[BioC] Re: Bioconductor Digest, Vol 20, Issue 2

Tarca Adi Laurentiu ltarca at rsvs.ulaval.ca
Mon Oct 4 15:41:11 CEST 2004

At 06:00 AM 10/2/2004, you wrote:
>Message: 15
>Date: Fri, 01 Oct 2004 14:39:04 -0400
>From: Tarca Adi Laurentiu <ltarca at rsvs.ulaval.ca>
>Subject: [BioC] limma question: topTable and classifyTests
>To: bioconductor at stat.math.ethz.ch
>Message-ID: < at biota.rsvs.ulaval.ca>
>Content-Type: text/plain; charset="us-ascii"

I see there was a problem with the concatenation of messages in 
Bioconductor Digest, Vol 20, Issue 2. My full message was

"Hi everybody,

I use limma to analyze a two-color microarrays data set. Using topTable I find
say 15 genes with "holm" adjusted p-values less than a given threshold 
pt=0.05, but if
I use classifyTestsP (specifying the same threshold and adjustment
method) I obtain much more than 15. Is there any explanation for this?
Here is the code, supposing that the normalized data is available as an 
object called MA.

design <-cbind("L-H1"=c(0,1,-1,0,1,0,-1,0),"L-H7"=c(-1,0,0,-1,0,1,0,1))
cor <- duplicateCorrelation(MA,design,ndups=2,spacing=1)
fit <- lmFit(MA,design,ndups=2,spacing=1,correlation=cor$consensus.correlation)
fit <- eBayes(fit)
[1] 15 11

So there are 15 genes with p.values less than 0.05. Now using classifyTestsP:

x<-classifyTestsP(fit,p.value=0.05, method="holm")
[1] 235

there appears to be 235.

What am I doing wrong?

Thanks a lot,
Laurentiu Tarca

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