CircRNAFisher: a systematic computational approach for de novo circular RNA identification.

CircRNAFisher: a systematic computational approach for de novo circular RNA identification.
Acta Pharmacol Sin. 2018 Jul 16;:
Authors: Jia GY, Wang DL, Xue MZ, Liu YW, Pei YC, Yang YQ, Xu JM, Liang YC, Wang P
Abstract
Circular RNAs (circRNAs) are emerging species of mRNA splicing products with largely unknown functions. Although several computational pipelines for circRNA identification have been developed, these methods strictly rely on uniquely mapped reads overlapping back-splice junctions (BSJs) and lack approaches to model the statistical significance of the identified circRNAs. Here, we reported a systematic computational approach to identify circRNAs by simultaneously utilizing BSJ overlapping reads and discordant BSJ spanning reads to identify circRNAs. Moreover, we developed a novel procedure to estimate the P-values of the identified circRNAs. A computational cross-validation and experimental validations demonstrated that our method performed favorably compared to existing circRNA detection tools. We created a standalone tool, CircRNAFisher, to implement the method, which might be valuable to computational and experimental scientists studying circRNAs.
PMID: 30013032 [PubMed - as supplied by publisher]

Source: Acta Pharmacologica Sinica - July 16, 2018 Category: Drugs & Pharmacology Authors: Jia GY, Wang DL, Xue MZ, Liu YW, Pei YC, Yang YQ, Xu JM, Liang YC, Wang P Tags: Acta Pharmacol Sin Source Type: research