This site contains the materials for an introductory R course run at Cambridge Makerere Summer School 2025.

29th September - 3rd October 2025

Description

R is one of the leading programming languages in Data Science and the most widely used within CRUK CI for interacting with, analyzing and visualizing cancer biology data sets.

In this training course, we aim to provide a friendly introduction to R pitched at a beginners level.

We will focus on manipulating tabular data and visualising data. We will be using a suite of packages known as the “tidyverse” to do this, in particular the dplyr and ggplot2 packages.

We will be using the RStudio graphical user interface to make working with R more user friendly.

Sessions

  1. Introduction to R - An introduction to RStudio, R objects, data types, functions and vectors
  2. Introduction to R - An introduction to other data structures
  3. Working with data - Working with tabular data in R
  4. Data visualization with ggplot2 - A common grammar to create scatter plots, bar charts, boxplots, histograms and line graphs for time series data
  5. Data manipulation using dplyr - Filtering and modifying tabular data, computing summary values, faceting with ggplot2
  6. Grouping and combining data - Advanced grouping and summarization operations, joining data from different tables, customizing ggplot2 plots
  7. Restructuring data for analysis - The concept of ‘tidy data’, pivoting and separating operations, ggplot2 extras
  8. R Markdown - Creating reproducible reports with R Markdown

Additional resources

  • The “R for Data Science” online book provides a more in-depth look at the tidyverse, covering the concepts introduced and more advanced techniques such as programming with function and iteration across vectors or lists
  • The “ggplot2: Elegant Graphics for Data Analysis” book provides a more in-depth look at ggplot book, covering the concepts introduced in this course and more advanced plotting and customistation
  • A number of very handy cheatsheets for a variety for R packages, including the tidyverse packages, can be found on the RStudio website. As you are beginning to learn how to use these pacakges it is well worth printing these out and having to hand.