Dear James, > Hi Rene, > > On 2/6/2013 11:29 AM, Ren? wrote: >> Dear James, >> >> I performed the pooled analysis as you suggested and compared the >> results to a >> pure B - A comparison (no subgroups specified). Interestingly, both >> analyses >> give different results (497 vs 15 genes with log2FC>= 1 and p< 0.05). >> Could you explain this huge difference? > > If I assume that by a pure B-A comparison you redefined your design > matrix so you only have three columns (A,B,C), and then did the B-A > comparison, then it is simple to explain. I would also guess that the > C-A comparison gives different results as well, depending on how you > define your design matrix. > > Note that the contrast calculates the difference between the means of > the two groups in the numerator and a measure of intra-group > variability in the denominator. So in heuristic terms, the numerator > says how different the groups are, and the denominator tells you if > that difference is 'large' or not, by comparing to the within group > variability. So if the groups are really 'tight' then a small > difference in means might result in a significant test, but if the > groups are really variable then the mean differences have to be pretty > big as well to achieve significance. > > How you define your groups has no bearing on the numerator, because > the difference of B-A is the same if you do B-A or if you do > (B1+B2+B3)/3-A. However, the denominator may well be quite different, > depending on the B1, B2, and B3 groups. > > In the instance where you did (B1+B2+B3)/3-A, the intra-group > variability for the denominator is based in the variability within the > A, B1, B2, B3, and C groups. So if all the B-type groups are pretty > tight, then you will likely get more differentially expressed genes. > > If you do the 'pure' B-A comparison, then the denominator is based on > the intra-group variability of the A,B,C groups. If the B1, B2, B3 > groups are pretty tight, but not really similar, then the combined B > group will be highly variable, so your denominator will tend to be > larger, resulting in fewer differentially expressed genes. Since the > denominator is the same for all contrasts, I would imagine the C-A > comparison has fewer genes as well. > > Does that help? > > Best, > > Jim > >> >> Best regards, >> Ren? Thank you for your very detailed explanation. Unfortunately, I observe the opposite result, so more genes are found when testing B - A than (B1+B2+B3)/3 - A. If I understand your explanation correctly, it means that I select more stringently in case of (B1+B2+B3)/3 - A due to a higher variation between the subgroups. Therefore, lowering the cutoff values would again correct my list of genes. Unfortunately I am doing a meta analysis of two independent data sets and I want to apply the same cutoff values for both data sets. This in turn would increase my second result list (same group comparison, i.e. B - A) from ~ 200 to a couple of thousand genes and thereby also introduce additional noise. Hence my question is: is there a possibility to somehow combine the results of both comparisons? Or is there a way to correct for the increased variance between the subgroups? Best regards, Ren?