gatk-variant-calling
GATK Best Practices for germline SNP/indel calling from WGS/WES BAMs. Per-sample HaplotypeCaller GVCFs, GenomicsDBImport, GenotypeGVCFs joint calling, VQSR or hard filters. Requires BWA-MEM2-aligned, markdup, BQSR BAMs. Use DeepVariant for a faster DL alternative; GATK is the NIH/ENCODE standard.
npx skills add BioTender-max/awesome-bio-agent-skills --skill gatk-variant-calling --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# GATK — Germline Variant Calling Pipeline ## Overview GATK (Genome Analysis Toolkit) implements the GATK Best Practices workflow for calling SNPs and indels from Illumina WGS and WES data. The pipeline runs HaplotypeCaller per sample (producing GVCF files), consolidates GVCFs with GenomicsDBImport, performs joint genotyping with GenotypeGVCFs, and filters variants with VQSR (Variant Quality Score Recalibration) or hard filters. GATK requires BWA-MEM2-aligned, duplicate-marked, and base quality score recalibrated (BQSR) BAM files as input. It integrates with Picard tools, samtools, and bcftools for pre- and post-processing. The GATK4 workflow is the NIH/ENCODE standard for germline variant calling in research and clinical genomics. ## When to Use - Calling germline SNPs and indels from WGS or WES samples for population genetics or clinical variant analysis - Running joint genotyping across multiple samples for cohort-scale studies (families, case-control) - Applying base quality score recalibration (BQSR) to improve variant calling accuracy before HaplotypeCaller - Generating GVCF files for scalable cohort expansion: add new samples without reprocessing existing ones - Producing va
- Overview
- When to Use
- Prerequisites
- Quick Start
- Workflow
- Step 1: Base Quality Score Recalibration (BQSR)
- Step 2: Call Variants with HaplotypeCaller (GVCF Mode)
- Step 3: Consolidate GVCFs with GenomicsDBImport
- Step 4: Joint Genotyping with GenotypeGVCFs
- Step 5: Variant Filtration (Hard Filters)
- Step 6: Parse VCF Results with Python
- Key Parameters
- Common Recipes
- Recipe 1: Single-Sample Variant Calling (No Cohort)
Install GATK4 wget https://github.com/broadinstitute/gatk/releases/download/4.6.0.0/gatk-4.6.0.0.zip unzip gatk-4.6.0.0.zip export GATK="$PWD/gatk-4.6.0.0/gatk" Or with conda conda install -c bioconda gatk4 Verify gatk --version GATK v4.6.0.0 Download GATK resource bundle files (GRCh38)
What does the gatk-variant-calling skill do?
GATK Best Practices for germline SNP/indel calling from WGS/WES BAMs. Per-sample HaplotypeCaller GVCFs, GenomicsDBImport, GenotypeGVCFs joint calling, VQSR or hard filters. Requires BWA-MEM2-aligned, markdup, BQSR BAMs. Use DeepVariant for a faster DL alternative; GATK is the NIH/ENCODE standard.
How do I install it?
Run `npx skills add BioTender-max/awesome-bio-agent-skills --skill gatk-variant-calling --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BioTender-max/awesome-bio-agent-skills, a repository with 144 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.