This series of hands-on workshops aims to introduce students to the concept of research reproducibility and to get the students practicing with using version control systems and with using modern techniques in R that make analyses less error prone and reproducible, and that make you more efficient, productive, and in control. Techniques for using version control systems to faciliate greater collaboration among peers will also be presented. The ultimate goal of the workshop is to show how to reduce the number of steps needed to go from the initial data analysis to the final written manuscript or thesis (hence the name Code As Manuscript). Given the applied nature of the concepts in these workshops, hands-on activities and live coding will be integrated into each workshop.


The expected goal of the workshops is that you will be able to:

  • Learn how to use R for common data analysis problems
  • Produce publication quality plots
  • Get your data into an easily analyzable format
  • Use R code in your manuscript/thesis to re-generate results and plots

By achieving these goals, you will be on your way to making an efficient and productive workflow, that will make it easier for you do to your work and research, and that is also scientifically rigorous and transparent. Because R is free and open source, these are skills you can take with you wherever your career takes you.


The workshop will cover the following topics:

  1. Intro to R and RStudio
  2. Data wrangling (management, organizing)
  3. Visualization
  4. Dynamic report generation

Date & time:


Intended audience:

Graduate students or post-docs whose research involves a fair amount of data analysis. No experience necessary for these workshops.


  • See the instructions page
  • Bring a positive, not-afraid-of-making-mistakes-or-feeling-unsure attitude!! Learning any language (either human or computer) is hard work and not easy, but can be done!


Because this is a hands-on workshop, at the end of each workshop, we have an activity for you to try out. And since this is a GPS-approved course, if you want to get a GPS credit, you will need to:

  1. Come to all the workshops (though we can be flexible).
  2. Complete each workshop assignment using R Markdown, copy contents of the generated .md file into a GitHub Issue, and attach the original .Rmd file to the Issue.

Don’t worry if this doesn’t make sense yet. We will go over these details in the workshop.


  • Luke Johnston, MSc, PhD (c)

You can contact the workshop email at: