AR
Data & Repro
armored-cart-design-agent
Design armored CAR-T cells with cytokine payloads and resistance mechanisms.
FreedomIntelligence/OpenClaw-Medical-SkillsView
Data & Repro
BI
bio-clinical-databases-tumor-mutational-burden
Maintainer FreedomIntelligence · Last updated April 1, 2026
Calculate tumor mutational burden from panel or WES data with proper normalization and clinical thresholds. Use when assessing immunotherapy eligibility or characterizing tumor immunogenicity.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-clinical-databases-tumor-mutational-burden
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- Python: cyvcf2 for VCF parsing + variant counting per panel region.
- Calculate TMB from my tumor sequencing data" → Compute tumor mutational burden as nonsynonymous coding mutations per megabase with proper panel normalization for immunotherapy eligibility assessment. Python: cyvcf2 for VCF parsing + variant counting per panel region.
- PANEL_SIZES_MB = { 'FoundationOne CDx': 0.8, 'MSK-IMPACT': 1.14, 'TruSight Oncology 500': 1.94, 'Oncomine Comprehensive': 1.5, 'WES (exome)': 30.0, # Approximate coding region 'WGS': 3000.0, # Approximate }.
- def calculate_tmb_panel(vcf_path, panel_name): '''Calculate TMB for known panel''' if panel_name not in PANEL_SIZES_MB: raise ValueError(f'Unknown panel: {panel_name}') return calculate_tmb(vcf_path, PANEL_SIZES_MB[panel_name]).
Source Doc
Excerpt From SKILL.md
TMB Calculation from VCF (Ensembl VEP 111+)
Goal: Calculate tumor mutational burden as nonsynonymous coding mutations per megabase from a somatic VCF.
Approach: Iterate through VCF variants, filter for coding nonsynonymous consequences via VEP/SnpEff annotations, and divide count by panel size.
Panel-Specific TMB (Ensembl VEP 111+)
Goal: Calculate TMB normalized to known gene panel capture region sizes.
Approach: Look up the panel's megabase coverage from a reference table and pass to the TMB calculator.
## TMB with Variant Filtering (Ensembl VEP 111+)
**Goal:** Calculate TMB with quality and germline filters to reduce false positives.
**Approach:** Apply VAF, depth, and gnomAD population frequency filters before counting coding nonsynonymous variants.
Use cases
- Use when assessing immunotherapy eligibility or characterizing tumor immunogenicity.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
Upstream Related Skills
- variant-calling/somatic-variant-calling - Input variants
- variant-calling/clinical-interpretation - ACMG/AMP classification
- variant-calling/variant-annotation - VEP/SnpEff annotation
Related skills
Related skills
AR
Data & Repro
arxiv-search
Search arXiv physics, math, and computer science preprints using natural language queries. Powered by Valyu semantic search.
FreedomIntelligence/OpenClaw-Medical-SkillsView
AU
Data & Repro
autonomous-oncology-agent
Autonomous oncology research agent: literature mining, trial matching, biomarker analysis, and treatment hypothesis generation.
FreedomIntelligence/OpenClaw-Medical-SkillsView
BI
Data & Repro
bio-cfdna-preprocessing
Preprocesses cell-free DNA sequencing data including adapter trimming, alignment optimized for short fragments, and UMI-aware duplicate remo…
FreedomIntelligence/OpenClaw-Medical-SkillsView