rmageddon 0.3.1
Small linting and building tool for R containers at QBiC
License: MIT License

Copyright (c) 2018 QBiC

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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 analyses
        
        1. Create project from [template](doc/Rmageddon-cookiecutter.md) 
        2. [Resolve](doc/Rmageddon.md) conda packages from R `sessionInfo` 
        3. [Lint](doc/Rmageddon.md) the project against the guidelines
        
        
        ## Motivation
        
        Performing 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 created
        **Rmageddon**, 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.
        
        ## Usage
        
        The 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).
        
        1. 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).
        2. Install Rmageddon. This is explained in the documentation for Rmageddon: [Rmageddon documentation](doc/Rmageddon.md)
        3. Create a docker environment using the cookiecutter template. This process is described in the documentation for the [Rmageddon-cookiecutter](doc/Rmageddon-cookiecutter.md)
        4. Run Rmageddon **build** on your sessioninfo. This is again explained in the documentation for Rmageddon: [Rmageddon documentation](doc/Rmageddon.md), especially in the **subcommand build** section.
        5. Ensure that your environment.yml file is now or still in your R-container which you created in step 3
        6. Add your R-scripts that you used for your analysis to your just created R-container 
        7. Validate your just created R-container: Run Rmageddon **lint** on it. Please refer to the documentation for Rmageddon: [Rmageddon documentation](doc/Rmageddon.md), especially in the **subcommand lint** section.
        8. 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).
        9. Enjoy!
        
        
Keywords: R,linting,lint,Docker,container
Platform: UNKNOWN