Scientific reproducibility: What is it for?

  • Reproducible research is key for scientific advancement.
  • RStudio can help you to organize, have better control over, and produce reproducible research.

Good Practices for Managing Projects in RStudio

  • Use best practices for file and folder organization. This includes using relative file paths as opposed to complete file paths.
  • Make sure that all data are backed up on multiple devices and that you treat raw data as read-only.
  • We can use Git and GitHub to keep track of what we’ve done in the past and what we plan to do in the future.
  • Rproj files are pivotal to keeping everything bundled and organized.

Navigating RStudio and Quarto Documents

  • RStudio has four panels to organize your code and environment.
  • Manage packages in RStudio using specific functions.
  • Quarto documents combine text and code.

Working with projects in RStudio

Introduction to Working with Quarto documents

  • Quarto lets you create reproducible documents.
  • An qmd file is comprised of a YAML header, formatted text in qmd, and code blocks.
  • The render function converts the file into the chosen output format.

Writing and Styling Qmd Documents

  • The visual editor has made formatting much easier.
  • You can apply Qmd styling without prior Quarto knowledge.
  • You can include inline code to narratives for basic calculations and dynamic information.

Adding Code to Quarto Documents

  • Knitr will render your code and markdown-formatted text and output your document format of choice.
  • Code chunks are runnable pieces of R code.
  • Setting your working directory at the project level can effectively mitigate path-related challenges encountered while working on Quarto documents.

Rendering & Customizing Code Outputs

  • Each time you render/knit the document, calculations and plots will run and be displayed.
  • Options for code chunks can be set at the document level.

Advanced Code Chunk Options

  • Learn how to externally source code source()
  • Learn how to modularize your code to make it more reproducible
  • Use a chunk at the beginning of your document to load libraries and data to make your document more efficient.

Bibliography, Citations & Cross-Referencing

  • Rstudio supports different lookup strategies to make the citation process easier.
  • Rstudio supports different citation styles.
  • The YAML can be adjusted to display uncited items in the reference list.
  • Use bookdown to cross-reference content.

Using Git in RStudio

  • RStudio integrates with Git to track and commit changes performed locally.
  • You may use .gitignore to determine which files Git should ignore when tracking changes.

Collaborating via GitHub

  • Setting up R Studio to authenticate with GitHub using a Personal Authentication Token (PAT).
  • Setting the Git repository Origin in your R Studio project enables pushing and pulling from your local copy of the repository to the repository on GitHub.

Managing Dependencies in R/RStudio

  • Run the sessionInfo() function to take a snapshot of your computational environment.
  • Groundhog is a handy tool for capturing your project’s package dependencies.
  • Make your R scripts reproducible by replacing library(pkg) with groundhog.library(pkg,date).

Publishing your project

  • You may choose to share and publish your data project before publishing its associated manuscript.
  • Sharing the code, data, and documentation is necessary to allow for inspection and research reproducibility.
  • The quarto-journals GitHub organization has journal article formats available for use.

Creating and sharing reproducible environments with renv

  • renv is a handy tool for capturing your project’s package dependencies
  • renv creates a JSON lock file which documents dependencies and let users restore the original versions used for a particular project