Hi, Is there an easy way to merge data from a fit object (from lmFit) and MA data (from normalizeWithinArrays) based on the genes? I mean, I want the p values from the fit object and the different M values (each column represents an original file), matching the data based on fit$gene or MA$gene. Basically, what I have now is: targets <- readTargets(targetFile) RG<-read.maimages(targets$FileName,columns=list(Rf="C5_Signal_Median", Rb="C5_Signal_SD",Gf="C3_Signal_Median",Gb="C3_Signal_SD"),annotation= c('Sel_Crt','Probe_Seq','Feature_ID')) RG.noBG <- backgroundCorrect(RG,method='none') MA.lnorm <- normalizeWithinArrays(RG.noBG, method="loess") design <- modelMatrix(targets,ref="Reference") fit<-lmFit(MA.lnorm,design) fit<-eBayes(fit) I could use the merge() function, but then I don't know before hand how many data files are being read with read.maimages. Thanks, G