Self-paced workshop
Introduction to R
About
About This Workshop
R is the standard programming language for genomics, bioinformatics, and biomedical data analysis. This workshop will take you from complete beginner to confident R user through hands-on exercises with real patient inflammation datasets.
Duration: 12-15 hours (work at your own pace)
Skills
What You’ll Learn
Foundations
- Navigate RStudio and understand the R environment
- Work with R data types and structures
- Read and write CSV files
- Address and subset data effectively
- Understand factors in R
Advanced Topics
- Create your own functions
- Use conditional statements (if/else)
- Automate analysis with loops
- Apply best practices for clean, reproducible code
Curriculum
Workshop Structure
Ten core lessons, each with clear explanations, hands-on coding exercises, key points summaries, and challenge problems to test your understanding.
01
Introduction to RStudio
Navigate the RStudio interface, understand the four panes, set your working directory, and create your first R script.
02
Data Types and Structures
Vectors, lists, matrices, and data frames — learn how R stores data and how to inspect and manipulate each type.
03
Analysing Patient Data
Your first real analysis! Load patient inflammation data, compute summary statistics, and generate your first plots.
04
Addressing Data
Subset rows and columns, extract values by index and name, and use logical conditions to filter datasets.
05
Reading and Writing CSV Files
Import data from CSV files, handle common formatting issues, and export your results back to disk.
06
Understanding Factors
Learn how R handles categorical data, reorder and relabel factor levels, and avoid common factor pitfalls.
07
Creating Functions
Write your own reusable functions, understand arguments and return values, and reduce code repetition.
08
Making Choices (Conditionals)
Use if, else, and else if to make your code respond to different conditions and handle edge cases.
09
Analysing Multiple Data Sets (Loops)
Automate repetitive tasks with for loops, process multiple patient files in one go, and combine results.
10
Best Practices for Writing R Code
Write clean, readable, reproducible code — naming conventions, commenting, project organisation, and debugging tips.
Who it’s for
Who Should Take This
Graduate Students
Starting computational research and need a solid foundation in data analysis.
Wet Lab Researchers
Needing to analyse your own data instead of relying on others.
Clinicians
Working with patient datasets and wanting reproducible, transparent analyses.
Anyone Beyond Excel
Wanting to move beyond spreadsheets for more powerful data analysis.
No programming background required — just bring curiosity and a laptop.
Before you begin
Get Set Up in 10 Minutes
STEP 01
Install Software
Download R (version 4.0+) — the programming language — and RStudio Desktop — the interface for R. Both free for Mac, Windows, and Linux.
STEP 02
Download Materials
Workshop files (datasets + exercises) are available in the workshop. A quick reference guide is also available. All materials are also accessible inside the workshop interface.
STEP 03
Start Lesson 1
Open RStudio, take a deep breath, and enter the workshop. We’ll walk you through everything from here.
Ready?
Ready to Get Started?
Everything you need is waiting inside. Begin learning R today.
Estimated completion: 12-15 hours • Self-paced • Always available