statNoiseq {metaseqR2} | R Documentation

## 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

    require(NOISeq)
    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)

[Package metaseqR2 version 1.0.11 Index]