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PMID: 22722343 Published · ppublish English Journal Article

Detecting differential usage of exons from RNA-seq data.

Genome research ·Vol. 22 ·No. 10 ·2012-10-00 ·Pages 2008-17

Anders S, Reyes A, Huber W

Abstract

RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. We present DEXSeq, a statistical method to test for differential exon usage in RNA-seq data. DEXSeq uses generalized linear models and offers reliable control of false discoveries by taking biological variation into account. DEXSeq detects with high sensitivity genes, and in many cases exons, that are subject to differential exon usage. We demonstrate the versatility of DEXSeq by applying it to several data sets. The method facilitates the study of regulation and function of alternative exon usage on a genome-wide scale. An implementation of DEXSeq is available as an R/Bioconductor package.

MeSH Terms
Algorithms Alternative Splicing Animals Cell Line Computational Biology/methods Databases, Nucleic Acid Exons Genomics/methods Humans Models, Genetic Pan troglodytes/genetics RNA/chemistry,genetics
Chemicals
RNA
Authors & Affiliations
3 authors, click to expand affiliations / ORCID
Anders Simon
European Molecular Biology Laboratory, 69111 Heidelberg, Germany. sanders@fs.tum.de
Reyes Alejandro
Huber Wolfgang
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Article Info
Journal
Genome research
Abbr.
Genome Res
ISSN
1549-5469
DOI
10.1101/gr.133744.111
Email
sanders@fs.tum.de
Published
2012-10-00
Epub
2012-00-21
Pages
2008-17
Language
English
Region
United States
NLM ID
9518021
PMCID
PMC3460195
Subset
IM
External Links
PubMed source DOI: 10.1101/gr.133744.111 PMC Full Text View journal details
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