Detect, classify, and QC viral contigs.
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Validate the pinned resource manifest and assemble the complete comparative evidence and reasoning bundle:
uv run --no-project python skills/bio-viromics/scripts/build_viromics_evidence.py \
viral_metrics.tsv --resources resources.json --hypotheses hypotheses.tsv \
--reflections reflections.tsv --comparative-dir comparison/ \
--out results/bio-viromics
The driver checksum-verifies geNomad, CheckV, GVClass, and vConTACT3 database resources; requires at least five hypotheses including a technical/null explanation; requires initial, intermediate, and final reflections; and persists marker, family-copy, synteny, ncRNA, and genome-frontier evidence under schemas/evidence-bundle.schema.json.
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Start from /tracking-taxonomy-updates QuickClade domain routing when assemblies, MAGs, genomes, or contigs have not already been screened. Viral, virus-like, mixed, or low-confidence contigs enter this skill; bacterial/archaeal and eukaryotic rows stay on their domain-specific routes unless later evidence contradicts the triage.
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Run virus detection with geNomad v1.8+ (use as primary plasmid-and-virus classifier).
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Run CheckV v1.0.1 for completeness, contamination, and host-removal QC.
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Infer the likely viral group from QuickClade, detection output, taxonomy hints, genome statistics, and marker/similarity evidence.
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Search the literature for that viral group and write a short analysis playbook: typical reference sets, markers, comparative analyses, genome features, plots, and outlier signals used by scientists studying that group.
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Choose taxonomy, clustering, phylogenetic, and comparative methods from the playbook:
- For bacteriophage and prokaryotic-virus gene-sharing taxonomy: vConTACT3 v3.0 (hierarchical genus-to-order assignment, >95% ICTV agreement; supersedes vConTACT2).
- For Nucleocytoviricota / giant viruses: gvclass v1.0 for genus-level classification combined with marker-gene phylogenies of NCLDV core genes.
- For RNA viruses, ssDNA viruses, or other groups not well-served by vConTACT3: use group-specific markers, phylogenomics, and protein-family approaches from the literature playbook rather than forcing a phage-oriented workflow.
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For prokaryotic-virus discovery, VirSorter2 v2.2.4 is a complementary detector to geNomad; combine with CheckV QC to remove false positives.
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For each viral genome or high-quality viral contig, call genes and annotate proteins when needed, then inspect the annotation set according to the playbook rather than a fixed global feature list.
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Compare each query viral genome to the literature-supported reference set. Report what matches expectations, what is missing, what is expanded, what is query-specific, and which patterns are likely artifacts.
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Genome-size frontier — for each query, compute where the genome size and gene count sit within the distribution of close relatives AND the literature-reported extremes for the inferred viral group. State percentile, distance from the group median, and whether the query approaches or exceeds known record-class sizes (cite the paper that defines that record). This applies even when the query is mid-distribution — the placement itself is the finding.
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Produce an interesting-findings table. If no strong discovery candidates are found, state that explicitly and list the literature-derived checks performed.
