📋 VCF Operations

VCF manipulation, filtering, merging, and summary statistics. Wraps bcftools and GATK SelectVariants.

CLI Reference

python omicsclaw.py run genomics-vcf-operations --demo
python omicsclaw.py run genomics-vcf-operations --input <data.vcf> --output <dir>

Why This Exists

• Without it: Massive cohort VCF files are intractable to manipulate or filter manually
• With it: Fast algebraic operations stream variants safely and precisely
• Why OmicsClaw: Translates complex bcftools syntax into plain intuitive language prompts

Workflow

1. Calculate: Map sequence ranges or filter criteria strings.
2. Execute: Perform stream-based querying over compressed index.
3. Assess: Ensure output satisfies the boundary limits dynamically.
4. Generate: Output sub-sampled VCF representations.
5. Report: Tabulate variant extraction statistics.

Example Queries

• "Filter this vcf file keeping only PASS variants"
• "Merge these sample vcfs using bcftools"

Output Structure

output_directory/
├── report.md
├── result.json
├── processed.vcf.gz
├── figures/
│   └── filter_stats.png
├── tables/
│   └── cohort_summary.csv
└── reproducibility/
    ├── commands.sh
    ├── environment.yml
    └── checksums.sha256

Safety

• Local-first: Strict offline processing without external upload.
• Disclaimer: Requires OmicsClaw reporting structures and disclaimers.
• Audit trail: Hyperparameters and operational flow states are logged fully.

Integration with Orchestrator

Trigger conditions:

• Automatically invoked dynamically based on tool metadata and user intent matching.

Chaining partners:

• variant-call

  — Upstream VCF source

• annotation

  — Downstream downstream impact modeling

Citations

• bcftools
• GATK