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wnon-virtual-dtor"])
# This option warns about operations that could result in
# integer overflow.
as_fn_append DEVWARN_CFLAGS " -Woverflow"
# This option tells the compiler to display diagnostics for 64-bit
# porting.
as_fn_append DEVWARN_CFLAGS " -Wp64"
# Determines whether warnings are issued for questionable pointer
# arithmetic.
as_fn_append DEVWARN_CFLAGS " -Wpointer-arith"
# his option determines whether a warning is issued about the
# use of #pragma once.
as_fn_append DEVWARN_CFLAGS " -Wpragma-once"
# Issue a warning when the order of member initializers does not
# match the order in which they must be executed.
# This option is supported with C++ only.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wreorder"])
# This option determines whether warnings are issued when a function
# uses the default int return type or when a return statement is
# used in a void function.
as_fn_append DEVWARN_CFLAGS " -Wreturn-type"
# This option determines whether a warning is issued when a variable
# declaration hides a previous declaration.
as_fn_append DEVWARN_CFLAGS " -Wshadow"
# This option warns for code that might violate the optimizer's
# strict aliasing rules. Warnings are issued only when using
# -fstrict-aliasing or -ansi-alias.
# AS_VAR_APPEND([DEVWARN_CFLAGS], [" -Wstrict-aliasing"])
# This option determines whether warnings are issued for functions
# declared or defined without specified argument types.
as_fn_append DEVWARN_CFLAGS " -Wstrict-prototypes"
# This option determines whether warnings are issued if any trigraphs
# are encountered that might change the meaning of the program.
as_fn_append DEVWARN_CFLAGS " -Wtrigraphs"
# This option determines whether a warning is issued if a variable
# is used before being initialized.
as_fn_append DEVWARN_CFLAGS " -Wuninitialized"
# This option determines whether a warning is issued if an unknown
# #pragma directive is used.
as_fn_append DEVWARN_CFLAGS " -Wunknown-pragmas"
# This option determines whether a warning is issued if a declared
# function is not used.
as_fn_append DEVWARN_CFLAGS " -Wunused-function"
# This option determines whether a warning is issued if a local or
# non-constant static variable is unused after being declared.
as_fn_append DEVWARN_CFLAGS " -Wunused-variable"
# This option issues a diagnostic message if const char* is
# converted to (non-const) char *.
as_fn_append DEVWARN_CFLAGS " -Wwrite-strings"
# Disable warning #981 operands are evaluated in unspecified order
# http://software.intel.com/en-us/articles/cdiag981/
as_fn_append DEVWARN_CFLAGS " -diag-disable 981"
;; #(
*) :
;;
esac
fi
# Compiler extra developer warning settings: --enable-devextrawarnings,
# appends DEVWARN_CFLAGS
# Will only have an effect if --enable-devwarnings also given
# Check whether --enable-devextrawarnings was given.
if test "${enable_devextrawarnings+set}" = set; then :
enableval=$enable_devextrawarnings;
fi
if test "x${enable_devwarnings}" = "xyes" &&
test "x${enable_devextrawarnings}" = "xyes"; then :
case ${CC} in #(
gcc) :
# flags used by Ubuntu 8.10 to check open has 2/3 arguments etc.
$as_echo "#define _FORTIFY_SOURCE 2" >>confdefs.h
# compiler flags
CPPFLAGS="-fstack-protector ${CPPFLAGS}"
# warnings used by Ubuntu 8.10
# -Wall already includes:
# -Wformat
as_fn_append DEVWARN_CFLAGS " -Wformat-security -Wl,-z,relro"
# -Wpadded means moving char to end of structs - but also flags
# end of struct so need to add padding at end
as_fn_append DEVWARN_CFLAGS " -Wpadded"
;; #(
*) :
;;
