Hi BioC, In a discussion with the same title as this Gordon advised the following for working with one colour data. 1. Use read.maimages() with dummy arguments for R & Rib 2. Background correct as usual using background Correct() 3. Normalize the GR$G matrix using normalizeBetweenArrays() 4. Use log2(RG$G) as input to lmFit() etc. In the 4th step log2(RG$G) as input if I use normalizeBetweenArrays first there is no $G component of the object to use as the input of lmFit(). That issue could be completely unrelated to the next. I'm trying to find differentially expressed genes between 2 arrays > R25 = cbind(R[,2], R[,5]) Have tried both of > RR25 <- normalizeBetweenArrays(R25$R, method="quantile") > RR25 <- normalizeBetweenArrays(R25, method="quantile") Then continue through to > g <- paste(R25$targets$SlideNumber) > g <- factor(g) > design <- model.matrix(~0+g) > colnames(design) <- levels(g) > fit <- lmFit(log2(R25), design) > cont.matrix<- makeContrasts(OneVFour="A9802-A9811",levels=design) > fit2 <- contrasts.fit(fit, cont.matrix) > fit2 <- eBayes(fit2) Error in ebayes(fit = fit, proportion = proportion, stdev.coef.lim = stdev.coef.lim) : No residual degrees of freedom in linear model fits Whatever I pass into normalizeBetweenArrays be it R25$R or R25 I have nothing to analyse by the time I get to the eBayes function. Is this related to me not following what Gordon advised correctly? I am doing something wrong in the differential expression analysis? Is it duff data? Any ideas? Thanks Elliott This message has been scanned for viruses by BlackSpider...{{dropped:3}}