Lots of posts today.... Actually this may also be of interest to others with similar designs. I remember reading on a previous thread that even with low (<3 reps) you could still use a linear model to estimate significant changes. Rather than just ask if this is really possible I decided to do it myself before seeing what others have to say. I know limma shrinks sample variance towards a pooled mean so in principle it should work. I used 7 genotypes, 2 treatments first with 3 replicates and then with just 2 replicates. For contrasts I compared each genotype untreated vs. treated (ebfit p<0.01). On average 3 replica detected 2500 changes, 2 reps detected 60% of these + 15% false +ves. I haven't looked at the effect of fdr correction or including fold change yet, but looking for other opinions. (actual #'s for the 7 comparisons are below). Obviously more reps are better, but the planned analysis isn't my data, just a suggestion for a collegue. Hopefully with a view to lowering the arbitary cutoff from 2x, to include some consistent changes that just miss the cutoff at present. Their design is slightly different - 10-15 treatments + 1 control x 2 reps. Thanks, Matt 3rep Both 2rep 1146 1386 161 1004 1509 248 1103 2006 404 899 1013 185 772 1258 197 958 1887 402 1165 1795 298 Average 1007 1551 271