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nfcore-sarek-wrapper

Orchestrates nf-core/sarek 3.8.1 for germline, tumor-only, and somatic variant calling with reproducibility bundles.

1.1k|257|Updated Feb 25, 2026
Search Tags:#genomics#nf-core#nextflow#somatic#variant calling#sarek#WES
One-click install
npx skills add https://github.com/ClawBio/ClawBio --skill nfcore-sarek-wrapper
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: nfcore-sarek-wrapper
Source: https://github.com/ClawBio/ClawBio/tree/main/skills/nfcore-sarek-wrapper
Command: npx skills add https://github.com/ClawBio/ClawBio --skill nfcore-sarek-wrapper

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Running nf-core/sarek correctly requires hand-crafting samplesheets, choosing between iGenomes keys and explicit FASTA references, pairing tumor/normal statuses properly, and composing Nextflow profiles — mistakes that surface only as opaque mid-pipeline failures. This Skill validates everything before launch and produces a portable, checksummed reproducibility bundle for every run.

Core Features & Use Cases

  • Strict preflight validation: Checks samplesheet structure per pipeline step, tool/mode compatibility (germline, tumor-only, paired somatic), reference availability, Java/Nextflow versions, and resume-state drift before Nextflow launches.
  • Full sarek 3.8.1 surface: Exposes 154 audited passthrough parameters covering mapping, BQSR, variant calling (HaplotypeCaller, Mutect2, Strelka, Manta, ASCAT, and more), and VEP/SnpEff annotation, with profile composition for docker, singularity, arm64, gpu, and spark.
  • Reproducibility and provenance: Every run emits params.yaml, a self-contained commands.sh replay script, manifest.json, checksums.sha256, and seven provenance JSON files, plus opt-in handoff to downstream clinical interpretation skills.
  • Use Case: A researcher with tumor-normal paired WES FASTQs runs a somatic analysis with Mutect2, Strelka, and VEP annotation, then replays the identical run on a colleague's machine using the generated bundle.

Quick Start

Ask the agent to run nf-core/sarek germline variant calling on your samplesheet with HaplotypeCaller and VEP annotation using the GATK.GRCh38 genome, or request a demo run with the upstream test profile.

Frequently Asked Questions about nfcore-sarek-wrapper

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I run nf-core/sarek for somatic tumor-normal variant calling?▼

Provide a samplesheet with patient, sample, status (0=normal, 1=tumor), and FASTQ or BAM/CRAM columns, then run the wrapper with --tools mutect2,strelka,manta,vep and --genome GATK.GRCh38. Preflight validates pairing per patient before Nextflow launches.

What samplesheet format does nf-core/sarek require?▼

Sarek accepts CSV, TSV, YAML, or JSON samplesheets with patient and sample always required. Mapping steps need lane plus fastq_1/fastq_2, spring, or bam; later steps need bam+bai or cram+crai; annotate needs vcf. The wrapper normalizes paths and validates rows per step.

Can I use a custom reference FASTA instead of iGenomes?▼

Yes. Pass --fasta with your reference and the wrapper automatically sets igenomes_ignore so the default GATK.GRCh38 bundle is not loaded. Sarek builds missing .fai and .dict indices from the FASTA automatically.

Why does Mutect2 warn about PON and germline resources?▼

Mutect2 without a panel of normals returns recurrent technical artifacts mixed with true somatic calls, and without a germline resource no germline filtering is applied. The wrapper warns when neither explicit nor iGenomes-inherited resources are effective; supply --pon and --germline-resource for production runs.

Does the sarek wrapper work offline or on air-gapped machines?▼

Real runs with local inputs and references work offline, and NXF_OFFLINE=true avoids remote config fetches. However --demo requires network access because the upstream test profile downloads public test data from GitHub, and the arm64 profile enables Wave container provisioning.

How do I reproduce a completed sarek run on another machine?▼

Each run writes a reproducibility/ bundle containing a self-contained commands.sh that pins the Nextflow engine and pipeline version. Use the bundled remap_paths.py with --old/--new and --refs-old/--refs-new to rebase data and reference paths, then --verify before replaying.

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