Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Genome Biology, (May 2014)DOI: 10.1186/s13059-014-0550-8
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.
Description
This article explains the use of DESeq2, an improvement on the software DESeq. This software is used to analyze RNA-seq data through analysis of fold changes between samples. Liu et al. used DESeq to process data in both of their studies.
