normalizeEdger: Normalization based on the edgeR package

In pmoulos/metaseqR2-local: An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms

Normalization based on the edgeR package

Description

This function is a wrapper over edgeR normalization. It accepts a matrix of gene counts (e.g. produced by importing an externally generated table of counts to the main metaseqr2 pipeline).

Usage

    normalizeEdger(geneCounts, sampleList,
        normArgs = NULL, output = c("matrix", "native"))

Arguments

geneCounts	a table where each row represents a gene and each column a sample. Each cell contains the read counts for each gene and sample. Such a table can be produced outside metaseqr2 and is imported during the basic metaseqr2 workflow.
sampleList	the list containing condition names and the samples under each condition.
normArgs	a list of edgeR normalization parameters. See the result of getDefaults("normalization", "edger") for an example and how you can modify it.
output	the class of the output object. It can be "matrix" (default) for versatility with other tools or "native" for the edgeR native S4 object (DGEList). In the latter case it should be handled with suitable edgeR methods.

Value

A matrix or a DGEList with normalized counts.

Author(s)

Panagiotis Moulos

Examples

dataMatrix <- metaseqR2:::exampleCountData(2000)
sampleList <- list(A=c("A1","A2"),B=c("B1","B2","B3"))
diagplotBoxplot(dataMatrix,sampleList)

normDataMatrix <- normalizeEdger(dataMatrix,sampleList)
diagplotBoxplot(normDataMatrix,sampleList)

pmoulos/metaseqR2-local documentation built on May 21, 2024, 3:46 a.m.