I have another related question regarding contrast design in this
"tissue-specific expression" framework. I get different results if I merge
several tissues into one group in the contrast matrix instead of assigning
each tissue a unique group. I think redesigning the contrast like this
simplifies the model and hence explains the difference in results.

Here is the new contrast design:
z = as.character(y$samples$group)
z[which(z != "tissue1")] = "group2"   # <-- label everything not tissue1 as
group2
z[which(z == "tissue1")] = "group1"  # <-- keep tissue1 as a separate
label, group1
#Design the new contrast matrix to find diff exp between group1 and group2
fac = factor(z)
design = model.matrix(~0+fac)
colnames(design) = levels(fac)
cont.matrix = makeContrasts(diff=group1 - group2, levels = design)

I cannot determine if the results are better or worse by looking at the top
genes. Should I really be consolidating disparate tissues like this, or is
the model richer by keeping all tissues separate?

Thanks,
Jaaved

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