[BioC] LIMMA decideTests result zero from contrast matrix

James W. MacDonald jmacdon at uw.edu
Fri May 4 16:06:10 CEST 2012

Hi Ekta,

On 5/4/2012 2:44 AM, Ekta Jain wrote:
> Dear All,
> I am using the LIMMA package to create 2 contrasts for my data and then calculating the vennCounts of the decideTests from the contrast.fit to be able to create venn Diagrams.
> The code works fine but the summary(results) shows zeros for all i.e. no gene were up regulated or downregulated. This is not true for my data since toptable output shows Log fold change greater than>  2.
> I am certain it is a small glitch somewhere at my end that i get zero counts for my summary(decideTests). Please find below my code and i would really appreciate any help here at all.
> Thanks,
> Ekta
> ## R Script ###
>> numGenes<- nrow(eset)
>> library(limma)
>> samples<- c("Un","Un","DMSO10","DMSO10","DMSO5","DMSO5");
>> fl<- as.factor(samples)
>> design<- model.matrix(~ 0+ fl)
>> colnames(design)<- levels(fl)
>> fit<- lmFit(eset, design)
>> cont.matrix<- makeContrasts(DMSO10-Un, DMSO5-Un, levels=design)
>> fit2<- contrasts.fit(fit, cont.matrix)
>> fit2<- eBayes(fit2)
>> tTUni<- topTable(fitUni, adjust="fdr", sort.by="B", number=numGenes)
Here you are outputting all genes, regardless of adjusted p-value. And 
you claim some have |log fold| > 2.
>> results<- decideTests(fit2)
>> vennDiagram(results,include=c("up","down"),counts.col=c("red","green"))
Here you are requiring that the genes have an FDR adjusted p-value < 
0.05, and not putting any constraints on fold change. Since these are 
different criteria, is it surprising you get different results?



> ## ### I get zero genes for upregulation and downregulation #####
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James W. MacDonald, M.S.
University of Washington
Environmental and Occupational Health Sciences
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