Thanks for replying Professor Smyth. I think my lengthy original post was
confusing. I have 18 tissues and I'm trying to design the contrast to find
the genes enriched/depleted in the 18th tissue (as compared to the average
of the other tissues). In the example at http://permalink.gmane.org/**
gmane.science.biology.**informatics.conductor/47950<http://permalink.gmane.org/gmane.science.biology.informatics.conductor/47950>,
you had to specially handle the 18th tissue in edgeR and I was curious how
to do this in limma. I think I've found the solution which return expected
results. If you see something wrong, please correct me.

#Limma
cont <- rep(-1,18)
cont[1] <- 0
fit2 <- contrasts.fit(fit, contrasts=cont)
fit2 <- eBayes(fit2)
top18 <- topTable(fit2, adjust="BH", sort="p")

which seems to be the analogous code to:

#edgeR
cont <- rep(-1,18)
cont[1] <- 0
ql <- glmQLFTest(fit, contrast=cont)
top18 <- topTags(ql)

Thanks,
Jaaved

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