TERIUS: accurate prediction of lncRNA via high-throughput sequencing data representing RNA-binding protein association.

ABSTRACT:

Background

LncRNAs are long regulatory non-coding RNAs, some of which are arguably predicted to have coding potential. Despite coding potential classifiers that utilize ribosome profiling data successfully detected actively translated regions, they are less sensitive to lncRNAs. Furthermore, lncRNA annotation can be susceptible to false positives obtained from 3' untranslated region (UTR) fragments of mRNAs.

Results

To lower these limitations in lncRNA annotation, we present a novel tool TERIUS that provides a two-step filtration process to distinguish between bona fide and false lncRNAs. The first step successfully separates lncRNAs from protein-coding genes showing enhanced sensitivity compared to other methods. To eliminate 3'UTR fragments, the second step takes advantage

SUBMITTER: Choi SW 

PROVIDER: S-EPMC5836835 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature