Identifying Differential Alternative Splicing Events from RNA Sequencing Data Using RNASeq-MATS

  • Juw Won Park
  • Collin Tokheim
  • Shihao Shen
  • Yi Xing
Part of the Methods in Molecular Biology book series (MIMB, volume 1038)

Abstract

RNA sequencing (RNA-Seq) has emerged as a powerful and increasingly cost-effective technology for analysis of transcriptomes. RNA-Seq has several significant advantages over gene expression microarrays, including its high sensitivity and accuracy, broad dynamic range, nucleotide-level resolution, ability to detect novel mRNA transcripts, and ability to analyze pre-mRNA alternative splicing. A major application of RNA-Seq is to detect differential alternative splicing, i.e., differences in exon splicing patterns among different biological conditions. We recently developed a statistical method multivariate analysis of transcript splicing (MATS) for detecting differential alternative splicing events from RNA-Seq data. Here, we describe a computational pipeline RNASeq-MATS based on the MATS algorithm. This pipeline automatically detects and analyzes differential alternative splicing events corresponding to all major types of alternative splicing patterns from RNA-Seq data.

Key words

RNA-Seq High-throughput sequencing Alternative splicing Transcriptome 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Juw Won Park
    • 1
  • Collin Tokheim
    • 1
  • Shihao Shen
    • 1
  • Yi Xing
    • 1
  1. 1.Department of Microbiology, Immunology, and Molecular GeneticsUCLALos AngelesUSA

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