Dear List, I have a question concerning missing values in limma. Consider the following short example: M = rbind(c(10,9,5,4,5,12,13,7,8),c(10,9,5,4,5,12,13,7,8)) w = rbind(c(1,1,1,1,1,1,1,1,1),c(1,1,1,1,1,0,0,0,0)) class = factor(c(1,1,2,2,2,1,1,2,2)) lab = factor(c(1,1,1,1,1,2,2,2,2)) design = model.matrix(~ 0 + class + lab) contrasts = makeContrasts(contrasts="class1-class2", levels=design) fit = lmFit(M, design=design, weights=w) fit2 = contrasts.fit(fit, contrasts) Obviously, the effect of "lab" can not be estimated for gene 2. All measurements of gene 2 in lab2 have weights = 0. However, the contrast of interest (here class1 - class2) can be estimated by using the observations from lab1, but in the limma-object (fit2 in the example above) the contrast is NA. Can someone explain me whether/why this is sensible? Thanks for your help, Hans-Ulrich