数据与复现临床医学与医药FreedomIntelligence/OpenClaw-Medical-Skills数据与复现

bio-variant-calling-clinical-interpretation

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Clinical variant interpretation using ClinVar, ACMG guidelines, and pathogenicity predictors. Prioritize variants for diagnostic and research applications. Use when interpreting clinical significance of variants.

OpenClawNanoClaw分析处理复现实验bio-variant-calling-clinical-interpretation🧬 bioinformatics (gptomics bio-* suite)bioinformatics — clinical databases & variant analysisclinical

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-variant-calling-clinical-interpretation

维护者: FreedomIntelligence
许可: MIT
最近更新: 2026年4月1日

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

Prioritize 、 interpret variants ，用于 clinical significance ，使用 databases 、 ACMG/AMP guidelines。

原始文档

SKILL.md 摘录

ClinVar Annotation

Goal: Annotate variants with ClinVar clinical significance and filter by pathogenicity.

Approach: Download the ClinVar VCF, add CLNSIG/CLNDN/CLNREVSTAT fields with bcftools annotate, then filter by significance level.

"Find pathogenic variants in my VCF" → Cross-reference variants against ClinVar clinical assertions and extract those classified as pathogenic or likely pathogenic.

Exclude benign

bcftools view -e 'INFO/CLNSIG~"Benign" || INFO/CLNSIG~"Likely_benign"'
with_clinvar.vcf.gz -Oz -o not_benign.vcf.gz


## ClinVar Significance Levels

| CLNSIG | Meaning | Action |
|--------|---------|--------|
| Pathogenic | Disease-causing | Report |
| Likely_pathogenic | Probably disease-causing | Report with caveat |
| Uncertain_significance | VUS | May report, needs follow-up |
| Likely_benign | Probably not disease-causing | Usually exclude |
| Benign | Not disease-causing | Exclude |
| Conflicting | Multiple interpretations | Manual review |