Hi- I have an Affy array experiment that I am analyzing that contains matched samples from separate patients. For each patient, there are 4 arrays which comprise a 2x2 factorial design (two tissues and two treatments). I wanted to incorporate both a paired/matched type approach to the limma design matrix and also the factorial nature or the experiment. I looked at the vignettes and came up with the following. Note: SID refers to the sample ID Here's my code: design <- model.matrix(~SID+(treatment*tissue)) design (Intercept) SID1 SID2 SID3 SID4 TreatmentA tissueB TreatmentA:tissueB 1 1 0 1 0 0 0 1 0 2 1 0 1 0 0 1 1 1 3 1 0 1 0 0 0 0 0 4 1 0 1 0 0 1 0 0 5 1 0 0 0 0 0 1 0 6 1 0 0 0 0 1 1 1 7 1 0 0 0 0 0 0 0 8 1 0 0 0 0 1 0 0 9 1 1 0 0 0 0 1 0 10 1 1 0 0 0 1 1 1 11 1 1 0 0 0 0 0 0 12 1 1 0 0 0 1 0 0 13 1 0 0 1 0 0 1 0 14 1 0 0 1 0 1 1 1 15 1 0 0 1 0 0 0 0 16 1 0 0 1 0 1 0 0 17 1 0 0 0 1 1 1 1 18 1 0 0 0 1 0 1 0 19 1 0 0 0 1 1 0 0 20 1 0 0 0 1 0 0 0 arrayw <- arrayWeights(eset, design = design) fit <- lmFit(eset, design, weights=arrayw) contrast.matrix = cbind(ContrastA=c(0,0,0,0,0,1,0,0),ContrastB=c(0,0,0,0,0,1,0,1), ConstrastDiff=c(0,0,0,0,0,0,0,1)) fit2 <- contrasts.fit(fit, contrast.matrix) fit3 <- eBayes(fit2) Does this look correct? ContrastA extracts the treatment difference for one tissue ContrastB extracts the treatment difference for the other tissue ContrastDiff extracts the interaction between the two and therefore the genes that differ with treatment between the two tissues Thanks, Fraser