nbinomTestForMatrices {DESeq}R Documentation

Perform row-wise tests for differences between the base means of two count matrices.

Description

This function is called by nbinomTest. Call it directly only if the S4 interface is unsuitable for your task.

Usage

nbinomTestForMatrices(countsA, countsB, sizeFactorsA, sizeFactorsB, dispsA, dispsB )

Arguments

countsA

A matrix of counts, where each column is a replicate

countsB

Another matrix of counts, where each column is a replicate

sizeFactorsA

Size factors for the columns of the matrix 'countsA'

sizeFactorsB

Size factors for the columns of the matrix 'countsB'

dispsA

The dispersions for 'countsA', a vector with one value per gene

dispsB

The same for 'countsB'

Details

See the vignette for an exact description of the null hypothesis tested.

Value

A vector of unadjusted p values, one for each row in the counts matrices.

Author(s)

Simon Anders, sanders@fs.tum.de

Examples

cds <- makeExampleCountDataSet()
cds <- estimateSizeFactors( cds )
cds <- estimateDispersions( cds, method="per-condition" )
colsA <- conditions(cds) == "A"
colsB <- conditions(cds) == "B"
bmvA <- getBaseMeansAndVariances( counts(cds)[,colsA], sizeFactors(cds)[colsA] )
bmvB <- getBaseMeansAndVariances( counts(cds)[,colsB], sizeFactors(cds)[colsB] )
pvals <- nbinomTestForMatrices( 
   counts(cds)[,colsA],
   counts(cds)[,colsB],
   sizeFactors(cds)[colsA],
   sizeFactors(cds)[colsB],
   fitInfo(cds,"A")$dispFunc( rowMeans( counts( cds, normalized=TRUE ) ) ),
   fitInfo(cds,"B")$dispFunc( rowMeans( counts( cds, normalized=TRUE ) ) ) )
names( pvals ) <- row.names( counts(cds) )
head( pvals )

# This here should give the same results:
head( nbinomTest( cds, "A", "B" )$pval )

[Package DESeq version 1.6.1 Index]