Circular RNA identification based on multiple seed matching.

Abstract:

:Computational detection methods have been widely used in studies on the biogenesis and the function of circular RNAs (circRNAs). However, all of the existing tools showed disadvantages on certain aspects of circRNA detection. Here, we propose an improved multithreading detection tool, CIRI2, which used an adapted maximum likelihood estimation based on multiple seed matching to identify back-spliced junction reads and to filter false positives derived from repetitive sequences and mapping errors. We established objective assessment criteria based on real data from RNase R-treated samples and systematically compared 10 circular detection tools, which demonstrated that CIRI2 outperformed its previous version CIRI and all other widely used tools, featured with remarkably balanced sensitivity, reliability, duration and RAM usage.

journal_name

Brief Bioinform

authors

Gao Y,Zhang J,Zhao F

doi

10.1093/bib/bbx014

subject

Has Abstract

pub_date

2018-09-28 00:00:00

pages

803-810

issue

5

eissn

1467-5463

issn

1477-4054

pii

3058729

journal_volume

19

pub_type

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