Dear Sindre, Just run edgeR as usual on all genes. Run topTags() with n=Inf to get a table of DE results for all genes: tab <- topTags(yourresults, n=Inf) Then subset the table for just the 5 genes you are interested in. For example, if your results include a column of gene symbols, this might be: tab5 <- tab[tab$table$Symbol %in% mygenes,] tab5 When you report the table, there is no need to include the FDR or multiple testing column because the genes have been chosen a priori. Just judge significance from the PValue column. Best wishes Gordon > Date: Thu, 30 Jan 2014 03:49:18 -0800 (PST) > From: "Sindre [guest]" <guest at="" bioconductor.org=""> > To: bioconductor at r-project.org, sindre.lee at studmed.uio.no > Subject: [BioC] Best way of presenting a sub-fraction of edgeR RNAseq > gene expression results in a publication > > > Hi! > We selected a priori 5 genes to analyse and want to include them in a > table for publication. > > Question is how to present them? Normally we would calculate fold > changes (or percent) with standard deviation and then mark if > significant. > > edgeR, as far as I understand, uses shrunken fold changes and the > dispersion is squeezed using an empirical Bayes method. Thus, its hard > to manually reproduce the results from logCPM values. > > So, whats the best way? > > Thank you! > > -- output of sessionInfo(): > > No codes used. > > -- > Sent via the guest posting facility at bioconductor.org. ______________________________________________________________________ The information in this email is confidential and intend...{{dropped:4}}