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

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

Resultado de la investigación: Review articlerevisión exhaustiva

13 Citas (Scopus)


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.

Idioma originalEnglish (US)
Páginas (desde-hasta)59-66
Número de páginas8
PublicaciónBiomolecular Concepts
EstadoPublished - mar 1 2015

ASJC Scopus subject areas

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


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