VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses

Guo, Jiarong; Bolduc, Ben; Zayed, Ahmed A.; Varsani, Arvind; Dominguez-Huerta, Guillermo; Delmont, Tom O.; Pratama, Akbar Adjie; Gazitúa, M. Consuelo; Vik, Dean; Sullivan, Matthew B.; Roux, Simon

doi:10.1186/s40168-020-00990-y

VirSorter2: a multi-classifier, expert-guided approach to detect diverse DNA and RNA viruses

Journal Article · Mon Feb 01 00:00:00 EST 2021 · Microbiome

DOI:https://doi.org/10.1186/s40168-020-00990-y· OSTI ID:1763830

Guo, Jiarong; Bolduc, Ben; Zayed, Ahmed A.; Varsani, Arvind; Dominguez-Huerta, Guillermo; Delmont, Tom O.; Pratama, Akbar Adjie; Gazitúa, M. Consuelo; Vik, Dean; ; Roux, Simon

Abstract Background

Viruses are a significant player in many biosphere and human ecosystems, but most signals remain “hidden” in metagenomic/metatranscriptomic sequence datasets due to the lack of universal gene markers, database representatives, and insufficiently advanced identification tools.

Results

Here, we introduce VirSorter2, a DNA and RNA virus identification tool that leverages genome-informed database advances across a collection of customized automatic classifiers to improve the accuracy and range of virus sequence detection. When benchmarked against genomes from both isolated and uncultivated viruses, VirSorter2 uniquely performed consistently with high accuracy (F1-score > 0.8) across viral diversity, while all other tools under-detected viruses outside of the group most represented in reference databases (i.e., those in the order Caudovirales ). Among the tools evaluated, VirSorter2 was also uniquely able to minimize errors associated with atypical cellular sequences including eukaryotic genomes and plasmids. Finally, as the virosphere exploration unravels novel viral sequences, VirSorter2’s modular design makes it inherently able to expand to new types of viruses via the design of new classifiers to maintain maximal sensitivity and specificity.

Conclusion

With multi-classifier and modular design, VirSorter2 demonstrates higher overall accuracy across major viral groups and will advance our knowledge of virus evolution, diversity, and virus-microbe interaction in various ecosystems. Source code of VirSorter2 is freely available ( https://bitbucket.org/MAVERICLab/virsorter2 ), and VirSorter2 is also available both on bioconda and as an iVirus app on CyVerse ( https://de.cyverse.org/de ).

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE; USDOE Office of Science (SC)

Grant/Contract Number:: AC02-05CH11231; SC0020173

OSTI ID:: 1763830

Alternate ID(s):: OSTI ID: 1808518

Journal Information:: Microbiome, Journal Name: Microbiome Journal Issue: 1 Vol. 9; ISSN 2049-2618

Publisher:: Springer Science + Business MediaCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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