Hello I have received some cDNA arrays to analyze with very few genes on them. There are only 32 different genes, each of which has been spotted on each array 8 times. There are also some (not many more controls and spikein spots). It is a reference design with unbalanced dye-swap based on biological replicates intended to compare three mutant types to a wild type. I didn't suggest it, just received the data after the experiment was performed (so I may be able to say what it died of :-) The design is as follows Array Cy3 Cy5 1 Mut-1 Wild 2 Mut-1 Wild 3 Wild Mut-1 4 Mut-2 Wild 5 Mut-2 Wild 6 Wild Mut-2 7 Mut-3 Wild 8 Mut-3 Wild 9 Wild Mut-3 My questions are: 1-How should I normalize the data? I ususally use marrayNorm with print-tip lowess, but I think this may not be adequate having so few spots. Another question refers to dye-swap normalization. I have read in some bioconductor courses slides that a self normalization may be adequate for dye-swap experiments. In this case a normalized estimate of the log ratio is obtained M values (1/2 (M-M')). My questions are 2- Doesn't it imply some information loss? I mean is it truth that for for every two arrays I only get an estimate? I may be missing something but I don't know what... 3-How should I manage the assimetry in dye swap? It seems unreasonable having first to average slides 1 and 2 and the combine it with three... Any help or reference will be great Thanks Teresa Casals ______________________________________________ Renovamos el Correo Yahoo!: ?100 MB GRATIS! Nuevos servicios, m?s seguridad