title: rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data.
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.
authors.affiliation: Departments of Microbiology, Immunology, & Molecular Genetics and.
authors.forename: Shihao
authors.initials: S
authors.lastname: Shen
authors.affiliation: Departments of Microbiology, Immunology, & Molecular Genetics and.
authors.forename: Juw Won
authors.initials: JW
authors.lastname: Park
authors.affiliation: Departments of Microbiology, Immunology, & Molecular Genetics and.
authors.forename: Zhi-xiang
authors.identifier: http://orcid.org/0000-0001-9230-2169
authors.initials: ZX
authors.lastname: Lu
authors.affiliation: Departments of Microbiology, Immunology, & Molecular Genetics and.
authors.forename: Lan
authors.initials: L
authors.lastname: Lin
authors.affiliation: Departments of Molecular Physiology and Biophysics and Pathology, University of Iowa, Iowa City, IA 52242.
authors.forename: Michael D
authors.initials: MD
authors.lastname: Henry
authors.affiliation: Statistics, University of California, Los Angeles, CA 90095; and.
authors.forename: Ying Nian
authors.initials: YN
authors.lastname: Wu
authors.affiliation: Statistics, University of California, Los Angeles, CA 90095; and.
authors.forename: Qing
authors.initials: Q
authors.lastname: Zhou
authors.affiliation: Departments of Microbiology, Immunology, & Molecular Genetics and yxing@ucla.edu.
authors.forename: Yi
authors.initials: Y
authors.lastname: Xing
mesh_terms: D017398:Alternative Splicing; D045744:Cell Line, Tumor; D003198:Computer Simulation; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000235:genetics / Q000473:pathology; D012313:RNA / Q000235:genetics*
chemical_list: D012313:RNA
keywords: RNA sequencing; alternative splicing; exon; isoform; transcriptome