PSCBS/ 0000755 0001762 0000144 00000000000 14564202212 011122 5 ustar ligges users PSCBS/NAMESPACE 0000644 0001762 0000144 00000031246 14564060172 012356 0 ustar ligges users # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # IMPORTS # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - importFrom("R.methodsS3", "setMethodS3") importFrom("R.methodsS3", "getMethodS3") importFrom("R.oo", "setConstructorS3") importFrom("R.utils", "use") ## Importing Object classes importFrom("R.oo", "Package") importFrom("R.utils", "Arguments") importFrom("R.utils", "GenericSummary") ## Importing functions importFrom("R.oo", "extend", "attachLocally", "startupMessage") importFrom("R.cache", "getCachePath", "loadCache", "saveCache") importFrom("R.utils", "cat", "capitalize", "copyDirectory", "createLink", "enter", "enterf", "exit", "filePath", "getAbsolutePath", "getRelativePath", "hpaste", "insert", "isDirectory", "isFile", "isPackageInstalled", "isZero", "less", "loadObject", "more", "popState", "popTemporaryFile", "printf", "pushState", "pushTemporaryFile", "resample", "saveObject", "stext", "subplots", "toCamelCase", "wrap") importFrom("matrixStats", "binMeans", "colCumsums", "colDiffs", "colMins", "colMaxs", "rowAlls", "rowAnys", "rowMins", "weightedMedian") importFrom("graphics", "abline", "arrows", "axis", "box", "lines", "mtext", "par", "plot", "points", "rect", "text") importFrom("grDevices", "col2rgb", "rgb") importFrom("stats", "approx", "cor", "cutree", "density", "end", "mad", "median", "na.omit", "quantile", "sd", "start", "weighted.mean") importFrom("utils", "capture.output", "file_test", "getFromNamespace", "head", "packageVersion", "str", "tail", "write.table", "packageDescription", "install.packages") importFrom("aroma.light", "callNaiveGenotypes", "findPeaksAndValleys", "normalizeTumorBoost") importFrom("DNAcopy", "segments.summary", "smooth.CNA", "CNA", "segment", "getbdry") importFrom("listenv", "listenv") importFrom("future", "%<-%", "%seed%", "%label%") importFrom("parallel", "nextRNGStream") # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # EXPORTS # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Export all public methods, that is, those without a preceeding dot # in their names. exportPattern("^[^\\.]") # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # S3 methods # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # AbstractCBS S3method("adjustPloidyScale", "AbstractCBS") S3method("all.equal", "AbstractCBS") S3method("as.data.frame", "AbstractCBS") S3method("clearCalls", "AbstractCBS") S3method("drawChangePoints", "AbstractCBS") S3method("drawKnownSegments", "AbstractCBS") S3method("dropChangePoint", "AbstractCBS") S3method("dropChangePoints", "AbstractCBS") S3method("dropRegion", "AbstractCBS") S3method("dropRegions", "AbstractCBS") S3method("extractChromosome", "AbstractCBS") S3method("extractChromosomes", "AbstractCBS") S3method("extractCNs", "AbstractCBS") S3method("extractRegion", "AbstractCBS") S3method("extractRegions", "AbstractCBS") S3method("extractSegment", "AbstractCBS") S3method("extractSegments", "AbstractCBS") S3method("getChangePoints", "AbstractCBS") S3method("getChromosomeOffsets", "AbstractCBS") S3method("getChromosomeRanges", "AbstractCBS") S3method("getChromosomes", "AbstractCBS") S3method("getLocusData", "AbstractCBS") S3method("getLocusSignalNames", "AbstractCBS") S3method("getMeanEstimators", "AbstractCBS") S3method("getSampleName", "AbstractCBS") S3method("getSegments", "AbstractCBS") S3method("getSegmentSizes", "AbstractCBS") S3method("getSegmentTrackPrefixes", "AbstractCBS") S3method("hclustCNs", "AbstractCBS") S3method("mergeThreeSegments", "AbstractCBS") S3method("mergeTwoSegments", "AbstractCBS") S3method("nbrOfChangePoints", "AbstractCBS") S3method("nbrOfChromosomes", "AbstractCBS") S3method("nbrOfLoci", "AbstractCBS") S3method("nbrOfSegments", "AbstractCBS") S3method("normalizeTotalCNs", "AbstractCBS") S3method("normalizeTotalCNs", "PSCBS") S3method("ploidy", "AbstractCBS") S3method("ploidy<-", "AbstractCBS") S3method("plotTracks", "AbstractCBS") S3method("print", "AbstractCBS") S3method("pruneByDP", "AbstractCBS") S3method("pruneByHClust", "AbstractCBS") S3method("renameChromosomes", "AbstractCBS") S3method("report", "AbstractCBS") S3method("resegment", "AbstractCBS") S3method("resetSegments", "AbstractCBS") S3method("sampleCNs", "AbstractCBS") S3method("sampleName", "AbstractCBS") S3method("sampleName<-", "AbstractCBS") S3method("seqOfSegmentsByDP", "AbstractCBS") S3method("setLocusData", "AbstractCBS") S3method("setMeanEstimators", "AbstractCBS") S3method("setPloidy", "AbstractCBS") S3method("setSampleName", "AbstractCBS") S3method("setSegments", "AbstractCBS") S3method("shiftTCN", "AbstractCBS") S3method("tileChromosomes", "AbstractCBS") S3method("updateMeans", "AbstractCBS") S3method("updateMeansTogether", "AbstractCBS") S3method("writeWIG", "AbstractCBS") # CBS S3method("all.equal", "CBS") S3method("as.character", "CBS") S3method("as.data.frame", "CBS") S3method("as.DNAcopy", "CBS") S3method("c", "CBS") S3method("callAmplifications", "CBS") S3method("callArms", "CBS") S3method("callGainsAndLosses", "CBS") S3method("callGLAO", "CBS") S3method("callOutliers", "CBS") S3method("drawCentromeres", "CBS") S3method("drawChromosomes", "CBS") S3method("drawLevels", "CBS") S3method("estimateDeltaCN", "CBS") S3method("estimateStandardDeviation", "CBS") S3method("extractCallsByLocus", "CBS") S3method("extractChromosomes", "CBS") S3method("extractCNs", "CBS") S3method("extractSegmentMeansByLocus", "CBS") S3method("extractSegments", "CBS") S3method("extractTotalCNs", "CBS") S3method("extractWIG", "CBS") S3method("extractWIG", "AbstractCBS") S3method("extractWIG", "PSCBS") S3method("getCallStatistics", "CBS") S3method("getCallStatisticsByArms", "CBS") S3method("getChangePoints", "CBS") S3method("getChromosomeRanges", "CBS") S3method("getFGA", "CBS") S3method("getFGG", "CBS") S3method("getFGL", "CBS") S3method("getFractionOfGenomeAltered", "CBS") S3method("getFractionOfGenomeGained", "CBS") S3method("getFractionOfGenomeLost", "CBS") S3method("getLocusData", "CBS") S3method("getLocusSignalNames", "CBS") S3method("getSegments", "CBS") S3method("getSegmentTrackPrefixes", "CBS") S3method("getSignalType", "CBS") S3method("getSmoothLocusData", "CBS") S3method("highlightArmCalls", "CBS") S3method("highlightCalls", "CBS") S3method("highlightLocusCalls", "CBS") S3method("isSegmentSplitter", "CBS") S3method("isWholeChromosomeGained", "CBS") S3method("isWholeChromosomeLost", "CBS") S3method("joinSegments", "CBS") S3method("mergeNonCalledSegments", "CBS") S3method("mergeTwoSegments", "CBS") S3method("nbrOfAmplifications", "CBS") S3method("nbrOfGains", "CBS") S3method("nbrOfLosses", "CBS") S3method("plot", "CBS") S3method("plotTracks", "CBS") S3method("plotTracksManyChromosomes", "CBS") S3method("pruneBySdUndo", "CBS") S3method("resegment", "CBS") S3method("segmentByCBS", "CBS") S3method("seqOfSegmentsByDP", "CBS") S3method("shiftTCN", "CBS") S3method("signalType", "CBS") S3method("signalType<-", "CBS") S3method("subset", "CBS") S3method("tileChromosomes", "CBS") S3method("updateBoundaries", "CBS") S3method("updateMeans", "CBS") S3method("updateMeansTogether", "CBS") S3method("writeLocusData", "CBS") S3method("writeSegments", "CBS") # CNA S3method("segmentByCBS", "CNA") # data.frame S3method("callSegmentationOutliers", "data.frame") S3method("encodeCalls", "data.frame") S3method("dropSegmentationOutliers", "data.frame") S3method("findLargeGaps", "data.frame") S3method("gapsToSegments", "data.frame") S3method("segmentByCBS", "data.frame") S3method("segmentByNonPairedPSCBS", "data.frame") S3method("segmentByPairedPSCBS", "data.frame") # default S3method("callAllelicBalance", "default") S3method("callSegmentationOutliers", "default") S3method("dropSegmentationOutliers", "default") S3method("exampleData", "default") S3method("findLargeGaps", "default") S3method("findNeutralCopyNumberState", "default") S3method("installDNAcopy", "default") S3method("segmentByCBS", "default") S3method("segmentByNonPairedPSCBS", "default") S3method("segmentByPairedPSCBS", "default") S3method("weightedQuantile", "default") # DNAcopy S3method("as.CBS", "DNAcopy") S3method("drawLevels", "DNAcopy") S3method("estimateStandardDeviation", "DNAcopy") S3method("extractSegmentMeansByLocus", "DNAcopy") S3method("getChromosomes", "DNAcopy") S3method("getSampleNames", "DNAcopy") S3method("nbrOfLoci", "DNAcopy") S3method("nbrOfSamples", "DNAcopy") S3method("nbrOfSegments", "DNAcopy") S3method("writeSegments", "DNAcopy") # matrix S3method("seqOfSegmentsByDP", "matrix") # NonPairedPSCBS S3method("callROH", "NonPairedPSCBS") S3method("getLocusData", "NonPairedPSCBS") S3method("resegment", "NonPairedPSCBS") S3method("updateMeans", "NonPairedPSCBS") # numeric S3method("testROH", "numeric") # PairedPSCBS S3method("adjustPloidyScale", "PairedPSCBS") S3method("applyByRegion", "PairedPSCBS") S3method("arrowsC1C2", "PairedPSCBS") S3method("arrowsDeltaC1C2", "PairedPSCBS") S3method("bootstrapCIs", "PairedPSCBS") S3method("bootstrapSegmentsAndChangepoints", "PairedPSCBS") S3method("bootstrapTCNandDHByRegion", "PairedPSCBS") S3method("calcStatsForCopyNeutralABs", "PairedPSCBS") S3method("callAB", "PairedPSCBS") S3method("callABandHighAI", "PairedPSCBS") S3method("callABandLowC1", "PairedPSCBS") S3method("callAllelicBalanceByDH", "PairedPSCBS") S3method("callCopyNeutral", "PairedPSCBS") S3method("callCopyNeutralByTCNofAB", "PairedPSCBS") S3method("callExtremeAllelicImbalanceByDH", "PairedPSCBS") S3method("callGainNeutralLoss", "PairedPSCBS") S3method("callGNL", "PairedPSCBS") S3method("callGNLByTCNofAB", "PairedPSCBS") S3method("callGNLByTCNofABv1", "PairedPSCBS") S3method("callLOH", "PairedPSCBS") S3method("callLowC1ByC1", "PairedPSCBS") S3method("callNTCN", "PairedPSCBS") S3method("callROH", "PairedPSCBS") S3method("callROHOneSegment", "PairedPSCBS") S3method("clearBootstrapSummaries", "PairedPSCBS") S3method("drawChangePointsC1C2", "PairedPSCBS") S3method("drawConfidenceBands", "PairedPSCBS") S3method("drawLevels", "PairedPSCBS") S3method("estimateDeltaAB", "PairedPSCBS") S3method("estimateDeltaABBySmallDH", "PairedPSCBS") S3method("estimateDeltaCN", "PairedPSCBS") S3method("estimateDeltaLOH", "PairedPSCBS") S3method("estimateDeltaLOHByMinC1ForNonAB", "PairedPSCBS") S3method("estimateHighDHQuantileAtAB", "PairedPSCBS") S3method("estimateKappa", "PairedPSCBS") S3method("estimateKappaByC1Density", "PairedPSCBS") S3method("estimateMeanForDH", "PairedPSCBS") S3method("estimateStdDevForHeterozygousBAF", "PairedPSCBS") S3method("extractC1C2", "PairedPSCBS") S3method("extractCallsByLocus", "PairedPSCBS") S3method("extractCNs", "PairedPSCBS") S3method("extractDeltaC1C2", "PairedPSCBS") S3method("extractDhSegment", "PairedPSCBS") S3method("extractLocusLevelC1C2", "PairedPSCBS") S3method("extractLocusLevelTCN", "PairedPSCBS") S3method("extractMinorMajorCNs", "PairedPSCBS") S3method("extractSegmentDataByLocus", "PairedPSCBS") S3method("extractSegments", "PairedPSCBS") S3method("extractTCNAndDHs", "PairedPSCBS") S3method("findBootstrapSummaries", "PairedPSCBS") S3method("getBootstrapLocusSets", "PairedPSCBS") S3method("getChromosomeOffsets", "PairedPSCBS") S3method("getChromosomeRanges", "PairedPSCBS") S3method("getLocusData", "PairedPSCBS") S3method("hasBootstrapSummaries", "PairedPSCBS") S3method("linesC1C2", "PairedPSCBS") S3method("linesDeltaC1C2", "PairedPSCBS") S3method("mergeTwoSegments", "PairedPSCBS") S3method("plot", "PairedPSCBS") S3method("plotC1C2", "PairedPSCBS") S3method("plotDeltaC1C2", "PairedPSCBS") S3method("plotTracks", "PairedPSCBS") S3method("plotTracks1", "PairedPSCBS") S3method("plotTracks2", "PairedPSCBS") S3method("plotTracksManyChromosomes", "PairedPSCBS") S3method("pointsC1C2", "PairedPSCBS") S3method("pointsDeltaC1C2", "PairedPSCBS") S3method("postsegmentTCN", "PairedPSCBS") S3method("resegment", "PairedPSCBS") S3method("segmentByNonPairedPSCBS", "PairedPSCBS") S3method("segmentByPairedPSCBS", "PairedPSCBS") S3method("seqOfSegmentsByDP", "PairedPSCBS") S3method("shiftTCN", "PairedPSCBS") S3method("tileChromosomes", "PairedPSCBS") S3method("unTumorBoost", "PairedPSCBS") S3method("updateMeans", "PairedPSCBS") S3method("updateMeansC1C2", "PairedPSCBS") S3method("updateMeansTogether", "PairedPSCBS") # PSCBS S3method("as.data.frame", "PSCBS") S3method("c", "PSCBS") S3method("drawChangePoints", "PSCBS") S3method("extractChromosomes", "PSCBS") S3method("getChangePoints", "PSCBS") S3method("getLocusData", "PSCBS") S3method("getLocusSignalNames", "PSCBS") S3method("getSegments", "PSCBS") S3method("getSegmentTrackPrefixes", "PSCBS") S3method("isLocallyPhased", "PSCBS") S3method("isSegmentSplitter", "PSCBS") S3method("writeSegments", "PSCBS") PSCBS/README.md 0000644 0001762 0000144 00000013354 14564057243 012423 0 ustar ligges users
