I am using RankProd for differential expression of array data. I've confirmed that all of my input gene names, rownames, etc are all gene- level and contain no duplicates. Yet, when I run RPadvance and look at the output of topGene(rankprodResult, cutoff=0.05, logged = TRUE, logbase=2)$Table1 and topGene(rankprodResult, cutoff=0.05, logged = TRUE, logbase=2)$Table2 I see that there is one gene which appears in both of those lists- with the same fold change but different p-values for the occurrence in Table1 and Table2. I then went and confirmed that my initial input did not contain duplicates again- which is indeed the case. The foldchange is 1.2744, which seems to indicate that the gene is actually downregulated and should only be in Table2. rankprod.table1[rankprod.table1[,"FC:(class1/class2)"] >= 1,] gene.index RP/Rsum FC:(class1/class2) pfp P.value 19582.0000 2031.3112 1.2744 0.0244 0.0017 What's going on here? I've used this method a few times before, and haven't seen this. I'm using the newest version of RankProd. (While I'm asking this already- are all the p-values of 0 from underflowing or from the method used to calculate those values? It feels quite strange sometimes to be presenting all these p-values of 0 in my results.) -- output of sessionInfo(): R version 3.0.1 (2013-05-16) Platform: x86_64-w64-mingw32/x64 (64-bit) locale: [1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United States.1252 LC_MONETARY=English_United States.1252 [4] LC_NUMERIC=C LC_TIME=English_United States.1252 attached base packages: [1] grid parallel stats graphics grDevices utils datasets methods base other attached packages: [1] pd.hugene.2.0.st_3.8.0 heatmap.plus_1.3 RankProd_2.32.0 [4] hugene20sttranscriptcluster.db_2.12.1 xlsx_0.5.1 xlsxjars_0.5.0 [7] rJava_0.9-4 annotate_1.38.0 org.Hs.eg.db_2.9.0 [10] GGally_0.4.4 reshape_0.8.4 plyr_1.8 [13] ggplot2_0.9.3.1 biomaRt_2.16.0 puma_3.2.1 [16] mclust_4.2 VennDiagram_1.6.4 scatterplot3d_0.3-33 [19] annaffy_1.32.0 KEGG.db_2.9.1 GO.db_2.9.0 [22] RSQLite_0.11.4 DBI_0.2-7 AnnotationDbi_1.22.6 [25] gplots_2.11.3 KernSmooth_2.23-10 caTools_1.14 [28] gdata_2.13.2 gtools_3.0.0 MASS_7.3-28 [31] RColorBrewer_1.0-5 affyPLM_1.36.0 preprocessCore_1.22.0 [34] simpleaffy_2.36.1 gcrma_2.32.0 genefilter_1.42.0 [37] oligo_1.24.2 oligoClasses_1.22.0 affy_1.38.1 [40] marray_1.38.0 limma_3.16.7 Biobase_2.20.1 [43] BiocGenerics_0.6.0 loaded via a namespace (and not attached): [1] affxparser_1.32.3 affyio_1.28.0 BiocInstaller_1.10.3 Biostrings_2.28.0 bit_1.1-10 bitops_1.0-5 [7] codetools_0.2-8 colorspace_1.2-2 dichromat_2.0-0 digest_0.6.3 dynamicTreeCut_1.21 ff_2.2-11 [13] foreach_1.4.1 GenomicRanges_1.12.4 gtable_0.1.2 impute_1.34.0 IRanges_1.18.3 iterators_1.0.6 [19] labeling_0.2 munsell_0.4.2 proto_0.3-10 RCurl_1.95-4.1 reshape2_1.2.2 scales_0.2.3 [25] splines_3.0.1 stats4_3.0.1 stringr_0.6.2 survival_2.37-4 tools_3.0.1 WGCNA_1.27-1 [31] XML_3.98-1.1 xtable_1.7-1 zlibbioc_1.6.0 -- Sent via the guest posting facility at bioconductor.org.