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A collection of project-related Dockerfiles for a controlled R environment with defined R packages

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R container library for R analyses

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A collection of project-related Dockerfiles for a controlled R environment with defined R packages.

Build new R analysis projects from the template

If you have a new R analysis project and want to add it to the R-container-lib, please follow the process described in Rmageddon. This README assumes that you have the setup as explained in Rmageddon.

1. Fork this repo

Please check the GitHub help pages for that.

2. Clone the fork

As easy as:

git clone https://github.com/<yourname>/r-container-lib

3. Create a new R analysis project using Rmageddon

This step is only necessary if you have not yet created a project using Rmageddon!
Please refer to Rmageddon .

4. Modify the template

Next, you still need to make some adjustments. The current project structure looks like this:

projects/
    projectA/
        scripts/
          myscript.R
        data/
        Dockerfile
        environment.yml     
    projectB/
        ...

Add a subfolder project[X] for your new project and copy its contents into it. Ensure that it contains a Dockerfile, an environment.yml file after the building process of Rmageddon, a data folder and finally a scripts folder with your R scripts.

5. Sanity check: lint

If you want to finally verify that your newly added project doesn't break any requirements you can run Rmageddon lint again on it. Please refer to Rmageddon .

6. Publish your R project

The only thing left is to submit a pull request or directly commit to this repository. If you don't remember git so well, this condensed cheatsheet may help Git Cheatsheet.

Author

This repo was created by Sven Fillinger (@sven1103), Quantitative Biology Center, University of Tübingen.

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A collection of project-related Dockerfiles for a controlled R environment with defined R packages

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