normalize.edger: Normalization based on the edgeR package

Description Usage Arguments Value Author(s) Examples

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 metaseqr pipeline).

Usage

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    normalize.edger(gene.counts, sample.list,
        norm.args = NULL, output = c("matrix", "native"))

Arguments

gene.counts

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 metaseqr and is imported during the basic metaseqr workflow.

sample.list

the list containing condition names and the samples under each condition.

norm.args

a list of edgeR normalization parameters. See the result of get.defaults("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

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require(DESeq)
data.matrix <- counts(makeExampleCountDataSet())
sample.list <- list(A=c("A1","A2"),B=c("B1","B2","B3"))
diagplot.boxplot(data.matrix,sample.list)

norm.data.matrix <- normalize.edger(data.matrix,sample.list)
diagplot.boxplot(norm.data.matrix,sample.list)

pmoulos/metaseqR documentation built on May 9, 2019, 12:58 a.m.