/rna-seq-star-deseq2

RNA-seq workflow using STAR and DESeq2

Primary LanguagePythonMIT LicenseMIT

Snakemake workflow: rna-seq-star-deseq2

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This workflow performs a differential expression analysis with STAR and Deseq2.

Authors

Usage

Simple

Step 1: Install workflow

If you simply want to use this workflow, download and extract the latest release. If you intend to modify and further extend this workflow or want to work under version control, fork this repository as outlined in Advanced. The latter way is recommended.

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 repository and, if available, its DOI (see above).

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

See the Snakemake documentation for further details.

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.

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.

Advanced

The following recipe provides established best practices for running and extending this workflow in a reproducible way.

  1. Fork the repo to a personal or lab account.
  2. Clone the fork to the desired working directory for the concrete project/run on your machine.
  3. Create a new branch (the project-branch) within the clone and switch to it. The branch will contain any project-specific modifications (e.g. to configuration, but also to code).
  4. Modify the config, and any necessary sheets (and probably the workflow) as needed.
  5. Commit any changes and push the project-branch to your fork on github.
  6. Run the analysis.
  7. Optional: Merge back any valuable and generalizable changes to the upstream repo via a pull request. This would be greatly appreciated.
  8. Optional: Push results (plots/tables) to the remote branch on your fork.
  9. Optional: Create a self-contained workflow archive for publication along with the paper (snakemake --archive).
  10. Optional: Delete the local clone/workdir to free space.

Testing

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