A gentle introduction to data science for healthcare professionals and clinical researchers.
This is the website for the short course Introduction to R for Clinical Data organized by the CHOP R User Group.
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 during the workshop, I suggest the following (none of the below are absolutely necessary!):
chopguest). If you are joining from your home network, you should be OK!The entire course will be recorded and made available to CHOP R User Group members 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.
If you’d like a refresher, we suggest that you download the course materials to your computer and follow along with a replay of the workshop.
Make sure you have both R and RStudio installed (see above).
To download 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. Unzip that file. Inside of the folder that was created by unzipping the file, double click intro-to-r-for-clinicians.Rproj to open a new RStudio session. You should be able to see the exercises folder (among other things) in the Files pane.
Now install all the packages we used in the training environment. To do so, run the following command in the Console:
install.packages(c(
"tidyverse",
"rmarkdown",
"shiny",
"flexdashboard",
"plotly",
"DT"
))
If you haven’t already done so, please consider joining the CHOP R User Group, which is open to anyone with a CHOP or Penn email address. Click here to sign up!
We won’t spam you, we promise, but you’ll get invites to user group meetings (semi-regular, about once a month or so) about all sorts of R-related topics, plus an invite to the Slack channel, where you can chat with folks (and ask questions) about R.
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. Other sections were improved upon by Amrom Obstfeld and Joe Rudolf. This site uses the distill package.