DESeq2 is implemented as a package for the R statistical environment and is available [10] as part of the Bioconductor project [11]. The count matrix and metadata, including the gene model and sample information, are stored in an S4 class derived from the SummarizedExperiment class of the GenomicRanges package [60]. SummarizedExperiment objects containing count matrices can be easily generated using the summarizeOverlaps function of the GenomicAlignments package [61]. This workflow automatically stores the gene model as metadata and additionally other information such as the genome and gene annotation versions. Other methods to obtain count matrices include the htseq-count script [62] and the Bioconductor packages easyRNASeq [63] and featureCount [64].