# PSCBS: Analysis of Parent-Specific DNA Copy Numbers The PSCBS package implements the parent-specific copy-number segmentation presented in Olshen et al. (2011). Package vignette ['Parent-specific copy-number segmentation using Paired PSCBS'](https://CRAN.R-project.org/package=PSCBS/vignettes/PairedPSCBS.pdf) provides a detailed introduction for running PSCBS segmentation. It's available as: ```r vignette("PairedPSCBS", package = "PSCBS") ``` Below is an excerpt of the example found in that vignette: ```r library(PSCBS) ## Get single-chromosome example data data <- exampleData("paired.chr01") str(data) # ’data.frame’: 73346 obs. of 6 variables: # $ chromosome: int 1 1 1 1 1 1 1 1 1 1 ... # $ x : int 1145994 2224111 2319424 2543484 2926730 2941694 3084986 3155127.. # $ CT : num 1.625 1.071 1.406 1.18 0.856 ... # $ betaT : num 0.757 0.771 0.834 0.778 0.229 ... # $ CN : num 2.36 2.13 2.59 1.93 1.71 ... # $ betaN : num 0.827 0.875 0.887 0.884 0.103 ... ## Drop total copy-number outliers data <- dropSegmentationOutliers(data) ## Identify chromosome arms from data gaps <- findLargeGaps(data, minLength = 1e+06) knownSegments <- gapsToSegments(gaps) ## Parent-specific copy-number segmentation fit <- segmentByPairedPSCBS(data, knownSegments = knownSegments) ## Get segments as a data.frame segments <- getSegments(fit, simplify = TRUE) segments # chromosome tcnId dhId start end tcnNbrOfLoci tcnMean # 1 1 1 1 554484 33414619 9413 1.381375 # 2 1 1 2 33414619 86993745 17433 1.378570 # 3 1 2 1 86993745 87005243 2 3.185100 # 4 1 3 1 87005243 119796080 10404 1.389763 # 5 1 3 2 119796080 119932126 72 1.470789 # 6 1 3 3 119932126 120992603 171 1.439620 # 7 1 4 1 120992604 141510002 0 NA # 8 1 5 1 141510003 185527989 13434 2.065400 # 9 1 6 1 185527989 199122066 4018 2.707400 # 10 1 7 1 199122066 206512702 2755 2.586100 # 11 1 8 1 206512702 206521352 14 3.871900 # 12 1 9 1 206521352 247165315 15581 2.637500 # tcnNbrOfSNPs tcnNbrOfHets dhNbrOfLoci dhMean c1Mean c2Mean # 1 2765 2765 2765 0.4868 0.3544608 1.0269140 # 2 4544 4544 4544 0.5185 0.3318907 1.0466792 # 3 0 0 0 NA NA NA # 4 2777 2777 2777 0.5203 0.3333347 1.0564285 # 5 8 8 8 0.0767 0.6789900 0.7917995 # 6 52 52 52 0.5123 0.3510514 1.0885688 # 7 0 0 NA NA NA NA # 8 3770 3770 3770 0.0943 0.9353164 1.1300836 # 9 1271 1271 1271 0.2563 1.0067467 1.7006533 # 10 784 784 784 0.2197 1.0089669 1.5771331 # 11 9 9 9 0.2769 1.3998854 2.4720146 # 12 4492 4492 4492 0.2290 1.0167563 1.6207438 ## Plot copy-number tracks plotTracks(fit) ```  ## Parallel processing The package supports segmentation of the chromosomes in parallel (asynchronously) via [futures](https://cran.r-project.org/package=future) by adding the following ```r future::plan("multisession") ``` to the beginning of the PSCBS script. Everything else will work the same. To reset to non-parallel processing, use `future::plan("sequential")`. To configure this automatically whenever the package is loaded, see future vignette '[A Future for R: Controlling Default Future Strategy](https://CRAN.R-project.org/package=future/vignettes/future-5-startup.html)'. ## References * Bengtsson H, Neuvial P, Speed TP. TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays, BMC Bioinformatics, 2010. DOI: [10.1186/1471-2105-11-245](https://doi.org/10.1186%2F1471-2105-11-245). PMID: [20462408](https://europepmc.org/article/MED/20462408), PMCID: [PMC2894037](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2894037/) * Olshen AB, Bengtsson H, Neuvial P, Spellman PT, Olshen RA, Seshan VA. Parent-specific copy number in paired tumor-normal studies using circular binary segmentation, Bioinformatics, 2011. DOI: [10.1093/bioinformatics/btr329](https://doi.org/10.1093%2Fbioinformatics%2Fbtr329). PMID: [21666266](https://europepmc.org/article/MED/21666266). PMCID: [PMC3137217](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3137217/) ## Installation R package PSCBS is available on [CRAN](https://cran.r-project.org/package=PSCBS) and can be installed in R as: ```r # install.packages("BiocManager") BiocManager::install(c("aroma.light", "DNAcopy")) install.packages("PSCBS") ``` ### Pre-release version To install the pre-release version that is available in Git branch `develop` on GitHub, use: ```r remotes::install_github("HenrikBengtsson/PSCBS", ref="develop") ``` This will install the package from source. PSCBS/man/ 0000755 0001762 0000144 00000000000 14564060172 011704 5 ustar ligges users PSCBS/man/dropChangePoints.AbstractCBS.Rd 0000644 0001762 0000144 00000002763 14564060313 017541 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.RESTRUCT.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{dropChangePoints.AbstractCBS} \alias{dropChangePoints.AbstractCBS} \alias{AbstractCBS.dropChangePoints} \alias{dropChangePoints,AbstractCBS-method} \title{Drops zero or more change points} \description{ Drops zero or more change points, which is done by dropping one change point at the time using \code{\link[PSCBS:dropChangePoint.AbstractCBS]{*dropChangePoint}()} and recalculating the segment statistics at the end. \emph{NOTE: This method only works if there is only one chromosome.} } \usage{ \method{dropChangePoints}{AbstractCBS}(fit, idxs, update=TRUE, ...) } \arguments{ \item{idxs}{An \code{\link[base]{integer}} \code{\link[base]{vector}} specifying the change points to be dropped.} \item{update}{If \code{\link[base:logical]{TRUE}}, segment statistics are updated.} \item{...}{Other arguments passed to \code{\link[PSCBS:dropChangePoint.AbstractCBS]{*dropChangePoint}()} and \code{\link[PSCBS:updateMeans.AbstractCBS]{*updateMeans}()}.} } \value{ Returns an \code{\link{AbstractCBS}} of the same class with \code{length(idxs)} segments. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/segmentByNonPairedPSCBS.Rd 0000644 0001762 0000144 00000015664 14564060314 016535 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % segmentByNonPairedPSCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{segmentByNonPairedPSCBS} \alias{segmentByNonPairedPSCBS.default} \alias{segmentByNonPairedPSCBS} \alias{segmentByNonPairedPSCBS.data.frame} \alias{segmentByNonPairedPSCBS.PairedPSCBS} \alias{segmentByNonPairedPSCBS} \title{Segment total copy numbers and allele B fractions using the Non-paired PSCBS method} \description{ Segment total copy numbers and allele B fractions using the Non-paired PSCBS method [1]. This method does not requires matched normals. This is a low-level segmentation method. It is intended to be applied to one tumor sample at the time. } \usage{ \method{segmentByNonPairedPSCBS}{default}(CT, betaT, ..., flavor=c("tcn", "tcn&dh", "tcn,dh", "sqrt(tcn),dh", "sqrt(tcn)&dh"), tauA=NA, tauB=1 - tauA, verbose=FALSE) } \arguments{ \item{CT}{A \code{\link[base]{numeric}} \code{\link[base]{vector}} of J tumor total copy number (TCN) ratios in [0,+\code{\link[base:is.finite]{Inf}}) (due to noise, small negative values are also allowed). The TCN ratios are typically scaled such that copy-neutral diploid loci have a mean of two.} \item{betaT}{A \code{\link[base]{numeric}} \code{\link[base]{vector}} of J tumor allele B fractions (BAFs) in [0,1] (due to noise, values may be slightly outside as well) or \code{\link[base]{NA}} for non-polymorphic loci.} \item{...}{Additional arguments passed to \code{\link{segmentByPairedPSCBS}}().} \item{flavor}{A \code{\link[base]{character}} specifying what type of segmentation and calling algorithm to be used.} \item{tauA, tauB}{Lower and upper thresholds (\code{tauA < tauB} for calling SNPs heterozygous based on the tumor allele B fractions (\code{betaT}). If \code{\link[base]{NA}}, then they are estimates from data. } \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns the segmentation results as a \code{\link{NonPairedPSCBS}} object. } \details{ Internally \code{\link{segmentByPairedPSCBS}}() is used for segmentation. This segmentation method does \emph{not} support weights. } \section{Reproducibility}{ The "DNAcopy::segment" implementation of CBS uses approximation through random sampling for some estimates. Because of this, repeated calls using the same signals may result in slightly different results, unless the random seed is set/fixed. } \section{Whole-genome segmentation is preferred}{ Although it is possible to segment each chromosome independently using Paired PSCBS, we strongly recommend to segment whole-genome (TCN,BAF) data at once. The reason for this is that downstream CN-state calling methods, such as the AB and the LOH callers, performs much better on whole-genome data. In fact, they may fail to provide valid calls if done chromosome by chromosome. } \section{Missing and non-finite values}{ The total copy number signals as well as any optional positions must not contain missing values, i.e. \code{\link[base]{NA}}s or \code{\link[base:is.finite]{NaN}}s. If there are any, an informative error is thrown. Allele B fractions may contain missing values, because such are interpreted as representing non-polymorphic loci. None of the input signals may have infinite values, i.e. -\code{\link[base:is.finite]{Inf}} or +\code{\link[base:is.finite]{Inf}}. If so, an informative error is thrown. } \section{Non-Paired PSCBS with known genotypes}{ If allele B fractions for the matched normal (\code{betaN}) are not available, but genotypes (\code{muN}) are, then it is possible to run Paired PSCBS. See \code{\link{segmentByPairedPSCBS}}() for details. } \examples{ verbose <- R.utils::Arguments$getVerbose(-10*interactive(), timestamp=TRUE) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Load SNP microarray data # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - data <- PSCBS::exampleData("paired.chr01") str(data) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Paired PSCBS segmentation # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Drop single-locus outliers dataS <- dropSegmentationOutliers(data) # Speed up example by segmenting fewer loci dataS <- dataS[seq(from=1, to=nrow(data), by=20),] str(dataS) R.oo::attachLocally(dataS) # Non-Paired PSCBS segmentation fit <- segmentByNonPairedPSCBS(CT, betaT=betaT, chromosome=chromosome, x=x, seed=0xBEEF, verbose=verbose) print(fit) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Bootstrap segment level estimates # (used by the AB caller, which, if skipped here, # will do it automatically) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fit <- bootstrapTCNandDHByRegion(fit, B=100, verbose=verbose) print(fit) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Calling segments in allelic balance (AB) # NOTE: Ideally, this should be done on whole-genome data # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Explicitly estimate the threshold in DH for calling AB # (which be done by default by the caller, if skipped here) deltaAB <- estimateDeltaAB(fit, flavor="qq(DH)", verbose=verbose) print(deltaAB) fit <- callAB(fit, delta=deltaAB, verbose=verbose) print(fit) # Even if not explicitly specified, the estimated # threshold parameter is returned by the caller stopifnot(fit$params$deltaAB == deltaAB) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Calling segments in loss-of-heterozygosity (LOH) # NOTE: Ideally, this should be done on whole-genome data # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Explicitly estimate the threshold in C1 for calling LOH # (which be done by default by the caller, if skipped here) deltaLOH <- estimateDeltaLOH(fit, flavor="minC1|nonAB", verbose=verbose) print(deltaLOH) fit <- callLOH(fit, delta=deltaLOH, verbose=verbose) print(fit) plotTracks(fit) # Even if not explicitly specified, the estimated # threshold parameter is returned by the caller stopifnot(fit$params$deltaLOH == deltaLOH) } \author{Henrik Bengtsson} \references{ [1] A.B. Olshen, H. Bengtsson, P. Neuvial, P.T. Spellman, R.A. Olshen, V.E. Seshan, \emph{Parent-specific copy number in paired tumor-normal studies using circular binary segmentation}, Bioinformatics, 2011 \cr [2] H. Bengtsson, P. Neuvial and T.P. Speed, \emph{TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays}, BMC Bioinformatics, 2010 \cr } \seealso{ To segment paired tumor-normal total copy numbers and allele B fractions, see \code{\link{segmentByPairedPSCBS}}(). To segment total copy numbers, or any other unimodal signals, see \code{\link{segmentByCBS}}(). } \keyword{IO} PSCBS/man/pruneByHClust.AbstractCBS.Rd 0000644 0001762 0000144 00000003031 14564060312 017025 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.HCLUST.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{pruneByHClust.AbstractCBS} \alias{pruneByHClust.AbstractCBS} \alias{AbstractCBS.pruneByHClust} \alias{pruneByHClust,AbstractCBS-method} \title{Prunes the CN profile by pruning and merging through hierarchical clustering} \description{ Prunes the CN profile by pruning and merging through hierarchical clustering. } \usage{ \method{pruneByHClust}{AbstractCBS}(fit, ..., size=NULL, distMethod="euclidean", hclustMethod="ward.D", merge=TRUE, update=TRUE, verbose=FALSE) } \arguments{ \item{...}{Arguments passed to \code{\link[stats]{cutree}}, particularly either of thresholds \code{h} or \code{k}.} \item{size, distMethod, hclustMethod}{Arguments (as well as some of \code{...}) passed to \code{\link[PSCBS:hclustCNs.AbstractCBS]{*hclustCNs}()}.} \item{merge}{If \code{\link[base:logical]{TRUE}}, consecutive segments that belong to the same PSCN cluster will be merged into one large segment.} \item{update}{If \code{\link[base:logical]{TRUE}}, segment means are updated afterwards, otherwise not.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns a pruned object of the same class. } \examples{\dontrun{ fitP <- pruneByHClust(fit, h=0.25) }} \author{Henrik Bengtsson} \keyword{internal} \keyword{methods} PSCBS/man/extractTCNAndDHs.PairedPSCBS.Rd 0000644 0001762 0000144 00000001704 14564060314 017232 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.EXTS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{extractTCNAndDHs.PairedPSCBS} \alias{extractTCNAndDHs.PairedPSCBS} \alias{PairedPSCBS.extractTCNAndDHs} \alias{extractTCNAndDHs,PairedPSCBS-method} \title{Extract TCN and DH mean levels per segment} \description{ Extract TCN and DH mean levels per segment. } \usage{ \method{extractTCNAndDHs}{PairedPSCBS}(fit, ...) } \arguments{ \item{...}{Arguments passed to \code{getSegments()}.} } \value{ Returns a \code{\link[base]{data.frame}}. } \author{Henrik Bengtsson} \seealso{ \code{\link[PSCBS:extractMinorMajorCNs.PairedPSCBS]{*extractMinorMajorCNs}()}. For more information see \code{\link{PairedPSCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/callGainsAndLosses.CBS.Rd 0000644 0001762 0000144 00000005637 14564060313 016322 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.CALL.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{callGainsAndLosses.CBS} \alias{callGainsAndLosses.CBS} \alias{CBS.callGainsAndLosses} \alias{callGainsAndLosses,CBS-method} \title{Calls gains and losses} \description{ Calls gains and losses. } \usage{ \method{callGainsAndLosses}{CBS}(fit, adjust=1, method=c("ucsf-mad", "ucsf-dmad"), ..., verbose=FALSE) } \arguments{ \item{adjust}{A positive scale factor adjusting the sensitivity of the caller, where a value less (greater) than 1.0 makes the caller less (more) sensitive.