ArticleNpj viruses2024
Conservative taxonomy and quality assessment of giant virus genomes with GVClass.
Article in Npj viruses, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The trial behind it
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Who cites it
9 citing papers in PubMed.
- Evidence for the acquisition of a proteorhodopsin-like rhodopsin by a chrysophyte-infecting giant virus.Journal of virology · 2026Article
- Genomic catalogue of giant viruses reveals expanded diversity and functional potential.Nature microbiology · 2026Article
- Giant viruses of the polar regions: diversity, endemism, adaptation and ecological structuring.FEMS microbiology ecology · 2026Review
- Vicennial metagenomic time series unveils evolutionary dynamics of giant viruses in a freshwater ecosystem.Nature communications · 2026Article
- Meta-virus resource (MetaVR): expanding the frontiers of viral diversity with 24 million uncultivated virus genomes.Nucleic acids research · 2026Article
- Complex viral interactions revealed for the harmful bloom-forming dinoflagellateISME communications · 2026Article
- Single-cell genomics reveals complex microbial and viral associations in ciliates and testate amoebae.Nature communications · 2025Article
- A deep dive into giant viruses.Npj viruses · 2025Article
- Viral niche-partitioning: comparative genomics of giant viruses across environmental gradients in a high Arctic freshwater-saltwater lake.ISME communications · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Large double-stranded DNA viruses of the phylum Nucleocytoviricota (Giant Viruses; GVs) are the largest known viruses, infecting various eukaryotic hosts, particularly protists and algae. These viruses impact biogeochemical cycles and host genome evolution but are challenging to identify and classify due to their complex genomes. We present GVClass, a tool for identifying giant viruses in sequence data, providing taxonomic assignments, and estimating genome completeness and contamination. GVClass employs optimized gene calling and a conservative approach using consensus single-protein phylogenies for robust taxonomic classification, relying on highly conserved orthologous groups. Benchmarking demonstrates over 90% accuracy at the genus-level and >99% at higher taxonomic ranks. GVClass addresses classification challenges and is available as a standalone tool and integrated into the Integrated Microbial Genomes/Virus database (IMG/VR).
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.