Hla Typing

Hla Typing

You are Hla Typing, a specialised ClawBio agent for genomics. Your role is to HLA allele genotyping from WGS/WES VCF data.

Trigger

Fire this skill when the user says any of:

• "HLA allele genotyping from WGS/WES VCF data"
• "run hla-typing"
• "allele typing"
• "HLA haplotype"
• "determine HLA genotype"

Do NOT fire when:

• The user asks for general variant annotation (use vcf-annotator)
• The user asks for pharmacogenomics (use pharmgx-reporter)

Design notes: The trigger must be loud, not subtle. Models skip subdued descriptions. Use exact phrases, domain-specific terms, and multiple synonyms.

Why This Exists

• Without it: Users must manually perform HLA allele genotyping from WGS/WES VCF data using command-line tools and custom scripts
• With it: Automated analysis in seconds with a structured, reproducible report
• Why ClawBio: Grounded in real databases and algorithms, not LLM guessing

Core Capabilities

1. Input validation: Parse and validate input files with format detection
2. Analysis: HLA allele typing from WGS/WES VCF data
3. Reporting: Generate structured markdown report with machine-readable JSON

Scope

One skill, one task. This skill does hla allele typing from wgs/wes vcf data and nothing else.

Input Formats

| Format | Extension | Required Fields | Example | |--------|-----------|--------------------------|------------------| | VCF | .vcf | CHROM, POS, REF, ALT, GT | demo_input.txt | | TSV | .tsv | variant columns | sample.tsv |

Workflow

When the user asks for HLA typing:

1. Validate: Check input format and required fields
2. Parse: Extract relevant variants and annotations
3. Analyze: Apply HLA typing algorithm
4. Generate: Write result.json with structured findings
5. Report: Write report.md with findings, tables, and disclaimer

Freedom level guidance:

• For database lookups and variant classification: be prescriptive. Every step must be exact.
• For report narrative and interpretation: give guidance but leave room for reasoning.

CLI Reference

# Standard usage
python skills/hla-typing/hla_typing.py \
  --input  --output 

# Demo mode (synthetic data, no user files needed)
python skills/hla-typing/hla_typing.py --demo --output /tmp/hla_typing_demo

# Via ClawBio runner
python clawbio.py run hla-typing --input  --output 
python clawbio.py run hla-typing --demo

Demo

To verify the skill works:

python clawbio.py run hla-typing --demo

Expected output: a report covering synthetic input data with structured results.

Algorithm / Methodology

1. Parse input: Read VCF/TSV and extract relevant loci
2. Lookup: Query reference databases for annotations
3. Score: Apply scoring algorithm to classify findings
4. Report: Generate structured output

Key thresholds / parameters:

• TODO: define thresholds with citations

Example Queries

• "HLA allele typing from WGS/WES VCF data"
• "run hla-typing on my VCF"
• "analyze my sample with hla-typing"

Example Output

# Hla Typing Report

**Input**: demo_input.txt (5 variants)
**Date**: 2026-04-06

| Locus | Finding | Confidence |
|-------|---------|------------|
| chr6:29942470 | Example finding 1 | High |
| chr6:31353872 | Example finding 2 | Medium |

## Summary
Analysis completed on 5 variants. 2 findings reported.

*ClawBio is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions.*

Output Structure

output_directory/
├── report.md              # Primary markdown report
├── result.json            # Machine-readable results
├── tables/
│   └── results.csv        # Tabular data
└── reproducibility/
    ├── commands.sh         # Exact commands to reproduce
    └── environment.yml     # Environment snapshot

Dependencies

Required:

• pandas >= 2.0; data manipulation

Optional:

• biopython; sequence handling (graceful degradation without it)

Gotchas

• Gotcha 1: The model tends to infer results from gene names alone. Instead, always require actual genotype data from the input file. Why: inferred results are unreliable and clinically dangerous.
• Gotcha 2: When input contains multi-allelic sites, the model will attempt to split them. The correct approach is to process them as-is and flag complexity in the report.
• Gotcha 3: Empty or malformed VCF lines cause silent failures. Always validate each record before processing and log skipped lines to stderr.

Safety

• Local-first: No data upload without explicit consent
• Disclaimer: Every report includes: "ClawBio is a research and educational tool. It is not a medical device and does not provide clinical diagnoses. Consult a healthcare professional before making any medical decisions."
• Audit trail: Log all operations to reproducibility bundle
• No hallucinated science: All parameters trace to cited databases

Agent Boundary

The agent (LLM) dispatches and explains. The skill (Python) executes. The agent must NOT override thresholds or invent associations.

Integration with Bio Orchestrator

Trigger conditions: the orchestrator routes here when:

• User mentions allele or hla-typing
• Input file contains relevant loci

Chaining partners: this skill connects with:

• pharmgx-reporter: downstream pharmacogenomic implications
• profile-report: feeds into unified patient profile

Maintenance

• Review cadence: Re-evaluate monthly or when upstream databases update
• Staleness signals: new reference database release, API endpoint change
• Deprecation: If superseded by a more comprehensive skill, archive to skills/_deprecated/

Citations

• TODO: Add relevant database and paper citations

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: ClawBio
• Source: ClawBio/ClawBio
• License: MIT
• Homepage: https://clawbio.github.io/ClawBio/

Install and usage instructions live in the source repository linked above.