} \item{method}{A \code{\link[base]{character}} string specifying the calling algorithm to use.} \item{...}{Additional/optional arguments used to override the default parameters used by the caller.} } \value{ Returns a \code{\link[PSCBS]{CBS}} object where \code{\link[base]{logical}} columns 'lossCall' and 'gainCall' have been appended to the segmentation table. } \section{The UCSF caller}{ If \code{method == "ucsf-mad"}, then segments are called using [1], i.e. a segment is called gained or lost if its segment level is at least two standard deviations away from the median segment level on Chr1-22, where standard deviation is estimated using MAD. Then same is done for \code{method == "ucsf-dmad"} with the difference that the standard deviation is estimated using a robust first order variance estimator. } \examples{ # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Simulating copy-number data # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - set.seed(0xBEEF) # Number of loci J <- 1000 mu <- double(J) mu[200:300] <- mu[200:300] + 1 mu[350:400] <- NA # centromere mu[650:800] <- mu[650:800] - 1 eps <- rnorm(J, sd=1/2) y <- mu + eps x <- sort(runif(length(y), max=length(y))) * 1e5 w <- runif(J) w[650:800] <- 0.001 # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Segmentation # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fit <- segmentByCBS(y, x=x) print(fit) plotTracks(fit) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # CALLS # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Call gains and losses by segments fitC <- callGainsAndLosses(fit) # Call amplifications by segments fitC <- callAmplifications(fitC) # Call outliers by loci fitC <- callOutliers(fitC) } \author{Henrik Bengtsson} \references{ [1] Fridlyand et al. \emph{Breast tumor copy number aberration phenotypes and genomic instability}, BMC Cancer, 2006. \cr } \seealso{ \code{\link[PSCBS:callAmplifications.CBS]{*callAmplifications}()}. \code{\link[PSCBS:callOutliers.CBS]{*callOutliers}()}. For more information see \code{\link{CBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/PSCBS-package.Rd 0000644 0001762 0000144 00000005170 14564060312 014435 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % 999.package.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{PSCBS-package} \alias{PSCBS-package} \docType{package} \title{Package PSCBS} \description{ Segmentation of allele-specific DNA copy number data and detection of regions with abnormal copy number within each parental chromosome. Both tumor-normal paired and tumor-only analyses are supported.. This package should be considered to be in an alpha or beta phase. You should expect the API to be changing over time. } \section{Installation and updates}{ To install this package, use \code{install.packages("PSCBS")}. } \section{To get started}{ To get started, see: \enumerate{ \item Vignettes '\href{../doc/index.html}{Parent-specific copy-number segmentation using Paired PSCBS}' and '\href{../doc/index.html}{Total copy-number segmentation using CBS}'. \item \code{\link{segmentByCBS}}() - segments total copy-numbers, or any other unimodal genomic signals, using the CBS method [3,4]. \item \code{\link{segmentByPairedPSCBS}}() - segments allele-specific tumor signal from a tumor \emph{with} a matched normal using the Paired PSCBS method [1,2]. \item \code{\link{segmentByNonPairedPSCBS}}() - segments allele-specific tumor signal from a tumor \emph{without} a matched normal using the Non-Paired PSCBS method adopted from [1,2]. } } \section{How to cite}{ Please use [1] and [2] to cite when using Paired PSCBS, and [3] and [4] when using CBS. When using Non-Paired PSCBS, please cite [1] and [2] as well. } \author{Henrik Bengtsson} \section{License}{ GPL (>= 2). } \references{ [1] A.B. Olshen, H. Bengtsson, P. Neuvial, P.T. Spellman, R.A. Olshen, V.E. Seshan, \emph{Parent-specific copy number in paired tumor-normal studies using circular binary segmentation}, Bioinformatics, 2011 \cr [2] H. Bengtsson, P. Neuvial and T.P. Speed, \emph{TumorBoost: Normalization of allele-specific tumor copy numbers from a single pair of tumor-normal genotyping microarrays}, BMC Bioinformatics, 2010 \cr [3] A.B. Olshen, E.S. Venkatraman (aka Venkatraman E. Seshan), R. Lucito and M. Wigler, \emph{Circular binary segmentation for the analysis of array-based DNA copy number data}, Biostatistics, 2004 \cr [4] E.S. Venkatraman and A.B. Olshen, \emph{A faster circular binary segmentation algorithm for the analysis of array CGH data}, Bioinformatics, 2007 \cr } \keyword{package} PSCBS/man/extractMinorMajorCNs.PairedPSCBS.Rd 0000644 0001762 0000144 00000002071 14564060314 020243 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.EXTS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{extractMinorMajorCNs.PairedPSCBS} \alias{extractMinorMajorCNs.PairedPSCBS} \alias{PairedPSCBS.extractMinorMajorCNs} \alias{extractMinorMajorCNs,PairedPSCBS-method} \alias{PairedPSCBS.extractC1C2} \alias{extractC1C2.PairedPSCBS} \alias{extractC1C2,PairedPSCBS-method} \title{Extract minor and major copy-number mean levels per segment} \description{ Extract minor and major copy-number mean levels per segment. } \usage{ \method{extractMinorMajorCNs}{PairedPSCBS}(fit, ...) } \arguments{ \item{...}{Not used.} } \value{ Returns a \code{\link[base]{data.frame}}. } \author{Henrik Bengtsson} \seealso{ \code{\link[PSCBS:extractTCNAndDHs.PairedPSCBS]{*extractTCNAndDHs}()} For more information see \code{\link{PairedPSCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/estimateKappaByC1Density.PairedPSCBS.Rd 0000644 0001762 0000144 00000006361 14564060314 021004 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.estimateKappa.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{estimateKappaByC1Density.PairedPSCBS} \alias{estimateKappaByC1Density.PairedPSCBS} \alias{PairedPSCBS.estimateKappaByC1Density} \alias{estimateKappaByC1Density,PairedPSCBS-method} \title{Estimate global background in segmented copy numbers} \description{ Estimate global background in segmented copy numbers based on the location of peaks in a weighted density estimator of the minor copy number mean levels. The global background, here called \eqn{\kappa}, may have multiple origins where normal contamination is one, but not necessarily the only one. \emph{Assumptions:} This estimator assumes that there are segments with C1=0 and C1=1, i.e. some deletions and, typically, some normal segements. } \usage{ \method{estimateKappaByC1Density}{PairedPSCBS}(this, typeOfWeights=c("dhNbrOfLoci", "sqrt(dhNbrOfLoci)"), adjust=1, from=0, minDensity=0.2, ..., verbose=FALSE) } \arguments{ \item{typeOfWeights}{A \code{\link[base]{character}} string specifying how weights are calculated.} \item{adjust}{A \code{\link[base]{numeric}} scale factor specifying the size of the bandwidth parameter used by the density estimator.} \item{from}{A \code{\link[base]{numeric}} scalar specifying the lower bound for the support of the estimated density.} \item{minDensity}{A non-negative \code{\link[base]{numeric}} threshold specifying the minimum density a peak should have in order to consider it a peak.} \item{...}{Not used.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns the background estimate as a \code{\link[base]{numeric}} scalar. } \section{Algorithm}{ \itemize{ \item Retrieve segment-level minor copy numbers and corresponding weights: \enumerate{ \item Grabs the segment-level C1 estimates. \item Calculate segment weights. The default (\code{typeOfWeights="dhNbrOfLoci"}) is to use weights proportional to the number of heterozygous SNPs. An alternative (\code{typeOfWeights="sqrt(dhNbrOfLoci)"}) is to use the square root of those counts. } \item Identify subset of regions with C1=0: \enumerate{ \item Estimates the weighted empirical density function (truncated at zero below). Tuning parameter 'adjust'. \item Find the first two peaks (with a density greater than tuning parameter 'minDensity'). \item Assumes that the two peaks corresponds to C1=0 and C1=1. \item Defines threshold Delta0.5 as the center location between these two peaks. } \item Estimate the global background signal: \enumerate{ \item For all segments with C1 < Delta0.5, calculate the weighted median of their C1:s. \item Let kappa be the above weighted median. This is the estimated background. } } } \author{Henrik Bengtsson} \seealso{ Instead of calling this method explicitly, it is recommended to use the \code{\link[PSCBS:estimateKappa.PairedPSCBS]{*estimateKappa}()} method. } \keyword{internal} \keyword{methods} PSCBS/man/getFractionOfGenomeLost.CBS.Rd 0000644 0001762 0000144 00000003204 14564060313 017324 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.CALL.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{getFractionOfGenomeLost.CBS} \alias{getFractionOfGenomeLost.CBS} \alias{CBS.getFractionOfGenomeLost} \alias{getFractionOfGenomeLost,CBS-method} \alias{CBS.getFractionOfGenomeGained} \alias{getFractionOfGenomeGained.CBS} \alias{getFractionOfGenomeGained,CBS-method} \alias{CBS.getFractionOfGenomeAltered} \alias{getFractionOfGenomeAltered.CBS} \alias{getFractionOfGenomeAltered,CBS-method} \alias{CBS.getFGL} \alias{getFGL.CBS} \alias{getFGL,CBS-method} \alias{CBS.getFGG} \alias{getFGG.CBS} \alias{getFGG,CBS-method} \alias{CBS.getFGA} \alias{getFGA.CBS} \alias{getFGA,CBS-method} \title{Calculates the fraction of the genome lost, gained, or aberrant either way} \description{ Calculates the fraction of the genome lost, gained, or aberrant either way (in sense of total copy numbers), using definitions closely related to those presented in [1]. } \usage{ \method{getFractionOfGenomeLost}{CBS}(fit, ...) } \arguments{ \item{...}{Not used.} } \value{ Returns a \code{\link[base]{double}} in [0,1]. } \author{Henrik Bengtsson} \references{ [1] Fridlyand et al. \emph{Breast tumor copy number aberration phenotypes and genomic instability}, BMC Cancer, 2006. \cr } \seealso{ Internally, \code{\link[PSCBS:getCallStatistics.CBS]{*getCallStatistics}()} is used. For more information see \code{\link{CBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/nbrOfSegments.AbstractCBS.Rd 0000644 0001762 0000144 00000002024 14564060313 017034 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{nbrOfSegments.AbstractCBS} \alias{nbrOfSegments.AbstractCBS} \alias{AbstractCBS.nbrOfSegments} \alias{nbrOfSegments,AbstractCBS-method} \title{Gets the number of segments} \description{ Gets the number of segments. } \usage{ \method{nbrOfSegments}{AbstractCBS}(this, splitters=FALSE, ...) } \arguments{ \item{splitters, ...}{Arguments passed to \code{\link[PSCBS:getSegments.AbstractCBS]{*getSegments}()}.} } \value{ Returns an \code{\link[base]{integer}}. } \author{Henrik Bengtsson} \seealso{ \code{\link[PSCBS:nbrOfChangePoints.AbstractCBS]{*nbrOfChangePoints}()} \code{\link[PSCBS:nbrOfChromosomes.AbstractCBS]{*nbrOfChromosomes}()} For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/mergeTwoSegments.PairedPSCBS.Rd 0000644 0001762 0000144 00000002366 14564060314 017475 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.RESTRUCT.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{mergeTwoSegments.PairedPSCBS} \alias{mergeTwoSegments.PairedPSCBS} \alias{PairedPSCBS.mergeTwoSegments} \alias{mergeTwoSegments,PairedPSCBS-method} \title{Merge two neighboring segments} \description{ Merge two neighboring segments by recalculating segment statistics. } \usage{ \method{mergeTwoSegments}{PairedPSCBS}(this, left, update=TRUE, verbose=FALSE, ...) } \arguments{ \item{left}{An \code{\link[base]{integer}} specifying the segments (left, left+1) to be merged.} \item{update}{If \code{\link[base:logical]{TRUE}}, segment statistics are updated.} \item{verbose}{A \code{\link[base]{logical}} or a \code{\link[R.utils]{Verbose}} object.} \item{...}{Not used.} } \value{ Returns a \code{\link{PairedPSCBS}} with one less segment. } \author{Henrik Bengtsson} \seealso{ To drop regions (a connected set of segments) see \code{dropRegions()}. For more information see \code{\link{PairedPSCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/segmentByCBS.Rd 0000644 0001762 0000144 00000021767 14564060314 014473 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % segmentByCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{segmentByCBS} \alias{segmentByCBS.default} \alias{segmentByCBS} \alias{segmentByCBS.data.frame} \alias{segmentByCBS.CBS} \alias{segmentByCBS.CNA} \alias{segmentByCBS} \title{Segment genomic signals using the CBS method} \description{ Segment genomic signals using the CBS method of the \pkg{DNAcopy} package. This is a convenient low-level wrapper for the \code{DNAcopy::segment()} method. It is intended to be applied to a sample at the time. For more details on the Circular Binary Segmentation (CBS) method see [1,2]. } \usage{ \method{segmentByCBS}{default}(y, chromosome=0L, x=NULL, index=seq_along(y), w=NULL, undo=0, avg=c("mean", "median"), ..., joinSegments=TRUE, knownSegments=NULL, seed=NULL, verbose=FALSE) } \arguments{ \item{y}{A \code{\link[base]{numeric}} \code{\link[base]{vector}} of J genomic signals to be segmented.} \item{chromosome}{Optional \code{\link[base]{numeric}} \code{\link[base]{vector}} of length J, specifying the chromosome of each loci. If a scalar, it is expanded to a vector of length J.} \item{x}{Optional \code{\link[base]{numeric}} \code{\link[base]{vector}} of J genomic locations. If \code{\link[base]{NULL}}, index locations \code{1:J} are used.} \item{index}{An optional \code{\link[base]{integer}} \code{\link[base]{vector}} of length J specifying the genomewide indices of the loci.} \item{w}{Optional \code{\link[base]{numeric}} \code{\link[base]{vector}} in [0,1] of J weights.} \item{undo}{A non-negative \code{\link[base]{numeric}}. If greater than zero, then arguments \code{undo.splits="sdundo"} and \code{undo.SD=undo} are passed to \code{DNAcopy::segment()}. In the special case when \code{undo} is +\code{\link[base:is.finite]{Inf}}, the segmentation result will not contain any changepoints (in addition to what is specified by argument \code{knownSegments}).} \item{avg}{A \code{\link[base]{character}} string specifying how to calculating segment mean levels \emph{after} change points have been identified.} \item{...}{Additional arguments passed to the \code{DNAcopy::segment()} segmentation function.} \item{joinSegments}{If \code{\link[base:logical]{TRUE}}, there are no gaps between neighboring segments. If \code{\link[base:logical]{FALSE}}, the boundaries of a segment are defined by the support that the loci in the segments provides, i.e. there exist a locus at each end point of each segment. This also means that there is a gap between any neighboring segments, unless the change point is in the middle of multiple loci with the same position. The latter is what \code{DNAcopy::segment()} returns. } \item{knownSegments}{Optional \code{\link[base]{data.frame}} specifying \emph{non-overlapping} known segments. These segments must not share loci. See \code{\link{findLargeGaps}}() and \code{\link{gapsToSegments}}().} \item{seed}{An (optional) \code{\link[base]{integer}} specifying the random seed to be set before calling the segmentation method. The random seed is set to its original state when exiting. If \code{\link[base]{NULL}}, it is not set.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns a \code{\link{CBS}} object. } \details{ Internally \code{\link[DNAcopy]{segment}} of \pkg{DNAcopy} is used to segment the signals. This segmentation method support weighted segmentation. } \section{Reproducibility}{ The \code{DNAcopy::segment()} implementation of CBS uses approximation through random sampling for some estimates. Because of this, repeated calls using the same signals may result in slightly different results, unless the random seed is set/fixed. } \section{Missing and non-finite values}{ Signals may contain missing values (\code{\link[base]{NA}} or \code{\link[base:is.finite]{NaN}}), but not infinite values (+/-\code{\link[base:is.finite]{Inf}}). Loci with missing-value signals are preserved and keep in the result. Likewise, genomic positions may contain missing values. However, if they do, such loci are silently excluded before performing the segmentation, and are not kept in the results. The mapping between the input locus-level data and ditto of the result can be inferred from the \code{index} column of the locus-level data of the result. None of the input data may have infinite values, i.e. -\code{\link[base:is.finite]{Inf}} or +\code{\link[base:is.finite]{Inf}}. If so, an informative error is thrown. } \examples{ # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Simulating copy-number data # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - set.seed(0xBEEF) # Number of loci J <- 1000 mu <- double(J) mu[200:300] <- mu[200:300] + 1 mu[350:400] <- NA # centromere mu[650:800] <- mu[650:800] - 1 eps <- rnorm(J, sd=1/2) y <- mu + eps x <- sort(runif(length(y), max=length(y))) * 1e5 w <- runif(J) w[650:800] <- 0.001 # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Segmentation # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fit <- segmentByCBS(y, x=x) print(fit) plotTracks(fit) xlab <- "Position (Mb)" ylim <- c(-3,3) xMb <- x/1e6 plot(xMb,y, pch=20, col="#aaaaaa", xlab=xlab, ylim=ylim) drawLevels(fit, col="red", lwd=2, xScale=1e-6) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # TESTS # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fit <- segmentByCBS(y, x=x, seed=0xBEEF) print(fit) ## id chromosome start end nbrOfLoci mean ## 1 y 0 55167.82 20774251 201 0.0164 ## 2 y 0 20774250.85 29320105 99 1.0474 ## 3 y 0 29320104.86 65874675 349 -0.0227 ## 4 y 0 65874675.06 81348129 151 -1.0813 ## 5 y 0 81348129.20 99910827 200 -0.0612 # Test #1: Reverse the ordering and segment fitR <- segmentByCBS(rev(y), x=rev(x), seed=0xBEEF) # Sanity check stopifnot(all.equal(getSegments(fitR), getSegments(fit))) # Sanity check stopifnot(all.equal(rev(getLocusData(fitR)$index), getLocusData(fit)$index)) # Test #2: Reverse, but preserve ordering of 'data' object fitRP <- segmentByCBS(rev(y), x=rev(x), preserveOrder=TRUE) stopifnot(all.equal(getSegments(fitRP), getSegments(fit))) # (Test #3: Change points inbetween data points at the same locus) x[650:654] <- x[649] fitC <- segmentByCBS(rev(y), x=rev(x), preserveOrder=TRUE, seed=0xBEEF) # Test #4: Allow for some missing values in signals y[450] <- NA fitD <- segmentByCBS(y, x=x, seed=0xBEEF) # Test #5: Allow for some missing genomic annotations x[495] <- NA fitE <- segmentByCBS(y, x=x, seed=0xBEEF) # Test #6: Undo all change points found fitF <- segmentByCBS(y, x=x, undo=Inf, seed=0xBEEF) print(fitF) stopifnot(nbrOfSegments(fitF) == 1L) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # MISC. # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Emulate a centromere x[650:699] <- NA fit <- segmentByCBS(y, x=x, seed=0xBEEF) xMb <- x/1e6 plot(xMb,y, pch=20, col="#aaaaaa", xlab=xlab, ylim=ylim) drawLevels(fit, col="red", lwd=2, xScale=1e-6) fitC <- segmentByCBS(y, x=x, joinSegments=FALSE, seed=0xBEEF) drawLevels(fitC, col="blue", lwd=2, xScale=1e-6) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Multiple chromosomes # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Appending CBS results fit1 <- segmentByCBS(y, chromosome=1, x=x) fit2 <- segmentByCBS(y, chromosome=2, x=x) fit <- c(fit1, fit2) print(fit) plotTracks(fit, subset=NULL, lwd=2, Clim=c(-3,3)) # Segmenting multiple chromosomes at once chromosomeWG <- rep(1:2, each=J) xWG <- rep(x, times=2) yWG <- rep(y, times=2) fitWG <- segmentByCBS(yWG, chromosome=chromosomeWG, x=xWG) print(fitWG) plotTracks(fitWG, subset=NULL, lwd=2, Clim=c(-3,3)) # Assert same results fit$data[,"index"] <- getLocusData(fitWG)[,"index"] # Ignore 'index' stopifnot(all.equal(getLocusData(fitWG), getLocusData(fit))) stopifnot(all.equal(getSegments(fitWG), getSegments(fit))) } \author{Henrik Bengtsson} \references{ [1] A.B. Olshen, E.S. Venkatraman (aka Venkatraman E. Seshan), R. Lucito and M. Wigler, \emph{Circular binary segmentation for the analysis of array-based DNA copy number data}, Biostatistics, 2004 \cr [2] E.S. Venkatraman and A.B. Olshen, \emph{A faster circular binary segmentation algorithm for the analysis of array CGH data}, Bioinformatics, 2007 \cr } \seealso{ To segment allele-specific tumor copy-number signals from a tumor \emph{with} a matched normal, see \code{\link{segmentByPairedPSCBS}}(). For the same \emph{without} a matched normal, see \code{\link{segmentByNonPairedPSCBS}}(). It is also possible to prune change points after segmentation (with identical results) using \code{\link[PSCBS:pruneBySdUndo.CBS]{pruneBySdUndo}()}. } \keyword{IO} PSCBS/man/report.AbstractCBS.Rd 0000644 0001762 0000144 00000003143 14564060313 015576 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.REPORT.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{report.AbstractCBS} \alias{report.AbstractCBS} \alias{AbstractCBS.report} \alias{report,AbstractCBS-method} \title{Generates a report of the segmentation results} \description{ Generates a report of the segmentation results. Currently reports can be generated for segmentation results of class \code{\link{CBS}} and \code{\link{PairedPSCBS}}. } \usage{ \method{report}{AbstractCBS}(fit, sampleName=getSampleName(fit), studyName, ..., rspTags=NULL, rootPath="reports/", .filename="*", skip=TRUE, envir=new.env(), verbose=FALSE) } \arguments{ \item{fit}{An \code{\link{AbstractCBS}} object.} \item{sampleName}{A \code{\link[base]{character}} string specifying the name of the sample segmented.} \item{studyName}{A \code{\link[base]{character}} string specifying the name of study/project.} \item{...}{Optional arguments passed to the RSP template.} \item{rspTags}{Optional \code{\link[base]{character}} \code{\link[base]{vector}} of tags for further specifying which RSP report to generate.} \item{rootPath}{The root directory where to write the report.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns the pathname of the generated PDF. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/writeSegments.CBS.Rd 0000644 0001762 0000144 00000003074 14564060313 015442 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.IO.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{writeSegments.CBS} \alias{writeSegments.CBS} \alias{CBS.writeSegments} \alias{writeSegments,CBS-method} \alias{writeWIG} \alias{writeWIG.AbstractCBS} \title{Writes the table of segments to file} \description{ Writes the table of segments to file. } \usage{ \method{writeSegments}{CBS}(fit, name=getSampleName(fit), tags=NULL, ext="tsv", path=NULL, addHeader=TRUE, createdBy=NULL, sep="\t", nbrOfDecimals=4L, splitters=FALSE, overwrite=FALSE, skip=FALSE, ...) } \arguments{ \item{name, tags}{Name and optional tags part of the filename}. \item{path}{The directory where the file will be written.} \item{addHeader}{If \code{\link[base:logical]{TRUE}}, header comments are written.} \item{createdBy}{A header comment of whom created the file.} \item{splitters}{If \code{\link[base:logical]{TRUE}}, each chromosome is separated by a row of missing values.} \item{overwrite, skip}{If an output file already exists, these arguments specifies what should happen.} \item{...}{Additional arguments pass to \code{getSegments()}.} } \value{ Returns the pathname of the the file written. } \author{Henrik Bengtsson} \seealso{ Utilizes \code{\link[PSCBS:getSegments.CBS]{*getSegments}()}. For more information see \code{\link{CBS}}.. } \keyword{internal} \keyword{methods} PSCBS/man/callSegmentationOutliers.Rd 0000644 0001762 0000144 00000004712 14564060314 017215 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % callSegmentationOutliers.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{callSegmentationOutliers} \alias{callSegmentationOutliers} \alias{callSegmentationOutliers.default} \alias{callSegmentationOutliers.data.frame} \alias{dropSegmentationOutliers} \alias{dropSegmentationOutliers.default} \alias{dropSegmentationOutliers.data.frame} \title{Calls/drops single-locus outliers along the genome} \description{ Calls/drops single-locus outliers along the genome that have a signal that differ significantly from the neighboring loci. } \usage{ \method{callSegmentationOutliers}{default}(y, chromosome=0, x=NULL, method="DNAcopy::smooth.CNA", ..., verbose=FALSE) \method{callSegmentationOutliers}{data.frame}(y, ...) \method{dropSegmentationOutliers}{default}(y, ...) \method{dropSegmentationOutliers}{data.frame}(y, ...) } \arguments{ \item{y}{A \code{\link[base]{numeric}} \code{\link[base]{vector}} of J genomic signals to be segmented.} \item{chromosome}{(Optional) An \code{\link[base]{integer}} scalar (or a \code{\link[base]{vector}} of length J contain a unique value). Only used for annotation purposes.} \item{x}{Optional \code{\link[base]{numeric}} \code{\link[base]{vector}} of J genomic locations. If \code{\link[base]{NULL}}, index locations \code{1:J} are used.} \item{method}{A \code{\link[base]{character}} string specifying the method used for calling outliers.} \item{...}{Additional arguments passed to internal outlier detection method.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ \code{callSegmentationOutliers()} returns a \code{\link[base]{logical}} \code{\link[base]{vector}} of length J. \code{dropSegmentationOutliers()} returns an object of the same type as argument \code{y}, where the signals for which outliers were called have been set to \code{\link[base]{NA}}. } \section{Missing and non-finite values}{ Signals as well as genomic positions may contain missing values, i.e. \code{\link[base]{NA}}s or \code{\link[base:is.finite]{NaN}}s. By definition, these cannot be outliers. } \author{Henrik Bengtsson} \seealso{ Internally \code{\link[DNAcopy]{smooth.CNA}} is utilized to identify the outliers. } \keyword{methods} \keyword{IO} PSCBS/man/exampleData.Rd 0000644 0001762 0000144 00000001400 14564060314 014411 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % exampleData.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{exampleData} \alias{exampleData.default} \alias{exampleData} \title{Gets an example data set} \description{ Gets an example data set. } \usage{ \method{exampleData}{default}(name=c("paired.chr01"), ...) } \arguments{ \item{name}{A \code{\link[base]{character}} string specifying the name of the data set.} \item{...}{Not used.} } \value{ Returns \code{\link[base]{data.frame}}. } \author{Henrik Bengtsson} \keyword{IO} \keyword{data} \keyword{internal} PSCBS/man/callAB.PairedPSCBS.Rd 0000644 0001762 0000144 00000005203 14564060314 015305 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.callAB.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{callAB.PairedPSCBS} \alias{callAB.PairedPSCBS} \alias{PairedPSCBS.callAB} \alias{callAB,PairedPSCBS-method} \alias{PairedPSCBS.callAllelicBalance} \alias{callAllelicBalance.PairedPSCBS} \alias{callAllelicBalance,PairedPSCBS-method} \title{Calls segments that are in allelic balance} \description{ Calls segments that are in allelic balance, i.e. that have equal minor and major copy numbers. } \usage{ \method{callAB}{PairedPSCBS}(fit, flavor=c("DeltaAB*"), ..., minSize=1, xorCalls=TRUE, force=FALSE) } \arguments{ \item{flavor}{A \code{\link[base]{character}} string specifying which type of call to use.} \item{...}{Additional arguments passed to the caller.} \item{minSize}{An optional \code{\link[base]{integer}} specifying the minimum number of data points in order to call a segments. If fewer data points, then the call is set to \code{\link[base]{NA}} regardless.} \item{xorCalls}{If \code{\link[base:logical]{TRUE}}, a region already called LOH, will for consistency never be called AB, resulting in either an AB call set to \code{\link[base:logical]{FALSE}} or \code{\link[base]{NA}} (as explained below).} \item{force}{If \code{\link[base:logical]{FALSE}}, and allelic-balance calls already exits, then nothing is done, otherwise the calls are done.