CNVPanelizerFromReadCounts: CNVPanelizerFromReadCounts

In CNVPanelizer: Reliable CNV detection in targeted sequencing applications

Description

Performs the workflow analysis with CNVPanelizer from the read counts and splitting the batch of samples analyzed

Usage

            CNVPanelizerFromReadCounts(sampleReadCounts,
                                       referenceReadCounts,
                                       genomicRangesFromBed,
                                       numberOfBootstrapReplicates = 10000,
                                       normalizationMethod = "tmm",
                                       robust = TRUE,
                                       backgroundSignificanceLevel = 0.05,
                                       outputDir = file.path(getwd(), "CNVPanelizer"))

Arguments

sampleReadCounts	samples read counts matrix
referenceReadCounts	reference read counts matrix
genomicRangesFromBed	genomic ranges from bed
numberOfBootstrapReplicates	number of bootstrap replicates
normalizationMethod	Normalization method ("tmm" or "tss")
robust	if TRUE, the median is used instead of mean
backgroundSignificanceLevel	The background Significance Level
outputDir	Output directory

Value

Returns a list with the results of each samples analyzed

Author(s)

Cristiano Oliveira

Examples

    
    
            CNVPanelizerFromReadCounts(sampleReadCounts,
                                       referenceReadCounts,
                                       genomicRangesFromBed,
                                       numberOfBootstrapReplicates = 10000,
                                       normalizationMethod = "tmm",
                                       robust = TRUE,
                                       backgroundSignificanceLevel = 0.05,
                                       outputDir = file.path(getwd(), "CNVPanelizer"))
    

CNVPanelizer documentation built on Nov. 8, 2020, 6:47 p.m.