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https://github.com/snakemake-workflows/single-cell-rna-seq

A single cell RNA-seq workflow, including highly variable gene analysis, cell type assignment and differential expression analysis.
https://github.com/snakemake-workflows/single-cell-rna-seq

Last synced: 23 days ago
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A single cell RNA-seq workflow, including highly variable gene analysis, cell type assignment and differential expression analysis.

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# Snakemake workflow: single-cell-rna-seq



[![Snakemake](https://img.shields.io/badge/snakemake-≥5.1.4-brightgreen.svg)](https://snakemake.readthedocs.io)

[![GitHub actions status](https://github.com/snakemake-workflows/single-cell-rna-seq/workflows/Tests/badge.svg?branch=master)](https://github.com/snakemake-workflows/single-cell-rna-seq/actions?query=branch%3Amaster+workflow%3ATests)

[![Snakemake-Report](https://img.shields.io/badge/snakemake-report-green.svg)](https://koesterlab.github.io/resources/snakemake-workflows/single-cell-rna-seq/report.html)



A single cell RNA-seq workflow following [Lun, McCarthy and Marioni 2016](https://f1000research.com/articles/5-2122/v2) and [Soneson and Robinson 2018](https://doi.org/10.1038/nmeth.4612), 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 already 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](https://help.github.com/en/articles/creating-a-repository-from-a-template).

2. [Clone](https://help.github.com/en/articles/cloning-a-repository) 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](https://snakemake.readthedocs.io/en/stable/executable.html) 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](https://koesterlab.github.io/resources/snakemake-workflows/single-cell-rna-seq/report.html).



#### 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: Obtain updates from upstream



Whenever you want to synchronize your workflow copy with new developments from upstream, do the following.



1. Once, register the upstream repository in your local copy: `git remote add -f upstream [email protected]:snakemake-workflows/single-cell-rna-seq.git` or `git remote add -f upstream https://github.com/snakemake-workflows/single-cell-rna-seq.git` if you do not have setup ssh keys.

2. Update the upstream version: `git fetch upstream`.

3. Create a diff with the current version: `git diff HEAD upstream/master workflow > upstream-changes.diff`.

4. Investigate the changes: `vim upstream-changes.diff`.

5. Apply the modified diff via: `git apply upstream-changes.diff`.

6. Carefully check whether you need to update the config files: `git diff HEAD upstream/master config`. If so, do it manually, and only where necessary, since you would otherwise likely overwrite your settings and samples.



#### Step 7: Contribute back



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



1. [Fork](https://help.github.com/en/articles/fork-a-repo) the original repo to a personal or lab account.

2. [Clone](https://help.github.com/en/articles/cloning-a-repository) 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 workflow path/to/fork`. Make sure to **not** accidentally copy config file contents or sample sheets. Instead, manually update the example config files if necessary.

4. Commit and push your changes to your fork.

5. Create a [pull request](https://help.github.com/en/articles/creating-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.