---
name: sarek
pipeline: nf-core/sarek
version: 3.9.0
commit: b97952e5bac68d5deb93d4a3349a45f146be9830
description: An open-source analysis pipeline to detect germline or somatic variants from whole genome or targeted sequencing
summary: nf-core/sarek is a workflow designed to detect variants on whole genome or targeted sequencing data. Initially designed for Human, and Mouse, it can work on any species with a reference genome. Sarek can also handle tumour / normal pairs and could include additional relapses.
has_samplesheet: true
input: samplesheet (patient, sample, sex, status, lane, fastq_1, fastq_2, spring_1, spring_2, table, cram, crai, bam, bai, contamination, vcf, variantcaller)
output: --outdir/ (per-module results); pipeline_info/ (reports, versions); MultiQC report
tools: ASCAT, alleleCount, BCFTools, BGZip, BWA-MEM, BWA-MEM2, CNVKIT, Condel, Control-FREEC, dbNSFP, DeepVariant, DragMap, EnsemblVEP, FastP, FastQC, FGBio, FreeBayes, GATK, GNU sed, goleft indexcov, HaplotypeCaller Joint Germline, LOFTEE, Manta, Mastermind, Mosdepth, MSIsensor2, MSISensorPro, MultiQC, NGSCheckMate, NVIDIA Clara Parabricks, Phenotypes, PIGZ, P7Zip, SAMtools, snpEff, SpliceAI, SpliceRegion, SPRING, Strelka2, SVDB, Tabix, TIDDIT, Varlociraptor, VCFTools, vcflib, Lofreq, MuSE, R, RColorBrewer
---
# sarek

nf-core/sarek is a workflow designed to detect variants on whole genome or targeted sequencing data. Initially designed for Human, and Mouse, it can work on any species with a reference genome. Sarek can also handle tumour / normal pairs and could include additional relapses.

## Run it
```bash
git submodule update --init pipelines/sarek/upstream   # first time only
nfclaw run sarek --input samplesheet.csv --outdir results -profile docker
# raw equivalent (the submodule is already pinned to this release, so no -r is needed):
nextflow run pipelines/sarek/upstream -profile docker --input samplesheet.csv --outdir results
```

This is the pinned latest release. To run a different one, list the available releases with `nfclaw versions sarek` and add `--pipeline-version X.Y.Z` to the command above (`nfclaw show sarek --pipeline-version X.Y.Z` prints that release's docs).

## Inputs
| column | type | required | allowed values | constraints |
|---|---|---|---|---|
| `patient` | string | yes |  | matches ^\S+$ |
| `sample` | string | yes |  | matches ^\S+$ |
| `sex` | string | no | XX, XY, NA |  |
| `status` | integer | no | 0, 1 |  |
| `lane` | integer or string | no |  | matches ^\S+$ |
| `fastq_1` | string (file path) | no |  | matches ^([\S\s]*\/)?[^\s\/]+\.f(ast)?q\.gz$ |
| `fastq_2` | string (file path) | no |  | matches ^([\S\s]*\/)?[^\s\/]+\.f(ast)?q\.gz$ |
| `spring_1` | string (file path) | no |  | matches ^\S+\.f(ast)?q\.gz.spring$ |
| `spring_2` | string (file path) | no |  | matches ^\S+\.f(ast)?q\.gz.spring$ |
| `table` | string (file path) | no |  | matches ^\S+\.table$ |
| `cram` | string (file path) | no |  | matches ^\S+\.cram$ |
| `crai` | string (file path) | no |  | matches ^\S+\.crai$ |
| `bam` | string (file path) | no |  | matches ^\S+\.bam$ |
| `bai` | string (file path) | no |  | matches ^\S+\.bai$ |
| `contamination` | number | no |  |  |
| `vcf` | string (file path) | no |  | matches ^\S+\.vcf(\.gz)?$ |
| `variantcaller` | string | no |  |  |

Additional row validation rules from the schema:
- When `fastq_2` is set, also provide `fastq_1`.
- When `spring_2` is set, also provide `spring_1`.
- At least one of these conditional requirements must be satisfied: `fastq_1` when `lane` is set; `spring_1` when `lane` is set; `bam` when `lane` is set.

The samplesheet is a CSV with this exact header; fill each value per the table above and `reference.md` (no example value is invented here):
```csv
patient,sample,sex,status,lane,fastq_1,fastq_2,spring_1,spring_2,table,cram,crai,bam,bai,contamination,vcf,variantcaller
```

## Required parameters
| parameter | type | allowed values | constraints | description |
|---|---|---|---|---|
| `--step` | string | mapping, markduplicates, prepare_recalibration, recalibrate, variant_calling, annotate |  | Starting step |
| `--outdir` | string (directory path) |  |  | The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure. |

## Other parameters
Beyond the required parameters above, every other parameter is optional. [reference.md](reference.md) documents them all — type, default, allowed values and constraints — organised into these groups (counts are full group sizes, so they include any required parameters already listed above):
- `annotation` (33 parameters)
- `fastq_preprocessing` (9 parameters)
- `general_reference_genome_options` (5 parameters)
- `generic_options` (17 parameters)
- `input_output_options` (4 parameters)
- `institutional_config_options` (10 parameters)
- `main_options` (7 parameters)
- `post_variant_calling` (10 parameters)
- `preprocessing` (6 parameters)
- `reference_genome_options` (36 parameters)
- `umi_processing` (10 parameters)
- `variant_calling` (25 parameters)

## Outputs
Results land in `--outdir`, organised into one sub-directory per pipeline step/module; standardized run metadata in `<outdir>/pipeline_info/` (execution report, software versions). A MultiQC HTML report aggregates QC across steps. `nfclaw run` also writes `<outdir>/provenance/` with the exact params file and run logs; unless `--no-provenance` it adds a run manifest (pinned version, commit and exact command), input/output SHA-256 checksums, and a replayable `commands.sh`.

The exact output files and directory layout for this release are documented upstream: https://github.com/nf-core/sarek/blob/3.9.0/docs/output.md

## Tools this pipeline runs
The tools/methods this pipeline runs, per the authors' own list: ASCAT, alleleCount, BCFTools, BGZip, BWA-MEM, BWA-MEM2, CNVKIT, Condel, Control-FREEC, dbNSFP, DeepVariant, DragMap, EnsemblVEP, FastP, FastQC, FGBio, FreeBayes, GATK, GNU sed, goleft indexcov, HaplotypeCaller Joint Germline, LOFTEE, Manta, Mastermind, Mosdepth, MSIsensor2, MSISensorPro, MultiQC, NGSCheckMate, NVIDIA Clara Parabricks, Phenotypes, PIGZ, P7Zip, SAMtools, snpEff, SpliceAI, SpliceRegion, SPRING, Strelka2, SVDB, Tabix, TIDDIT, Varlociraptor, VCFTools, vcflib, Lofreq, MuSE, R, RColorBrewer.

Full list with references: https://github.com/nf-core/sarek/blob/3.9.0/CITATIONS.md

## Demo
```bash
nfclaw run sarek --demo --outdir results   # adds the upstream test profile (-profile test,docker)
```

## Full reference
Every parameter — name, type, required, hidden, allowed values, constraints, default and description — is in [reference.md](reference.md). Use it as the source of truth; do not guess flags. Nextflow's nf-schema validates every parameter against this schema at runtime, so an unknown or invalid value fails fast. Upstream usage: https://github.com/nf-core/sarek/blob/3.9.0/docs/usage.md

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