normalize.edger {metaseqR} | R Documentation

## 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 metaseqr pipeline).

### Usage

        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

    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)

[Package metaseqR version 1.24.0 Index]