DESeq2 hence offers to practitioners a wide set of features with state-of-the-art inferential power. Its use cases are not limited to RNA-seq data or other transcriptomics assays; rather, many kinds of high-throughput count data can be used. Other areas for which DESeq or DESeq2 have been used include chromatin immunoprecipitation sequencing assays (e.g., ; see also the DiffBind package ,), barcode-based assays (e.g., ), metagenomics data (e.g., ), ribosome profiling  and CRISPR/Cas-library assays . Finally, the DESeq2 package is integrated well in the Bioconductor infrastructure  and comes with extensive documentation, including a vignette that demonstrates a complete analysis step by step and discusses advanced use cases.
Sweave vignettes for reproducing all figures and tables in this paper, including data objects for the experiments mentioned, and code for aligning reads and for benchmarking, can be found in a package DESeq2paper .
RNA-seq was used to explore the developmental transcriptome of D. melanogaster. Mapped read counts are available from the ReCount project . Specifically the pooled version of the modencodefly dataset from the ReCount website  provides read counts summarized by Ensembl 61 gene IDs for 30 whole-animal biological samples. We discarded the larval, pupal and adult stages and kept only the 12 embryonic samples. Genes were retained in the analysis if they achieved cpm >1 for any embryonic stage. Effective library sizes were estimated by TMM scale-normalization  using edgeR software  prior to the voom analysis.
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