This course covers basic concepts on relational databases, parsing files, dashboards, and interactive visualizations using the R programming language.

• Patrick Mathias, MD PhD
  University of Washington Medicine

• Shannon Haymond, PhD
  Northwestern University Feinberg School of Medicine

• A laptop or workstation with access to the internet, and the ability to download files is required
• Complete the following survey so we can better understand your R experience and what you want out of the course: MSACL Intermediate R Pre-Course Survey
• A zip file with the data for the course can be downloaded here
• You are welcome to continue using whatever version of R and RStudio you already have on your computer, but you may run into issues running old versions. Our recommendation (if it won't disrupt your working R environment too much):
  • Install the latest version of R by choosing the closest CRAN mirror here at https://cran.r-project.org/mirrors.html and downloading the version for your operating system
  • If you don't already have a recent version, install the latest version of RStudio Desktop at https://www.rstudio.com/products/rstudio/download/#download
• Open RStudio and confirm you are able to install packages by running install.packages("tidyverse", dependencies = TRUE)
• In addition to the tidyverse set of packages, install additional packages with the following command: install.packages(c("fs", "janitor", "DBI", "RSQLite", "plotly", "flexdashboard", "DT", "kable"), dependencies = TRUE).
  • If you are running a Windows operating system, first install RTools from this site. Then install taskscheduleR by running install.packages("taskscheduleR", dependencies = TRUE).
  • If you are running a Mac or Linux operating system, install cronR by running install.packages("cronR", dependencies = TRUE).
• Optional: If you would like to generate pdf reports with R Markdown and do not already have LaTeX installed on your computer, run install.packages("tinytex", dependencies = TRUE). Then run the following from the RStudio console to install TinyTeX: tinytex::install_tinytex(). Note that you may get error messages when installing on Windows that are OK to click through.

There are multiple ways to access and interact with the course content.

1. Download this github repository as a zip file and install it on your computer (e.g. C:\Users\jdoe\Desktop\Projects\databases-dashboards-in-R).
2. Use git functionality in RStudio by creating a project from version control that is "cloned" from the class repository. This is an option if you have some familiarity with Git. Create a new project (File menu -> New Project), select "Version Control" then "Git" and enter the URL for the course repository when prompted. This will clone the contents from the repo into the directory you specify.
3. You can refer to this website and copy and paste content as the course goes long.

This course is our attempt to integrate a number of already existing outstanding resources for learning R and put a mass spec spin on them. We have tried to include as many links to relevant resources as we can and hopefully have not missed sources of material and inspiration. We should call out a number of people and resources that directly or indirectly have provided content and inspiration for this course:

• Randy Julian and Adam Zabell for their efforts developing the original content for the MSACL intermediate course and for supplying the mass spec data set these courses are built on
• R for Data Science, the online textbook by Garrett Grolemund and Hadley Wickham, is invaluable in navigating the tidyverse and learning R in general
• Data Carpentry for their posted lessons, including this lesson on databases.
• Blog posts and documentation by Jenny Bryan
• Data Science in the Tidyverse, a RStudio course with materials posted online
• Amy Willis' Advanced R Course repository as a resource for understanding content in a longer, advanced R course
• Keith Baggerly and Karl Broman's Reproducible Research module at the Summer Institute in Statistics for Big Data - a big thank you to Keith Baggerly for all of his input and guidance!