Statistical and Computational Methods for High-Throughput Sequencing Data Analysis of Alternative Splicing.
The burgeoning field of high-throughput sequencing significantly improves our ability to understand the complexity of transcriptomes. Alternative splicing, as one of the most important driving forces for transcriptome diversity, can now be studied at an unprecedent resolution. Efficient and powerful computational and statistical methods are in urgent need to facilitate the characterization and quantification of alternative splicing events. Here we discuss methods in splice junction read mapping, and methods in exon-centric or isoform-centric quantification of alternative splicing. In addition, we discuss HITS-CLIP and splicing QTL analyses which are novel high-throughput sequencing based approaches in the dissection of splicing regulation.
Molecular and Computational Biology, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089, USA.
Liang
L
Chen
Alternative splicing; High-throughput sequencing; RNA-seq; Transcript isoform