VirBot: an RNA viral contig detector for metagenomic data

Guowei Chen, Xubo Tang, Mang Shi, Yanni Sun*

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

11 Citations (Scopus)
68 Downloads (CityUHK Scholars)

Abstract

Without relying on cultivation, metagenomic sequencing greatly accelerated the novel RNA virus detection. However, it is not trivial to accurately identify RNA viral contigs from a mixture of species. The low content of RNA viruses in metagenomic data requires a highly specific detector, while new RNA viruses can exhibit high genetic diversity, posing a challenge for alignment-based tools. In this work, we developed VirBot, a simple yet effective RNA virus identification tool based on the protein families and the corresponding adaptive score cutoffs. We benchmarked it with seven popular tools for virus identification on both simulated and real sequencing data. VirBot shows its high specificity in metagenomic datasets and superior sensitivity in detecting novel RNA viruses.
Original languageEnglish
Article numberbtad093
JournalBioinformatics
Volume39
Issue number3
Online published16 Feb 2023
DOIs
Publication statusPublished - Mar 2023

Funding

This work was supported by Hong Kong Research Grants Council (RGC) General Research Fund (GRF) [11206819] and Hong Kong Innovation and Technology Fund (ITF) [MRP/071/20X].

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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