R/Medicine 101: Intro to R for Clinicians

Welcome!

This is the website for the R/Medicine 2020 pre-conference short course Introduction to R for Clinicians.

You’ll learn about R Markdown, 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 2020 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.
Join one of the two pre-course technology check sessions - details are in the pre-course email.
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.

Optional (but highly recommended)

To help us better understand our learners, please complete the pre-course survey. We appreciate it!
Install R and RStudio Desktop on your computer. We made video with step by step instructions for installing these on macOS (here) or Windows (here).
You may wish to download and/or print a copy of the course slides. PowerPoint slide decks are available here.

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

R for Data Science (by Hadley Wickham and Garrett Grolemund)
- Solutions Manual (by Jeffrey Arnold)
R Markdown: The Definitive Guide (by Yihui Xie, JJ Allaire, and Garrett Grolemund)
Fundamentals of Data Visualization (by Claus Wilke)
RStudio Cheatsheets

Acknowledgments

This course draws from various sources, most notably Garrett Grolemund’s Welcome to the Tidyverse and Greg Wilson’s Teaching Tech Together. The section of the course discussing dashboards was initially developed by Patrick Mathias. This site uses the distill package.