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BioMed Central, Genome Biology, 12(15), 2014

DOI: 10.1186/s13059-014-0550-8

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Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.

Journal article published in 2014 by Michael I. Love, Wolfgang Huber ORCID, Simon Anders ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

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 .