Subject
A collection of best practices and how-to guides for managing R workflows. These guides are designed to help you leverage R studio to build stable, high-performance research projects.
By following these strategies, you can minimize "dependency nightmare" and protect your productivity from sudden changes in system configurations. Also these strategies allow better encapsulation of projects to migrate to high performance computing or sharing with collaborators. Our goal is to provide you with the framework needed to create portable, reproducible, and scalable research projects.
Information
Informational: Best Practices for Portable and Reproducible R Code Across OS Platforms
Replicating data analysis across different operating systems (Windows, macOS, and Linux) can be a major challenge. Differences in file paths, operating system-specific packages, and shifting package versions often lead to the frustrating "it worked on my machine" dilemma. By adopting a disciplined workflow in RStudio using isolated projects along with the renv and here packages, you can ensure your analysis remains fully portable, reproducible, and resilient over time.
Informational: Managing Library Paths and Packages in RStudio
Managing library paths and packages in RStudio is critical for stable and reproducible workflows. Focusing on user-level configuration and package installations helps avoid permission issues and keeps environments clean and portable.
How-To: Getting started with Rstudio
Quick start guide to using Rstudio on University-managed computers including installation from Company Portal, utilization of creating unique renv environments for each project, adding additional packages and creating snapshots of configurations for portability and reproducibility.".
Index of R/RStudio Guides
Organized listing of How-To guides for installation, configuration, and utilization of R, RStudio, and Rtools.