esac
fi
# Compile deprecated functions still used in the book text for 6.2.0
# Check whether --enable-buildbookdeprecated was given.
if test "${enable_buildbookdeprecated+set}" = set; then :
enableval=$enable_buildbookdeprecated;
fi
# Compile all deprecated functions
# Check whether --enable-buildalldeprecated was given.
if test "${enable_buildalldeprecated+set}" = set; then :
enableval=$enable_buildalldeprecated;
fi
if test "x${enable_buildbookdeprecated}" = "xyes" ||
test "x${enable_buildalldeprecated}" = "xyes"; then :
$as_echo "#define AJ_COMPILE_DEPRECATED_BOOK 1" >>confdefs.h
fi
if test "x${enable_buildalldeprecated}" = "xyes"; then :
$as_echo "#define AJ_COMPILE_DEPRECATED 1" >>confdefs.h
fi
# Add extensions to Solaris for some reentrant functions
case ${host_os} in #(
solaris*) :
as_fn_append CFLAGS " -D__EXTENSIONS__" ;; #(
*) :
;;
esac
# Test whether --with-sgiabi given for IRIX (n32m3 n32m4 64m3 64m4)
case ${host_os} in #(
irix*) :
case ${CC} in #(
gcc) :
;; #(
cc) :
#
# Handle SGI compiler flags
#
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for sgiabi" >&5
$as_echo_n "checking for sgiabi... " >&6; }
# Check whether --with-sgiabi was given.
if test "${with_sgiabi+set}" = set; then :
withval=$with_sgiabi; if test "$withval" != no ; then
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: yes" >&5
$as_echo "yes" >&6; }
case $host_os in
irix*)
if test "$withval" = n32m3 ; then
CFLAGS="-n32 -mips3 $CFLAGS"
LD="/usr/bin/ld -n32 -mips3 -IPA -L/usr/lib32"
if test -d /usr/freeware ; then
LDFLAGS="-L/usr/freeware/lib32 $LDFLAGS"
fi
fi
if test "$withval" = n32m4 ; then
CFLAGS="-n32 -mips4 $CFLAGS"
LD="/usr/bin/ld -n32 -mips4 -IPA -L/usr/lib32"
if test -d /usr/freeware ; then
LDFLAGS="-L/usr/freeware/lib32 $LDFLAGS"
fi
fi
if test "$withval" = 64m3 ; then
CFLAGS="-64 -mips3 $CFLAGS"
LD="/usr/bin/ld -64 -mips3 -IPA -L/usr/lib64"
if test -d /usr/freeware ; then
LDFLAGS="-L/usr/freeware/lib64 $LDFLAGS"
fi
fi
if test "$withval" = 64m4 ; then
CFLAGS="-64 -mips4 $CFLAGS"
LD="/usr/bin/ld -64 -mips4 -IPA -L/usr/lib64"
if test -d /usr/freeware ; then
LDFLAGS="-L/usr/freeware/lib64 $LDFLAGS"
fi
fi
;;
esac
fi
else
{ $as_echo "$as_me:${as_lineno-$LINENO}: result: no" >&5
$as_echo "no" >&6; }
fi
;; #(
*) :
;;
esac
;; #(
*) :
;;
esac
PCRE_MAJOR="7"
PCRE_MINOR="9"
PCRE_DATE="11-Apr-2009"
PCRE_VERSION="${PCRE_MAJOR}.${PCRE_MINOR}"
POSIX_MALLOC_THRESHOLD="-DPOSIX_MALLOC_THRESHOLD=10"
PCRE_LIB_VERSION="0:1:0"
PCRE_POSIXLIB_VERSION="0:0:0"
