[BioC] Finding differentially expressed genes using Ebayes

[John Herbert]

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);

Any help appreciated on this, thank you. 

Kind regards,

John.


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Bioinformatics Officer

Molecular Angiogenesis group
First Floor, Institute of Biomedical Research
The University of Birmingham
Medical School
Edgbaston
Birmingham
B15 2TT  (UK)

j.m.herbert at bham.ac.uk

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