* I've been using the affy package for a few days, and found it very well made, and really useful. By the way, thanks to all of yours for building a well documented and coherent software collection, which remains somewhat rare in the microarray domain, everyone tending to write it's own little program... * Yesterday, after switching to the 1.0 version (on Win2K / R1.5.0) , I experienced the following problem while fitting the Li & Wong Model : // liw2 = express(pl1, normalize = F, summary.stat = li.wong) // Background correcting // Preparing Data // Computing expression. This may take a while. // Error in data.matrix[, !phi.outliers] %*% phi[!phi.outliers] : // non-conformable arguments What does this error mean ? I had no problem when applying the default summary.stat with affy 1.0 and the same plobe level object. I had no problem either with the former version, the same plob and Li.Wong . Thank you in advance. JS, * PS. One minor thing maybe somebody can help me with : I have 12 yeast chips to analyse and the experimental design is quite well suited for ANOVA (1 factor A with 2 levels, 1 factor B with 3 levels, 2 reps C for each). I tried 'lm' and 'aov' on R but encountered serious memory problems despite setting memory.limit(size = 4000) and having 1GoRam plus a lot of free hard drive. I tried 'anovan' from Matlab Stat Toolbox, which of course resulted in a complete failure. In fact I'm not necesserally interested in fitting a whole model, with thousands of gene effects, but just in calculating the average A, B , C , A*B , A*C , B*C effects. I know it can be done with proc anova on SAS but if it were possible, would prefer to do the whole thing under R. Does anyone know any package or function I could use ?