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

bio-variant-calling-joint-calling

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

Joint genotype calling across multiple samples using GATK CombineGVCFs and GenotypeGVCFs. Essential for cohort studies, population genetics, and leveraging VQSR. Use when performing joint genotyping across multiple samples.

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

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

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

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

CLI：gatk HaplotypeCaller -ERC GVCF → gatk GenomicsDBImport → gatk GenotypeGVCFs。
Joint genotype my cohort samples" → Combine per-sample gVCFs into single cohort callset ，支持 consistent genotyping across all sites，enabling VQSR 、 population-level analysis. CLI：gatk HaplotypeCaller -ERC GVCF → gatk GenomicsDBImport → gatk GenotypeGVCFs。
gatk HaplotypeCaller \ -R reference.fa \ -I sample1.bam \ -O sample1.g.vcf.gz \ -ERC GVCF。

原始文档

SKILL.md 摘录

Why Joint Calling?

Improved sensitivity - Leverage information across samples
Consistent genotyping - Same sites called across all samples
VQSR eligible - Requires cohort for machine learning filtering
Population analysis - Allele frequencies across cohort

With intervals (faster)

gatk HaplotypeCaller
-R reference.fa
-I sample1.bam
-O sample1.g.vcf.gz
-ERC GVCF
-L intervals.bed


## Process all samples

for bam in *.bam; do
    sample=$(basename $bam .bam)
    gatk HaplotypeCaller \
        -R reference.fa \
        -I $bam \
        -O ${sample}.g.vcf.gz \
        -ERC GVCF &
done
wait