Dear BioC, I would greatly appreciate your help if you could help me out in setting up design and contrast matrix for the following experimental set up; I have 5 groups of samples with their WT (ES) type, Differentiated type and Differentiated_purified( with puromycin treatment on differentiated to have pure cells)type. To make it clear aES, aDiff, aDiff_pure, bES, bDiff, bDiff_pure, cES, aDiff, cDiff_pure, dES, dDiff, dDiff_pure, eES, eDiff, eDiff_pure. All are with biological triplicates. I wish to model interaction (two way anova) using limma package's lmFit function (differentiation and pure_treatment) to find out the effect of Differentiation and Differentiated_purification. With regard to differentiation, I would try with setting the level; Diff<-factor(c(1,1,1,2,2,2,2,2,2,1,1,1,2,2,2,2,2,2,1,1,1,2,2,2,2,2,2,1 ,1,1,2,2,2,2,2,2,1,1,1,2,2,2,2,2,2)) - Here all WT as 1 and other as 2. Is it right?. With regard to differentiated_purification, Diff_pure<-factor(c(1,1,1,1,1,1,2,2,2,1,1,1,1,1,1,2,2,2,1,1,1,1,1,1,2, 2,2,1,1,1,1,1,1,2,2,2,1,1,1,1,1,1,2,2,2)) - WT and Diff as 1 and Diff_purified as 2. design<-model.matrix(~Diff+Diff_pure) Is it right?. and how to set the model if I wish to have the interaction effect between Diff and Diff_pure?. Please help me out in setting up the Contrast matrix too; Is it right? contrast.matrix <- makeContrasts( ,level=design)). I am in need of your valuable and timely help , please help me out. Thanking you in advance, antony