name: bio-genomics-phasing description: 'Haplotype phasing analysis: phase block N50, phased fraction, PS (Phase Set) field parsing, pipe-delimited genotype detection. Wraps WhatsHap, SHAPEIT5, Eagle2.' tool_type: mixed primary_tool: genomics measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:
- read_file
- run_shell_command
π Haplotype Phasing
Haplotype phasing for variant data. Wraps WhatsHap, SHAPEIT, and Eagle.
CLI Reference
python omicsclaw.py run genomics-phasing --demo
python omicsclaw.py run genomics-phasing --input <data.vcf> --output <dir>
Why This Exists
- Without it: Variants remain independent loci without knowledge of allelic connectivity
- With it: Haplotypes are formed spanning genes, essential for compound heterozygote analysis
- Why OmicsClaw: Standardizes input and output across read-backed and population-backed phasing tools
Workflow
- Calculate: Prepare VCF indices and sequence mappings.
- Execute: Run haplotype graph resolution algorithms.
- Assess: Perform switch error evaluation and quality flagging.
- Generate: Output structured phased VCF representation.
- Report: Synthesize N50 phase block stats into tables.
Example Queries
- "Phase this vcf file using WhatsHap"
- "Use SHAPEIT for population phasing of variants"
Output Structure
output_directory/
βββ report.md
βββ result.json
βββ phased.vcf.gz
βββ figures/
β βββ phase_block_distribution.png
βββ tables/
β βββ phasing_metrics.csv
βββ reproducibility/
βββ commands.sh
βββ environment.yml
βββ 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-callβ Upstream generation of raw VCFsannotationβ Downstream annotation of phased haplotypes
Citations
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