This workshop will provide an introduction to statistical methods and software for differential expression analysis based on RNA-seq read counts. All of the methods considered involve a negative binomial distribution for the counts as a starting point. In addition, the statistical methods all utilize some form of empirical Bayes analysis by which gene-specific error variances are ‘shrunk’ towards a common value or a trend obtained by fitting a smooth to a mean-variance plot. Analysis using the open source R packages, limma, edgeR and DESeq2, will be illustrated and compared. All three packages are available in Bioconductor, an open source project focused on the analysis of data from emerging biological assays.