[BioC] LIMMA adjusted P Values

[Vijay Kumar]

Dear Sean,

Thank you so much for having look at my design.

Regards,
Kishor

On Fri, Oct 23, 2009 at 4:36 PM, Sean Davis <seandavi at gmail.com> wrote:
>
>
> On Fri, Oct 23, 2009 at 7:00 AM, Vijay Kumar <viku781 at 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 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
>> >
>> >
>
>