normalizeEdaseq {metaseqR2} | R Documentation

## Normalization based on the EDASeq package

### Description

This function is a wrapper over EDASeq 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

        normalizeEdaseq(geneCounts, sampleList,
            normArgs = NULL, geneData = 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 EDASeq normalization parameters. See the result of `getDefaults("normalization",` `"edaseq")` for an example and how you can modify it.
`geneData` | an optional annotation data frame (such the ones produced by `getAnnotation`) which contains the GC content for each gene and from which the gene lengths can be inferred by chromosome coordinates.
`output` | the class of the output object. It can be `"matrix"` (default) for versatility with other tools or `"native"` for the EDASeq native S4 object (SeqExpressionSet). In the latter case it should be handled with suitable EDASeq methods.

### Value

A matrix or a SeqExpressionSet 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)

    lengths <- round(1000*runif(nrow(dataMatrix)))
    starts <- round(1000*runif(nrow(dataMatrix)))
    ends <- starts + lengths
    gc=runif(nrow(dataMatrix))
    geneData <- data.frame(
      chromosome=c(rep("chr1",nrow(dataMatrix)/2),
        rep("chr2",nrow(dataMatrix)/2)),
      start=starts,end=ends,gene_id=rownames(dataMatrix),gc_content=gc,
      row.names=rownames(dataMatrix)
    )
    normDataMatrix <- normalizeEdaseq(dataMatrix,sampleList,
      geneData=geneData)
    diagplotBoxplot(normDataMatrix,sampleList)

[Package metaseqR2 version 1.0.11 Index]