Dear all, We have performed a time-series experiment (2h, 6h, 10h, 48h, ) on dual-channel arrays where we want to compare gene expression between treated and time-matched untreated cells. For every time-point three hybridizations were performed including one dye-swap. Each time-course was hybridized at the same time. So for a given time point we have 3 different microarrays comparing: Tx -> Ux Tx ->Ux Ux ->Tx T=treated cells?; U=untreated cells at corresponding time-point?; x=given time-point. Is it possible in this case (unbalanced design) to use randomized blocks in LIMMA to estimate variability between the three microarray batches (time-courses)? If affirmative, the R code I would use looks as follows: > design = cbind( T2vsU2=c(1,1,-1,0,0,0,0,0,0,0,0,0), > T6vsU6=c(0,0,0,1,1,-1,0,0,0,0,0,0), > T10vsU10=c(0,0,0,0,0,0,1,1,-1,0,0,0), > T48vsU48=c(0,0,0,0,0,0,0,0,-0,1,1,-1)) > blocks = c( 1,2,3,1,2,3,1,2,3,1,2,3) > dupcor = duplicateCorrelation(MA, design=design, block=blocks) Is this piece of code appropriate to model the randomized blocks (the three time-courses)? Many thanks in advance, Serge Serge Eifes Laboratoire de Biologie Moleculaire et Cellulaire du Cancer (LBMCC) Hopital Kirchberg 9,rue Edward steichen L-2540 LUXEMBOURG