Package: rmageddon
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SOFTWARE.Description: # Rmageddon[![Build Status](https://travis-ci.org/qbicsoftware/rmageddon-cli.svg?branch=master)](https://travis-ci.org/qbicsoftware/rmageddon-cli)
[![codecov](https://codecov.io/gh/qbicsoftware/rmageddon-cli/branch/master/graph/badge.svg)](https://codecov.io/gh/qbicsoftware/rmageddon-cli)
[![PyPI version](https://badge.fury.io/py/rmageddon.svg)](https://badge.fury.io/py/rmageddon)A small linting and building command line tool for reproducible R analysis with Docker at QBiC.## Steps to reproducible R analysesCreate project from [template](doc/Rmageddon-cookiecutter.md)[Resolve](doc/Rmageddon.md) conda packages from RsessionInfo[Lint](doc/Rmageddon.md) the project against the guidelines## MotivationPerforming a reproducible analysis with R and share the environment status of an R installation with the
necessary packages and all that with the correct version is a very challenging task.In order to face this issue, under the umbrella of better reproducibility of computational results, we createdRmageddon, a small command-line tool, that assists in the build of Docker container with specified version of R and
a dedicated, version-defined package installation. Moreover, Rmageddon provides cookiecutter templates for the easy creation of docker environments for your R analysis.The container collection is hosted on a different GitHub repository: [R-container-lib](https://github.com/qbicsoftware/r-container-lib). All containers there passed the linting and have been build with Rmageddon.## UsageThe complete workflow for the creation of a new container for your R-analysis is depicted in the following image:![Rmageddon_workflow](https://user-images.githubusercontent.com/21954664/53096328-2acf5580-351f-11e9-898a-1b8ce790afee.png)This README will guide you through the complete process of starting with the sessioninfo of your R-analysis and finally sharing your docker powered R-environment on our [R-container-lib](https://github.com/qbicsoftware/r-container-lib).Create a sessioninfo from your R-analysis. The official R-documentation explains this process well: [Sessioninfo](https://www.rdocumentation.org/packages/utils/versions/3.5.2/topics/sessionInfo).Install Rmageddon. This is explained in the documentation for Rmageddon: [Rmageddon documentation](doc/Rmageddon.md)Create a docker environment using the cookiecutter template. This process is described in the documentation for the [Rmageddon-cookiecutter](doc/Rmageddon-cookiecutter.md)Run Rmageddonbuildon your sessioninfo. This is again explained in the documentation for Rmageddon: [Rmageddon documentation](doc/Rmageddon.md), especially in thesubcommand buildsection.Ensure that your environment.yml file is now or still in your R-container which you created in step 3Add your R-scripts that you used for your analysis to your just created R-containerValidate your just created R-container: Run Rmageddonlinton it. Please refer to the documentation for Rmageddon: [Rmageddon documentation](doc/Rmageddon.md), especially in thesubcommand lintsection.If validation was successful your R-container is now ready to be added to our R-container library. Please refer to the final documentation of the [R-container-lib](https://github.com/qbicsoftware/r-container-lib).Enjoy!Keywords: R,linting,lint,Docker,container
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