title: Integrative analysis of many RNA-seq datasets to study alternative splicing.
abstract: Alternative splicing is an important gene regulatory mechanism that dramatically increases the complexity of the proteome. However, how alternative splicing is regulated and how transcription and splicing are coordinated are still poorly understood, and functions of transcript isoforms have been studied only in a few limited cases. Nowadays, RNA-seq technology provides an exceptional opportunity to study alternative splicing on genome-wide scales and in an unbiased manner. With the rapid accumulation of data in public repositories, new challenges arise from the urgent need to effectively integrate many different RNA-seq datasets for study alterative splicing. This paper discusses a set of advanced computational methods that can integrate and analyze many RNA-seq datasets to systematically identify splicing modules, unravel the coupling of transcription and splicing, and predict the functions of splicing isoforms on a genome-wide scale.
authors.affiliation: Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
authors.forename: Wenyuan
authors.initials: W
authors.lastname: Li
authors.affiliation: Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
authors.forename: Chao
authors.initials: C
authors.lastname: Dai
authors.affiliation: Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
authors.forename: Shuli
authors.initials: S
authors.lastname: Kang
authors.affiliation: Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA. Electronic address: xjzhou@usc.edu.
authors.forename: Xianghong Jasmine
authors.initials: XJ
authors.lastname: Zhou
mesh_terms: D017398:Alternative Splicing; D019295:Computational Biology; D003627:Data Interpretation, Statistical; D066264:Datasets as Topic; D017423:Sequence Analysis, RNA / Q000379:methods*
keywords: Alternative splicing; Integrative analysis; RNA-seq data