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Multivariate Analysis of Transcript Splicing (MATS)

Multivariate Analysis of Transcript Splicing (MATS)

Xing Lab, Children's Hospital of Philadelphia

Updates

  • 06/01/2020
    • Release of rMATS 4.1.0
      • Add command line arguments to run parts of the computation on different machines (--task, --tmp)
      • Add command line argument to allow variable read lengths (--variable-read-length)
      • Add command line argument for paired statistical analysis with PAIRADISE (--paired-stats)
      • Add command line arguments to allow splicing events to be detected that involve an unannotated splice site (--novelSS, --mil, --mel). This is an experimental feature
      • Replace fromGTF.novelEvents output files with fromGTF.novelJunction and fromGTF.novelSpliceSite
      • Compatible with both Python 2 and Python 3
      • Only one sample group is required if --statoff is used
      • Bug fix of the effective length calculation
      • Bug fix of novel event classification
      • Bug fix of MXE event detection
      • Source code is available
  • 04/25/2018
    • Release of rMATS 4.0.2
      • Fixed a bug related to single-end reads.
      • Fixed a bug in the test data set.
  • 11/15/2017
    • Release of rMATS 4.0.1
      • PSI is always provided in AS_Event.MATS.JCEC.txt even if the statistical model is turned off.
      • Written in C, Python and Cython.
      • Pre-built binary program for Linux and Mac OS Yosemite.
      • Improved numerical optimization.
      • rMATS v4.0.1 (turbo) achieves about 100 fold increase in speed compared to the published Python/R code (rMATS <= v3.2.5).
      • Reduced memory usage and storage usage compared to rMATS v3.2.5.
      • rMATS v4.0.1 (turbo) is multi-threaded (able to make the best of multi-core system) while rMATS v3.2.5 are not. More details can be found here.
  • 05/01/2017
    • Release of rMATS-docker 0.1beta
      • Beta release of a much faster and slimmer version of rMATS in docker container.
        • All required packages are packed in the docker container.
        • Counting procedure is 20-100 times faster.
        • Statistical part is 300-500 times faster.
        • Intermediate files are ~1000 times smaller.
  • 08/18/2016
    • Release of rMATS 3.2.5
      • Added support for multiple versions of samtools. rMATS was tested with samtools v1.2 and v1.3.1.
  • 07/29/2016
    • Release of rMATS 3.2.4
      • Improved and faster counting procedure.
      • Improved numerical optimization.
      • Improved prerequisites validation.
      • Optional detection of novel splice sites (unannotated splice sites).
  • 05/02/2016
    • Release of rMATS 3.2.2.beta
      • Changed default aligner to STAR: rMATS now aligns fastq files with STAR.
  • 03/03/2016
    • Release of rMATS 3.2.1.beta
      • Fixed a bug related to read counting of short exons.
  • 02/12/2016
    • Release of rMATS 3.2.0.beta, a major update with important features added to rMATS:
      • Detection of novel splice sites and novel exons: rMATS now finds novel splice sites and novel exons.
      • Detection of micro-exons: rMATS now detects micro-exons involved in AS events.
      • Strand-specific data: rMATS now works with strand-specific data.
      • Multi-exon (N>2) spanning reads: rMATS now handles junction reads that span more than 2 exons.
      • rMATS now works with most recent version of samtools (tested with samtools v1.2).
  • 2/25/2015
    • Release of rMATS 3.0.9,
      • Increased the stability of numerical optimization.
      • Deprecated -expressionChange option.
  • 11/26/2014
    • Official announcement for the release of replicate MATS (rMATS):
      • We have developed replicate MATS (rMATS) to detect differential alternative splicing from replicate RNA-seq data.
      • MATS 3.0.0 and beyond is rMATS. Please download the latest version (currently MATS 3.0.8) from our website.
  • 04/09/2014
    • Release of PrimerSeq,
      • We released a primer design tool, PrimerSeq, for designing RT-PCR primers from MATS output.
  • 8/26/2013
    • Release of MATS 3.0.8,
      • Improved the optimization procedure for the paired replicate model.
  • 4/5/2013
  • 11/16/2012
    • Release of MATS 3.0.6.beta,
      • Fixed a bug related to handling TopHat 2.x.x or Bowtie 2.x.x output.
      • Fixed a ‘wc’ command bug related to running MATS on MacOS, thanks to Peter Stoilov for pointing this out.
  • 11/7/2012
    • Release of MATS 3.0.5.beta,
      • BAM files from TopHat 2.x.x or Bowtie 2.x.x now work properly.
  • 10/18/2012
    • Release of MATS 3.0.4.beta,
      • Fixed a bug related to gene expression level calculation.
  • 10/12/2012
    • Release of MATS 3.0.3.beta,
      • Fixed a bug related to gene expression level calculation.
  • 8/30/2012
    • Release of MATS 3.0.2.beta,
      • Fixed a bug related to default insert sizes and standard distribution.
  • 8/24/2012
    • Release of MATS 3.0.1.beta,
      • A bug related to Ubuntu (tested on 12.04) is fixed.
  • 8/9/2012
    • Release of MATS 3.0.0.beta, a major update with important features added to MATS:
      • Replicate data support: MATS now works with replicate RNA-Seq data from both paired and unpaired study design.
      • Improved filtering system: MATS now filters out AS events where large gene expression fold changes may confound the analysis.
      • MacOS support: MATS now supports both Linux and MacOS (tested on MacOS 10.8.1).
  • 5/25/2012
    • Release of MATS 2.1.0
      • MATS now works with both read sequence files (fastq) and mapped reads files (bam). Using bam files adds flexibility in mapping because MATS will skip the read mapping step.
      • A bug related to an empty AS event file is fixed.
  • 5/15/2012
    • Release of MATS 2.0.0, a major update with important features added to MATS:
      • Simplified running procedure: MATS now only requires the raw RNA-Seq data, a genome sequence file, and a gene/transcript annotation file in GTF format as the input.
      • Ability to analyze different types of alternative splicing events: MATS now automatically detects and analyzes alternative splicing events corresponding to all major types of alternative splicing patterns.
      • Improved statistical power: MATS now works with both exon-exon junction reads and exon body reads which leads to improved statistical power.
  • 3/5/2012
    • Release of MATS 1.2.0, added a new method to calculate P-values by likelihood-ratio test, which is ~100x faster than the Bayesian method.
  • 2/16/2012
    • Release of MATS 1.1.0, adds Ensembl version of mouse annotation.
  • 12/15/2011
    • Release of MATS 1.0.0, the initial version of MATS was opened.



