statNoiseq: Statistical testing with NOISeq

In pmoulos/metaseqR2: An R package for the analysis and result reporting of RNA-Seq data by combining multiple statistical algorithms

Statistical testing with NOISeq

Description

This function is a wrapper over NOISeq statistical testing. It accepts a matrix of normalized gene counts or an S4 object specific to each normalization algorithm supported by metaseqR2.

Usage

    statNoiseq(object, sampleList, contrastList = NULL,
        statArgs = NULL, geneData = NULL, logOffset = 1)

Arguments

object	a matrix or an object specific to each normalization algorithm supported by metaseqR2, containing normalized counts. See also Details.
sampleList	the list containing condition names and the samples under each condition.
contrastList	vector of contrasts as defined in the main help page of metaseqr2. See also Details.
statArgs	a list of edgeR statistical algorithm parameters. See the result of getDefaults("statistics", "noiseq") for an example and how you can modify it.
geneData	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.
logOffset	a number to be added to each element of data matrix in order to avoid Infinity on log type data transformations.

Details

Regarding object, apart from matrix (also for NOISeq), the object can be a SeqExpressionSet (EDASeq), CountDataSet (DESeq), DGEList (edgeR), DESeqDataSet (DESeq2), SeqCountSet (DSS) or ABSDataSet (ABSSeq).

Regarding contrastList it can also be a named structured list of contrasts as returned by the internal function metaseqR2:::makeContrastList.

Value

A named list of NOISeq q-values, whose names are the names of the contrasts.

Author(s)

Panagiotis Moulos

Examples

dataMatrix <- metaseqR2:::exampleCountData(1000)
sampleList <- list(A=c("A1","A2"),B=c("B1","B2","B3"))
contrast <- "A_vs_B"
lengths <- round(1000*runif(nrow(dataMatrix)))
starts <- round(1000*runif(nrow(dataMatrix)))
ends <- starts + lengths
gc=runif(nrow(dataMatrix))
biotype=rep("protein_coding",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,biotype=biotype
)
normArgs <- metaseqR2:::getDefaults("normalization","noiseq")
normDataMatrix <- normalizeNoiseq(dataMatrix,sampleList,normArgs,
    geneData)
p <- statNoiseq(normDataMatrix,sampleList,contrast,
    geneData=geneData)

pmoulos/metaseqR2 documentation built on May 20, 2024, 5:48 a.m.