This course is the next step after the introductory course. It has several objectives. First, it will discuss effective programming with R, including data manipulation with tidyverse, functional programming and object-oriented programming, debugging, scalability, and reproducible workflows. Second, it will explore key principles of creating and designing data visualizations. Topics include effective composition and layout, effective use of color, improving figure clarity, and techniques for visualizing multidimensional data. The discussion will be supported by examples with ggplot2 graphing library in R. Finally, a lecture on principles of statistical design and data analysis will prepare the participants to the topics of the following week.

The course will combine lectures and practical hands-on exercises. The discussion of programming with R is based on the following textbooks:

Target audience

    Target audience are experimental scientists, bioinformaticians, computer scientists, data scientists, statisticians or engineers, with a minimal prior exposure to R (e.g., at the level of the course ‘Beginner’s statistics in R’) is expected.


    • Kylie Bemis, Steven Braun, Laurent Gatto, Olga Vitek