An empirical Bayes change-point model for identifying 3′ and 5′ alternative splicing by next-generation RNA sequencing

Document Type

Article

Publication Date

6-15-2016

Abstract

Motivation: Next-generation RNA sequencing (RNA-seq) has been widely used to investigate alternative isoform regulations. Among them, alternative 3′ splice site (SS) and 5′ SS account for more than 30% of all alternative splicing (AS) events in higher eukaryotes. Recent studies have revealed that they play important roles in building complex organisms and have a critical impact on biological functions which could cause disease. Quite a few analytical methods have been developed to facilitate alternative 3′ SS and 5′ SS studies using RNA-seq data. However, these methods have various limitations and their performances may be further improved. Results: We propose an empirical Bayes change-point model to identify alternative 3′ SS and 5′ SS. Compared with previous methods, our approach has several unique merits. First of all, our model does not rely on annotation information. Instead, it provides for the first time a systematic framework to integrate various information when available, in particular the useful junction read information, in order to obtain better performance. Second, we utilize an empirical Bayes model to efficiently pool information across genes to improve detection efficiency. Third, we provide a flexible testing framework in which the user can choose to address different levels of questions, namely, whether alternative 3′ SS or 5′ SS happens, and/or where it happens. Simulation studies and real data application have demonstrated that our method is powerful and accurate.

Identifier

84976499972 (Scopus)

Publication Title

Bioinformatics

External Full Text Location

https://doi.org/10.1093/bioinformatics/btw060

e-ISSN

14602059

ISSN

13674803

PubMed ID

26873932

First Page

1823

Last Page

1831

Issue

12

Volume

32

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