ViralQC: a tool for assessing completeness and contamination of predicted viral contigs
Cheng Peng, Jiayu Shang, Jiaojiao Guan, Yanni Sun · 2026
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Description
Peng and colleagues built ViralQC, a quality-control tool for viral genome fragments pulled from metagenomic sequencing, in a 2026 paper. Such samples yield mostly microbial DNA. Would-be viral sequences often carry host material or are partial, so judging their quality is needed before listing new viruses.
Peng combined DNA and protein foundation models, large pretrained neural networks, into an ensemble that flags microbial contamination inside supposed viral sequences. It estimated completeness from how the encoded proteins are arranged. Benchmarked against CheckV, the current standard tool, ViralQC detected contamination more sharply in fragments longer than ten thousand bases while keeping similar accuracy. Its completeness estimates were more accurate for fragments that were more than half complete. The authors offer the tool as a sharper filter for the flood of new viruses from such studies, with source code posted openly.
Catalog record
| CREATOR | Cheng Peng, Jiayu Shang, Jiaojiao Guan, Yanni Sun |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 42 KB |
| LICENSE | https://creativecommons.org/licenses/by/4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |