Abstract
Summary: 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.
Cite
CITATION STYLE
Chen, G., Tang, X., Shi, M., & Sun, Y. (2023). VirBot: an RNA viral contig detector for metagenomic data. Bioinformatics, 39(3). https://doi.org/10.1093/bioinformatics/btad093
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