Pedro, > I do not know if there is any forum where to ask people or > share experience about this package. The best place to discuss affylmGUI is on the Bioconductor mailing list: http://www.bioconductor.org/mailList.html https://www.stat.math.ethz.ch/mailman/listinfo/bioconductor I hope you don't mind that I've copied my reply to the mailing list, in case anyone out there wants to improve upon my answers. > In the table with ranked genes differentially express what is > the column M and A? are the values for the M A plot blot??? The terms M and A are most well known in the two-color microarray literature, e.g. see: http://www.statsci.org/smyth/pubs/mareview.pdf but they can also be applied to Affymetrix arrays. M is a log ratio comparing gene expression levels. (Base 2 is used for the logarithm) e.g. log_2(Mutant_expr_level/WildType_expr_level) A is an average log intensity. (Again, the logarithm is in base 2) Obviously, you can't get absolute gene expression levels from microarrays. For two-color arrays, the A value will depend on the scanner intensity. For two-color arrays it is actually a little confusing because we use M to mean a log-ratio between the Red and Green channels on one array, but later after we have averaged between replicate arrays (or more formally, after we have fitted a linear model), then we use M to mean a log-ratio between gene expression levels (e.g. comparing Treatment vs Control or Wild-Type vs Mutant). An M value of positive 1 means a fold-change of 2 and an M value of -1 means a fold-change of 0.5 (or equivalently, a fold-change of 2 in the other direction). If you want to convert the M column to fold-changes you can use =2^M in Excel, e.g. if the M column is column "E" and the first M value was in cell E2, then you could create a column G entitled "Fold Change", and in cell G2, you could type the formula: =2^E2 and then fill-down. (I'm assuming that you know how to get the toptable into Excel by first saving as tab-delimited text.) FDR is False Discovery Rate, a method for multiple-testing correction. I think the default method in limma, limmaGUI, affylmGUI is: Holm, S. (1979). A simple sequentially rejective multiple test procedure. _Scandinavian Journal of Statistics_, *6*, 65-70. For references to other multiple-testing correction methods, from the R prompt, type: ?p.adjust Hope this helps, James ---------------------------------------------------------------------- ---- James Wettenhall Tel: (+61 3) 9345 2629 Division of Genetics and Bioinformatics Fax: (+61 3) 9347 0852 The Walter & Eliza Hall Institute E-mail: wettenhall@wehi.edu.au of Medical Research, Mobile: (+61 / 0 ) 438 527 921 1G Royal Parade, Parkville, Vic 3050, Australia http://www.wehi.edu.au