[BioC] LIMMA adjusted P Values

[Vijay Kumar]

Dear Sean,

I will definitely go through the documentation of topTable. But could
you please help me with the design of the
expreiment.

I have 2 control and 2 treated.

Below is my design

         design <- model.matrix(~ -1+factor(c(1,1,2,2)))
	 colnames(design) <- c("group1", "group2")
	 contrast.matrix <- makeContrasts(group2-group1,levels=design)

	 fit <- lmFit(data2.log, design)
	 fit2 <- contrasts.fit(fit, contrast.matrix)
	 fit2 <- eBayes(fit2)
         top <- topTable(fit2, coef=1, adjust="fdr", sort.by="P")

Thanks,
Vijay

On Fri, Oct 23, 2009 at 4:14 PM, Sean Davis <seandavi at gmail.com> wrote:
>
>
> On Fri, Oct 23, 2009 at 5:44 AM, Vijay Kumar <viku781 at gmail.com> wrote:
>>
>> Dear All,
>>
>> The topTable of LIMMA is returning adjusted P Values which are all
>> equal to 1. What does that mean. am I doing some thing wrong. Someone
>> please help me understand about adjusted P Values of LIMMA.
>>
>
> Hi, Vijay.  You will want to read the help for the topTable() function.  It
> explains how the adjustment is done.
>
> All the adjusted p-values equal to 1 suggests that there is no differential
> expression detected in your experiment.
>
> Sean
>
>