Hi, I'm analyzing a dataset of 50 samples. Each of these samples has a dye-swapped replicate. All the replicates are side by side in the dataset (1, -1, 2, -2, 3, -3, etc...) I'm interested in some contrasts between predefined groups. I built a design matrix with the 1 and -1 that correspond to the samples (without or with dye-swap) belonging to a each group (sick1, sick2, sick3): sick1 sick2 sick3 1 0 0 -1 0 0 0 1 0 0 -1 0 1 0 0 -1 0 0 0 0 1 0 0 -1 0 0 1 0 0 -1 ... .. But this is not enough to proceed the analysis, because the 1s and -1s are replicates. So I tried to estimate the correlation within replication block: biolrep <- c(1,1,2,2,3,3,..... 50,50) corfit <- duplicateCorrelation(data, design, ndups = 1, block = biolrep) And I have corfit$consensus = -0.84 (good, they are dye swapped) And I fit the model fit <- lmFit(data, design, block = biolrep, cor = corfit$consensus) Then I create and extract my contrasts: cont.matrix <- makeContrasts( sick1.2 = sick1-sick2 ...etc) fit2 <- contrasts.fit(fit, cont.matrix) fit2 <- eBayes(fit2) I'm not sure I understood very well everything. There's some mistakes I'm making? Any suggestion will be really appreciated... Thanks Giulio _________________________________________________________________ [[alternative HTML version deleted]]