[HTML][HTML] Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

MI Love, W Huber, S Anders - Genome biology, 2014 - Springer
Genome biology, 2014Springer
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 …
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 .
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