• Leon Eyrich Jessen
• Assistant Professor of Bioinformatics at DTU Health Tech
• Machine Learning and Immunoinformatics
• T-cell receptor specificity modelling and analysis
• Wetlab bio-engineer turned bioinformatician
• ~10y base R experience
• ~4y of Tidyverse experience
• Other stuff: Python, Perl, C, C++, java, basic, php, css, html… bla bla
• Also teach 22145 Immunological Bioinformatics

1. Course Introduction
2. Reproducibility and Replicability in modern Bio Data Science
   • Talk: “How to organize a project - The most important talk you never heard!”
3. Getting started with RStudio and Rmarkdown
4. Exercises: R - The very basics

• You’re the first batch of students in this course!
• Therefore, I will develop and adjust the course as we go along
• Please approach me with feedback

Online

• Official course website
• DTU Course Base

Text Book(s)

• Main: R for Data Science by Garrett Grolemund and Hadley Wickham
• Also: Statistical Inference via Data Science - A moderndive into R and the tidyverse by Chester Ismay and Albert Y. Kim
• Also: Mastering Shiny by Hadley Wickham
• Also: Introduction to Data Science, Data Analysis and Prediction Algorithms with R by Rafael A. Irizarry

(See schedule for details)

• Active Learning: Strong emphasis on students working, rather than me talking
• First ~1h will be recap of exercises and subject-of-the-day introduction
• Next ~3h will be hands-on exercises
• Communication: Slack!

• General course objectives from DTU Course Base:
  • The overall aim of the course is to provide students with a toolkit of concrete skills in modern bio data science in Tidyverse R via the RStudio IDE. There will be a strong application-oriented focus on moving from a messy to a clean data set. Followed by data transformation, gaining insight through EDA and communication through data visualization using ggplot. All in the context of reproducible data analysis. Furthermore, the focus will be on the design and organization of a modern bio data science project in Tidyverse R. In this course we will work with biology related data sets.

• Pre-course questionnaire

• Expected work load: 1 ECTS ~28h, so 5 ECTS ~140h, distributed on 13 weeks and an exam, ~10h/week

• Let’s go, onwards to RStudio Cloud

• Go to the online book chapter you have read today and work through it