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. Researchers at UCLA recently developed a statistical method multivariate analysis of transcript splicing (MATS) for detecting differential alternative splicing events from RNA-Seq data. Here, they 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.
Availability – RNASeq-MATS is available at: http://rnaseq-mats.sourceforge.net/
- Park JW, Tokheim C, Shen S, Xing Y. (2013) Identifying Differential Alternative Splicing Events from RNA Sequencing Data Using RNASeq-MATS. Methods Mol Biol 1038, 171-9. [abstract]