nf-core/sarek

Edit

Introduction

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.

It’s built using Nextflow, a workflow tool to run tasks across multiple compute infrastructures in a very portable manner. It comes with docker containers making installation trivial and results highly reproducible.

It’s listed on Elixir - Tools and Data Services Registry and Dockstore.

Quick Start

i. Install Nextflow

ii. Install either Docker or Singularity for full pipeline reproducibility (please only use Conda as a last resort; see docs)

iii. Download the pipeline and test it on a minimal dataset with a single command

nextflow run nf-core/sarek -profile test,<docker/singularity/conda/institute>

Please check nf-core/configs to see if a custom config file to run nf-core pipelines already exists for your Institute. If so, you can simply use -profile <institute> in your command. This will enable either docker or singularity and set the appropriate execution settings for your local compute environment.

iv. Start running your own analysis!

nextflow run nf-core/sarek -profile <docker/singularity/conda/institute> --input '*.tsv' --genome GRCh38

See usage docs for all of the available options when running the pipeline.

Documentation

The nf-core/sarek pipeline comes with documentation about the pipeline, found in the docs/ directory:

1. Installation
2. Pipeline configuration
   • Local installation
   • Adding your own system config
   • Install on a secure cluster
   • Reference genomes
   • Extra documentation on reference
3. Running the pipeline
   • Examples
   • Input files documentation
   • Documentation about containers
4. Output and how to interpret the results
   • Extra documentation on variant calling
   • Complementary information about ASCAT
   • Complementary information about Sentieon
   • Extra documentation on annotation
5. Troubleshooting

Credits

Sarek was developed at the National Genomics Infastructure and National Bioinformatics Infastructure Sweden which are both platforms at SciLifeLab, with the support of The Swedish Childhood Tumor Biobank (Barntumörbanken).

Main authors:

• Maxime Garcia
• Szilveszter Juhos

Helpful contributors:

• Adrian Lärkeryd
• Alexander Peltzer
• Chela James
• David Mas-Ponte
• Francesco L
• Friederike Hanssen
• Gisela Gabernet
• Harshil Patel
• James A. Fellows Yates
• Jesper Eisfeldt
• Johannes Alneberg
• Lucia Conde
• Malin Larsson
• Marcel Martin
• Nilesh Tawari
• Olga Botvinnik
• Phil Ewels
• Sabrina Krakau
• Sebastian-D
• Tobias Koch
• Winni Kretzschmar
• arontommi
• bjornnystedt
• cgpu
• gulfshores
• pallolason
• silviamorins

Contributions & Support

If you would like to contribute to this pipeline, please see the contributing guidelines.

For further information or help, don’t hesitate to get in touch on Slack (you can join with this invite) or contact us: maxime.garcia@scilifelab.se, szilveszter.juhos@scilifelab.se

CHANGELOG

• CHANGELOG

Acknowledgements

Citation

If you use nf-core/sarek for your analysis, please cite the Sarek article as follows:

Garcia M, Juhos S, Larsson M et al. Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants [version 1; peer review: 2 approved] F1000Research 2020, 9:63 doi: 10.12688/f1000research.16665.1.

You can cite the sarek zenodo record for a specific version using the following doi: 10.5281/zenodo.3476426

You can cite the nf-core publication as follows:

The nf-core framework for community-curated bioinformatics pipelines.

Philip Ewels, Alexander Peltzer, Sven Fillinger, Harshil Patel, Johannes Alneberg, Andreas Wilm, Maxime Ulysse Garcia, Paolo Di Tommaso & Sven Nahnsen.

Nat Biotechnol. 2020 Feb 13. doi: 10.1038/s41587-020-0439-x.
ReadCube: Full Access Link