ReportTables {CNVPanelizer} | R Documentation |
This function generates the final report of the CNV detection procedure. One data frame is generated for each sample of interest.
ReportTables(geneNames, samplesNormalizedReadCounts, referenceNormalizedReadCounts, bootList, backgroundNoise)
geneNames |
Describe |
samplesNormalizedReadCounts |
Describe |
referenceNormalizedReadCounts |
Describe |
bootList |
A list as returned by the |
backgroundNoise |
A list of background noise as returned by the
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Returns a list of tables, one for each sample of interest. Each of these tables contains numerical information of the aberration status of each gene. For a detailed description see the Vignette.
Thomas Wolf, Cristiano Oliveira
data(sampleReadCounts) data(referenceReadCounts) ## Gene names should be same size as row columns geneNames <- row.names(referenceReadCounts) ampliconNames <- NULL normalizedReadCounts <- CombinedNormalizedCounts(sampleReadCounts, referenceReadCounts, ampliconNames = ampliconNames) # After normalization data sets need to be splitted again to perform bootstrap samplesNormalizedReadCounts = normalizedReadCounts["samples"][[1]] referenceNormalizedReadCounts = normalizedReadCounts["reference"][[1]] # Should be used values above 10000 replicates <- 10 # Perform the bootstrap based analysis bootList <- BootList(geneNames, samplesNormalizedReadCounts, referenceNormalizedReadCounts, replicates = replicates) backgroundNoise = Background(geneNames, samplesNormalizedReadCounts, referenceNormalizedReadCounts, bootList, replicates = replicates) reportTables <- ReportTables(geneNames, samplesNormalizedReadCounts, referenceNormalizedReadCounts, bootList, backgroundNoise)