[BioC] interaction effect (4x2)
seb at gerega.net
Thu Feb 28 04:24:33 CET 2008
I am having trouble setting up the design for a microarray analysis.
It involves 40 samples that are split into 4 groups and are treated in
one of 2 ways.
What I want to do is identify genes with an interaction effect between
group and treatment.
What would the best way to go about this? I have attempted the following:
interDesign = model.matrix(~factor(sDrug) * factor(sGroup))
interFit = lmFit(lumi.N.P, interDesign)
interCont = cbind(c(0,0,0,0,0,1,0,0),c(0,0,0,0,0,0,1,0),c(0,0,0,0,0,0,0,1))
interFit = contrasts.fit(interFit, interCont)
interFit = eBayes(interFit)
interDTest = decideTests(interFit, method="nestedF",
which(abs(interDTest[,1]) == 1 | abs(interDTest[,2]) == 1 |
abs(interDTest[,3]) == 1)
Is this a suitable way to identify the genes with an interaction effect?
So far, from looking at expression profiles, I don't seem to be picking
out interesting genes....
Any help would be greatly appreciated.
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