Dear all. I have used Limma to analyse my data and I got no differentially expressed genes correcting with multiple testing using fdr. Then a colleague of mine analysed the data and used samr, the package by the guys from Stanford, http://www-stat.stanford.edu/~tibs/SAM/ and got ~600 genes with an fdr < 0.05. I immediately thought I had done something wrong in my Limma analysis and double checked a zillion times but I couldn't find any errors. When I compared the ranking for the 1000 most differentially expressed genes of Limma and samr they look very similar with few discrepancies. I attached a picture of the ranking. Then I compared the t-scores for the same genes and they were also almost the same. I also attached an image of that. The scores for Limma are a little bit more significant. Its when I do the adjustment for multiple testing that I get differences (I attached another picture). As I understand it the fdr level for a certain delta-cutoff is in samr approximated by balanced permutations of the two groups. Thereby one can find out the median number of differentially expressed genes comparing the two groups in e.g. 100 permutations which is the fdr for that level. In Limma the general fdr definition by Benjamini & Hochberg is used if I understand it right. I was really surprised that I got so different results using the same correction for multiple testing, whereas one is based on permutation of the same data and the other is based on the old Benjamini definition. What is more correct in this situation? I would really appreciate if someone could give me some advice. Best regards, Johan ? ? ? sessionInfo() R version 2.7.0 (2008-04-22) i386-apple-darwin8.10.1 locale: sv_SE.UTF-8/sv_SE.UTF-8/C/C/sv_SE.UTF-8/sv_SE.UTF-8 attached base packages: [1] splines tools stats graphics grDevices utils datasets [8] methods base other attached packages: [1] samr_1.25 impute_1.0-5 AnnBuilder_1.18.0 [4] XML_1.95-2 siggenes_1.14.0 multtest_1.20.0 [7] survival_2.34-1 KTH.hsOligo.db_1.0.0 hsOligo_2.0.1 [10] kth_1.2.1 geneplotter_1.18.0 lattice_0.17-6 [13] aroma_0.94 R.io_0.37 R.graphics_0.42 [16] R.colors_0.5.3 R.basic_0.49 aroma.light_1.8.1 [19] R.utils_1.0.2 R.oo_1.4.3 R.methodsS3_1.0.1 [22] limma_2.14.5 annotate_1.18.0 xtable_1.5-2 [25] AnnotationDbi_1.2.2 RSQLite_0.6-9 DBI_0.2-4 [28] Biobase_2.0.1 loaded via a namespace (and not attached): [1] KernSmooth_2.22-22 RColorBrewer_1.0-2 grid_2.7.0 ********************************************* Johan Lindberg Royal Institute of Technology AlbaNova University Center Stockholm Center for Physics, Astronomy and Biotechnology School of Molecular Biotechnology Department of Gene Technology Visiting address: Roslagstullsbacken 21, Floor 3 106 91 Stockholm, Sweden Delivering address: Roslagsv?gen 30 B 104 06 Stockholm, Sweden Phone (office) +46 8 553 783 44 Fax + 46 8 553 784 81 http://www.ktharray.se/ http://www.arrayadvice.se/ *********************************************