metaseqR (version 1.12.2)

normalize.edaseq: 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 metaseqr pipeline).

Usage

normalize.edaseq(gene.counts, sample.list,
        norm.args = NULL, gene.data = 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 EDASeq normalization parameters. See the result of get.defaults("normalization", "edaseq") for an example and how you can modify it.

gene.data

an optional annotation data frame (such the ones produced by get.annotation) 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.

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)

lengths <- round(1000*runif(nrow(data.matrix)))
starts <- round(1000*runif(nrow(data.matrix)))
ends <- starts + lengths
gc=runif(nrow(data.matrix))
gene.data <- data.frame(
    chromosome=c(rep("chr1",nrow(data.matrix)/2),
        rep("chr2",nrow(data.matrix)/2)),
    start=starts,end=ends,gene_id=rownames(data.matrix),gc_content=gc
)
norm.data.matrix <- normalize.edaseq(data.matrix,sample.list,
    gene.data=gene.data)
diagplot.boxplot(norm.data.matrix,sample.list)