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
Last synced: 4 months ago
JSON representation
An awesome list of resources for reproducible research in R. Includes a table of comparison for different tools.
- Host: GitHub
- URL: https://github.com/datasnakes/awesome-reproducible-R
- Owner: datasnakes
- License: unlicense
- Created: 2018-10-28T16:09:11.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2023-10-01T02:24:08.000Z (over 1 year ago)
- Last Synced: 2024-04-16T02:29:35.057Z (12 months ago)
- Topics: r, r-consortium, r-core, reproducible-research, reproducible-science, ropensci, rtools
- Language: R
- Size: 11.7 KB
- Stars: 13
- Watchers: 7
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
Awesome Lists containing this project
- jimsghstars - datasnakes/awesome-reproducible-R - An awesome list of resources for reproducible research in R. Includes a table of comparison for different tools. (R)
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
[](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