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

Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15: 15:550. doi:10.1186/s13059-014-0550-8.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0025-0992-5 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0025-0999-8
Genre: Journal Article

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© 2014 Love et al; licensee BioMed Central
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 Creators:
Love, Michael I.1, Author              
Huber, Wolfgang, Author
Anders, Simon, Author
Affiliations:
1IMPRS for Computational Biology and Scientific Computing - IMPRS-CBSC (Kirsten Kelleher), Dept. of Computational Molecular Biology (Head: Martin Vingron), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1479666              

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 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.

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Language(s): eng - English
 Dates: 2014-11-192014-12-05
 Publication Status: Published online
 Pages: -
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 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1186/s13059-014-0550-8
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Title: Genome Biology
Source Genre: Journal
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Publ. Info: London : BioMed Central Ltd.
Pages: - Volume / Issue: 15 Sequence Number: 15:550 Start / End Page: - Identifier: ISSN: 1465-6906
CoNE: https://pure.mpg.de/cone/journals/resource/1000000000224390_1