mediciprime / single-cell-rna-seq

A single cell RNA-seq workflow following http://dx.doi.org/10.12688/f1000research.9501.2

Snakemake workflow: single-cell-rna-seq

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.

Authors

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

Usage

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 develop this workflow, fork this repository. Please consider providing any generally applicable modifications via a pull request.

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 files config.yaml and cells.tsv.

Step 3: Execute workflow

Test your configuration by performing a dry-run via

snakemake -n

Execute the workflow locally via

snakemake --use-conda --cores $N

using $N cores. Alternatively, it can be run in cluster or cloud environments (see the docs for 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 report with all results via:

snakemake --report report.html

Example output from our test dataset can be seen here.