Hi all: I have a situation in which I am not able to interpret the output of the function gseattperm in the package Category. I have six arrays belonging to two groups. I am able to get some pathways that are different between the two groups using the KEGG- based GSEA method (described in section 13.2.2 of the chapter 13 (Gene Set Enrichment Analysis) of the book Bioconductor Case Studies (Hahne et al 2008). The KEGGmnplot and heatmap are similar to what is described in that section. However when I try permutation testing (section 13.2.3), gseattperm returns a matrix of two columns with all missing values. I am not sure if it is unusual. I copy the code below. Thanks for any feedback. Saroj ----------------------------------- # Non-speci?ce ?ltering to reduce low-varibility genes: > mydat.f = nsFilter(mydat, remove.dupEntrez = FALSE, var.cutoff = 0.5)$eset # Get the collection of genesets for the data and compute incidence matrix: > gsc = GeneSetCollection(mydat.f, setType = KEGGCollection()) > Am = incidence(gsc) > (dim(Am)) [1] 195 5119 # Retain only the genes mentioned in the incidence matrix: > nsF = mydat.f[colnames(Am), ] > nsF$Treatment = as.factor(nsF$Treatment) # Reduce the incidence matrix by removing all gene sets that have fewer than ten genes in them: > selectedRows = (rowSums(Am) > 10) > Am2 = Am[selectedRows, ] > dim(Am2) [1] 173 5119 # Run permutation testing: > NPERM = 1000 > pvals = gseattperm(nsF, nsF$Treatment, Am2, NPERM) > sumis.na(pvals[, 1]))) [1] 173 > sumis.na(pvals[, 2]))) [1] 173 > sessionInfo() R version 2.7.2 (2008-08-25) x86_64-unknown-linux-gnu locale: LC_CTYPE=en_US.UTF-8;LC_NUMERIC=C;LC_TIME=en_US.UTF-8;LC_COLLATE=en_US .UTF-8;LC_MONETARY=C;LC_MESSAGES=en_US.UTF-8;LC_PAPER=en_US.UTF-8;LC_N AME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=en_US.UTF-8;LC_IDENTI FICATION=C attached base packages: [1] splines tools stats graphics grDevices utils datasets [8] methods base other attached packages: [1] mouse4302.db_2.2.0 GSEABase_1.2.2 Category_2.6.0 [4] annotate_1.18.0 xtable_1.5-3 AnnotationDbi_1.2.2 [7] RSQLite_0.7-0 DBI_0.2-4 graph_1.19.6 [10] genefilter_1.20.0 survival_2.34-1 Biobase_2.0.1 loaded via a namespace (and not attached): [1] cluster_1.11.11 RBGL_1.17.2 XML_1.96-0 -----------------------------------------------