# Checks for header files.
{ $as_echo "$as_me:${as_lineno-$LINENO}: checking for X" >&5
$as_echo_n "checking for X... " >&6; }
# Check whether --with-x was given.
if test "${with_x+set}" = set; then :
withval=$with_x;
fi
# $have_x is `yes', `no', `disabled', or empty when we do not yet know.
if test "x$with_x" = xno; then
# The user explicitly disabled X.
have_x=disabled
else
case $x_includes,$x_libraries in #(
*\'*) as_fn_error $? "cannot use X directory names containing '" "$LINENO" 5;; #(
*,NONE | NONE,*) if ${ac_cv_have_x+:} false; then :
$as_echo_n "(cached) " >&6
else
# One or both of the vars are not set, and there is no cached value.
ac_x_includes=no ac_x_libraries=no
rm -f -r conftest.dir
if mkdir conftest.dir; then
cd conftest.dir
cat >Imakefile <<'_ACEOF'
incroot:
@echo incroot='${INCROOT}'
usrlibdir:
@echo usrlibdir='${USRLIBDIR}'
libdir:
@echo libdir='${LIBDIR}'
_ACEOF
if (export CC; ${XMKMF-xmkmf}) >/dev/null 2>/dev/null && test -f Makefile; then
# GNU make sometimes prints "make[1]: Entering ...", which would confuse us.
for ac_var in incroot usrlibdir libdir; do
eval "ac_im_$ac_var=\`\${MAKE-make} $ac_var 2>/dev/null | sed -n 's/^$ac_var=//p'\`"
done
# Open Windows xmkmf reportedly sets LIBDIR instead of USRLIBDIR.
for ac_extension in a so sl dylib la dll; do
if test ! -f "$ac_im_usrlibdir/libX11.$ac_extension" &&
test -f "$ac_im_libdir/libX11.$ac_extension"; then
ac_im_usrlibdir=$ac_im_libdir; break
fi
done
# Screen out bogus values from the imake configuration. They are
# bogus both because they are the default anyway, and because
# using them would break gcc on systems where it needs fixed includes.
case $ac_im_incroot in
/usr/include) ac_x_includes= ;;
*) test -f "$ac_im_incroot/X11/Xos.h" && ac_x_includes=$ac_im_incroot;;
esac
case $ac_im_usrlibdir in
/usr/lib | /usr/lib64 | /lib | /lib64) ;;
*) test -d "$ac_im_usrlibdir" && ac_x_libraries=$ac_im_usrlibdir ;;
esac
fi
cd ..
rm -f -r conftest.dir
fi
# Standard set of common directories for X headers.
# Check X11 before X11Rn because it is often a symlink to the current release.
ac_x_header_dirs='
/usr/X11/include
/usr/X11R7/include
/usr/X11R6/include
/usr/X11R5/include
/usr/X11R4/include
/usr/include/X11
/usr/include/X11R7
/usr/include/X11R6
/usr/include/X11R5
/usr/include/X11R4
/usr/local/X11/include
/usr/local/X11R7/include
/usr/local/X11R6/include
/usr/local/X11R5/include
/usr/local/X11R4/include
/usr/local/include/X11
/usr/local/include/X11R7
/usr/local/include/X11R6
/usr/local/include/X11R5
/usr/local/include/X11R4
/usr/X386/include
/usr/x386/include
/usr/XFree86/include/X11
/usr/include
/usr/local/include
/usr/unsupported/include
/usr/athena/include
/usr/local/x11r5/include
/usr/lpp/Xamples/include
/usr/openwin/include
/usr/openwin/share/include'
if test "$ac_x_includes" = no; then
# Guess where to find include files, by looking for Xlib.h.
# First, try using that file with no special directory specified.
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
_ACEOF
if ac_fn_c_try_cpp "$LINENO"; then :
# We can compile using X headers with no special include directory.
ac_x_includes=
else
for ac_dir in $ac_x_header_dirs; do
if test -r "$ac_dir/X11/Xlib.h"; then
ac_x_includes=$ac_dir
break
fi
done
fi
rm -f conftest.err conftest.i conftest.$ac_ext
fi # $ac_x_includes = no
if test "$ac_x_libraries" = no; then
# Check for the libraries.
# See if we find them without any special options.
# Don't add to $LIBS permanently.
ac_save_LIBS=$LIBS
LIBS="-lX11 $LIBS"
cat confdefs.h - <<_ACEOF >conftest.$ac_ext
/* end confdefs.h. */
#include
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