} } \value{ Returns a \code{\link{PairedPSCBS}} object with allelic-balance calls. } \section{AB and LOH consistency}{ Biologically, a segment can not be both in allelic balance (AB) and in loss-of-heterozygosity (LOH) at the same time. To avoid reporting such inconsistencies, the LOH caller will, if argument \code{xorCalls=TRUE}, never report a segment to be in LOH if it is already called to be in AB. However, regardless of of the AB call, a segment is still always tested for LOH, to check weather the LOH caller is consistent with the AB caller or not. Thus, in order to distinguish the case where the AB caller and LOH caller agree from when they disagree, we report either (AB,LOH)=(TRUE,FALSE) or (TRUE,NA). The former is reported when they are consistent, and the latter when they are not, or when the AB caller could not call it. } \author{Henrik Bengtsson} \seealso{ Internally, one of the following methods are used: \code{\link[PSCBS:callAllelicBalanceByDH.PairedPSCBS]{*callAllelicBalanceByDH}()}. } \keyword{internal} \keyword{methods} PSCBS/man/CBS.Rd 0000644 0001762 0000144 00000005401 14564060313 012577 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{CBS} \docType{class} \alias{CBS} \title{The CBS class} \description{ A CBS object holds results from the Circular Binary Segmentation (CBS) method for \emph{one} sample for one or more chromosomes. Package: PSCBS \cr \bold{Class CBS}\cr \code{list}\cr \code{~~|}\cr \code{~~+--}\code{\link[PSCBS]{AbstractCBS}}\cr \code{~~~~~~~|}\cr \code{~~~~~~~+--}\emph{\code{CBS}}\cr \bold{Directly known subclasses:}\cr \cr public abstract class \bold{CBS}\cr extends \emph{\link[PSCBS]{AbstractCBS}}\cr } \usage{ CBS(...) } \arguments{ \item{...}{Arguments passed to the constructor of \code{\link{AbstractCBS}}.} } \section{Fields and Methods}{ \bold{Methods:}\cr \tabular{rll}{ \tab \code{as} \tab -\cr \tab \code{c} \tab -\cr \tab \code{estimateStandardDeviation} \tab -\cr \tab \code{plotTracks} \tab -\cr \tab \code{pruneBySdUndo} \tab -\cr \tab \code{segmentByCBS} \tab -\cr \tab \code{seqOfSegmentsByDP} \tab -\cr \tab \code{writeSegments} \tab -\cr } \bold{Methods inherited from AbstractCBS}:\cr adjustPloidyScale, all.equal, as.data.frame, clearCalls, drawChangePoints, drawKnownSegments, dropChangePoint, dropChangePoints, dropRegion, dropRegions, extractCNs, extractChromosome, extractChromosomes, extractRegions, extractSegments, extractWIG, getChangePoints, getChromosomeOffsets, getChromosomeRanges, getChromosomes, getLocusData, getLocusSignalNames, getMeanEstimators, getSampleName, getSegmentSizes, getSegmentTrackPrefixes, getSegments, mergeThreeSegments, mergeTwoSegments, nbrOfChangePoints, nbrOfChromosomes, nbrOfLoci, nbrOfSegments, normalizeTotalCNs, ploidy, ploidy<-, plotTracks, print, pruneByDP, pruneByHClust, renameChromosomes, report, resegment, resetSegments, sampleCNs, sampleName, sampleName<-, seqOfSegmentsByDP, setLocusData, setMeanEstimators, setPloidy, setSampleName, setSegments, shiftTCN, tileChromosomes, updateMeans, writeWIG \bold{Methods inherited from list}:\cr Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, all.equal, as.data.frame, attachLocally, callHooks, coerce,ANY,list-method, relist, type.convert, within } \section{Difference to DNAcopy object}{ A CBS object is similar to DNAcopy objects with the major difference that a CBS object holds only one sample, whereas a DNAcopy object can hold more than one sample. } \section{See also}{ The \code{\link{segmentByCBS}}() method returns an object of this class. } \author{Henrik Bengtsson} \keyword{classes} PSCBS/man/estimateStandardDeviation.CBS.Rd 0000644 0001762 0000144 00000003130 14564060313 017732 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.EXTS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{estimateStandardDeviation.CBS} \alias{estimateStandardDeviation.CBS} \alias{CBS.estimateStandardDeviation} \alias{estimateStandardDeviation,CBS-method} \title{Estimates the whole-genome standard deviation of the signals} \description{ Estimates the whole-genome standard deviation of the signals. } \usage{ \method{estimateStandardDeviation}{CBS}(fit, chromosomes=NULL, method=c("diff", "res", "abs", "DNAcopy"), estimator=c("mad", "sd"), na.rm=TRUE, weights=NULL, ...) } \arguments{ \item{chromosomes}{An optional \code{\link[base]{vector}} specifying the subset of chromosomes used for the estimate. If \code{\link[base]{NULL}}, all chromosomes are used.} \item{method}{A \code{\link[base]{character}} string specifying the method used.} \item{estimator}{A \code{\link[base]{character}} string or a \code{\link[base]{function}} specifying the internal estimator.} \item{na.rm}{If \code{\link[base:logical]{TRUE}}, missing values are dropped, otherwise not.} \item{weights}{An optional \code{\link[base]{double}} \code{\link[base]{vector}} of \code{nbrOfLoci()} non-negative weights.} \item{...}{Not used.} } \value{ Returns a non-negative \code{\link[base]{numeric}} scale. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{CBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/normalizeTotalCNs.AbstractCBS.Rd 0000644 0001762 0000144 00000002050 14564060313 017667 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{normalizeTotalCNs.AbstractCBS} \alias{normalizeTotalCNs.AbstractCBS} \alias{AbstractCBS.normalizeTotalCNs} \alias{normalizeTotalCNs,AbstractCBS-method} \alias{normalizeTotalCNs} \alias{normalizeTotalCNs.PSCBS} \title{Normalizes copy numbers such that the whole-genome average total copy number is two} \description{ Normalizes copy numbers such that the whole-genome average total copy number is two. } \usage{ \method{normalizeTotalCNs}{AbstractCBS}(...) } \arguments{ \item{...}{Additional arguments passed to the normalization method.} } \value{ Returns a normalized AbstractCBS object of the same class as \code{fit}. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{AbstractCBS}}.. } \keyword{internal} \keyword{methods} PSCBS/man/getSegments.PSCBS.Rd 0000644 0001762 0000144 00000002111 14564060314 015322 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PSCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{getSegments.PSCBS} \alias{getSegments.PSCBS} \alias{PSCBS.getSegments} \alias{getSegments,PSCBS-method} \title{Gets the segments} \description{ Gets the segments. } \usage{ \method{getSegments}{PSCBS}(fit, simplify=FALSE, splitters=TRUE, addGaps=FALSE, ...) } \arguments{ \item{simplify}{If \code{\link[base:logical]{TRUE}}, redundant and intermediate information is dropped.}# \item{splitters}{If \code{\link[base:logical]{TRUE}}, "splitters" between chromosomes are preserved, otherwise dropped.} \item{...}{Not used.} } \value{ Returns a SxK \code{\link[base]{data.frame}}, where S in the number of segments, and K is the number of segment-specific fields. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{PSCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/as.data.frame.AbstractCBS.Rd 0000644 0001762 0000144 00000001627 14564060313 016674 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{as.data.frame.AbstractCBS} \alias{as.data.frame.AbstractCBS} \alias{AbstractCBS.as.data.frame} \alias{as.data.frame,AbstractCBS-method} \title{Gets the table of segments} \description{ Gets the table of segments. } \usage{ \method{as.data.frame}{AbstractCBS}(x, ...) } \arguments{ \item{...}{Not used.} } \value{ Returns a \code{\link[base]{data.frame}}, where each row corresponds to a unique segment. } \author{Henrik Bengtsson} \seealso{ Utilizes \code{\link[PSCBS:getSegments.AbstractCBS]{*getSegments}()}. For more information see \code{\link{AbstractCBS}}.. } \keyword{internal} \keyword{methods} PSCBS/man/gapsToSegments.data.frame.Rd 0000644 0001762 0000144 00000003015 14564060314 017134 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % gapsToSegments.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{gapsToSegments.data.frame} \alias{gapsToSegments.data.frame} \alias{gapsToSegments} \title{Gets the genomic segments that are complementary to the gaps} \description{ Gets the genomic segments that are complementary to the gaps, with default chromosome boundaries being \code{-Inf} and \code{+Inf}. } \usage{ \method{gapsToSegments}{data.frame}(gaps, resolution=1L, minLength=0L, dropGaps=FALSE, ...) } \arguments{ \item{gaps}{A \code{\link[base]{data.frame}} with columns \code{chromosome}, \code{start}, and \code{stop}. Any overlapping gaps will throw an error.} \item{resolution}{A non-negative \code{\link[base]{numeric}} specifying the minimum length unit, which by default equals one nucleotide/base pair.} \item{minLength}{Minimum length of segments to be kept.} \item{dropGaps}{If \code{\link[base:logical]{TRUE}}, the gaps themselves are not part of the output.} \item{...}{Not used.} } \value{ Returns \code{\link[base]{data.frame}} of least one row with columns \code{chromosome} if that argument is given), \code{start}, \code{stop} and \code{length}. The segments are ordered along the genome. } \author{Henrik Bengtsson} \seealso{ \code{\link{findLargeGaps}}(). } \keyword{methods} \keyword{IO} PSCBS/man/weightedQuantile.Rd 0000644 0001762 0000144 00000003715 14564060314 015502 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % weightedQuantile.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{weightedQuantile} \alias{weightedQuantile.default} \alias{weightedQuantile} \title{Weighted Quantile Value} \usage{ \method{weightedQuantile}{default}(x, w, probs=c(0, 0.25, 0.5, 0.75, 1), na.rm=TRUE, method=c("wtd.quantile"), ...) } \description{ Computes a weighted quantile of a numeric vector. } \arguments{ \item{x}{a \code{\link[base]{numeric}} \code{\link[base]{vector}} containing the values whose weighted quantile is to be computed.} \item{w}{a numeric \code{\link[base]{vector}} of weights the same length as \code{x} giving the weights to use for each element of \code{x}. Negative weights are treated as zero weights. Default value is equal weight to all values.} \item{probs}{a \code{\link[base]{numeric}} \code{\link[base]{vector}} of quantiles in [0,1] to be retrieved.} \item{na.rm}{a \code{\link[base]{logical}} value indicating whether \code{\link[base]{NA}} values in \code{x} should be stripped before the computation proceeds, or not.} \item{method}{If \code{"wtd.quantile"}, then an internal copy of \code{Hmisc::wtd.quantile()} is used. No other methods are currently supported.} \item{...}{Additional arguments passed to the estimator.} } \value{ Returns the weighted quantile. } \author{Henrik Bengtsson} \seealso{ Internally the following functions may be used: \code{\link[stats]{quantile}} (if no weights are specified), or an internal copy of \code{Hmisc::wtd.quantile()}. For a weighted median estimator, \code{\link[matrixStats]{weightedMedian}} of the \pkg{matrixStats} package. } \keyword{univar} \keyword{robust} \keyword{internal} PSCBS/man/findNeutralCopyNumberState.Rd 0000644 0001762 0000144 00000003241 14564060314 017451 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % findNeutralCopyNumberState.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{findNeutralCopyNumberState} \alias{findNeutralCopyNumberState.default} \alias{findNeutralCopyNumberState} \title{Call segments to be copy neutral based on allelic imbalance calls and total copy number estimates} \description{ Call segments to be copy neutral based on allelic imbalance calls and total copy number estimates. } \usage{ \method{findNeutralCopyNumberState}{default}(C, isAI, weights=NULL, ..., minDensity=1e-10, flavor=c("firstPeak", "maxPeak"), verbose=FALSE) } \arguments{ \item{C}{A \code{\link[base]{numeric}} \code{\link[base]{vector}} of region-level total copy number estimates.} \item{isAI}{A \code{\link[base]{logical}} \code{\link[base]{vector}} of "allelic imbalance" calls.} \item{weights}{An optional \code{\link[base]{numeric}} \code{\link[base]{vector}} of non-negative weights.} \item{...}{Further arguments to be passed to the density estimation function.} \item{minDensity}{A \code{\link[base]{numeric}} value, below which density peaks are discarded.} \item{flavor}{A \code{\link[base]{character}} string specifying how to identify the mode of the AB segments.} \item{verbose}{If \code{\link[base:logical]{TRUE}}, extra information is output.} } \value{ A \code{\link[base]{logical}} \code{\link[base]{vector}} of "neutral copy number state" calls. } \author{Pierre Neuvial, Henrik Bengtsson} \keyword{internal} PSCBS/man/resetSegments.AbstractCBS.Rd 0000644 0001762 0000144 00000002123 14564060313 017110 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{resetSegments.AbstractCBS} \alias{resetSegments.AbstractCBS} \alias{AbstractCBS.resetSegments} \alias{resetSegments,AbstractCBS-method} \title{Reset the segments} \description{ Reset the segments. More precisely, it removes columns in the segmentation result table that have been added by methods after the actual segmentation method, e.g. bootstrap estimated mean level quantiles and various calls. It leave the basic segmentation results untouched, i.e. the partitioning and the segment means. } \usage{ \method{resetSegments}{AbstractCBS}(fit, ...) } \arguments{ \item{...}{Not used.} } \value{ Returns an object if the same class as the input result. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/callAllelicBalanceByDH.PairedPSCBS.Rd 0000644 0001762 0000144 00000003344 14564060314 020351 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.callAB.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{callAllelicBalanceByDH.PairedPSCBS} \alias{callAllelicBalanceByDH.PairedPSCBS} \alias{PairedPSCBS.callAllelicBalanceByDH} \alias{callAllelicBalanceByDH,PairedPSCBS-method} \title{Calls segments that are in allelic balance} \description{ Calls segments that are in allelic balance by thresholding on DH using a predetermined threshold. The variability of the DH mean levels is taken into account via a bootstrap estimator. } \usage{ \method{callAllelicBalanceByDH}{PairedPSCBS}(fit, delta=estimateDeltaAB(fit, flavor = "qq(DH)"), alpha=0.05, ..., verbose=FALSE) } \arguments{ \item{flavor}{A \code{\link[base]{character}} string specifying which type of call to use.