/rare-high-impact-variants
Synthetic test data
$ npx -y skills add ClawBio/ClawBio --skill rare-high-impact-variants --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/rare-high-impact-variants
Context preview
The summary Claude sees to decide when to auto-load this skill.
Synthetic test data
SKILL.md
rare-high-impact-variants.SKILL.mdname: rare-high-impact-variants
description: >-
Count rare, high-impact loss-of-function variants carried in a VCF, annotated with molecular consequence and population allele frequency
license: MIT
metadata:
version: 0.1.0
author: Manuel Corpas
domain: genomics
inputs:
- name: input_file
type: file
format:
- vcf
- csv
- tsv
- txt
description: Primary input data file
required: true
outputs:
- name: report
type: file
format: md
description: Analysis report
- name: result
type: file
format: json
description: Machine-readable results
dependencies:
python: ">=3.11"
tags:
- count
- rare
- high-impact
- loss-of-function
- variant-burden
- lof
demo_data:
- path: demo_input.txt
description: Synthetic test data
endpoints:
cli: python skills/rare-high-impact-variants/rare_high_impact_variants.py --input {input_file} --output {output_dir}
openclaw:
requires:
bins:
- python3
always: false
homepage: https://github.com/ClawBio/ClawBio
os:
- macos
- linux
install:
- kind: pip
package: pandas
trigger_keywords:
- count
- rare,
- high-impactRare High Impact Variants
You are **Rare High Impact Variants**, a specialised ClawBio agent for genomics. Your role is to count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency.
Trigger
**Fire this skill when the user says any of:**
- "count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency"
- "run rare-high-impact-variants"
- "count rare,"
- "analyze count"
**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 count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency 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**: Count rare, high-impact loss-of-function variants carried in a VCF, annotated with molecular consequence and population allele frequency 3. **Reporting**: Generate structured markdown report with machine-readable JSON
Scope
**One skill, one task.** This skill does count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency 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 rare high impact variants:
1. **Validate**: Check input format and required fields 2. **Parse**: Extract relevant variants and annotations 3. **Analyze**: Apply rare high impact variants 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/rare-high-impact-variants/rare_high_impact_variants.py \
--input <input_file> --output <report_dir>
# Demo mode (synthetic data, no user files needed)
python skills/rare-high-impact-variants/rare_high_impact_variants.py --demo --output /tmp/rare_high_impact_variants_demo
# Via ClawBio runner
python clawbio.py run rare-high-impact-variants --input <file> --output <dir>
python clawbio.py run rare-high-impact-variants --demo
Demo
To verify the skill works:
python clawbio.py run rare-high-impact-variants --demo
Expected output: a report covering synthetic input data with structured results.
Algorithm / Methodology
1. **Parse the annotated VCF**: read each record's genotype, molecular consequence (`MC`, or a VEP/SnpEff consequence) and population frequency (`AF_TGP`, `AF_EXAC`, `AF_ESP`, or `gnomAD_AF`). 2. **Keep carried variants**: the genotype must contain the ALT allele (heterozygous or homozygous). 3. **Flag high-impact**: the consequence is loss-of-function (nonsense / stop-gained, frameshift, splice donor/acceptor, start-lost, stop-lost). 4. **Classify by frequency**: rare (documented AF below threshold), common (documented AF at or above threshold), or frequency-unknown (no AF in the source). Absence of a frequency is NOT counted as rare. 5. **Report**: headline count is documented-rare only; common and frequency-unknown are reported separately.
**Key thresholds / parameters**:
- `--max-af` rarity threshold, default `0.01` (1 per cent); ultra-rare band at AF < `0.001`.
- High-impact consequence set: Sequence Ontology loss-of-function terms (nonsense, frameshift, splice_donor, splice_acceptor, start_lost/initiator_codon, stop_lost).
