title: Moderated estimation of fold change and  dispersion for RNA-seq data with DESeq2.
abstract: In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html webcite.
authors.forename: Michael I
authors.initials: MI
authors.lastname: Love
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Huber
authors.forename: Simon
authors.initials: S
authors.lastname: Anders
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D059014:High-Throughput Nucleotide Sequencing; D008957:Models, Genetic; D012313:RNA / Q000032:analysis*; D017423:Sequence Analysis, RNA; D012984:Software
chemical_list: D012313:RNA