} \item{delta}{(Tuning parameter) A non-negative \code{\link[base]{numeric}} threshold.} \item{alpha}{A \code{\link[base]{numeric}} in [0,1] specifying the upper and lower quantiles calculated by the bootstrap estimator.} \item{...}{Additional arguments passed to the bootstrap estimator \code{\link[PSCBS:bootstrapTCNandDHByRegion.PairedPSCBS]{*bootstrapTCNandDHByRegion}()}.} } \value{ Returns a \code{\link{PairedPSCBS}} object with allelic-balance calls. } \author{Henrik Bengtsson} \section{Algorithm}{ \itemize{ \item Foo \item Bar } } \seealso{ Instead of calling this method explicitly, it is recommended to use the \code{\link[PSCBS:callAllelicBalance.PairedPSCBS]{*callAllelicBalance}()} method. } \keyword{internal} \keyword{methods} PSCBS/man/nbrOfChromosomes.AbstractCBS.Rd 0000644 0001762 0000144 00000001706 14564060313 017553 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{nbrOfChromosomes.AbstractCBS} \alias{nbrOfChromosomes.AbstractCBS} \alias{AbstractCBS.nbrOfChromosomes} \alias{nbrOfChromosomes,AbstractCBS-method} \title{Gets the number of chromosomes} \description{ Gets the number of chromosomes. } \usage{ \method{nbrOfChromosomes}{AbstractCBS}(this, ...) } \arguments{ \item{...}{Arguments passed to \code{\link[PSCBS:getChromosomes.AbstractCBS]{*getChromosomes}()}.} } \value{ Returns an \code{\link[base]{integer}}. } \author{Henrik Bengtsson} \seealso{ \code{\link[PSCBS:getChromosomes.AbstractCBS]{*getChromosomes}()}. For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/installDNAcopy.Rd 0000644 0001762 0000144 00000002176 14564060314 015063 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % installDNAcopy.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{installDNAcopy} \alias{installDNAcopy.default} \alias{installDNAcopy} \title{Install the DNAcopy package} \usage{ \method{installDNAcopy}{default}(..., force=FALSE) } \description{ Install the DNAcopy package, if missing. } \arguments{ \item{...}{Arguments passed to the install function.} \item{force}{If \code{\link[base:logical]{FALSE}} and the \pkg{DNAcopy} package is already installed, then it will not be re-install. If \code{\link[base:logical]{TRUE}}, it will be installed.} } \value{ Returns nothing. } \details{ This function is will download and call the \code{biocLite()} installation function from the Bioconductor Project website. This function will also make sure that \pkg{DNAcopy} is loaded so that it is reported by \code{\link[utils]{sessionInfo}}. } \author{Henrik Bengtsson} \keyword{internal} PSCBS/man/mergeNonCalledSegments.CBS.Rd 0000644 0001762 0000144 00000001650 14564060313 017165 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.CALL.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{mergeNonCalledSegments.CBS} \alias{mergeNonCalledSegments.CBS} \alias{CBS.mergeNonCalledSegments} \alias{mergeNonCalledSegments,CBS-method} \title{Merge neighboring segments that are not called} \description{ Merge neighboring segments that are not called } \usage{ \method{mergeNonCalledSegments}{CBS}(fit, ..., verbose=FALSE) } \arguments{ \item{...}{Not used.} \item{verbose}{\code{\link[R.utils]{Verbose}}.} } \value{ Returns an object of the same class with the same of fewer number of segments. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{CBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/mergeThreeSegments.AbstractCBS.Rd 0000644 0001762 0000144 00000002400 14564060313 020053 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.RESTRUCT.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{mergeThreeSegments.AbstractCBS} \alias{mergeThreeSegments.AbstractCBS} \alias{AbstractCBS.mergeThreeSegments} \alias{mergeThreeSegments,AbstractCBS-method} \title{Merge a segment and its two flanking segments} \description{ Merge a segment and its two flanking segments into one segment, and recalculating the segment statistics. } \usage{ \method{mergeThreeSegments}{AbstractCBS}(fit, middle, ...) } \arguments{ \item{middle}{An \code{\link[base]{integer}} specifying the three segments (middle-1, middle, middle+1) to be merged.} \item{...}{Additional arguments passed to \code{\link[PSCBS:mergeTwoSegments.AbstractCBS]{*mergeTwoSegments}()}.} } \value{ Returns an \code{\link{AbstractCBS}} of the same class with two less segment. } \author{Henrik Bengtsson} \seealso{ Internally \code{\link[PSCBS:mergeTwoSegments.AbstractCBS]{*mergeTwoSegments}()} is used. For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/ploidy.AbstractCBS.Rd 0000644 0001762 0000144 00000002542 14564060313 015565 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{ploidy.AbstractCBS} \alias{ploidy.AbstractCBS} \alias{AbstractCBS.ploidy} \alias{ploidy,AbstractCBS-method} \alias{AbstractCBS.ploidy<-} \alias{ploidy<-.AbstractCBS} \alias{ploidy<-,AbstractCBS-method} \alias{AbstractCBS.setPloidy} \alias{setPloidy.AbstractCBS} \alias{setPloidy,AbstractCBS-method} \alias{AbstractCBS.adjustPloidyScale} \alias{adjustPloidyScale.AbstractCBS} \alias{adjustPloidyScale,AbstractCBS-method} \alias{adjustPloidyScale.PairedPSCBS} \alias{adjustPloidyScale} \alias{ploidy} \alias{ploidy<-} \alias{setPloidy} \title{Gets and sets ploidy} \description{ Gets and sets ploidy. } \usage{ \method{ploidy}{AbstractCBS}(fit, ...) \method{ploidy}{AbstractCBS}(fit) <- value } \arguments{ \item{fit}{An \code{\link{AbstractCBS}} object.} \item{value}{An \code{\link[base]{integer}} (in \eqn{1,2,\ldots}) specifying the genome ploidy .} \item{...}{Not used.} } \value{ Returns (invisibly) an updated object. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{AbstractCBS}}.. } \keyword{internal} \keyword{methods} PSCBS/man/hclustCNs.AbstractCBS.Rd 0000644 0001762 0000144 00000002357 14564060312 016176 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.HCLUST.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{hclustCNs.AbstractCBS} \alias{hclustCNs.AbstractCBS} \alias{AbstractCBS.hclustCNs} \alias{hclustCNs,AbstractCBS-method} \title{Performs a hierarchical clustering of the CN mean levels} \description{ Performs a hierarchical clustering of the CN mean levels. } \usage{ \method{hclustCNs}{AbstractCBS}(fit, size=NULL, distMethod="euclidean", hclustMethod="ward.D", ..., verbose=FALSE) } \arguments{ \item{size}{Argument passed to \code{\link[PSCBS:sampleCNs.AbstractCBS]{*sampleCNs}()}.} \item{distMethod, hclustMethod}{Argument \code{method} for \code{\link[stats]{dist}} and "stats::hclust", respectively.} \item{...}{Not used.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns a \code{hclust} object as returned by \code{\link[stats]{hclust}}. } \author{Henrik Bengtsson} \seealso{ This method is utilized by \code{\link[PSCBS:pruneByHClust.AbstractCBS]{*pruneByHClust}()}. } \keyword{internal} \keyword{methods} PSCBS/man/updateMeansTogether.AbstractCBS.Rd 0000644 0001762 0000144 00000002064 14564060312 020233 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.HCLUST.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{updateMeansTogether.AbstractCBS} \alias{updateMeansTogether.AbstractCBS} \alias{AbstractCBS.updateMeansTogether} \alias{updateMeansTogether,AbstractCBS-method} \alias{updateMeansTogether.CBS} \alias{updateMeansTogether.PairedPSCBS} \title{Updates the CN mean levels jointly in sets of segments} \description{ Updates the CN mean levels jointly in sets of segments as if they were one large segment. The locus-level data is not updated/modified. } \usage{ \method{updateMeansTogether}{AbstractCBS}(...) } \arguments{ \item{...}{Not used.} } \value{ Returns an object of the same class. } \author{Henrik Bengtsson} \seealso{ This method is utilized by \code{\link[PSCBS:pruneByHClust.AbstractCBS]{*pruneByHClust}()}. } \keyword{internal} \keyword{methods} PSCBS/man/AbstractCBS.Rd 0000644 0001762 0000144 00000004220 14564060313 014261 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{AbstractCBS} \docType{class} \alias{AbstractCBS} \title{The AbstractCBS class} \description{ Package: PSCBS \cr \bold{Class AbstractCBS}\cr \code{list}\cr \code{~~|}\cr \code{~~+--}\emph{\code{AbstractCBS}}\cr \bold{Directly known subclasses:}\cr \emph{\link[PSCBS]{CBS}}, \emph{\link[PSCBS]{NonPairedPSCBS}}, \emph{\link[PSCBS]{PSCBS}}, \emph{\link[PSCBS]{PairedPSCBS}}\cr public abstract class \bold{AbstractCBS}\cr extends list\cr All CBS-style segmentation results extend this class, e.g. \code{\link{CBS}} and \code{\link{PairedPSCBS}}. } \usage{ AbstractCBS(fit=list(), sampleName=fit$sampleName, ...) } \arguments{ \item{fit}{A \code{\link[base]{list}} structure containing the segmentation results.} \item{sampleName}{A \code{\link[base]{character}} string.} \item{...}{Not used.} } \section{Fields and Methods}{ \bold{Methods:}\cr \tabular{rll}{ \tab \code{adjustPloidyScale} \tab -\cr \tab \code{extractCNs} \tab -\cr \tab \code{getChangePoints} \tab -\cr \tab \code{getChromosomes} \tab -\cr \tab \code{getLocusData} \tab -\cr \tab \code{getSegmentSizes} \tab -\cr \tab \code{getSegments} \tab -\cr \tab \code{mergeThreeSegments} \tab -\cr \tab \code{nbrOfChangePoints} \tab -\cr \tab \code{nbrOfChromosomes} \tab -\cr \tab \code{nbrOfLoci} \tab -\cr \tab \code{nbrOfSegments} \tab -\cr \tab \code{normalizeTotalCNs} \tab -\cr \tab \code{ploidy} \tab -\cr \tab \code{ploidy<-} \tab -\cr \tab \code{plotTracks} \tab -\cr \tab \code{sampleCNs} \tab -\cr \tab \code{writeWIG} \tab -\cr } \bold{Methods inherited from list}:\cr Ops,nonStructure,vector-method, Ops,structure,vector-method, Ops,vector,nonStructure-method, Ops,vector,structure-method, all.equal, as.data.frame, attachLocally, callHooks, coerce,ANY,list-method, relist, type.convert, within } \author{Henrik Bengtsson} \keyword{classes} \keyword{internal} PSCBS/man/getCallStatistics.CBS.Rd 0000644 0001762 0000144 00000004441 14564060313 016227 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.CALL.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{getCallStatistics.CBS} \alias{getCallStatistics.CBS} \alias{CBS.getCallStatistics} \alias{getCallStatistics,CBS-method} \title{Calculates various call statistics per chromosome} \description{ Calculates various call statistics per chromosome. } \usage{ \method{getCallStatistics}{CBS}(fit, regions=NULL, shrinkRegions=TRUE, ..., verbose=FALSE) } \arguments{ \item{regions}{An optional \code{\link[base]{data.frame}} with columns "chromosome", "start", and "end" specifying the regions of interest to calculate statistics for. If \code{\link[base]{NULL}}, all of the genome is used.} \item{shrinkRegions}{If \code{\link[base:logical]{TRUE}}, regions are shrunk to the support of the data.} \item{...}{Not used.} \item{verbose}{\code{\link[R.utils]{Verbose}}.} } \value{ Returns a CxK \code{\link[base]{data.frame}}, where C is the number of regions that meet the criteria setup by argument \code{regions} and (K-4)/2 is the number of call types. The first column is the chromosome index, the second and the third are the first and last position, and the fourth the length (=last-first+1) of the chromosome. The following columns contains call summaries per chromosome. For each chromosome and call type, the total length of such calls on that chromosome is reported together how large of a fraction of the chromosome such calls occupy. } \details{ The estimators implemented here are based solely on the segmentation results, which is very fast. In the original proposal by Fridlyand et al. [1], the authors estimates the parameters by converting segment-level calls back to locus-level calls and there do the calculations. The difference between the two approaches should be minor, particularly for large density arrays. } \author{Henrik Bengtsson} \references{ [1] Fridlyand et al. \emph{Breast tumor copy number aberration phenotypes and genomic instability}, BMC Cancer, 2006. \cr } \seealso{ For more information see \code{\link{CBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/getBootstrapLocusSets.PairedPSCBS.Rd 0000644 0001762 0000144 00000003352 14564060314 020514 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.BOOT.sets.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{getBootstrapLocusSets.PairedPSCBS} \alias{getBootstrapLocusSets.PairedPSCBS} \alias{PairedPSCBS.getBootstrapLocusSets} \alias{getBootstrapLocusSets,PairedPSCBS-method} \alias{getBootstrapLocusSets} \title{Generates original and bootstrapped segment-specific index sets} \description{ Generates original and bootstrapped segment-specific index sets, which can be used to calculate various bootstrap summaries, e.g. segment mean levels. } \usage{ \method{getBootstrapLocusSets}{PairedPSCBS}(fit, B=1000L, by=c("betaTN", "betaT"), seed=NULL, verbose=FALSE, .validate=FALSE, ...) } \arguments{ \item{B}{A non-negative \code{\link[base]{integer}} specifying the number of bootstrap samples.} \item{by}{Should \code{betaTN} or \code{betaT} be used?} \item{seed}{An (optional) \code{\link[base]{integer}} specifying the random seed to be set before sampling indices. The random seed is set to its original state when exiting. If \code{\link[base]{NULL}}, it is not set.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} \item{.validate}{If \code{\link[base:logical]{TRUE}}, additional sanity checks are performed to validate the correctness. This is only needed for troubleshooting if it is suspected there is a bug.} \item{...}{Not used.} } \value{ Returns a \code{\link[base]{list}}. } \author{Henrik Bengtsson} \seealso{ This is used internally by various bootstrap methods. } \keyword{internal} \keyword{methods} PSCBS/man/pruneBySdUndo.CBS.Rd 0000644 0001762 0000144 00000005257 14564060313 015350 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.PRUNE.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{pruneBySdUndo.CBS} \alias{pruneBySdUndo.CBS} \alias{CBS.pruneBySdUndo} \alias{pruneBySdUndo,CBS-method} \title{Prune the CBS profile by dropping change points that are too small} \description{ Prune the CBS profile by dropping change points that are too small, where "too small" means that the amplitude of the change points is less than a multiple of the overall standard deviation of the copy-number signals. } \usage{ \method{pruneBySdUndo}{CBS}(fit, rho=3, sigma="DNAcopy", ..., verbose=FALSE) } \arguments{ \item{fit}{A \code{\link{CBS}} object.