normalize.nbpseq: Normalization based on the NBPSeq package

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

Description

This function is a wrapper over DESeq 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.nbpseq(gene.counts, sample.list,
        norm.args = NULL, libsize.list = 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 NBPSeq normalization parameters. See the result of get.defaults("normalization", "nbpseq") for an example and how you can modify it.
libsize.list	an optional named list where names represent samples (MUST be the same as the samples in sample.list) and members are the library sizes (the sequencing depth) for each sample. If not provided, the default is the column sums of the gene.counts matrix.
output	the class of the output object. It can be "matrix" (default) for versatility with other tools or "native" for the NBPSeq native S4 object (a specific list). In the latter case it should be handled with suitable NBPSeq methods.

Value

A matrix with normalized counts or a list with the normalized counts and other NBPSeq specific parameters.

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.nbpseq(data.matrix,sample.list)
diagplot.boxplot(norm.data.matrix,sample.list)

pmoulos/metaseqR documentation built on Dec. 21, 2020, 6:19 a.m.