pfNbinomTest: The Polyfit extension to the DESeq functions nbinomTest() and...

In Polyfit: Add-on to DESeq to improve p-values and q-values

Description

Polyfit extensions to the DESeq functions nbinomTest and nbinomTestForMatrices which test for differences between the base means of two conditions (i.e., for differential expression in the case of RNA-Seq).

Usage

pfNbinomTest(cds, condA, condB, pvals_only = FALSE, eps = NULL)
pfNbinomTestForMatrices(countsA, countsB, sizeFactorsA, sizeFactorsB, dispsA, dispsB )

Arguments

cds	a CountDataSet with size factors and raw variance functions
condA	one of the conditions in 'cds'
condB	another one of the conditions in 'cds'
pvals_only	return only a vector of (unadjusted) p values instead of the data frame described below
eps	This argument is no longer used. Do not use it
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

These functions have the same behaviour as the DESeq functions nbinomTest and nbinomTestForMatrices, except that the ‘flagpole’ in the P-value histogram, particularly at p = 1 is redistributed using the function twoSidedPValueFromDiscrete.

Value

pfNbinomTest gives a data frame with the following columns:

id	The ID of the observable, taken from the row names of the counts slots.
baseMean	The base mean (i.e., mean of the counts divided by the size factors) for the counts for both conditions
baseMeanA	The base mean (i.e., mean of the counts divided by the size factors) for the counts for condition A
baseMeanB	The base mean for condition B
foldChange	The ratio meanB/meanA
log2FoldChange	The log2 of the fold change
pval	The p value for rejecting the null hypothesis 'meanA==meanB'
padj	The adjusted p values (adjusted with 'p.adjust( pval, method="BH")')

pfNbinomTestForMatrices gives a vector of unadjusted p values, one for each row in the counts matrices.

Author(s)

Conrad Burden, [e-mail], based on software by Simon Anders

References

Burden, C.J., Qureshi, S. and Wilson, S.R. (2014). Error estimates for the analysis of differential expression from RNA-seq count data, PeerJ PrePrints 2:e400v1.

Anders, S. and Huber, W. (2010). Differential expression analysis for sequence count data. Genome Biology, 11(10), R106.

Examples

cds <- makeExampleCountDataSet()
cds <- estimateSizeFactors( cds )
cds <- estimateDispersions( cds )
nbT <- nbinomTest( cds, "A", "B" )
head( nbT )
nbTPolyfit <- pfNbinomTest( cds, "A", "B" )
head( nbTPolyfit )

oldpar <- par(mfrow=c(1,2))
hist(nbT$pval,breaks=seq(0,1,by=0.01), 
   				xlab="P-value", main="DESeq")
hist(nbTPolyfit$pval,breaks=seq(0,1,by=0.01), 
 					xlab="P-value", main="polyfit-DESeq")
par(oldpar)

Polyfit documentation built on Nov. 8, 2020, 5:26 p.m.