lparsons/kas-seq-workflow

KAS-Seq Analysis Workflow

Snakemake workflow: KAS-seq Snakemake Workflow

Workflow to perform KAS-seq analysis

This is the template for a new Snakemake workflow. Replace this text with a comprehensive description, covering the purpose and domain. Insert your code into the respective folders, i.e. scripts, rules and envs. Define the entry point of the workflow in the Snakefile and the main configuration in the config.yaml file.

The workflow is written using Snakemake.

Dependencies are installed using Bioconda where possible.

Setup environment and run workflow

1. Clone workflow into working directory

   git clone <repo> <dir>
   cd <dir>

2. Download input data

   Copy data from URL to data directory

3. Edit config as needed

   nano config.yaml

4. Install dependencies into isolated environment

   conda env create -n <project> --file environment.yaml

5. Activate environment

   source activate <project>

6. Execute workflow

   snakemake -n

7. 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.

Running workflow on gen-comp1

snakemake --cluster-config cluster_config.cetus.yaml \
    --drmaa " --cpus-per-task={cluster.n} --mem={cluster.memory} --qos={cluster.qos}" \
    --use-conda -w 60 -rp -j 1000

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 should be executed via continuous integration with Travis CI.