This R package is part of a series of (planned) packages that are aimed at creating a toolkit for doing reproducible and open science. Many researchers (especially in biomedicine, medicine, or health, which is my area of research) have little to no knowledge on what open science is or what reproducibility is, let alone how to do it. My goal is create an (opinionated) toolkit to automate and simplify the process of doing open and reproducible science.
This specific package is a project directory generator (prodigenr). It will create a standardized project folder structure with the necessary template files for managing and analyzing data and for creating common scientific output (posters, slides, abstracts, manuscripts). Because of the standardized structure and because of the focus on a "one project, one scientific output", this allows the final code and documents to be fairly modular, self-contained, easy to share and make public... and be as reproducible as possible. This folder structure also makes use of the existing and established applications and workflows (RStudio, devtools, and usethis). This package aims to make it easier to adhere to open scientific practices by following a standard, consistent, and established folder and file structure for data analysis projects.
Install using the R console via CRAN:
Or for the development version:
# Development version # install.packages("remotes") remotes::install_github('lwjohnst86/prodigenr')
The main function is the
prodigen command. So, for instance, if you
want a manuscript project, type out:
library(prodigenr) setup_project("DiseaseDiet", tempdir()) # open up the newly created project via the Rproj file. Then: create_manuscript() # Or... create_poster() # etc.
This then creates a directory tree, with template files for starting
your analysis! The main secondary function is the
command, which lists the available template projects and files (submit
a PR if you want another template included!):
For a more detailed tutorial, see the introduction vignette:
There are several existing packages for creating projects, each of which has it's own pros and cons. Try them out and see which you like!
prodigenr tries to use ideas from R packages/devtools while still being as simple as possible and be more specific to academic researchers primarily in biomedical/non-computer science fields. However, it can always improve! I welcome any suggestions, just submit a GitHub issue!
See the contributing documentation for information on how to contribute. There is also the roadmap for an overview of the goals and timelines. Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
Special thanks to @zsemnani for creating the logo!
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