Skip to Main Content

HSLS MolBio Workshops

Information & resources for hands-on bioinformatics classes.


Register to participate in our very first R Bootcamp Week for a deep dive into R programming. The bootcamp unfolds through a series of focused sessions that cover the entire data analysis process, from importing and cleaning data to sophisticated data manipulation and visualization techniques using the tidyverse package. A description of each session is provided below: 


  • Day 1: In "Introduction to R, RStudio, and Quarto Markdown," you'll familiarize yourself with the RStudio interface and learn to create integrated Quarto Markdown documents. 

  • Day 2: "Data Centric R with tidyverse" offers an exploration into R's data types and the analytical prowess of the tidyverse package, broadening your data analysis capabilities. 

  • Day 3: Advance your skills in "Data Exploration in R with tidyverse," focusing on data summarization and the art of visualization with ggplot2. 

  • Day 4: Complete your bootcamp with "Data Wrangling in R with tidyverse," mastering sophisticated data manipulation and cleaning techniques to tackle more complex data challenges. 


Each workshop builds on the last, ensuring a comprehensive understanding and practical application of R for data analysis. 


By the end of this workshop, learners should be able to:  

  • Use the RStudio Server to create Quarto Markdown documents that combine R code with output and text 

  • Use R to import and examine data 

  • Produce numerical and graphical summaries of a data set and its variables 

  • Perform basic data cleaning and management with R 

Target Audience

The target audience for this workshop series is beginners and intermediates in data science, particularly those interested in learning R programming for data importation, exploration, cleaning, and visualization. 


  • None

Course Materials

Prior to Workshop

  • If you do not have any previous knowledge of R/RStudio, or do not have it downloaded on your computer, please follow the instructions given in the Overview Folder. It is important you complete this before the first day. The document will also provide links to additional help and resources for R programming.

Day 1 (June 11, 2024)

Day 2 (June 12, 2024)

Day 3 (June 13, 2024)

Day 4 (June 14, 2024)