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Last data update: 2014.03.03

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

pfNbinomTest

R Documentation

The Polyfit extension to the DESeq functions nbinomTest() and nbinomTestForMatrices()

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, conrad.burden@anu.edu.au, 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)

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(Polyfit)
Loading required package: DESeq
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: locfit
locfit 1.5-9.1 	 2013-03-22
Loading required package: lattice
    Welcome to 'DESeq'. For improved performance, usability and
    functionality, please consider migrating to 'DESeq2'.
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/Polyfit/pfNbinomTest.Rd_%03d_medium.png", width=480, height=480)
> ### Name: pfNbinomTest
> ### Title: The Polyfit extension to the DESeq functions nbinomTest() and
> ###   nbinomTestForMatrices()
> ### Aliases: pfNbinomTest pfNbinomTestForMatrices
> 
> ### ** Examples
> 
> cds <- makeExampleCountDataSet()
> cds <- estimateSizeFactors( cds )
> cds <- estimateDispersions( cds )
> nbT <- nbinomTest( cds, "A", "B" )
> head( nbT )
        id  baseMean  baseMeanA baseMeanB foldChange log2FoldChange      pval
1 gene_1_T 691.17043  316.71443 940.80777  2.9705239     1.57071738 0.1181887
2 gene_2_F  19.28415   19.68099  19.01959  0.9663942    -0.04931635 0.8356644
3 gene_3_F  61.69449   73.43875  53.86498  0.7334680    -0.44719406 0.5890611
4 gene_4_F 260.09763  232.04474 278.79956  1.2014905     0.26482526 0.7905044
5 gene_5_F 692.91586 1046.12178 457.44526  0.4372773    -1.19337980 0.1730757
6 gene_6_F 164.81349  206.63188 136.93456  0.6626982    -0.59357620 0.4102879
       padj
1 0.5717126
2 1.0000000
3 0.9735589
4 1.0000000
5 0.6889195
6 0.9004707
> nbTPolyfit <- pfNbinomTest( cds, "A", "B" )
> head( nbTPolyfit )
        id  baseMean  baseMeanA baseMeanB foldChange log2FoldChange      pval
1 gene_1_T 691.17043  316.71443 940.80777  2.9705239     1.57071738 0.1180088
2 gene_2_F  19.28415   19.68099  19.01959  0.9663942    -0.04931635 0.8140754
3 gene_3_F  61.69449   73.43875  53.86498  0.7334680    -0.44719406 0.5789490
4 gene_4_F 260.09763  232.04474 278.79956  1.2014905     0.26482526 0.7882567
5 gene_5_F 692.91586 1046.12178 457.44526  0.4372773    -1.19337980 0.1724955
6 gene_6_F 164.81349  206.63188 136.93456  0.6626982    -0.59357620 0.4068913
       padj
1 0.5645545
2 0.9952024
3 0.9576691
4 0.9909575
5 0.6783692
6 0.8843828
> 
> 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)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>