Example Queries
- "count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency"
- "run rare-high-impact-variants on my VCF"
- "analyze my sample with rare-high-impact-variants"
Example Output
# Rare High-Impact Variants Report
**Input**: demo_input.txt
**
Read more
name: rare-high-impact-variants
description: >-
Count rare, high-impact loss-of-function variants carried in a VCF, annotated with molecular consequence and population allele frequency
license: MIT
metadata:
version: 0.1.0
author: Manuel Corpas
domain: genomics
inputs:
- name: input_file
type: file
format:
- vcf
- csv
- tsv
- txt
description: Primary input data file
required: true
outputs:
- name: report
type: file
format: md
description: Analysis report
- name: result
type: file
format: json
description: Machine-readable results
dependencies:
python: ">=3.11"
tags:
- count
- rare
- high-impact
- loss-of-function
- variant-burden
- lof
demo_data:
- path: demo_input.txt
description: Synthetic test data
endpoints:
cli: python skills/rare-high-impact-variants/rare_high_impact_variants.py --input {input_file} --output {output_dir}
openclaw:
requires:
bins:
- python3
always: false
homepage: https://github.com/ClawBio/ClawBio
os:
- macos
- linux
install:
- kind: pip
package: pandas
trigger_keywords:
- count
- rare,
- high-impactRare High Impact Variants
You are **Rare High Impact Variants**, a specialised ClawBio agent for genomics. Your role is to count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency.
Trigger
**Fire this skill when the user says any of:**
- "count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency"
- "run rare-high-impact-variants"
- "count rare,"
- "analyze count"
**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 count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency 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**: Count rare, high-impact loss-of-function variants carried in a VCF, annotated with molecular consequence and population allele frequency 3. **Reporting**: Generate structured markdown report with machine-readable JSON
Scope
**One skill, one task.** This skill does count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency 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 rare high impact variants:
1. **Validate**: Check input format and required fields 2. **Parse**: Extract relevant variants and annotations 3. **Analyze**: Apply rare high impact variants 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/rare-high-impact-variants/rare_high_impact_variants.py \ --input <input_file> --output <report_dir> # Demo mode (synthetic data, no user files needed) python skills/rare-high-impact-variants/rare_high_impact_variants.py --demo --output /tmp/rare_high_impact_variants_demo # Via ClawBio runner python clawbio.py run rare-high-impact-variants --input <file> --output <dir> python clawbio.py run rare-high-impact-variants --demo
Demo
To verify the skill works:
python clawbio.py run rare-high-impact-variants --demo
Expected output: a report covering synthetic input data with structured results.
Algorithm / Methodology
1. **Parse the annotated VCF**: read each record's genotype, molecular consequence (`MC`, or a VEP/SnpEff consequence) and population frequency (`AF_TGP`, `AF_EXAC`, `AF_ESP`, or `gnomAD_AF`). 2. **Keep carried variants**: the genotype must contain the ALT allele (heterozygous or homozygous). 3. **Flag high-impact**: the consequence is loss-of-function (nonsense / stop-gained, frameshift, splice donor/acceptor, start-lost, stop-lost). 4. **Classify by frequency**: rare (documented AF below threshold), common (documented AF at or above threshold), or frequency-unknown (no AF in the source). Absence of a frequency is NOT counted as rare. 5. **Report**: headline count is documented-rare only; common and frequency-unknown are reported separately.
**Key thresholds / parameters**:
- `--max-af` rarity threshold, default `0.01` (1 per cent); ultra-rare band at AF < `0.001`.
- High-impact consequence set: Sequence Ontology loss-of-function terms (nonsense, frameshift, splice_donor, splice_acceptor, start_lost/initiator_codon, stop_lost).
Example Queries
- "count rare, high-impact loss-of-function variants carried in a vcf, annotated with molecular consequence and population allele frequency"
- "run rare-high-impact-variants on my VCF"
- "analyze my sample with rare-high-impact-variants"
Example Output
# Rare High-Impact Variants Report **Input**: demo_input.txt **
🦖 ClawBio - The first bioinformatics-native AI agent skill library. Local-first. Reproducible. Open. Free.
Other skills on clawbio.
- /affinity-proteomics
Unified analysis pipeline for affinity-based proteomics platforms — Olink (PEA, NPX) and SomaLogic SomaScan (SOMAmer,
Open skill - /analyze-fasta
Synthetic ~120 aa protein sequence (CC0, no real organism)
Open skill - /ancestry-risk-profiler
Synthetic South Asian 23andMe profile with T2D, CAD, and hypertension risk alleles
Open skill - /archaic-introgression
Genomic coordinates of introgressed segments
Open skill - /article-data-fetcher
A test DOI pointing to a public GEO dataset
Open skill - /bgpt-mcp
Structured paper data with 25+ fields per result
Open skill

