CNVPanelizer (version 1.2.2)

PlotBootstrapDistributions: PlotBootstrapDistributions

Description

Plots the generated bootstrap distribution as violin plots. Genes showing significant values are marked in a different color.

Usage

PlotBootstrapDistributions(bootList, reportTables, outputFolder = getwd(), sampleNames = NULL, save = FALSE, scale = 7)

Arguments

bootList

List of bootstrapped read counts for each sample data

reportTables

List of report tables for each sample data

outputFolder

Path to the folder where the data plots will be created

sampleNames

List with sample names

save

Boolean to save the plots to the output folder

scale

Numeric scale factor

Value

A list with ggplot2 objects.

Examples

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)

PlotBootstrapDistributions(bootList, reportTables, save = FALSE)