clinvar-database
$
npx mdskill add aipoch/medical-research-skills/clinvar-databaseQuery ClinVar variants by gene, condition, or significance.
- Retrieves variant records with clinical significance and phenotype data.
- Depends on NCBI E-utilities and bcftools for data access.
- Executes searches using gene names, conditions, or significance terms.
- Delivers structured variant records and annotated VCF entries.
SKILL.md
.github/skills/clinvar-databaseView on GitHub ↗
--- name: clinvar-database description: Utilities for querying the NCBI ClinVar database to retrieve variant records, clinical significance, and phenotype relationships; use when searching variants by gene/condition/significance, interpreting Pathogenic/Benign/VUS classifications, or annotating VCF files with ClinVar annotations. license: MIT author: aipoch --- > **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills) ## When to Use - You need to find ClinVar variant records by **gene**, **condition/phenotype**, or **clinical significance** (e.g., *BRCA1* + *pathogenic*). - You want to interpret a variant’s **clinical significance** (Pathogenic/Benign/VUS) and **review status** for reporting or triage. - You need to **annotate a VCF** with ClinVar identifiers and interpretation fields as part of a variant annotation pipeline. - You want to perform **bulk retrieval** of ClinVar datasets for offline analysis or periodic database refresh. - You are building a workflow that relies on **NCBI E-utilities** to programmatically query ClinVar. ## Key Features - **ClinVar search** via NCBI E-utilities using flexible query terms (gene/condition/significance). - **Clinical interpretation retrieval**, including clinical significance categories and review status. - **VCF annotation** workflow integration (leveraging `bcftools`) to enrich variants with ClinVar data. - **Bulk data access** through ClinVar FTP downloads for large-scale processing. - Reference documentation: - API details: `references/api_reference.md` - Clinical significance definitions: `references/clinical_significance.md` ## Dependencies - Python `>=3.8` - `requests` (Python package) - `bcftools` (system dependency; required for VCF annotation) - `pandas` (Python package; optional for downstream data processing) ## Example Usage ### 1) Search ClinVar for pathogenic variants in a gene ```bash python scripts/search.py --term "BRCA1[gene] AND pathogenic[CLNSIG]" ``` ### 2) Annotate a VCF with ClinVar data ```bash python scripts/annotate.py --input input.vcf --output annotated.vcf ``` ## Implementation Details - **Search (`scripts/search.py`)** - Uses **NCBI E-utilities** to query ClinVar with a user-provided `--term`. - The query term supports ClinVar/Entrez syntax (e.g., `BRCA1[gene]`, `pathogenic[CLNSIG]`) to filter by gene and clinical significance. - Output is expected to include matching ClinVar records/identifiers suitable for follow-up interpretation or annotation. - **Interpretation fields** - Clinical significance values (e.g., Pathogenic/Benign/VUS) and related interpretation guidance follow ClinVar conventions; see `references/clinical_significance.md`. - Review status (e.g., level of evidence/review) is retrieved alongside significance where available. - **VCF annotation (`scripts/annotate.py`)** - Takes an input VCF (`--input`) and produces an annotated VCF (`--output`). - Integrates with `bcftools` to add ClinVar-derived annotations to variant records (requires `bcftools` installed and available on `PATH`). - Designed for pipeline use: deterministic input/output files and command-line parameters. - **Bulk downloads** - Supports obtaining ClinVar datasets via FTP for offline indexing/annotation workflows. - Recommended when you need reproducible, high-throughput annotation without repeated API calls.
More from aipoch/medical-research-skills
- 3d-molecule-ray-tracerGenerate photorealistic rendering scripts for PyMOL and UCSF ChimeraX.
- abstract-summarizerTransform lengthy academic papers into concise, structured 250-word abstracts.
- abstract-trimmerPrecision editing tool that reduces abstract word count through intelligent compression techniques, maintaining scientific rigor while meeting strict journal and conference requirements.
- academic-abstract-refinerRefines long medical academic texts into SCI-style unstructured Chinese and English abstracts; use when you need to condense drafts/reports/summaries into bilingual abstracts and generate Summary_Report.md.
- academic-cv-generatorGenerate structured academic CVs from free-form Chinese/English text and export to Word (.docx). Use this skill when you are asked to organize, generate, or optimize an academic CV (e.g., publications/projects/awards) into a consistent, formatted document with uniform-colored section headers and optional bilingual output.
- academic-highlight-generatorGenerates submission-ready Elsevier/SCI Highlights from manuscript text or extracted PDF/DOCX/TXT content. Use when a user needs 3-5 concise, evidence-grounded highlight bullets for a research paper, review, meta-analysis, case report, or bioinformatics manuscript.
- academic-norm-reviewDetects content similarity, verifies standardized citations and abbreviations, and flags potential academic integrity risks; use it before submission, during academic writing QA, or for compliance reviews.
- academic-poster-generatorComplete workflow for generating academic research posters from PDF literature; use when you need to extract paper content from PDFs and produce a LaTeX-based poster (beamerposter/tikzposter/baposter) with mandatory figure generation and a final rendered HTML deliverable.
- acronym-unpackerIntelligent medical abbreviation disambiguation tool that resolves ambiguous acronyms using clinical context, specialty-specific knowledge, and document-level semantic analysis.
- active-comparator-single-soc-faers-safety-comparisonGenerates complete FAERS pharmacovigilance study designs for multi-drug or class-level safety comparison inside one predefined SOC or AE family using active comparators, disproportionality analysis, subgroup characterization, and reviewer-facing evidence control.