Citation

Shen S., Park JW., Lu ZX., Lin L., Henry MD., Wu YN., Zhou Q., Xing Y. rMATS: Robust and Flexible Detection of Differential Alternative Splicing from Replicate RNA-Seq Data. PNAS, 111(51):E5593-601. doi: 10.1073/pnas.1419161111

Park JW., Tokheim C., Shen S., Xing Y. Identifying differential alternative splicing events from RNA sequencing data using RNASeq-MATS. Methods in Molecular Biology: Deep Sequencing Data Analysis, 2013;1038:171-179 doi: 10.1007/978-1-62703-514-9_10

Shen S., Park JW., Huang J., Dittmar KA., Lu ZX., Zhou Q., Carstens RP., Xing Y. MATS: A Bayesian Framework for Flexible Detection of Differential Alternative Splicing from RNA-Seq Data. Nucleic Acids Research, 2012;40(8):e61 doi: 10.1093/nar/gkr1291

About MATS

MATS is a computational tool to detect differential alternative splicing events from RNA-Seq data. The statistical model of MATS calculates the P-value and false discovery rate that the difference in the isoform ratio of a gene between two conditions exceeds a given user-defined threshold. From the RNA-Seq data, MATS can automatically detect and analyze alternative splicing events corresponding to all major types of alternative splicing patterns. MATS handles replicate RNA-Seq data from both paired and unpaired study design.



Software Download
  • STAR indexes download are available from the STAR site.

Pre-requisites


Documentation

rMATS Companion

  • rMATS-STAT: standalone statistical model to test for differential splicing.

Questions/Comments

Have comments or questions about rMATS? Please post them on the rMATS Users Google Group.