A survey of computational methods in transcriptome-wide alternative splicing analysis

Jianbo Wang, Zhenqing Ye, Tim H.M. Huang, Huidong Shi, Victor Jin

Research output: Contribution to journalReview articlepeer-review

13 Scopus citations


Alternative splicing is widely recognized for its roles in regulating genes and creating gene diversity. Consequently the identification and quantification of differentially spliced transcripts is pivotal for transcriptome analysis. Here, we review the currently available computational approaches for the analysis of RNA-sequencing data with a focus on exon-skipping events of alternative splicing and discuss the novelties as well as challenges faced to perform differential splicing analyses. In accordance with operational needs we have classified the software tools, which may be instrumental for a specific analysis based on the experimental objectives and expected outcomes. In addition, we also propose a framework for future directions by pinpointing more extensive experimental validation to assess the accuracy of the software predictions and improvements that would facilitate visualizations, data processing, and downstream analyses along with their associated software implementations.

Original languageEnglish (US)
Pages (from-to)59-66
Number of pages8
JournalBiomolecular Concepts
Issue number1
StatePublished - Mar 1 2015


  • RNA-sequencing (RNA-seq)
  • alternative splicing (AS)
  • differential splicing
  • exon-skipping
  • graph-based exon-skipping scanner (GESS)

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Cellular and Molecular Neuroscience


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