Journal article
MATS: a Bayesian framework for flexible detection of differential alternative splicing from RNA-Seq data
Nucleic acids research, Vol.40(8), pp.e61-e61
04/2012
DOI: 10.1093/nar/gkr1291
PMCID: PMC3333886
PMID: 22266656
Abstract
Ultra-deep RNA sequencing has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We develop MATS (multivariate analysis of transcript splicing), a bayesian statistical framework for flexible hypothesis testing of differential alternative splicing patterns on RNA-Seq data. MATS uses a multivariate uniform prior to model the between-sample correlation in exon splicing patterns, and a Markov chain Monte Carlo (MCMC) method coupled with a simulation-based adaptive sampling procedure to calculate the P-value and false discovery rate (FDR) of differential alternative splicing. Importantly, the MATS approach is applicable to almost any type of null hypotheses of interest, providing the flexibility to identify differential alternative splicing events that match a given user-defined pattern. We evaluated the performance of MATS using simulated and real RNA-Seq data sets. In the RNA-Seq analysis of alternative splicing events regulated by the epithelial-specific splicing factor ESRP1, we obtained a high RT-PCR validation rate of 86% for differential exon skipping events with a MATS FDR of <10%. Additionally, over the full list of RT-PCR tested exons, the MATS FDR estimates matched well with the experimental validation rate. Our results demonstrate that MATS is an effective and flexible approach for detecting differential alternative splicing from RNA-Seq data.
Details
- Title: Subtitle
- MATS: a Bayesian framework for flexible detection of differential alternative splicing from RNA-Seq data
- Creators
- Shihao Shen - Department of Biostatistics, University of Iowa, Iowa City, IA 52242, USAJuw Won ParkJian HuangKimberly A DittmarZhi-xiang LuQing ZhouRuss P CarstensYi Xing
- Resource Type
- Journal article
- Publication Details
- Nucleic acids research, Vol.40(8), pp.e61-e61
- Publisher
- England
- DOI
- 10.1093/nar/gkr1291
- PMID
- 22266656
- PMCID
- PMC3333886
- ISSN
- 0305-1048
- eISSN
- 1362-4962
- Grant note
- T32HL007638 / NHLBI NIH HHS R01 GM088342 / NIGMS NIH HHS UL1RR024979 / NCRR NIH HHS R01GM088809 / NIGMS NIH HHS R01 GM088342-02 / NIGMS NIH HHS UL1 RR024979 / NCRR NIH HHS R01GM088342 / NIGMS NIH HHS R01CA120988 / NCI NIH HHS P30 DK054759 / NIDDK NIH HHS P30DK054759 / NIDDK NIH HHS
- Language
- English
- Date published
- 04/2012
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9983985959902771
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