Dear Arvid,

you can check for yourself: if what you see is a result of limma's
eBayes() step then the logFC's of your two analyses should remain
the same while t-statistics and p-values etc. should improve when
using all of your data.

Cheers,

 - axel



On Thu, Jul 17, 2014 at 3:59 PM, Arvid Sondén <arvid.sonden@gu.se> wrote:

> Dear all,
>
> I am currently working with gene expression analysis in limma. I have a
> total of 146 samples divided into 21 groups. What I want to do is pairwise
> comparisons between one group (the control group) and the others. The
> following code shows this for the first pairwise comparison between group B
> and the control group, also adding batch effects to the model. All groups
> are included in the "Group" variable.
>
> design <- model.matrix(~0+Group+Batch)
> fit<-lmFit(y$E,design)
> cont  <- makeContrasts( " GroupB- GroupControl", levels=design)
> fit <- contrasts.fit(fit, cont)
> fit <- eBayes(fit)
> tt <- topTable(fit, adjust="BH",  coef=" GroupB-GroupControl ",
> genelist=y$genes, number=Inf)
>
> >From the beginning I was only working with this first comparison, and was
> only using the data from group B and the control group. Now I have extended
> this to all the data and all the pairwise comparisons. Since I am using all
> of the data in the lmFit function the fit is different from before when I
> was only using a part of the data. What makes me confused is that the
> difference is quite large. Now I have 1378 significant genes compared to
> 203 before for the GroupB-GroupControl comparison after the BH correction.
>
> Is there a possible limma specific explanation for this? I have read the
> documentation on the functions, and the limma user's guide, but I can't say
> that I have fully understood what is going on inside the lmFit function. On
> a more conceptual level I understand that the linear model will change when
> I add new data and new variables, but it seems to be a too large change in
> my eyes since the actual comparison is still the same.
>
> Best regards,
>
> Arvid
>
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>



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Axel Klenk
Research Informatician
Information Management Drug Discovery

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