
Thanks for the suggestion, Gordon. I really appreciate it.

> Date: Sun, 24 Apr 2011 09:37:37 +1000
> From: smyth@wehi.EDU.AU
> To: genome1976@hotmail.com
> CC: bioconductor@r-project.org
> Subject: [BioC] LIMMA: donor effect
> 
> Dear Som,
> 
> The usual way to deal with the donor effect is to include a factor for 
> donor in the design matrix.  This ensures that all your comparisons are 
> made within donor:
> 
>    design <- model.matrix(~Donor+Dose*Time)
> 
> Usually I would prefer to correct for the batch effect in the design 
> matrix, rather than pre-correcting with ComBat, because it ensures that 
> the degrees of freedom reflect that fact that batch correction the has 
> been done.
> 
> Best wishes
> Gordon
> 
> > Date: Fri, 22 Apr 2011 13:49:59 -0400
> > From: somnath bandyopadhyay <genome1976@hotmail.com>
> > To: <genome1976@hotmail.com>
> > Cc: bioconductor-bounces@r-project.org, bioconductor@stat.math.ethz.ch
> > Subject: [BioC] LIMMA: donor effect
> >
> >
> > I am trying to analyze microarray data for a project where whole blood 
> > was collected from 4 different donors and was treated with a compound at 
> > 2 time-points at 4 different doses. I am interested in genes that are 
> > differentially regulated with dose, with time and also dose*time. When I 
> > run a PCA on the entire data, the separation of groups is mainly by 
> > donors. How do I run a limma analysis (factors, design matrix) to get to 
> > the genes of interest (mentioned earlier)? I am not interested in genes 
> > that are differentially expressed across donors. Any suggestion would be 
> > greatly appreciated.
> >
> > Thanks,
> > Som.
> >
> > Would it be O.K. to use ComBat to get rid off donor effects by treating 
> > each donor as a batch?
> 
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