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Snakemake workflow: star-arriba-fusion-calling

Snakemake GitHub actions status run with conda workflow catalog

A standardized snakemake workflow to map RNAseq reads with star and call fusions on the resulting alignment files with arriba. The main input are RNAseq reads; as a second input, users can provide structural variant calls to improve arriba's filtering.

Usage

The usage of this workflow is described in the Snakemake Workflow Catalog.

Detailed information about input data and workflow configuration can also be found in the config/README.md.

If you use this workflow in a paper, don't forget to give credits to the authors by citing the URL of this repository or its DOI.

Deployment options

To run the workflow from command line, change the working directory.

cd path/to/snakemake-workflow-name

Adjust options in the default config file config/config.yaml. Before running the complete workflow, you can perform a dry run using:

snakemake --dry-run

To run the workflow with test files using conda:

snakemake --cores 2 --sdm conda --directory .test

Authors

  • David Lähnemann
    • German Cancer Consortium (DKTK), partner site Essen-Düsseldorf, A partnership between DKFZ and University Hospital Essen
    • Bioinformatics and Computational Oncology, Institute for AI in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
    • https://orcid.org/0000-0002-9138-4112
  • Felix Mölder
    • Institute of Pathology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
    • Bioinformatics and Computational Oncology, Institute for AI in Medicine (IKIM), University Hospital Essen, University of Duisburg-Essen, Essen, Germany
    • https://orcid.org/0000-0002-3976-9701

References

Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., & Gingeras, T. R. STAR: ultrafast universal RNA-seq aligner. Bioinformatics (Oxford, England), 29(1), 15–21, 2013. https://doi.org/10.1093/bioinformatics/bts635

Sebastian Uhrig, Julia Ellermann, Tatjana Walther, Pauline Burkhardt, Martina Fröhlich, Barbara Hutter, Umut H. Toprak, Olaf Neumann, Albrecht Stenzinger, Claudia Scholl, Stefan Fröhling and Benedikt Brors. Accurate and efficient detection of gene fusions from RNA sequencing data. Genome Research. March 2021 31: 448-460; Published in Advance January 13, 2021. https://doi.org/10.1101/gr.257246.119

Köster, J., Mölder, F., Jablonski, K. P., Letcher, B., Hall, M. B., Tomkins-Tinch, C. H., Sochat, V., Forster, J., Lee, S., Twardziok, S. O., Kanitz, A., Wilm, A., Holtgrewe, M., Rahmann, S., & Nahnsen, S. Sustainable data analysis with Snakemake. F1000Research, 10:33, 10, 33, 2021. https://doi.org/10.12688/f1000research.29032.2.

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A standardized snakemake workflow to map RNAseq reads with star and call fusions on the resulting alignment files with arriba.

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