A systematic evaluation of bioinformatics tools for identification of long noncoding RNAs.

ABSTRACT: High-throughput RNA sequencing unveiled the complexity of transcriptome and significantly increased the records of long noncoding RNAs (lncRNAs), which were reported to participate in a variety of biological processes. Identification of lncRNAs is a key step in lncRNA analysis, and a bunch of bioinformatics tools have been developed for this purpose in recent years. While these tools allow us to identify lncRNA more efficiently and accurately, they may produce inconsistent results, making selection a confusing issue. We compared the performance of 41 analysis models based on 14 software packages and different data sets, including high-quality data and low-quality data from 33 species. In addition, computational efficiency, robustness, and joint prediction of the models were explored. As a

SUBMITTER: Duan Y 

PROVIDER: S-EPMC7749630 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature