Dear Gurus, I am attempting to analyze a bunch of microarray experiments from the GEO database. I have experience with Affymetrix chips, so it was reasonably simple to download the datasets/series of interest, retrieve the relevant columns from the GSM files (figure out whether they were normalized, logged, etc), and perform the comparisons I need using limma. Now I am struggling to do the same for other platforms, in particular, two-color platforms. The first few such experiments I have looked at look reasonably simple. However, I aven't been able to figure out how to obtain a data structure that lmFit can use from the GSM files. I decided to try the GEOquery package to interface with GEO. gse <- getGEO("GSE2998") exprs <- exprs(gse[[1]]) The exprs matrix now contains the VALUE column from each GSM file, which in this particular case is "The log2-transformed ratio of the Lowess-normalized fluorescence values (Ch2/Ch1) exported from GeneTraffic". For one of the comparisons that I am interested in, there are two chips of relevance. GSM65523, with treated Cy3 and untreated Cy5 GSM65567, with treated Cy3 and untreated Cy5 I thought that the best way to compare treated to untreated would be something like: targets <- matrix(c("GSM65523", "noHS", "HS", "GSM65567", "noHS", "HS"), ncol=3, byrow=TRUE, dimnames=list(NULL, c("SlideNumber", "Cy3", "Cy5"))) design <- modelMatrix(targets, ref="noHS") lmFit(exprs, design) But, of course, exprs doesn't contain any channel info, just the log ratio between the channels. Should I be retrieving different columns from the GSM files? How can I build a data structure from that data that lmFit can use? Is there a better way to do simple comparisons of two-channel GEO datasets? Thank you so much for any help you can provide! Best, Ana