
The identification of switch-like alternative splicing exons among multiple samples with RNA-Seq data
Author(s) -
Zhiyi Qin,
Xuegong Zhang
Publication year - 2017
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0178320
Subject(s) - exon , intron , alternative splicing , computational biology , biology , tandem exon duplication , genetics , rna splicing , exon trapping , gene , alu element , rna , human genome , computer science , genome
Alternative splicing is an ubiquitous phenomenon in most human genes and has important functions. The switch-like exon is the type of exon that has a high level of usage in some tissues, but has a low level of usage in the other tissues. They usually undergo strong tissue-specific regulations. There is still a lack a systematic method to identify switch-like exons from multiple RNA-seq samples. We proposed a novel method called iterative Tertile Absolute Deviation around the mode (iTAD) to profile the distribution of exon relative usages among multiple samples and to identify switch-like exons and other types of exons using a robust statistic estimator. We validated the method with simulation data, and applied it on RNA-seq data of 16 human body tissues and detected 3,100 switch-like exons. We found that switch-like exons tend to be more associated with Alu elements in their flanking intron regions than other types of exons.