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BytesAgain β€Ί Skills β€Ί Genomics
πŸ¦€ ClawHub

Genomics

by @ivangdavila

Interpret genomic variants with ACMG classification, pharmacogenomics, and clinical annotation from ClinVar and gnomAD.

Versionv1.0.0
Downloads1,271
Stars⭐ 1
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TERMINAL
clawhub install genomics

πŸ“– About This Skill

name: Genomics slug: genomics version: 1.0.0 homepage: https://clawic.com/skills/genomics description: Interpret genomic variants with ACMG classification, pharmacogenomics, and clinical annotation from ClinVar and gnomAD. metadata: {"clawdbot":{"emoji":"🧬","requires":{"bins":[]},"os":["linux","darwin","win32"]}}

Setup

On first use, read setup.md for integration guidelines. Ask user consent before creating ~/genomics/ workspace.

When to Use

User has processed genomic data (VCF files) and needs clinical interpretation. Agent handles variant classification, pharmacogenomics recommendations, and annotation lookup. NOT for raw data processing β€” use bioinformatics skill for alignment and variant calling.

Architecture

Memory lives in ~/genomics/. See memory-template.md for structure.

~/genomics/
β”œβ”€β”€ memory.md           # Context + preferences + interpretation history
└── cases/              # Active interpretation cases

Quick Reference

| Topic | File | |-------|------| | Setup process | setup.md | | Memory template | memory-template.md |

Core Rules

1. Classify Variants Using ACMG Guidelines

Every variant needs systematic classification:

| Category | Criteria | |----------|----------| | Pathogenic | PVS1, PS1-4, PM1-6, PP1-5 weighted | | Likely Pathogenic | Strong + moderate evidence | | VUS | Insufficient or conflicting evidence | | Likely Benign | BS1-4, BP1-7 weighted | | Benign | Strong benign evidence |

Never classify without evidence. State "insufficient data" when appropriate.

2. Check Population Frequency First

Before clinical interpretation, verify frequency:

| Source | Use For | |--------|---------| | gnomAD v4 | Global population frequency | | gnomAD non-cancer | Somatic analysis | | Population-specific | Ancestry-appropriate filtering |

MAF >1% in any population = likely benign for rare disease.

3. Cross-Reference Multiple Databases

| Database | Information | |----------|-------------| | ClinVar | Clinical classifications + submitter evidence | | OMIM | Gene-disease relationships | | HGMD | Literature-reported mutations | | UniProt | Protein function + domains |

Single-source interpretation is insufficient. Triangulate evidence.

4. Report Pharmacogenomics Actionably

For drug-gene interactions, provide:
  • Diplotype (e.g., CYP2D6 *1/*4)
  • Predicted phenotype (poor/intermediate/normal/ultra-rapid metabolizer)
  • Drug list affected
  • Dosing guidance (CPIC/DPWG when available)

    • 5. Separate Germline from Somatic Context

    | Context | Key Differences | |---------|-----------------| | Germline | Family implications, carrier testing, predictive | | Somatic | Tumor-specific, therapy selection, no inheritance |

    Always state which context you're interpreting.

    6. Acknowledge Uncertainty

  • Novel variants often lack evidence
  • VUS β‰  benign β€” requires ongoing monitoring
  • Reclassification happens (ClinVar updates monthly)
  • Computational predictions are supportive, not definitive

    • Pharmacogenomics Reference

    High-Priority Drug-Gene Pairs (CPIC Level A)

    | Gene | Drugs | Clinical Action | |------|-------|-----------------| | CYP2D6 | Codeine, tramadol, tamoxifen, SSRIs | Dosing/alternative | | CYP2C19 | Clopidogrel, PPIs, voriconazole | Dosing/alternative | | CYP2C9 + VKORC1 | Warfarin | Dosing algorithm | | DPYD | Fluorouracil, capecitabine | Dose reduction/avoid | | TPMT + NUDT15 | Azathioprine, mercaptopurine | Dose reduction | | HLA-B*57:01 | Abacavir | Contraindication | | HLA-B*15:02 | Carbamazepine | Contraindication (Asian ancestry) | | SLCO1B1 | Simvastatin | Dose cap/alternative statin | | G6PD | Rasburicase, primaquine | Contraindication | | CYP3A5 | Tacrolimus | Dosing adjustment |

    Phenotype Interpretation

    | Metabolizer Status | Meaning | Typical Action | |--------------------|---------|----------------| | Poor (PM) | Little/no enzyme activity | Alternative drug or dose ↓↓ | | Intermediate (IM) | Reduced activity | Consider dose ↓ | | Normal (NM) | Expected activity | Standard dosing | | Rapid/Ultra-rapid (UM) | Increased activity | Dose ↑ or alternative |

    Annotation Resources

    | Resource | URL | Content | |----------|-----|---------| | ClinVar | ncbi.nlm.nih.gov/clinvar | Clinical variant classifications | | gnomAD | gnomad.broadinstitute.org | Population frequencies | | OMIM | omim.org | Gene-disease relationships | | PharmGKB | pharmgkb.org | Drug-gene annotations | | CPIC | cpicpgx.org | Pharmacogenomics guidelines | | ClinGen | clinicalgenome.org | Gene-disease validity | | Franklin | franklin.genoox.com | Variant interpretation aid | | VarSome | varsome.com | ACMG auto-classification |

    Common Interpretation Traps

  • Ignoring population specificity β€” Variants common in African populations may look rare in European-biased databases
  • Trusting single ClinVar submitter β€” Check submitter count and review status (β‰₯2 submitters, no conflict preferred)
  • Conflating computational prediction with evidence β€” CADD/REVEL are supportive, not diagnostic
  • Missing compound heterozygosity β€” Two VUS in trans can be pathogenic together
  • Outdated database versions β€” gnomAD v4 has 800K+ exomes vs v2's 125K
  • Ignoring gene-level constraint β€” pLI/LOEUF scores indicate tolerance to loss-of-function

    • External Endpoints

    This skill does NOT automatically call external APIs. All database references are for manual lookup:

    | Resource | When Used | Data Sent | |----------|-----------|-----------| | ClinVar, gnomAD, OMIM | User manually visits | None by this skill | | PharmGKB, CPIC | User manually visits | None by this skill | | VarSome, Franklin | User manually visits | None by this skill |

    No automatic network requests. The skill provides URLs and guidance for manual lookup only.

    Security & Privacy

    Data that stays local:

  • All interpretation work runs locally
  • No variant data sent externally by this skill
  • No automatic API calls to any database

    • This skill does NOT:

  • Make network requests automatically
  • Upload patient variants anywhere
  • Connect to databases without explicit user action
  • Store identifiable genomic information outside ~/genomics/

    • Related Skills

    Install with clawhub install if user confirms:
  • medicine β€” clinical decision support
  • biology β€” molecular mechanisms
  • chemistry β€” drug metabolism pathways
  • health β€” patient care context

    • Feedback

  • If useful: clawhub star genomics
  • Stay updated: clawhub sync

    • ⚑ When to Use

    User has processed genomic data (VCF files) and needs clinical interpretation. Agent handles variant classification, pharmacogenomics recommendations, and annotation lookup. NOT for raw data processing β€” use bioinformatics skill for alignment and variant calling.

    βš™οΈ Configuration

    On first use, read setup.md for integration guidelines. Ask user consent before creating ~/genomics/ workspace.