rMATS: robust and flexible detection of differential alternative splicing from replicate RNA-Seq data
Open accessAbstract
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.
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Transcriptomic data revealed thousands of splicing events unique to the G191 variants compared to control using rMATs software.
“Transcriptomic data also revealed thousands of splicing events unique to the G191 variants compared to control using rMATs software (Fig. 3A, 70).”
From EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery (2026) · cites this paper as [70]
rMATS analysis identified 560 genes that showed different AS events between oASD and oTD mice in either brain region.
“rMATS analysis (Shen et al., 2014) identified 560 genes that showed different AS events between oASD and oTD mice in either brain region (PFC: 265 events, STR: 257 events, Full dataset: 243 events): 123 with 3’ or 5’ alternative start sites (A3SS/A5SS) events, 78 with mutually exclusive exon (MXE) events, 381 with skipped exon (SE) events, and eight with retained introns (RI).”
From Human Gut Microbiota from Autism Spectrum Disorder Promote Behavioral Symptoms in Mice (2019) · cites this paper as Shen et al., 2014
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EXOSC3 G191 Variants Trigger System-Wide Recalibration of RNA Processing Machinery
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“3A, 70 ). rMATs detects five specific splicing events: skipped Exon (SE) occurs when an exon is included in some transcripts but omitted in others; Alternative 5 ′ (A5SS) and 3 ′ (A3SS) Splice Sites involve different splice site selections, altering exon length; Mutually Exclusive Exons (MXE)…”
- Authors
- Shen, S., Park, J. W., Lu, Z.-X., Lin, L., Henry, M. D., Wu, Y. N., Zhou, Q., & Xing, Y.
- Affiliations
- Departments of aMicrobiology, Immunology, & Molecular Genetics and
- University of Iowa (US)
- University of California, Los Angeles (US)
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2014-12-05
- Volume
- 111
- Issue
- 51
- Pages
- E5593-601
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC4280593
- OpenAlex
- W2066231767
- Cited by
- 2,713
- References
- 37
- Citations by year
- 2026: 284 · 2025: 385 · 2024: 409 · 2023: 371 · 2022: 331 · 2021: 310 · 2020: 211 · 2019: 133 · 2018: 133 · 2017: 82 · 2016: 44 · 2015: 15 · 2014: 3 · 2013: 1
- FWCI
- 19.67
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- HHS | National Institutes of Health (R01GM088342, R21NS075825)
- National Science Foundation (NSF) (DMS-1055286)
- Alfred P. Sloan Foundation (Sloan Foundation) (N/A)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- differential splicing, rMATS, mats, RNA-seq, biological replicates, hierarchical models, sampling uncertainty, hypothesis testing, pre-mRNA splicing, research design, prostate cancer cell lines
- MeSH terms
- Computer Simulation, Humans, Male, Prostatic Neoplasms, RNA, Alternative Splicing, Cell Line, Tumor, High-Throughput Nucleotide Sequencing
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