Molecular Biology and EvolutionBioinformaticsPeer-reviewed journal article
VirID: Beyond Virus Discovery - An Integrated Platform for Comprehensive RNA Virus Characterization
Ziyue YangiD, Yongtao ShaniD, Xue LiuiD, Guowei CheniD, Yuanfei PaniD, Qinyu GouiD, Jie ZouiD, Zilong ChangiD, Qiang ZengiD, Chunhui YangiD, Jianbin KongiD, Yanni SuniD, Shaochuan LiiD, Xu ZhangiD, Wei-Chen WuiD, Chunmei LiiD, Hong PengiD, Edward Charles HolmesiD, Deyin GuoiD, Mǎng ShīiD
Abstract
RNA viruses exhibit vast phylogenetic diversity and can significantly impact public health and agriculture. However, current bioinformatics tools for viral discovery from metagenomic data frequently generate false positive virus results, overestimate viral diversity, and misclassify virus sequences. Additionally, current tools often fail to determine virus-host associations, which hampers investigation of the potential threat posed by a newly detected virus. To address these issues we developed VirID, a software tool specifically designed for the discovery and characterization of RNA viruses from metagenomic data. The basis of VirID is a comprehensive RNA-dependent RNA polymerase (RdRP) database to enhance a workflow that includes RNA virus discovery, phylogenetic analysis, and phylogeny-based virus characterization. Benchmark tests on a simulated data set demonstrated that VirID had high accuracy in profiling viruses and estimating viral richness. In evaluations with real-world samples, VirID was able to identity RNA viruses of all type, but also provided accurate estimations of viral genetic diversity and virus classification, as well as comprehensive insights into virus associations with humans, animals, and plants. VirID therefore offers a robust tool for virus discovery and serves as a valuable resource in basic virological studies, pathogen surveillance, and early warning systems for infectious disease outbreaks.
- organism: human
- organism: plant (other)
- assay: metagenomics
- research focus: database / resource
- research focus: software / tool
- approach: statistical model
- Citations
- 9
- FWCI
- 1.22
- Field percentile
- top 22%
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