[BioC] duplicateCorrelation and day effect in limma

[Naomi Altman]

You could do it either way, and your use of duplicateCorrelation is correct.

--Naomi

At 07:57 AM 6/28/2006, Pedro López Romero wrote:
>Dear list,
>
>I have a simple doubt concerning how I should deal with the *replicate day*
>effect using limma.
>It is clear that I have a *day effect* in my data that it has to be taken
>into account in the model. I am using 2 different model specifications and I
>do not know if one of them is correct.
>
>
>a) A first solution is simply to include in the model the *day effect* as an
>additional fixed effect. I will assume that there is not interaction between
>*day effect* and *treatment effect*, so my design matrix will be of the
>form:
>
>     design=model.matrix(~  - 1 +  factor(treatment) + factor(day) )
>
>     fit=lmFit(eset,design)
>
>
>b) My question is if I can take into account the *day effect* as random
>effect using duplicateCorrelation.
>
>        famrep=c( 
)
>         corfit=duplicateCorrelation(eset,ndups=1,block=famrep)
>
>        design=model.matrix(~  - 1 +  factor(treatment))
>
>        fit=lmFit(eset,design,block=famrep,cor=corfit$consensus)
>
>
>        Would be this second approach a valid one?
>
>
>
>
>I will appreciate any comment on this.-
>Thanks a lot.-
>
>Pedro
>
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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111