loading . . . First community challenge for automated virus taxonomy The rapid rate of virus discovery renders manual curation by taxonomy experts increasingly impractical, creating a need for reliable software that can reproducibly assign viral contigs to taxa at all fifteen ranks of the virus taxonomy. We led an open community challenge for the computational taxonomic classification of viruses and assembled a dataset of virus sequences combining expert-curated and metagenomic sequences. Seventeen teams contributed a total of thirty-four automated, fully reproducible classification pipelines. Most tools correctly assigned viruses belonging to established species, genera, or families, but viruses that are unclassified at those lower ranks remain challenging. This study provides datasets, open-source software, novel approaches, and recommendations to benchmark computational taxonomic classification of viruses, and support organizing the many viruses discovered in big omics data.
### Competing Interest Statement
The authors have declared no competing interest.
National Natural Science Foundation of China, 32270019
Pawsey Supercomputing Research Centres Setonix Supercomputer
National Center for Biotechnology Information of the National Library of Medicine (NLM), National Institutes of Health (NIH), 5U01DE034196-02
São Paulo Research Foundation, 2021/10577-0
Research Foundation Flanders, 11L1325N
National Science Centre, Poland, DEC-2022/45/B/ST6/03032
European Research Council, 865694, 955974, 101137311
Deutsche Forschungsgemeinschaft, 39071386
Alexander von Humboldt Foundation
Australian Research Council, DP250103825, FL250100019
European Union, ViroInf, 955974
National Research Foundation of Korea, 2020M3-A9G7-103933, RS-2021-NR061659, RS-2021-NR056571, RS-2024-00396026
Samsung DS research fund
Novo Nordisk Foundation, NNF24SA0092560
UKRI Horizon Europe Guarantee program, EP/Y029585/1
National Institute of Allergy and Infectious Diseases, U24AI162625
National Natural Science Foundation of China, 32270019
Swedish Research Council, 2023-03310_VR
Italian national Node (MIRRI-IT) of the European Research Infrastructure MIRRI-ERIC
Mississippi Agricultural and Forestry Experiment Station, 58-6066-3-044
USDA-NIFA SCRI
NIFA-USDA, 7006130
Hong Kong Innovation and Technology Fund, MRP/071/20X
he University of Melbournes Research Computing Services and the Petascale Campus Initiative
National Science Foundation, 2412446
Poznan Supercomputing and Networking Center, pl0074-02
U.S. Department of Energy Joint Genome Institute, DE-AC02-05CH11231 https://www.biorxiv.org/content/10.64898/2026.07.04.736517v1
