Snakemake workflow: gnnotator

A Snakemake workflow for genome annotation

• Snakemake workflow: gnnotator
  • Usage
  • Deployment options
  • Authors
  • References
  • TODO

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. This workflow need to run with conda and apptainer / singularity.

cd gnnotator

Provide your own input data in the data/ directory. The default config file is located at config/config.yml. Before running the complete workflow, you can perform a dry run using:

snakemake --dry-run

You can prepare the environments with:

snakemake --sdm conda apptainer --conda-create-envs-only

Run the workflow with 20 cores:

snakemake --cores 20 --sdm conda apptainer

It's recommended to run the workflow with slurm, and do not forget to change account in the slurm/config.yaml file if you are using slurm.

snakemake --sdm conda apptainer --profile slurm

Use the --ri to rerun the uncompleted jobs:

snakemake --sdm conda apptainer --profile slurm --ri

Authors

• RuLei Chen

  • Develop the snakemake workflow
  • Center for Excellence in Molecular Plant Sciences
  • ORCID
  • github

• ZhouLin Gu

  • Design the original pipeline
  • Center for Excellence in Molecular Plant Sciences
  • ORCID

References

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.

TODO