R/Medicine 101: Intro to R for Clinical Data

A gentle introduction to data science for healthcare professionals and clinical researchers.
Authors
Affiliations
Stephan Kadauke

Children’s Hospital of Philadelphia

Joseph Rudolf

University of Utah

Patrick Mathias

University of Washington

Welcome!

This is the website for the R/Medicine 2022 pre-conference short course Introduction to R for Clinical Data.

You’ll learn about Quarto, a framework for reproducible data science, and how to perform essential data science tasks such as data import, visualization, transformation, and communication.

For the best experience, we suggest the following (none of the below are absolutely necessary!):

  • If available to you, use two monitors (or another two-screen setup such as a laptop and a tablet or two laptops).
  • To avoid issues caused by overzealous firewalls, you may want to connect from a personal (not work-issued) device using a non-work wireless network.
  • Please use a recent version of macOS or Windows - we have had issues with Linux.
  • We highly recommend you use the Google Chrome browser to access the RStudio Server training environment.

The entire course will be recorded and made available to registered R/Medicine 2022 conference participants for replay. To protect the privacy of participants, no breakouts, video feeds, or chats will be recorded. We also request that you refrain from recording or screen-grabbing any part of the course.

Pre-work

Essential

  • Install the latest version of Zoom.
  • Install the latest version of Google Chrome.
  • We may need to use RStudio Cloud as a backup training environment. Please sign up for a free account here.
  • We want to provide a welcoming and supportive learning environment for everyone. To help us do so, please take a look at our code of conduct.

After the course

If you would like to practice with the materials from the course, go to the GitHub repository, and click the green button labeled “Code” to download the repository as a .ZIP file.

To install all the packages we used in the training environment, open RStudio and run the following command in the Console:

install.packages(c(
  "tidyverse",
  "rmarkdown",
  "shiny",
  "flexdashboard",
  "plotly",
  "DT"
))

Resources

License

All of the material in this GitHub repository is copyrighted under the Creative Commons BY-SA 4.0 copyright to make the material easy to reuse. We encourage you to reuse it and adapt it for your own teaching as you like!

Acknowledgments

This course draws from various sources, most notably Garrett Grolemund’s Welcome to the Tidyverse and Greg Wilson’s Teaching Tech Together. This site was built using Quarto.