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Detecting differential usage of exons from RNA-Seq data
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  • Published: 04 April 2012

Detecting differential usage of exons from RNA-Seq data

  • Simon Anders1,
  • Alejandro Reyes1 &
  • Wolfgang Huber1 

Nature Precedings (2012)Cite this article

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  • 25 Citations

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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 employs generalized linear models and offers reliable control of false discoveries by taking biological variation into account. DEXSeq detects genes, and in many cases specific exons, that are subject to differential exon usage with high sensitivity. 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.This preprint has subsequently been published in Genome Research (doi:10.1101/gr.133744.111)

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Authors and Affiliations

  1. European Molecular Biology Laboratory https://www.nature.com/nature

    Simon Anders, Alejandro Reyes & Wolfgang Huber

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  1. Simon Anders
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  2. Alejandro Reyes
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  3. Wolfgang Huber
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Correspondence to Simon Anders.

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Anders, S., Reyes, A. & Huber, W. Detecting differential usage of exons from RNA-Seq data. Nat Prec (2012). https://doi.org/10.1038/npre.2012.6837.2

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  • Received: 04 April 2012

  • Accepted: 04 April 2012

  • Published: 04 April 2012

  • DOI: https://doi.org/10.1038/npre.2012.6837.2

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Keywords

  • RNA-Seq
  • alternative isoform regulation
  • DEXSeq

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