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University of California, Los Angeles, 현 University of Louisville

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Proc. Natl. Acad. Sci. USA, December 23, 2014 vol. 111 no. 51 E5593-E5601 | doi: 10.1073/pnas.1419161111 rMATS: Robust and flexible detection of differential alternative splicing from replicate RNA-Seq data

Abstract

Shihao Shen^a,1, Juw Won Park^a,1, Zhi-xiang Lu^a, Lan Lin^a, Michael D. Henry^b,c, Ying Nian Wu^d, Qing Zhou^d, and Yi Xing^a,2

Departments of ^aMicrobiology, Immunology, & Molecular Genetics and
^dStatistics, University of California, Los Angeles, CA 90095; and
Departments of ^bMolecular Physiology and Biophysics and
^cPathology, University of Iowa, Iowa City, IA 52242

Abstract
Ultra-deep RNA sequencing (RNA-Seq) has become a powerful approach for genome-wide analysis of pre-mRNA alternative splicing. We previously developed multivariate analysis of transcript splicing (MATS), a statistical method for detecting differential alternative splicing between two RNA-Seq samples. Here we describe a new statistical model and computer program, replicate MATS (rMATS), designed for detection of differential alternative splicing from replicate RNA-Seq data. rMATS uses a hierarchical model to simultaneously account for sampling uncertainty in individual replicates and variability among replicates. In addition to the analysis of unpaired replicates, rMATS also includes a model specifically designed for paired replicates between sample groups. The hypothesis-testing framework of rMATS is flexible and can assess the statistical significance over any user-defined magnitude of splicing change. The performance of rMATS is evaluated by the analysis of simulated and real RNA-Seq data. rMATS outperformed two existing methods for replicate RNA-Seq data in all simulation settings, and RT-PCR yielded a high validation rate (94%) in an RNA-Seq dataset of prostate cancer cell lines. Our data also provide guiding principles for designing RNA-Seq studies of alternative splicing. We demonstrate that it is essential to incorporate biological replicates in the study design. Of note, pooling RNAs or merging RNA-Seq data from multiple replicates is not an effective approach to account for variability, and the result is particularly sensitive to outliers. The rMATS source code is freely available at rnaseq-mats.sourceforge.net/. As the popularity of RNA-Seq continues to grow, we expect rMATS will be useful for studies of alternative splicing in diverse RNA-Seq projects.

RNA sequencing, alternative splicing, exon, isoform, transcriptome

¹S.S. and J.W.P. contributed equally to this work.
²To whom correspondence should be addressed.

Author contributions: S.S., Y.N.W., Q.Z., and Y.X. designed research; S.S., J.W.P., Z.-x.L., and L.L. performed research; S.S., J.W.P., L.L., and M.D.H. contributed new reagents/analytic tools; S.S., Z.-x.L., and Y.X. analyzed data; and S.S. and Y.X. wrote the paper.

논문정보

형식Research article
게재일2014년 12월 (BRIC 등록일 2015-01-06)
연구진국외 연구진
분야
피인용횟수60회 이상 인용된 논문 (상위피인용논문 등록일 2017-05-17)

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