Content

We will be covering a number of advanced 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

If you want to check out the course materials from 2022, you can find them here.