Detecting differential usage of exons from RNA-seq data
- ↵* Corresponding author; email: sanders{at}fs.tum.de
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.
- Received October 21, 2011.
- Accepted June 14, 2012.
- © 2012, Published by Cold Spring Harbor Laboratory Press
This manuscript is Open Access.
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