We will be covering a number of topics in R programming with focus on R features helpful in bioinformatics and computational biology data analyses workflow:
- Reproducible research in R (Quarto, Rmarkdown, Knitr)
- Collaborative work using Git and GitHub, CD/CI
- R code style guide & best practices
- Code debugging, optimization and profiling
- Parallelisation and vectorization in R
- Writing own functions
- Understanding and using the system of R classes: S3, S4, R6 and RC
- Anatomy of an R package: writing your own package from scratch
- Tidy data flow with tidyverse
- Using the language of graphics, ggplot2
- Developing simple web applications using shiny
- R and Python integration using reticulate
- Streamlined modelling using tidymodels
- Team project work - developing data analyses workflow in R using acquired skills
Course materials will be made available at the beginning of the course and will remain open and publicly accessible online for at least a year.
Invited speakers
Schedule
The morning session begins every day at 08:30 until 12:30 with breakfast at 08:30 to 09:00 and 30 min break at 10:30. The lunch break is 12:30 to 13:30. The afternoon session runs from 13:30 till 17:00 with a 30 min coffee break at 15:00.
Note! Due to time differences, guest lectures may happen later in the evening (after 17:00).