[BioC] limma and blocks

[Fangxin Hong]

I haven't use the "block"option myself, but I believe those two models are
different. Model 1 treats your block effect as random effect, and model 2
treats it as a fixed effect. If that is the case, your model 1 should fits
the data better, as block usually treated as random effect with mean 0.

Please indicate if I am wrong or anyone knows this issue better.

Fx


> Model 1:
>
> biorep <- c(rep(1,16),rep(2,16))
>
> fit <- lmFit(mydata, design, block= biorep)
>
> fit <- eBayes(fit)



> ...
>
>
>
> Model 2:
>
> blockdiff <- c(rep(1,16),rep(-1,16))
>
> blockdesign <- cbind(design, Block=blockdiff)
>
> fitblock <-lmFit(mydata, blockdesign)
>
> fitblock <- eBayes(fitblock)
>
> ...
>
>
>
> I would appreciate any tip that could put me in the right track!
>
>
>
> Thanks,
>
>
>
> Françoise
>
>
>
>
>
>
>
>
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-- 
Fangxin Hong, Ph.D.
Plant Biology Laboratory
The Salk Institute
10010 N. Torrey Pines Rd.
La Jolla, CA 92037
E-mail: fhong at salk.edu