Introduction

This site contains the materials for an R course run by the Bioinformatics Core at the Cancer Research UK Cambridge Institute.

March-April 2025

Instructors

  • Abigail Edwards
  • Ashley Sawle
  • Chandra Chilamakuri
  • Kamal Kishore

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 but also for those who have been on R training courses previously and would like a refresher or to consolidate their skills.

  • Lesson on Tuesday and Friday in parallel session at 13:00 pm lasting 90 minutes in Room 313.

  • An online catch-up session every Monday at 13.00 p.m. on teams to go over the assignments and for asking questions about the main session.

  • More in-depth material covering the concepts introduced in the teaching lesson to go through in your own time.

  • A weekly assignment consisting of exercises to practice some of the concepts covered in that and previous week’s lessons.

  • Please contact bioinformatics team (340A) if you have any questions. You could also email us on .

  • More in-depth ggplot book covering the concepts introduced in this course to go through in your own time https://ggplot2-book.org/.

  • More in-depth tidyverse book covering the concepts introduced in this course to go through in your own time https://r4ds.had.co.nz/.

Schedule

  1. Introduction to R - An introduction to RStudio, R objects, data types, functions and vectors

  2. Data Structures - An introduction to R data structures

  3. Working with data - Reading data into R tabular data

  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. [Advanced Concepts of R-Studio] - The concepts of using Rmarkdown for reproducible research

  8. [Restructuring data for analysis] - The concept of ‘tidy data’, pivoting and separating operations, ggplot2 extras