Dear all, I used MTP from the multtest package to compute bootstrap based raw and adjusted t-test P values (group 1 = 7 samples, group 2 = 3 samples). Why are some raw P values in the output exactly zero? I could not change this by using scientific notation, with varying number of significant digits. In the example below, 10 digits are used; increasing this does not make a difference. I expected all P values > 0, with the minimum P value determined by the number of bootstrap iterations, here 1000. Hence the raw P value minimum should be 1e-03, as indeed the lowest *positive* P values are. Another question is: why some raw P values that are *equal* correspond to adjusted P values that are *different*? For example, raw P = 1e-03 corresponds to adjusted P = 8.4e-02, 8.6e-02, etc. I could not find the answer in the MTP help page, its vignettes, FAQ, etc. A similar, but not identical, problem was reported on this mailing list before, without a solution: https://stat.ethz.ch/pipermail/bioconductor/2007-December/020492.html Thank you for your help. Best regards, Timur -- Timur Shtatland, PhD Center for Molecular Imaging Research Massachusetts General Hospital 149 13th Street, Room 5408 Charlestown, MA 02129 tshtatland at mgh dot harvard dot edu ############################################################ > B <- 1000 > seed <- 99 > TTBoot <- MTP(X=esetGcrmaExprsFiltered, Y=TT, test = "t.twosamp.unequalvar", alternative = "two.sided", typeone="fdr", method="ss.maxT", fdr.method="conservative", B=B, seed=seed) running bootstrap... iteration = 100 200 300 400 500 600 700 800 900 1000 > print(TTBoot) Multiple Testing Procedure Object of class: MTP sample size = 10 number of hypotheses = 5413 test statistics = t.twosamp.unequalvar type I error rate = fdr nominal level alpha = 0.05 multiple testing procedure = ss.maxT Call: MTP(X = esetGcrmaExprsFiltered, Y = TT, test = "t.twosamp.unequalvar", alternative = "two.sided", typeone = "fdr", fdr.method = "conservative", B = B, method = "ss.maxT", seed = seed) Slots: Class Mode Length Dimension statistic numeric numeric 5413 estimate numeric numeric 5413 sampsize integer numeric 1 rawp numeric numeric 5413 adjp numeric numeric 5413 conf.reg array logical 0 0,0,0 cutoff matrix logical 0 0,0 reject matrix logical 5413 5413,1 nulldist matrix numeric 5413000 5413,1000 call call call 10 seed integer numeric 1 ... > MTPRes <- data.frame(PRaw=TTBoot at rawp, PAdj=TTBoot at adjp) > print(format(subset(MTPRes[order(MTPRes$PRaw, MTPRes$PAdj), ], PAdj < 0.1), digits=10, scientific=TRUE)) PRaw PAdj 202508_s_at 0e+00 0.000000000e+00 203130_s_at 0e+00 0.000000000e+00 206780_at 0e+00 0.000000000e+00 218820_at 0e+00 0.000000000e+00 205825_at 0e+00 8.000000000e-03 203000_at 0e+00 1.400000000e-02 204465_s_at 0e+00 1.400000000e-02 206282_at 0e+00 1.400000000e-02 206502_s_at 0e+00 1.400000000e-02 208399_s_at 0e+00 1.400000000e-02 209598_at 0e+00 1.400000000e-02 209755_at 0e+00 1.400000000e-02 212805_at 0e+00 1.400000000e-02 203001_s_at 0e+00 2.400000000e-02 204811_s_at 0e+00 2.400000000e-02 205174_s_at 0e+00 2.400000000e-02 205646_s_at 0e+00 2.400000000e-02 206051_at 0e+00 2.400000000e-02 212624_s_at 0e+00 2.800000000e-02 204035_at 0e+00 3.000000000e-02 221261_x_at 0e+00 3.200000000e-02 206915_at 0e+00 3.400000000e-02 206104_at 0e+00 4.000000000e-02 210036_s_at 0e+00 5.000000000e-02 218380_at 0e+00 5.000000000e-02 213135_at 0e+00 6.200000000e-02 204870_s_at 0e+00 6.400000000e-02 218952_at 0e+00 6.400000000e-02 205120_s_at 0e+00 6.600000000e-02 211597_s_at 0e+00 6.666666667e-02 205348_s_at 0e+00 6.800000000e-02 212190_at 0e+00 7.000000000e-02 213186_at 0e+00 7.000000000e-02 203485_at 0e+00 7.200000000e-02 203572_s_at 0e+00 8.400000000e-02 209583_s_at 0e+00 8.400000000e-02 212895_s_at 0e+00 8.400000000e-02 206001_at 0e+00 8.600000000e-02 206135_at 0e+00 8.600000000e-02 212843_at 0e+00 8.600000000e-02 204059_s_at 0e+00 8.800000000e-02 210826_x_at 0e+00 9.000000000e-02 213438_at 0e+00 9.000000000e-02 218675_at 0e+00 9.000000000e-02 201116_s_at 0e+00 9.200000000e-02 203272_s_at 0e+00 9.600000000e-02 204793_at 0e+00 9.800000000e-02 204720_s_at 1e-03 8.400000000e-02 221207_s_at 1e-03 8.400000000e-02 204540_at 1e-03 8.600000000e-02 209992_at 1e-03 8.888888889e-02 210246_s_at 1e-03 9.000000000e-02 > print(dim(esetGcrmaFiltered)) Features Samples 5413 10 > sessionInfo() R version 2.6.0 (2007-10-03) powerpc-apple-darwin8.10.1 locale: en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8 attached base packages: [1] splines tools stats graphics grDevices utils datasets methods base other attached packages: [1] multtest_1.18.0 affydata_1.11.3 affyQCReport_1.16.0 geneplotter_1.16.0 lattice_0.16-5 [6] annotate_1.16.1 AnnotationDbi_1.0.6 RSQLite_0.6-4 DBI_0.2-4 RColorBrewer_1.0-2 [11] affyPLM_1.14.0 xtable_1.5-2 simpleaffy_2.14.05 gcrma_2.10.0 matchprobes_1.10.0 [16] genefilter_1.16.0 survival_2.32 affy_1.16.0 preprocessCore_1.0.0 affyio_1.6.1 [21] Biobase_1.16.1 loaded via a namespace (and not attached): [1] KernSmooth_2.22-21 grid_2.6.0 > version _ platform powerpc-apple-darwin8.10.1 arch powerpc os darwin8.10.1 system powerpc, darwin8.10.1 status major 2 minor 6.0 year 2007 month 10 day 03 svn rev 43063 language R version.string R version 2.6.0 (2007-10-03) # platform: PowerPC G4, Mac OS 10.4.11. The information transmitted in this electronic communica...{{dropped:10}}