Snakemake workflow: single-cell-rna-seq

A single cell RNA-seq workflow following Lun, McCarthy and Marioni 2016 and Soneson and Robinson 2018, with added more recent functionality.

Authors

• Johannes Köster, https://koesterlab.github.io

Usage

In any case, if you use this workflow in a paper, don't forget to give credits to the authors by citing the URL of this (original) repository and, if available, its DOI (see above).

Step 1: Obtain a copy of this workflow

1. Create a new github repository using this workflow as a template.
2. Clone the newly created repository to your local system, into the place where you want to perform the data analysis.

Step 2: Configure workflow

Configure the workflow according to your needs via editing the file config.yaml.

Step 3: Execute workflow

Test your configuration by performing a dry-run via

snakemake --use-conda -n

Execute the workflow locally via

snakemake --use-conda --cores $N

using $N cores or run it in a cluster environment via

snakemake --use-conda --cluster qsub --jobs 100

or

snakemake --use-conda --drmaa --jobs 100

If you not only want to fix the software stack but also the underlying OS, use

snakemake --use-conda --use-singularity

in combination with any of the modes above. See the Snakemake documentation for further details.

Step 4: Investigate results

After successful execution, you can create a self-contained interactive HTML report with all results via:

snakemake --report report.html

This report can, e.g., be forwarded to your collaborators. An example (using some trivial test data) can be seen here.

Step 5: Commit changes

Whenever you change something, don't forget to commit the changes back to your github copy of the repository:

git commit -a
git push

Step 6: Contribute back

In case you have also changed or added steps, please consider contributing them back to the original repository:

1. Fork the original repo to a personal or lab account.
2. Clone the fork to your local system, to a different place than where you ran your analysis.
3. Copy the modified files from your analysis to the clone of your fork, e.g., cp -r envs rules scripts path/to/fork. Make sure to not accidentally copy config file contents or sample sheets.
4. Commit and push your changes to your fork.
5. Create a pull request against the original repository.

Testing

Test cases are in the subfolder .test. They are automtically executed via continuous integration with Travis CI.