ECTS credits: 3

 

Course parameters:

Language: English

Level of course: PhD course

Time of year: June 2026

No. of contact hours/hours in total incl. preparation, assignment(s) or the like: 40 contact hours, 30 hours preparation (reading, computer exercises)

Capacity limits: 20 participants

 

Objectives of the course:

Students will learn to produce publication-quality visualisations of biological data using open-source software tools.

 

Learning outcomes and competences:

At the end of the course, the student should be able to:

- Import tabular data into R or Julia

- Carry out basic data manipulation in R or Julia as preparation for plotting

- Generate several kinds of plots using R and Julia

- Navigate relevant documentation and resources for the software tools we will use

- Display data in a clear and honest manner

- Display data in a way that effectively communicates a message

 

Compulsory programme:

Students must be present for lectures and classroom activities and submit a final project.

 

Course contents:

• Prior to course week: Background reading, setting up your computer, and tutorials for basics in R and Julia
• R and ggplot2 crash course – making basic plots
• Grammar of graphics - ggplot2’s internal logic and making advanced plots
• Julia crash course – basic plots with Julia
• Data wrangling – getting your raw data into a form ready for plotting, importing from tricky file formats
• Large language models as coding assistants for visualising data
• Making your plots publication ready using ggpubr and Inkscape
• Principles of good data visualisation – making the right decisions about how to display your data
• Independent projects – learn to apply course knowledge to datasets from your own research, carry out a peer critique of each others’ graphics

 

Prerequisites:

This course is intended for PhD students in the life sciences.

Prior experience with R, Julia or other programming is not required.

 

Name of lecturer:

Ian P.G. Marshall (Dept. of Biology)

 

Type of course/teaching methods:

- Short lectures and discussions

- Computer-based activities to learn how to make basic kinds of plots

- A project where students apply principles learnt in the class with data from their own research

 

Literature:

Course readings will include chapters from ggplot2: Elegant Graphics for Data Analysis by Hadley Wickham and Visual Display of Quantitative Information by Edward Tufte, web-based programming tutorials, and additional journal literature.

 

Time:

June 8-12, 8:30 – 16:30 each day

 

Place:

Aarhus University Campus, Aarhus C (Biologiens Hus, 1223-146)

 

Registration:

Deadline for registration is May 1, 2026. Information regarding admission will be sent out no later than May 5.

Please register by email to Ian P.G. Marshall (ianpgm@bio.au.dk) and include two paragraphs in the main body of the email: a short summary of your PhD project and a summary of the kinds of data you are interested in visualising (you can link to example figures or papers if you like). Qualified applicants will be admitted in the order that they apply.