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 [[alternative HTML version deleted]]