Data transformation with R tidyverse
Overview
Data transformation (“data wrangling”) is the process of preparing raw data for analysis.

Data wrangling includes cleaning (handling missing values, removing outliers), restructuring (consistent naming of variables, formatting), calculating derived variables, and generally ensuring we have consistent, well-organised data.
Data wrangling will often be the most time-consuming part of any analysis and it is a fundamental aspect of bioinformatics.
This course for data analysts focusses on applications of ideas in the tidyverse. It will be held the first time in February 2026.
This course replaces the R tidyverse workshop previously held from 2017 to 2025.

Course outline
- Tidy data principles
- Data import with readr and tidyr
- Data transformation with dplyr
- Joins, pivots and reshaping
- Data visualisation
Address
University of Luxembourg Belval campus Esch-sur-Alzette
Registration
Instructors
Tyler McInnes (LCSB, Elixir-Luxembourg)
Roland Krause (LCSB, Elixir-Luxembourg)