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https://github.com/datasnakes/awesome-reproducible-R

An awesome list of resources for reproducible research in R. Includes a table of comparison for different tools.
https://github.com/datasnakes/awesome-reproducible-R

List: awesome-reproducible-R

r r-consortium r-core reproducible-research reproducible-science ropensci rtools

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An awesome list of resources for reproducible research in R. Includes a table of comparison for different tools.

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README 

        
# awesome-reproducible-R [![Awesome][awesome-badge]](https://github.com/sindresorhus/awesome)



An awesome list of resources for reproducible research in R, which includes a comparison table of different tools.



## Labels



This awesome list contains sections that qualify a list item based on it's __primary feature__.  However, some items might have multiple features or uncommon features.  In order to account for this, we have provided a system of acronyms that will be used to label each item.  Additionally, all of the primary feature acronyms describe the items as __proprietary__ or __native__ based on how closely they rely on existing R based technologies.  In the next section we list these qualifying acronyms, and give details on what they are meant to convey.



### Primary Features



* __Comprehensive Tools__ (_NCT/PCT_) - A suite of tools that accomplishes multiple tasks simultaneously.

* __Project Management__ (_NPM/PPM_) - Helps plan, organize, manage, and develope R projects.

* __Package Management__ (_NPM/PPM_) - Automates the process of installing, upgrading, configuring, or removing R packages from the library path (_.libPath_).

* __R Installation__ (_NRI/PRI_) - Installs the R programming language or manage multiple version of the R programming language.

* __Repository Management__ (_NRM/PRM_) - Creates or updates local or remote package repositories.

* __Repository__ (_NR/PR_) - Public storage locations for retrieving and installing R packages.



### Other Features



* __Command Line Interface__ (_CLI_) - A text based user interface that is accessed by typing a single line of text commands into the terminal or command prompt.

* __Graphical User Interface__ (_GUI_) - A graphical based user interface that is accessed through various icons, menus, and other visual indicators to display information and user controls.

* __Virtual Environment__ (_VE_) - A tool that helps to keep the dependencies of multiple R projects separate by creating an isolated directory tree for installation files and library paths.

* __Virtual Operating System__ (_VOS_) - A tool that virtualizes an appplication or software inside a containerized operating system.

* __R Package__ (_RP_) - The tool is an R package or is primarily written in R.

* __Python Package__ (_PP_) - The tool is a Python package or is primarily written in Python.

* __Other Language__ (_OL_) - The tools is written in another language.

* __Other Feature__ (_OF_) - The tool has a feature not described on the current list.



## Contents



- [Comprehensive Tools](#comprehensive-tools)

- [Project Management](#project-management)

- [Package Management](#package-management)

- [R Installation](#installation)

- [Repository Management](#repo-management)



### Comprehensive Tools



These packages or frameworks incorporate package, project, and data management into one tool/



- [rrtools](https://github.com/benmarwick/rrtools) - The goal of rrtools is to provide instructions, templates, and functions for making a basic compendium suitable for writing reproducible research with R

- [RSuite](https://rsuite.io) - R Suite is an R package which together with R Suite CLI tool enables you to design deployment workflow that fits you and makes R your primary data science platform.



### Package Management



These tools are designed to manage packages or package repositories.



- [reproducible](https://github.com/PredictiveEcology/reproducible) – A set of tools for R that enhance reproducibility beyond package management.



### Project Management



These tools are designed to manage projects.



- [template](https://github.com/Pakillo/template) – A template for research projects structured as R packages.

- [workflowr](https://github.com/jdblischak/workflowr) -  Organize your project into a research website.

- [ProjectTemplate](https://github.com/KentonWhite/ProjectTemplate) - Automatically build a directory for a new R project with a standardized subdirectory structure.



### Data Management



These tools are designed to manage data.



- [DataPackageR](https://github.com/ropensci/DataPackageR) – An R package to enable reproducible data processing, packaging and sharing.

- [archivist](https://github.com/pbiecek/archivist) - An R package that stores copies of all objects along with their metadata



## Contribute



Contributions are welcome! Please read the [contribution guidelines](CONTRIBUTING.md) first.



## License



[![CC0](http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg)](https://creativecommons.org/publicdomain/zero/1.0/)



To the extent possible under law, the Datasnakes have waived all copyright

and related or neighboring rights to this work. See [LICENSE](LICENSE).



[awesome-badge]: https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg