On Mon, May 11, 2009 at 7:53 AM, John Herbert <j.m.herbert@bham.ac.uk>wrote:

> Hello.
> I have 6 gpr files, 3 from cancer and 3 from normals. I have normalised
> them with printtiplowess and removed the control spots. My question is about
> finding differentially expressed genes with Ebayes. I have run the code
> below and get some strange results that are very different to using Samr. I
> am thinking I trust samr more as when I look at the results by eye, they
> seem to order the genes coffectly based on fold ratio. However, it could be
> that I am not using ebayes correctly.
>
> So, the design is supposed to represent cancer (the 1s) and normal (the
> 2s). Is this the correct way to construct a design matrix? I want to compare
> gene expression between cancer and normal (3 replicates each).
>
> design <- model.matrix(~factor(c(1,1,1,2,2,2)));
>
> fit <- lmFit(probes_only.imp, design);
>
> fit <- eBayes(fit);
>
> probes_only.imp_50_ebayes <- topTable(fit, n=20);
>

Hi, John.  I think you will need to include a contrast matrix in your
calculations.  Refer to the Limma user guide for details.

Sean

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