First Steps with R

Oct 2026 Three days, Belval Campus, Luxembourg Register here

This training course is the recommended starting point for anyone who wants to begin using R for data analysis.

R is a powerful and flexible programming language used by academics, corporations and governments all over the world.

This course will give an introduction to R and RStudio (an integrated development environment for R) in an interactive manner. It is designed to give you a sound understanding of data types and structures and the range of statistical and graphical tools. You will get foundations, essentials for attending the advanced training course.

The course will be held on-site in October and runs over one half day, one full day, and one half day.

Successful completion of the assignments will be awarded with 1 ECTS.

Learning objectives:

By the end of this course, learners will be able to:

  • Organise and reproduce their work using projects, scripts, and readable code.
  • Understand the fundamentals of R: how functions, objects, and packages work together, as well as how the R pipe can chain functions into reproducible workflows.
  • Import and ‘wrangle’ data: take messy, inconsistent data and transform it into tidy data which makes analysis easy.
  • Explore and visualise data with ggplot2, iteratively building plots for exploration and presentation.
  • Carry out a complete bioinformatics-style workflow end to end.

Course outline

This course is structured around three days:

Day 1: Getting Started with R and RStudio

  • Working reproducibly with RStudio Projects, scripts, and Quarto documents
  • The RStudio interface: customising the layout, panes, and editor
  • Fundamentals of the R language: functions, objects, arguments, and packages
  • Importing flat data (CSV) and examining it with core inspection functions
  • Writing clean, readable code with the pipe and consistent style
  • Interpreting errors and warnings, and first steps in exploratory visualisation with ggplot2

Day 2: Working with Data (Data Wrangling)

  • What data wrangling is and why it dominates an analyst’s time
  • The core dplyr verbs for rows: arrange(), filter(), distinct()
  • The core dplyr verbs for columns: relocate(), select(), rename(), mutate()
  • Building filter criteria with Boolean and comparison operators
  • Deriving new variables with mutate() and case_when()
  • Computing grouped summaries with group_by()
  • Introduction to version control with git

Day 3: Importing and Visualising Data (Exploratory Data Analysis)

  • Importing with readr and cleaning messy, inconsistently named data
  • The ggplot2 grammar of graphics and iterative plot building
  • Titles, labels, themes, and fine control of plot aesthetics
  • Layering geoms, faceting, and combining plots with patchwork
  • A range of geoms for different data: points, boxplots, heatmaps, line and area charts
  • A complete start-to-finish workflow on a real dataset: import, explore, wrangle, visualise and refine

Requirements

  • Have a computer ready with a recent version of R (4.5.0 or later) and RStudio (1.2 or later) installed. You will receive instructions and support for setting up your computer in advance of the workshop.

Instructors

Tyler McInnes

Eléonore Schiltz

Registration

Registration will open is now open.

Address

The workshop will be held at:

University of Luxembourg Belval campus Esch-sur-Alzette

Contact

Tyler McInnes

Tyler McInnes (LCSB, Elixir-Luxembourg)