Dear all, I am trying to write the R code for the analysis of a microarray experiment involving both technical replication and common reference design. The targets file is: --------------------------------------------------------------------- FileName Cy3 Cy5 Array1A.gpr Ref1 WT1 Array1B.gpr Ref1 WT1 Array2A.gpr Ref2 WT2 Array2B.gpr Ref2 WT2 Array3A.gpr Ref3 MU1 Array3B.gpr Ref3 MU1 Array4A.gpr Ref4 MU2 Array4B.gpr Ref4 MU2 --------------------------------------------------------------------- I am interested in the comparison MU vs WT. "Ref" is a RNA universal used here as common reference. Numbers indicate the technical groups. I already wrote a piece of R code based on the limma users guide but I am not sure if I did it well (I am not an statistician) Could you please tell me if the script below is correct? if not, how may I change it? Thanks in advance, ...and thanks to Dr. Gordon Smyth and cols. for limma package! The R code: --------------------------------------------------------------------- library(limma); targets<-readTargets("Targets.txt"); RG<-read.maimages(targets$FileName,columns=list(Rf="F635 Median", Gf="F532 Median", Rb="B635 Median", Gb="B532 Median"),annotation=c("Block","Row","Column","ID","Name")); RG<-backgroundCorrect(RG,method="normexp",offset=50); MA<-normalizeWithinArrays(RG,method="loess"); MA<-normalizeBetweenArrays(MA,method="quantile"); design<-cbind(MU1vsRef3=c(0,0,0,0,1,1,0,0),MU2vsRef4=c(0,0,0,0,0,0,1,1 ),WT1vsRef1=c(1,1,0,0,0,0,0,0),WT2vsRef2=c(0,0,1,1,0,0,0,0)); fit <- lmFit(MA,design); cont.matrix<-makeContrasts(MUvsWT=((MU1vsRef3+MU2vsRef4)/2-(WT1vsRef1+ WT2vsRef2)/2),levels=design); fit2<-contrasts.fit(fit,cont.matrix); fit2<-eBayes(fit2); topTable(fit2,adjust="BH"); --------------------------------------------------------------------- Supplementary material: The design matrix generated: > design MU1vsRef3 MU2vsRef4 WT1vsRef1 WT2vsRef2 [1,] 0 0 1 0 [2,] 0 0 1 0 [3,] 0 0 0 1 [4,] 0 0 0 1 [5,] 1 0 0 0 [6,] 1 0 0 0 [7,] 0 1 0 0 [8,] 0 1 0 0 The contrast matrix generated: > cont.matrix Contrasts Levels MUvsWT MU1vsRef3 0.5 MU2vsRef4 0.5 WT1vsRef1 -0.5 WT2vsRef2 -0.5 All the best, Juan Carlos Oliveros BioinfoGP, CNB-CSIC