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Genome Biol. 2014;15(12):550.

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.

PMID:
25516281
PMCID:
PMC4302049
DOI:
10.1186/s13059-014-0550-8
[Indexed for MEDLINE]
Free PMC Article
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