Data & ReproClinical MedicineFreedomIntelligence/OpenClaw-Medical-SkillsData & Reproduction

bio-variant-calling-joint-calling

Maintainer FreedomIntelligence · Last updated April 1, 2026

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.

OpenClawNanoClawAnalysisReproductionbio-variant-calling-joint-calling🧬 bioinformatics (gptomics bio-* suite)bioinformatics — clinical databases & variant analysisjoint

Original source

FreedomIntelligence/OpenClaw-Medical-Skills

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

Maintainer: FreedomIntelligence
License: MIT
Last updated: April 1, 2026

Skill Snapshot

Key Details From SKILL.md

2 min

Key Notes

CLI: gatk HaplotypeCaller -ERC GVCF → gatk GenomicsDBImport → gatk GenotypeGVCFs.
Joint genotype my cohort samples" → Combine per-sample gVCFs into a single cohort callset with consistent genotyping across all sites, enabling VQSR and 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.

Source Doc

Excerpt From SKILL.md

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