nfcore/sarek repository overview

⁠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.

The pipeline is 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

1. Install Nextflow⁠ (>=20.04.0)

2. Install any of Docker⁠, Singularity⁠, Podman⁠, Shifter⁠ or Charliecloud⁠ for full pipeline reproducibility (please only use Conda⁠ as a last resort; see docs⁠)

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

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

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   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.

4. Start running your own analysis!

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

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

⁠Pipeline Summary

By default, the pipeline currently performs the following:

• Sequencing quality control (FastQC)
• Map Reads to Reference (BWA mem)
• Mark Duplicates (GATK MarkDuplicatesSpark)
• Base (Quality Score) Recalibration (GATK BaseRecalibrator, GATK ApplyBQSR)
• Preprocessing quality control (samtools stats)
• Preprocessing quality control (Qualimap bamqc)
• Overall pipeline run summaries (MultiQC)

⁠Documentation

The nf-core/sarek pipeline comes with documentation about the pipeline: usage⁠ and output⁠.

⁠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)⁠. QBiC⁠ later joined and helped with further development.

Main authors:

• Gisela Gabernet⁠
• Maxime Garcia⁠
• Friederike Hanssen⁠
• Szilveszter Juhos⁠

Helpful contributors:

• Adrian Lärkeryd⁠
• Alexander Peltzer⁠
• Chela James⁠
• David Mas-Ponte⁠
• Francesco L⁠
• Harshil Patel⁠
• James A. Fellows Yates⁠
• Jesper Eisfeldt⁠
• Johannes Alneberg⁠
• José Fernández Navarro⁠
• Lucia Conde⁠
• Malin Larsson⁠
• Marcel Martin⁠
• Nilesh Tawari⁠
• Olga Botvinnik⁠
• Paul Cantalupo⁠
• 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 the Slack #sarek channel⁠ (you can join with this invite⁠), or contact us: Maxime Garcia⁠, Szilvester Juhos⁠

⁠CHANGELOG

• CHANGELOG⁠

⁠Acknowledgements

⁠Citations

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

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

In addition, references of tools and data used in this pipeline can be found in the CITATIONS.md⁠ file.

You can cite the nf-core publication as follows: