[BioC] Differential gene expression of a cluster or group of genes

Gordon K Smyth smyth at wehi.EDU.AU
Sun Nov 10 11:19:15 CET 2013

The function you are trying to remember may be



> Date: Thu, 7 Nov 2013 14:13:38 +0100
> From: January Weiner <january.weiner at gmail.com>
> To: Bioconductor mailing list <bioconductor at r-project.org>
> Subject: [BioC] Differential gene expression of a cluster or group of
> 	genes
> Hello,
> this sounds like a rather trivial question but somehow the an answer 
> eludes me. I am analysing gene expression data with limma in a 
> two-factor model with interactions. No problems there.
> What I would like to do is to first cluster the genes (using my own 
> clustering procedure that I'm working on), and then search for clusters 
> that are differentially expressed (e.g. factor A is significant in 
> cluster X, or interaction is significant in cluster Y etc.). I have 
> concocted my own bootstrapping procedure, but would prefer to use an 
> established tool if possible.
> I remember that there was a tool or package for randomisation-based GO 
> analysis in R which allowed to specify arbitrary linear models for 
> comparisons, but can't seem to be able to find it right now.
> On the other hand, I could treat the assignments to clusters like 
> assignments to GO categories and just test the significant genes for 
> enrichment.
> Which approach and which package would you recommend?
> j.
> -------- January Weiner --------------------------------------

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