Hi Sabrina.
This is really a limma question, not an aroma.affymetrix one, but I'll
take a quick stab. Basically, you'll notice that regardless of the
value you set for 'p', you'll get the same t-statistics and p-values.
It only changes the B values (posterior log odds).
Cheers,
Mark
On 9-Jan-10, at 1:14 AM, sabrina wrote:
Hi, all:
A quick question. I know after we extract frima score, I should use
eBayes to do the following:
assume we have design matrix and contrast matrix,
fit<-lmFit(exFirma,design)
fit2<-contrasts.fit(fit,cont.matrix);
fit2<-eBayes(fit2,proportion=p);
the default setting for p is 0.01 that is for gene expression. Is 0.01
also a good guess for this firma score purpose? Or should I use 0.001
or some other values? Thanks!
Sabrina
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Epigenetics Laboratory, Garvan
Bioinformatics Division, WEHI
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