Man pages for jmonlong/PopSV
Population-based detection of structural variants from Read-Depth signal

aneuploidy.flagFlag chromosomal aneuploidy
bin.bamGet read counts from BAM file
bin.bam.2dGet read counts between pairs of bins from BAM file
bin.bwGet read counts from BigWig coverage file
breakpoint.finder.interactiveInteractive breakpoint finder
call.abnormal.covCall abnormal bins
chrplotChromosom plot of CNVs
chunk.binSplit the bins in chunks for parallel normalization
cluster.regionsCluster samples using their abnormal regions
cn.plotPlot copy-number estimates in a region.
comp.index.filesCompress and index BED-like files
correct.GCCorrect GC bias
coverage.plotPlot the bin coverage in a region
coverage.plot.rawPlot the raw coverage in a region
createEmptyDFCreate empty data.frame
draw.controlsSelect control genomic regions for enrichment analysis
fdrtool.quantileP-values estimation
fdrtool.quantile.2NP-values estimation from mixture of 2 centered normal
filter.noncovered.binsFilter non-covered bins
find.comparable.binsFind comparable bins between two sample cohort.
fragment.genomeFragment a genome
fragment.genome.hg19Fragment hg19 genome
freq.rangeFrequency computation for ranges
gender.predictPredict the gender of sample(s)
getGCGC content computation for specific bins
getGC.hg19GC content computation for specific bins
init.filenamesInit file names for analysis
localMaxLocal maximum
mean.sd.outlierRMean and standard diviation after outlier removal
med.normGlobal median normalization
medvar.normMedian-variance normalization of bin counts
medvar.norm.internalMedian-variance normalization of bin counts
mergeConsBin.cbsSegmentation using CBS (NOT READY)
mergeConsBin.reduceMerge nearby bins
mergeConsBin.simpleSimple merge of abnormal bins
mergeConsBin.zMerge abnormal consecutive bins
normQCNormalized bin count QC metrics for normalization benchmark
norm.tm.optTrimmed-Mean normalization optimized
pair.discordant.readsPair discordant reads
pca.normPCA-based normalization of bin counts
PopSV-packagePopulation-based detection of structural variants from...
qc.sampleQC samples
qc.samplesJoin and QC the reference samples
qc.samples.clusterQC sample : clustering
qc.zshift.unaffectedQC: Z-score bias in unaffected samples
quant.normQuantile normalization
quick.countCounts reads across samples in a small number of bins
read.bedixRetrieve a subset of an indexed BED file.
samples.mergeMerge data.frame across samples
sv.summaryAbnormal regions summary
sv.summary.interactiveInteractive summary of the calls
tmm.normTrimmed-Mean M normalization
tnK.normWeighted targeted normalization using K-mean optimization.
tn.normTargeted-normalization of bin counts
tn.norm.qcQC graphs for Targeted Normalization
tn.norm.qc.divTargeted normalization QC: diversity of the supporting bins
tn.test.sampleSingle sample targeted normalization and test
weight.ref.pcaWeight sample difference from a set of reference samples
winsorWinsorize a vector
write.split.samplesSplit and write results in one file per sample
writeVcfWrite VCF file
z.compZ-score computation
z.normZ-score normalization
z.thres.cons.binsZ-score thresholding using bin consecutiveness.
jmonlong/PopSV documentation built on Oct. 20, 2017, 12:58 a.m.