I am analysing affymetrix chips. I have 4 ethanol treated chips and 5 water treated chips. I wanted to find which genes are differentially expressed when exposed to ethanol. Using the limma using guide I have got this code so far ==================================================== files <- c("E2h_1.CEL", "E2h_2.CEL", "E2h_3.CEL", "E2h_4.CEL","W05h_1.CEL", "W0h_1.CEL", "W2h_1.CEL", "W2h_2.CEL", "W4h_1.CEL") Data <- ReadAffy(filenames = files) Data_gcrma <- gcrma(Data) type <- c("eth","eth","eth","eth","wat", "wat", "wat", "wat", "wat") design <- model.matrix(~factor(type)) colnames(design) <- c("Eth", "Wat_vs_Eth") fit<-lmFit(Data_gcrma,design) fit <- eBayes(fit) options(digits=2) topTable(fit,coef=2, n=50, adjust="fdr") ============================================================ printing the design matrix gives Eth Wat_vs_Eth 1 1 0 2 1 0 3 1 0 4 1 0 5 1 1 6 1 1 7 1 1 8 1 1 9 1 1 attr(,"assign") [1] 0 1 attr(,"contrasts") attr(,"contrasts")$"factor(type)" [1] "contr.treatment" What I want to know is do I have the design matrix the correct way round? Are the positive M values printed from topTable those upregulated on exposure to ethanol compared to water? Cheers Sue