On Fri, Oct 23, 2009 at 7:00 AM, Vijay Kumar <viku781@gmail.com> wrote:

> 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.
>
>
Hi, Vijay.  This is covered in the limma User Guide pretty thoroughly.  That
said, what you did below looks OK at a quick glance.

Sean


> 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@gmail.com> wrote:
> >
> >
> > On Fri, Oct 23, 2009 at 5:44 AM, Vijay Kumar <viku781@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
> >
> >
>

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