Hi all, usually I analyze my MS data (around 3,000 proteins, 4 replicates (too little?) using benjamini hochberg correction for multiple testing. (or permutation based q value calculation however the comp.fdr function (DEDS package) gives me different raw p value then i get using normal t.test (same properties uneq var, unpaired) - they seem to be already corrected (same value appears multiple times)) Anyway i was wondering whether i can use the SAM package as it is? And furthermore, why the max q value is 0.35 (and not 1?). Shouldnt be there proteins/genes that would be called significantly changed if we had applied a FDR of 1. Sorry if this question is kinda silly .. SAM Analysis for the Two-Class Unpaired Case Assuming Unequal Variances s0 = 0.0382 (The 10 % quantile of the s values.) Number of permutations: 70 (complete permutation) MEAN number of falsely called variables is computed. Delta p0 False Called FDR cutlow cutup j2 j1 1 0.1 0.407 2433.900 2781 0.3563 -0.222 0.170 1354 1623 2 1.1 0.407 52.900 581 0.0371 -2.095 2.199 327 2796 3 2.2 0.407 3.800 96 0.0161 -3.866 3.881 50 3004 4 3.2 0.407 1.286 36 0.0145 -5.316 5.120 16 3030 5 4.2 0.407 0.514 15 0.0140 -6.751 6.412 7 3042 6 5.3 0.407 0.186 5 0.0151 -8.386 10.158 4 3049 7 6.3 0.407 0.157 4 0.0160 -8.985 10.158 3 3049 8 7.3 0.407 0.057 2 0.0116 -11.773 Inf 2 3050 9 8.4 0.407 0.057 2 0.0116 -11.773 Inf 2 3050 10 9.4 0.407 0.043 1 0.0174 -12.454 Inf 1 3050 For a FDR cutoff of o.05 i can either use the find delta function or just pick 1.1 to be on the safe site. BEsts