title: A survey of computational methods in transcriptome-wide alternative splicing analysis.
abstract: 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.
authors.forename: Jianbo
authors.initials: J
authors.lastname: Wang
authors.forename: Zhenqing
authors.initials: Z
authors.lastname: Ye
authors.forename: Tim H-M
authors.initials: TH
authors.lastname: Huang
authors.forename: Huidong
authors.initials: H
authors.lastname: Shi
authors.forename: Victor
authors.initials: V
authors.lastname: Jin
mesh_terms: D019295:Computational Biology; D044127:Epigenesis, Genetic; D020869:Gene Expression Profiling / Q000379:methods; D042421:Histone Code; D012326:RNA Splicing; D017423:Sequence Analysis, RNA; D011795:Surveys and Questionnaires