sv-callers

Highly portable parallel workflow to detect structural variants in cancer genomes.

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372 commits | Last update: November 09, 2020

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What sv-callers can do for you

  • Enables comprehensive detection of structural variants (SVs) by combining multiple tools
  • Supports both single-sample (germline) and paired-sample (somatic) SV analyses
  • Makes the analyses scalable and easily portable across HPC clusters (e.g., using GridEngine, Slurm etc.) or compute clouds
  • It's easy to use, deploy and extend with new tools

This Snakemake-based workflow combines several state-of-the-art tools (i.e. Manta, DELLY, LUMPY and GRIDSS) for detecting structural variants (SVs) in whole genome sequencing data. The workflow is easy to use and to deploy on any Linux-based machine. In particular, the workflow supports automated software deployment, easy configuration and addition of new analysis tools as well as enables to scale from a single computer to different HPC clusters with minimal effort.

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Tags
  • High performance computing
  • Workflow technologies
  • Big data
Programming Language
  • Python
  • Java
License
  • Apache-2.0
Source code

Participating organizations

Contributors

  • Arnold Kuzniar
    Netherlands eScience Center
  • Stefan Verhoeven
    Netherlands eScience Center
  • Jason Maassen
    Netherlands eScience Center
  • Luca Santuari
    University Medical Center Utrecht
Contact person
Arnold Kuzniar
Netherlands eScience Center

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