} \item{rho}{A positive \code{\link[base]{double}} scalar specifying the number of standard deviations (\code{rho*sigma}) required in order to keep a change point. More change points are dropped the greater this value is.} \item{sigma}{The whole-genome standard deviation of the locus-level copy number signals. The default is to calculate it from the data and as done in the \pkg{DNAcopy} package.} \item{...}{(Optional) Additional arguments passed to the standard deviation estimator function.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns a \code{\link{CBS}} object (of the same class as \code{fit}). } \details{ This method corresponds to using the \code{undo} argument when calling \code{\link{segmentByCBS}}(), which in turn corresponds to using the \code{undo.splits="sdundo"} and \code{undo.SD} of the underlying \code{\link[DNAcopy]{segment}} method. } \examples{ # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Simulating copy-number data # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - set.seed(0xBEEF) # Number of loci J <- 1000 mu <- double(J) mu[1:100] <- mu[1:100] + 0.3 mu[200:300] <- mu[200:300] + 1 mu[350:400] <- NA # centromere mu[650:800] <- mu[650:800] - 1 eps <- rnorm(J, sd=1/2) y <- mu + eps x <- sort(runif(length(y), max=length(y))) * 1e5 w <- runif(J) w[650:800] <- 0.001 # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Segmentation # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fit <- segmentByCBS(y, x=x) print(fit) plotTracks(fit) # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Post-segmentation pruning # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fitP <- pruneBySdUndo(fit, rho=1) drawLevels(fitP, col="red") } \author{Henrik Bengtsson, Pierre Neuvial} \keyword{internal} \keyword{methods} PSCBS/man/nbrOfChangePoints.AbstractCBS.Rd 0000644 0001762 0000144 00000002076 14564060313 017640 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{nbrOfChangePoints.AbstractCBS} \alias{nbrOfChangePoints.AbstractCBS} \alias{AbstractCBS.nbrOfChangePoints} \alias{nbrOfChangePoints,AbstractCBS-method} \title{Gets the number of change points} \description{ Gets the number of change points, which is defined as the number of segments minus the number of chromosomes. } \usage{ \method{nbrOfChangePoints}{AbstractCBS}(fit, ignoreGaps=FALSE, dropEmptySegments=TRUE, ...) } \arguments{ \item{...}{Not used.} } \value{ Returns an \code{\link[base]{integer}}. } \author{Henrik Bengtsson} \seealso{ \code{\link[PSCBS:nbrOfSegments.AbstractCBS]{*nbrOfSegments}()} \code{\link[PSCBS:nbrOfChromosomes.AbstractCBS]{*nbrOfChromosomes}()} For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/callCopyNeutral.PairedPSCBS.Rd 0000644 0001762 0000144 00000003246 14564060314 017275 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.callCopyNeutral.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{callCopyNeutral.PairedPSCBS} \alias{callCopyNeutral.PairedPSCBS} \alias{PairedPSCBS.callCopyNeutral} \alias{callCopyNeutral,PairedPSCBS-method} \alias{PairedPSCBS.callNTCN} \alias{callNTCN.PairedPSCBS} \alias{callNTCN,PairedPSCBS-method} \title{Calls segments that have a neutral total copy number} \description{ Calls segments that have a neutral total copy number (NTCN), i.e. that have a TCN that corresponds to the ploidy of the genome. } \usage{ \method{callCopyNeutral}{PairedPSCBS}(fit, flavor=c("TCN|AB"), ..., minSize=1, force=FALSE) } \arguments{ \item{flavor}{A \code{\link[base]{character}} string specifying which type of call to use.} \item{...}{Additional arguments passed to the caller.} \item{minSize}{An optional \code{\link[base]{integer}} specifying the minimum number of data points in order to call a segments. If fewer data points, then the call is set to \code{\link[base]{NA}} regardless.} \item{force}{If \code{\link[base:logical]{FALSE}}, and copy-neutral calls already exits, then nothing is done, otherwise the calls are done.} } \value{ Returns a \code{\link{PairedPSCBS}} object with copy-neutral calls. } \author{Henrik Bengtsson} \seealso{ Internally, one of the following methods are used: \code{\link[PSCBS:callCopyNeutralByTCNofAB.PairedPSCBS]{*callCopyNeutralByTCNofAB}()}. } \keyword{internal} \keyword{methods} PSCBS/man/callCopyNeutralByTCNofAB.PairedPSCBS.Rd 0000644 0001762 0000144 00000003611 14564060314 020661 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.callCopyNeutral.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{callCopyNeutralByTCNofAB.PairedPSCBS} \alias{callCopyNeutralByTCNofAB.PairedPSCBS} \alias{PairedPSCBS.callCopyNeutralByTCNofAB} \alias{callCopyNeutralByTCNofAB,PairedPSCBS-method} \title{Calls regions that are copy neutral} \description{ Calls regions that are copy neutral from the total copy numbers (TCNs) of segments in allelic balance (AB). } \usage{ \method{callCopyNeutralByTCNofAB}{PairedPSCBS}(fit, delta=estimateDeltaCN(fit), alpha=0.05, ..., force=FALSE, verbose=FALSE) } \arguments{ \item{fit}{A PairedPSCBS fit object as returned by \code{\link[PSCBS]{segmentByPairedPSCBS}}.} \item{delta}{A non-negative \code{\link[base]{double}} specifying the width of the "acceptance" region. Defaults to half of the distance between two integer TCN states, i.e. 1/2. This argument should be shrunken as a function of the amount of the normal contamination and other background signals.} \item{alpha}{A \code{\link[base]{double}} in [0,0.5] specifying the significance level of the confidence intervals used.} \item{...}{Additional arguments passed to \code{\link[PSCBS:calcStatsForCopyNeutralABs.PairedPSCBS]{*calcStatsForCopyNeutralABs}()}.} \item{force}{If \code{\link[base:logical]{TRUE}}, an already called object is skipped, otherwise not.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns a \code{\link{PairedPSCBS}} fit object where a column with the copy-neutral call. } \details{ ... } %% examples "../incl/callCopyNeutralByTCNofAB.PairedPSCBS.Rex" \author{Henrik Bengtsson} \keyword{internal} \keyword{methods} PSCBS/man/c.CBS.Rd 0000644 0001762 0000144 00000001621 14564060313 013020 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.RESTRUCT.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{c.CBS} \alias{c.CBS} \alias{CBS.c} \alias{c,CBS-method} \alias{c.PSCBS} \title{Concatenates segmentation results} \description{ Concatenates segmentation results. } \usage{ \method{c}{CBS}(..., addSplit=TRUE) } \arguments{ \item{\dots}{One or more \code{\link{AbstractCBS}} objects to be combined.} \item{addSplit}{If \code{\link[base:logical]{TRUE}}, a "divider" is added between chromosomes.} } \value{ Returns an \code{\link{AbstractCBS}} object of the same class in \dots. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{CBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/as.data.frame.CBS.Rd 0000644 0001762 0000144 00000001531 14564060313 015202 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{as.data.frame.CBS} \alias{as.data.frame.CBS} \alias{CBS.as.data.frame} \alias{as.data.frame,CBS-method} \title{Gets the table of segments} \description{ Gets the table of segments. } \usage{ \method{as.data.frame}{CBS}(x, ...) } \arguments{ \item{...}{Not used.} } \value{ Returns a \code{\link[base]{data.frame}}, where each row corresponds to a unique segment. } \author{Henrik Bengtsson} \seealso{ Utilizes \code{\link[PSCBS:getSegments.CBS]{*getSegments}()}. For more information see \code{\link{CBS}}.. } \keyword{internal} \keyword{methods} PSCBS/man/estimateKappa.PairedPSCBS.Rd 0000644 0001762 0000144 00000002417 14564060314 016763 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.estimateKappa.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{estimateKappa.PairedPSCBS} \alias{estimateKappa.PairedPSCBS} \alias{PairedPSCBS.estimateKappa} \alias{estimateKappa,PairedPSCBS-method} \title{Estimate global background in segmented copy numbers} \description{ Estimate global background in segmented copy numbers. The global background, here called \eqn{\kappa}, may have multiple origins where normal contamination is one, but not necessarily the only one. } \usage{ \method{estimateKappa}{PairedPSCBS}(this, flavor=c("density(C1)"), ...) } \arguments{ \item{flavor}{A \code{\link[base]{character}} string specifying which type of estimator to use.} \item{...}{Additional arguments passed to the estimator.} } \value{ Returns the background estimate as a \code{\link[base]{numeric}} scalar. } \author{Henrik Bengtsson} \seealso{ Internally, one of the following methods are used: \code{\link[PSCBS:estimateKappaByC1Density.PairedPSCBS]{*estimateKappaByC1Density}()}. } \keyword{internal} \keyword{methods} PSCBS/man/findLargeGaps.Rd 0000644 0001762 0000144 00000003233 14564060314 014700 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % findLargeGaps.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{findLargeGaps} \alias{findLargeGaps.default} \alias{findLargeGaps} \alias{findLargeGaps.data.frame} \title{Identifies gaps of a genome where there exist no observations} \description{ Identifies gaps of a genome where there exist no observations. } \usage{ \method{findLargeGaps}{default}(chromosome=NULL, x, minLength, resolution=1L, ...) } \arguments{ \item{chromosome}{(Optional) An \code{\link[base]{integer}} \code{\link[base]{vector}} of length J of chromosome indices.} \item{x}{A \code{\link[base]{numeric}} \code{\link[base]{vector}} of J of genomic locations.} \item{minLength}{A positive \code{\link[base]{numeric}} scalar specifying the minimum length of a gap.} \item{resolution}{A non-negative \code{\link[base]{numeric}} specifying the minimum length unit, which by default equals one nucleotide/base pair.} \item{...}{Not used.} } \value{ Returns \code{\link[base]{data.frame}} zero or more rows and with columns \code{chromosome} (if given), \code{start}, \code{stop}, and \code{length}. } \author{Henrik Bengtsson} \seealso{ Use \code{\link{gapsToSegments}}() to turn the set of identified gaps into the complementary set of segments such that they can be passed to \code{\link{segmentByCBS}}(), \code{\link{segmentByPairedPSCBS}}() and \code{\link{segmentByNonPairedPSCBS}}() via argument \code{knownSegments}. } \keyword{IO} PSCBS/man/estimateDeltaABBySmallDH.PairedPSCBS.Rd 0000644 0001762 0000144 00000004300 14564060314 020654 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.estimateDeltaAB.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{estimateDeltaABBySmallDH.PairedPSCBS} \alias{estimateDeltaABBySmallDH.PairedPSCBS} \alias{PairedPSCBS.estimateDeltaABBySmallDH} \alias{estimateDeltaABBySmallDH,PairedPSCBS-method} \title{Estimate a threshold for calling allelic balance from DH} \description{ Estimate a threshold for calling allelic balance from DH. } \usage{ \method{estimateDeltaABBySmallDH}{PairedPSCBS}(fit, q1=0.05, q2=0.9, ..., verbose=FALSE) } \arguments{ \item{q1}{A \code{\link[base]{numeric}} value specifying the weighted quantile of the segment-level DHs used to identify segments with small DH means.} \item{q2}{A \code{\link[base]{numeric}} value specifying the quantile of the locus-level DH signals for those segments with small DH mean levels.} \item{...}{Not used.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns the threshold estimate as a \code{\link[base]{numeric}} scalar. } \section{Algorithm}{ \itemize{ \item Grabs the segment-level DH estimates. \item Calculate segment weights proportional to the number of heterozygous SNPs. \item Calculate \eqn{\Delta} as the 5\% quantile of the weighted DH means. \item Choose the segments with means less than \eqn{\Delta}. \item Calculate threshold \eqn{\Delta_{AB}} as the 90\% "symmetric" quantile of the observed locus-level DHs from the selected segments in Step 4. The q:th "symmetric" quantile is estimated by estimating the ((1-q), 50\%) quantiles, calculating their distance as "50\%-(1-q)" and add to the median (50\%), i.e. "median + (median-(1-q))" = "2*median-1 + q", which should equal q if the distribution is symmetric. } } \author{Henrik Bengtsson} \seealso{ Instead of calling this method explicitly, it is recommended to use the \code{\link[PSCBS:estimateDeltaAB.PairedPSCBS]{*estimateDeltaAB}()} method. } \keyword{internal} \keyword{methods} PSCBS/man/estimateDeltaLOHByMinC1ForNonAB.PairedPSCBS.Rd 0000644 0001762 0000144 00000004460 14564060314 021773 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.estimateDeltaLOH.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{estimateDeltaLOHByMinC1ForNonAB.PairedPSCBS} \alias{estimateDeltaLOHByMinC1ForNonAB.PairedPSCBS} \alias{PairedPSCBS.estimateDeltaLOHByMinC1ForNonAB} \alias{estimateDeltaLOHByMinC1ForNonAB,PairedPSCBS-method} \title{Estimate a threshold for calling LOH from DH} \description{ Estimate a threshold for calling LOH from DH based on the location of guessed C1=0 and C1=1 peaks. } \usage{ \method{estimateDeltaLOHByMinC1ForNonAB}{PairedPSCBS}(this, midpoint=1/2, maxC=3 * (ploidy(this)/2), ..., verbose=FALSE) } \arguments{ \item{midpoint}{A \code{\link[base]{numeric}} scalar in [0,1] specifying the relative position of the midpoint between the estimated locations of C1=0 and C1=1 mean parameters.} \item{maxC}{Maximum total copy number of a segment in order to be included in the initial set of segments.} \item{...}{Not used.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns the estimated LOH threshold as a \code{\link[base]{numeric}} scalar or -\code{\link[base:is.finite]{Inf}}. In case it is not possible to estimate the LOH threshold, then -\code{\link[base:is.finite]{Inf}} is returned. } \details{ This method requires that calls for allelic balances already have been me made, cf. \code{\link[PSCBS:callAllelicBalance.PairedPSCBS]{*callAllelicBalance}()}. } \section{Algorithm}{ \itemize{ \item Grabs the segment-level C1 estimates. \item Calculate segment weights proportional to the number of heterozygous SNPs. \item Estimate the C1=1 location as the weighted median C1 for segments that have been called to be in allelic balance. \item Estimate the C1=0 location as the smallest C1 among segments that are not in allelic balance. \item Let the LOH threshold be the midpoint of the estimates C1=0 and C1=1 locations. } } \author{Henrik Bengtsson} \seealso{ Instead of calling this method explicitly, it is recommended to use the \code{\link[PSCBS:estimateDeltaLOH.PairedPSCBS]{*estimateDeltaLOH}()} method. } \keyword{internal} \keyword{methods} PSCBS/man/dropRegions.AbstractCBS.Rd 0000644 0001762 0000144 00000004106 14564060313 016556 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.RESTRUCT.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{dropRegions.AbstractCBS} \alias{dropRegions.AbstractCBS} \alias{AbstractCBS.dropRegions} \alias{dropRegions,AbstractCBS-method} \alias{AbstractCBS.dropRegion} \alias{dropRegion.AbstractCBS} \alias{dropRegion,AbstractCBS-method} \title{Drops chromosomal regions (a connected set of segments)} \description{ Drops chromosomal regions (a connected set of segments) each of a certain size (number of segments). \emph{None of the statistics are recalculated}. } \usage{ \method{dropRegions}{AbstractCBS}(this, regions, H=1, ..., asMissing=FALSE, verbose=FALSE) } \arguments{ \item{regions}{An \code{\link[base]{integer}} \code{\link[base]{vector}} of length R specifying the indices of the left most segment in each of the R regions to be dropped.} \item{H}{A non-negative \code{\link[base]{integer}} specifying the size of each region, i.e. the number of segments per region.} \item{...}{Additional arguments passed to \code{\link[PSCBS:extractRegions.AbstractCBS]{*extractRegions}()}.} \item{asMissing}{If \code{\link[base:logical]{TRUE}}, dropped segments are replaced by missing values, otherwise they are truly dropped.} \item{verbose}{A \code{\link[base]{logical}} or a \code{\link[R.utils]{Verbose}} object.} } \value{ Returns an \code{\link{AbstractCBS}} object of the same class with (at most) R*H segments dropped. If some regions overlap (share segments), then fewer than R*H segments are dropped. } \author{Henrik Bengtsson} \seealso{ Internally \code{\link[PSCBS:extractRegions.AbstractCBS]{*extractRegions}()} is used. See also \code{\link[PSCBS:dropChangePoint.AbstractCBS]{*dropChangePoint}()} and \code{\link[PSCBS:mergeTwoSegments.AbstractCBS]{*mergeTwoSegments}()}. For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/randomSeed.Rd 0000644 0001762 0000144 00000002575 14564060314 014263 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % randomSeed.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{randomSeed} \alias{randomSeed} \title{Sets and resets the .Random.seed in the global environment} \description{ Sets and resets the .Random.seed in the global environment. } \usage{ randomSeed(action=c("set", "advance", "reset", "get"), seed=NULL, kind=NULL, n=1L, backup=TRUE) } \arguments{ \item{action}{A \code{\link[base]{character}} string specifying the action.} \item{seed}{Random seed to be set; only for \code{action="set"}. If \code{length(seed) == 1}, then \code{set.seed(seed)} is used, otherwise \code{.Random.seed} is assigned the value.} \item{kind}{(optional) A \code{\link[base]{character}} string specifying type of random number generator to use, cf. \code{\link[base]{RNGkind}}().} \item{n}{Number of random seeds to generate by \code{action}.} \item{backup}{If \code{\link[base:logical]{TRUE}}, the previous (seed, kind) state is recorded such that it can be reset later.} } \value{ Returns a \code{.Random.seed}. If more than one is returned, the they are returned as a \code{\link[base]{list}}. } \author{Henrik Bengtsson} \keyword{internal} PSCBS/man/getChromosomes.AbstractCBS.Rd 0000644 0001762 0000144 00000001770 14564060313 017265 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{getChromosomes.AbstractCBS} \alias{getChromosomes.AbstractCBS} \alias{AbstractCBS.getChromosomes} \alias{getChromosomes,AbstractCBS-method} \title{Gets the set of chromosomes} \description{ Gets the set of chromosomes in the segmentation result. } \usage{ \method{getChromosomes}{AbstractCBS}(this, ...) } \arguments{ \item{...}{Arguments passed to \code{\link[PSCBS:getSegments.AbstractCBS]{*getSegments}()}.} } \value{ Returns a unique and sorted \code{\link[base]{vector}} of chromosomes segmented. } \author{Henrik Bengtsson} \seealso{ \code{\link[PSCBS:nbrOfChromosomes.AbstractCBS]{*nbrOfChromosomes}()}. For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/getSmoothLocusData.CBS.Rd 0000644 0001762 0000144 00000002107 14564060313 016347 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % CBS.SMOOTH.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{getSmoothLocusData.CBS} \alias{getSmoothLocusData.CBS} \alias{CBS.getSmoothLocusData} \alias{getSmoothLocusData,CBS-method} \title{Gets smoothed locus-level data} \description{ Gets smoothed locus-level data. } \usage{ \method{getSmoothLocusData}{CBS}(fit, by, ...) } \arguments{ \item{fit}{An \code{\link{CBS}} object.} \item{by}{A \code{\link[base]{numeric}} scalar specifying the bin size.} \item{...}{Not used.} } \value{ Returns a \code{\link[base]{data.frame}} where the first three columns are 'chromosome', 'x' (position), and 'count' (number of loci average over for the given bin), and the remaining ones are the smoothed locus-level data. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{CBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/callLOH.PairedPSCBS.Rd 0000644 0001762 0000144 00000005077 14564060314 015456 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % PairedPSCBS.callLOH.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{callLOH.PairedPSCBS} \alias{callLOH.PairedPSCBS} \alias{PairedPSCBS.callLOH} \alias{callLOH,PairedPSCBS-method} \title{Calls segments that are in LOH} \description{ Calls segments that are in LOH, i.e. that have "zero" minor copy number. } \usage{ \method{callLOH}{PairedPSCBS}(fit, flavor=c("SmallC1", "LargeDH"), ..., minSize=1, xorCalls=TRUE, force=FALSE) } \arguments{ \item{flavor}{A \code{\link[base]{character}} string specifying which type of call to use.} \item{...}{Additional arguments passed to the caller.} \item{minSize}{An optional \code{\link[base]{integer}} specifying the minimum number of data points in order to call a segments. If fewer data points, then the call is set to \code{\link[base]{NA}} regardless.} \item{xorCalls}{If \code{\link[base:logical]{TRUE}}, a region already called AB, will for consistency never be called LOH, resulting in either an LOH call set to \code{\link[base:logical]{FALSE}} or \code{\link[base]{NA}} (as explained below).} \item{force}{If \code{\link[base:logical]{FALSE}}, and allelic-balance calls already exits, then nothing is done, otherwise the calls are done.} } \value{ Returns a \code{\link{PairedPSCBS}} object with LOH calls. } \section{AB and LOH consistency}{ Biologically, a segment can not be both in allelic balance (AB) and in loss-of-heterozygosity (LOH) at the same time. To avoid reporting such inconsistencies, the LOH caller will, if argument \code{xorCalls=TRUE}, never report a segment to be in LOH if it is already called to be in AB. However, regardless of of the AB call, a segment is still always tested for LOH, to check weather the LOH caller is consistent with the AB caller or not. Thus, in order to distinguish the case where the AB caller and LOH caller agree from when they disagree, we report either (AB,LOH)=(TRUE,FALSE) or (TRUE,NA). The former is reported when they are consistent, and the latter when they are not, or when the LOH caller could not call it. } \author{Henrik Bengtsson} \seealso{ Internally, one of the following methods are used: \code{\link[PSCBS:callLowC1ByC1.PairedPSCBS]{*callLowC1ByC1}()}, \code{\link[PSCBS:callExtremeAllelicImbalanceByDH.PairedPSCBS]{*callExtremeAllelicImbalanceByDH}()}. } \keyword{internal} \keyword{methods} PSCBS/man/nbrOfLoci.AbstractCBS.Rd 0000644 0001762 0000144 00000001547 14564060313 016146 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{nbrOfLoci.AbstractCBS} \alias{nbrOfLoci.AbstractCBS} \alias{AbstractCBS.nbrOfLoci} \alias{nbrOfLoci,AbstractCBS-method} \title{Gets the number of loci} \description{ Gets the number of loci. } \usage{ \method{nbrOfLoci}{AbstractCBS}(fit, splitters=FALSE, ...) } \arguments{ \item{splitters, ...}{Arguments passed to \code{\link[PSCBS:getLocusData.AbstractCBS]{*getLocusData}()}.} } \value{ Returns an \code{\link[base]{integer}}. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{AbstractCBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/pruneByDP.AbstractCBS.Rd 0000644 0001762 0000144 00000002502 14564060312 016130 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.PRUNE.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{pruneByDP.AbstractCBS} \alias{pruneByDP.AbstractCBS} \alias{AbstractCBS.pruneByDP} \alias{pruneByDP,AbstractCBS-method} \title{Prunes the CN profile using dynamical programming} \description{ Prunes the CN profile using dynamical programming by specifying the target number of segments or alternative how of many change points to drop. } \usage{ \method{pruneByDP}{AbstractCBS}(fit, nbrOfSegments, ..., verbose=FALSE) } \arguments{ \item{nbrOfSegments}{An \code{\link[base]{integer}} specifying the number of segments after pruning. If negative, the it specifies the number of change points to drop.} \item{...}{Optional arguments passed to \code{\link[PSCBS:seqOfSegmentsByDP.AbstractCBS]{*seqOfSegmentsByDP}()}.} \item{verbose}{See \code{\link[R.utils]{Verbose}}.} } \value{ Returns a pruned object of the same class. } \examples{\dontrun{ # Drop two segments fitP <- pruneByDP(fit, nbrOfSegments=-2) }} \author{Henrik Bengtsson, Pierre Neuvial} \references{ [1] ... \cr } \keyword{internal} \keyword{methods} PSCBS/man/getSampleName.AbstractCBS.Rd 0000644 0001762 0000144 00000001743 14564060313 017011 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{getSampleName.AbstractCBS} \alias{getSampleName.AbstractCBS} \alias{AbstractCBS.getSampleName} \alias{getSampleName,AbstractCBS-method} \alias{AbstractCBS.sampleName} \alias{sampleName.AbstractCBS} \alias{sampleName,AbstractCBS-method} \title{Gets the name of the sample segmented} \description{ Gets the name of the sample segmented. } \usage{ \method{getSampleName}{AbstractCBS}(fit, ...) } \arguments{ \item{...}{Not used.} } \value{ Returns a \code{\link[base]{character}} string. } \author{Henrik Bengtsson} \seealso{ \code{\link[PSCBS:setSampleName.AbstractCBS]{*setSampleName}()}. For more information see \code{\link{AbstractCBS}}.. } \keyword{internal} \keyword{methods} PSCBS/man/as.DNAcopy.CBS.Rd 0000644 0001762 0000144 00000003377 14564060313 014507 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % DNAcopy.EXTS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{as.DNAcopy.CBS} \alias{as.DNAcopy.CBS} \alias{CBS.as.DNAcopy} \alias{as.DNAcopy,CBS-method} \title{Coerces a CBS object to a DNAcopy object} \description{ Coerces a CBS object to a DNAcopy object. } \usage{ \method{as.DNAcopy}{CBS}(fit, ...) } \arguments{ \item{fit}{A \code{\link{CBS}} object."} \item{...}{Not used.} } \value{ Returns a \code{\link{DNAcopy}} object (of the \pkg{DNAcopy} package). } \examples{ # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Simulating copy-number data # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - set.seed(0xBEEF) # Number of loci J <- 1000 mu <- double(J) mu[200:300] <- mu[200:300] + 1 mu[350:400] <- NA # centromere mu[650:800] <- mu[650:800] - 1 eps <- rnorm(J, sd=1/2) y <- mu + eps x <- sort(runif(length(y), max=length(y))) * 1e5 w <- runif(J) w[650:800] <- 0.001 # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - # Segmentation # - - - - - - - - - - - - - - - - - - - - - - - - - - - - - fit <- segmentByCBS(y, x=x) print(fit) plotTracks(fit) # Coerce an CBS object to a DNAcopy object fitD <- as.DNAcopy(fit) # Coerce an DNAcopy object to a CBS object fitC <- as.CBS(fitD) # Sanity check fitD2 <- as.DNAcopy(fit) stopifnot(all.equal(fitD2, fitD)) fitC2 <- as.CBS(fitD2) stopifnot(all.equal(fitC2, fitC)) } \author{Henrik Bengtsson} \seealso{ \code{\link[PSCBS:as.CBS.DNAcopy]{as.CBS()}}. For more information see \code{\link{CBS}}. } \keyword{internal} \keyword{methods} PSCBS/man/setSampleName.AbstractCBS.Rd 0000644 0001762 0000144 00000001734 14564060313 017025 0 ustar ligges users %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Do not modify this file since it was automatically generated from: % % AbstractCBS.R % % by the Rdoc compiler part of the R.oo package. %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% \name{setSampleName.AbstractCBS} \alias{setSampleName.AbstractCBS} \alias{AbstractCBS.setSampleName} \alias{setSampleName,AbstractCBS-method} \alias{AbstractCBS.sampleName<-} \alias{sampleName<-.AbstractCBS} \alias{sampleName<-,AbstractCBS-method} \title{Sets the name of the sample segmented} \description{ Sets the name of the sample segmented. } \usage{ \method{setSampleName}{AbstractCBS}(fit, name, ...) } \arguments{ \item{name}{A \code{\link[base]{character}} string.} \item{...}{Not used.} } \value{ Returns (invisibly) an updated object. } \author{Henrik Bengtsson} \seealso{ For more information see \code{\link{AbstractCBS}}.. } \keyword{internal} \keyword{methods} PSCBS/man/figures/ 0000755 0001762 0000144 00000000000 14564051545 013354 5 ustar ligges users PSCBS/man/figures/ex-PSCBS-paired.chr01.png 0000644 0001762 0000144 00000154565 14564051545 017544 0 ustar ligges users PNG IHDR Q I IDATx{eUuNtJ}p|RQcW~tۭC=Q[CPꇩHRD\ 4'xvY- !T$(c4z}`.mcyk9{(jc1_5sq $ @ $ @ $ @ $ @ $ @ $ @ $ @ $ @ $ @ $ @ $ @ $ @ $ @ $ (x+ۄG}t]|3暰 طo5kr!_b=|ۛ|%7VZՄ} ă>x<묳j7nݺmN+ $Оn ڤY~.痿|+Qw 4Mo<>OFonk M?"<蠃g>_֮]+űe˖[?~_n4$ Ьeg>G+9s=5k4 UhV@|g}gݨ Z H H H @f4u# 2] 4 Op M)R{Q b} P; $ @ $ FA8eU @#Lٿ]*@@ Ngh +Ԋ=o( `VЦxKd($7 @ӦݽbF2֬?++{__5 M,Uvψ|4CfEm۶nڵ T @F}i7j}ǎ_U{GyCen;qϞ= PnSҬcyᇷo938DžFC @oFЈ4 K___g>gqQGը; foS_c qr""bf9 hY>S 4 e*T YN4 zh4]U4E;hgX @]hWPu3Z @̔j<^=T4 4 Ŗ8 uY,h 4H-\ꪎ[2}7 dSBhANnq](*6<4 d*/p$(@n%pRd'^݇Noh 6F].n W~qr4# OBC@ ^ Uӷ&w-6%^ "d3U+a0UN7F-63 *DZM~9Yg_k#NljڍZSk5;RC@ mP{