| name | genomics-variant-calling |
| description | Load when summarising small variants (SNVs / indels) from a VCF or computing demo-pattern variant statistics (Ti/Tv ratio, per-chromosome distribution, SNP / indel split). Skip when filtering / merging VCFs (use `genomics-vcf-operations`), when calling structural variants (use `genomics-sv-detection`), or when adding functional annotations (use `genomics-variant-annotation`). |
| version | 0.5.0 |
| author | OmicsClaw |
| license | MIT |
| tags | ["genomics","variant-calling","snv","indel","vcf","ti-tv"] |
| requires | ["pandas","numpy"] |
genomics-variant-calling
When to use
The user has a VCF (or a BAM intended for calling) and wants
small-variant summary statistics: total variant count, SNP / indel
split, Ti/Tv ratio, per-chromosome distribution. The script does
not invoke an external caller (GATK HaplotypeCaller, Mutect2,
DeepVariant, FreeBayes, etc.) — it summarises an existing VCF or
generates a demo VCF for downstream-skill smoke tests.
For variant filtering / normalisation use genomics-vcf-operations;
for SVs use genomics-sv-detection; for functional annotation use
genomics-variant-annotation.
Inputs & Outputs
| Input | Format | Required |
|---|
| Variants | .vcf or .bam (BAM only used as a placeholder; no calling is run) | yes (unless --demo) |
| Output | Path | Notes |
|---|
| Variant table | tables/variants.csv | per-variant CHROM/POS/REF/ALT/QUAL |
| Per-chromosome | tables/variants_per_chrom.csv | counts per chromosome |
| Report | report.md + result.json | always; result.json["data"]["variants_per_chrom"] mirrors the table |
Flow
- Load VCF (
--input <file.vcf>) or generate a demo VCF at output_dir/demo_variants.vcf with --n-variants records (genomics_variant_calling.py:94).
- Parse records; classify SNP vs indel; compute Ti/Tv on biallelic SNPs.
- Aggregate per-chromosome counts.
- Write
tables/variants.csv (genomics_variant_calling.py:300) + tables/variants_per_chrom.csv (:308) + report.md + result.json envelope (:314).
Gotchas
- No external caller is invoked. This skill does NOT run GATK / Mutect2 / DeepVariant / FreeBayes — it ingests a VCF and summarises it. To actually CALL variants, run an external pipeline first; this skill consumes the resulting VCF.
--input REQUIRED unless --demo. genomics_variant_calling.py:289 raises ValueError("--input required when not using --demo"); non-existent paths raise FileNotFoundError at :292.--n-variants only affects --demo (genomics_variant_calling.py:278, default 500). It is silently ignored when --input is set.- Multi-allelic VCF rows ARE split per-ALT.
genomics_variant_calling.py:181-182 iterates for a in alt.split(","): and emits one CSV row per ALT allele. Output row counts therefore exceed input VCF line counts on multi-allelic data — no need to pre-normalise unless your downstream consumer requires one row per VCF line.
- Demo VCF is a minimal SNV set (no indels, no structural variants, no genotype fields). Useful for orchestrator smoke tests; do NOT use for biological inference.
Key CLI
python omicsclaw.py run genomics-variant-calling --demo --output /tmp/var_demo
python omicsclaw.py run genomics-variant-calling --demo --n-variants 2000 \
--output /tmp/var_demo_large
python omicsclaw.py run genomics-variant-calling \
--input cohort.vcf --output results/
See also
references/parameters.md — every CLI flagreferences/methodology.md — SNP / indel / Ti-Tv definitionsreferences/output_contract.md — tables/variants.csv schema- Adjacent skills:
genomics-alignment (upstream — produces the BAM that calling consumes), genomics-vcf-operations (downstream — VCF filtering / merging), genomics-variant-annotation (downstream — functional impact), genomics-sv-detection (parallel — SVs instead of small variants)
