| name | alterlab-nf-core-sarek |
| description | Runs FASTQ-to-VCF germline and somatic variant calling via the Nextflow nf-core/sarek pipeline pinned to -r 3.8.1 — builds the samplesheet.csv (patient, sex, status, sample, lane, fastq_1, fastq_2), runs bwa-mem/bwa-mem2/dragmap alignment plus GATK4 MarkDuplicates and BQSR against the GATK GRCh38 resource bundle (dbSNP, Mills/1000G indels), and selects callers — explicitly correcting that sarek defaults to Strelka when --tools is unset (pass haplotypecaller for GATK best practice or deepvariant for CNN accuracy), with a non-Nextflow manual GATK4 fallback. Use when the user wants a variant-calling pipeline, FASTQ to VCF, germline or somatic SNV/indel calling, nf-core/sarek, GATK best-practices alignment-to-VCF, or BQSR/HaplotypeCaller/Mutect2/DeepVariant; annotate hits with alterlab-clinvar/alterlab-gnomad/alterlab-cosmic, parse VCFs with alterlab-pysam, store at scale with alterlab-tiledbvcf. Part of the AlterLab Academic Skills suite. |
| license | MIT |
| allowed-tools | Read Write Edit Bash(python:*) Bash(uv:*) Bash(nextflow:*) |
| compatibility | Requires Nextflow plus a container engine (Docker/Singularity/Apptainer) or conda; the pipeline pulls nf-core/sarek 3.8.1 and reference bundles over the network on first run. The manual GATK4 fallback needs bwa-mem2 + samtools + gatk4 (bioconda) and runs offline once references are local. No API key. Indexing, BQSR and variant calling are long, compute-heavy jobs — good candidates to run locally rather than through repeated API calls. |
| metadata | {"skill-author":"AlterLab","version":"1.0.0","last_updated":"2026-06-06"} |
nf-core/sarek — FASTQ-to-VCF Variant Calling
The workflow-runner entry point for raw-reads-to-variants: drive the
Nextflow nf-core/sarek pipeline (pinned -r 3.8.1)
to take germline or somatic short-read FASTQ through alignment, GATK4 duplicate
marking and base-quality recalibration, and SNV/indel calling, then hand the
resulting VCFs to the suite's database and parsing skills for interpretation.
This skill is the command-line / workflow counterpart to the suite's
Python-library bioinformatics skills. Use it for the raw-data-to-VCF leg;
use the library skills (alterlab-pysam, alterlab-tiledbvcf) once you hold a VCF.
When to Use This Skill
Trigger this skill when the user wants to:
- Go from FASTQ to VCF — call variants on whole-genome (WGS) or whole-exome
(WES) short reads.
- Run germline SNV/indel calling (one or many normal samples).
- Run somatic / tumor-normal calling (matched tumor + normal, or tumor-only).
- Use nf-core/sarek specifically, or want a reproducible "GATK
best-practices alignment-to-VCF" pipeline without hand-writing every step.
- Resume a run from an intermediate
--step (already have BAM/CRAM, only need
recalibration or variant calling).
Does NOT Trigger — route adjacent requests here
| The request is really about… | Route to |
|---|
| Parsing / filtering / reading an existing VCF/BAM in Python (pysam/htslib) | alterlab-pysam |
| Storing / querying large multi-sample variant stores (TileDB-VCF arrays) | alterlab-tiledbvcf |
| Clinical significance of a called variant (pathogenic/benign) | alterlab-clinvar |
| Population allele frequencies for a called variant | alterlab-gnomad |
| Somatic mutation catalogue / cancer census lookup | alterlab-cosmic |
| RNA-seq transcript/gene quantification (salmon/kallisto), not DNA variants | alterlab-rnaseq-quant |
| 16S/ITS FASTQ → feature table |
