Description
R is a highly-regarded, free, software environment for statistical analysis, with many useful features that promote and facilitate reproducible research.
In this course, we give an introduction to the R environment and explain how it can be used to import, manipulate and analyse tabular data. After the course you should feel confident to start exploring your own dataset, using the materials and references provided.
Please note that although we will demonstrate how to perform statistical analysis in R, we will not cover the theory of statistical analysis in this course. Those seeking an in-depth explanation of how to perform and interpret statistical tests are advised to attend other specialized courses such as the Statistical analysis using R. Moreover, those with some programming experience in other languages (e.g. Python, Perl) might wish to attend the follow-on Data Analysis and Visualisation in R course.
Trainers
Aiora Zabala, University of Cambridge
Ashley Sawle, CRUK
Avazeh Ghanbarian, University of Cambridge
Chandra Chilamakuri, CRUK
Cristian Riccio, Sanger Institute
Hugo Tavares, The Sainsbury Laboratory
Jan Attig, Crick Institute
Jing Su, CRUK
Mark Dunning, CRUK
Mukarram Hossain, University of Cambridge
Sandra Cortijo, The Sainsbury Laboratory
Silvia Hadeler, University of Cambridge
Stephanie Owen, CRUK
Audience and Prerequisites
- No prior programming experience is required, but those attending should be able to use a plain text editor.
- A very basic knowledge of UNIX would be an advantage, but nothing will be assumed and extremely little will be required.
- Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals.
Syllabus, Tools and Resources:
During this course you will learn about:
- The RStudio interface to R
- The many ways to access help about R
- Basic object types in R
- Importing tabular data into R
- Manipulating data in R
- Using in-built functions
- Statistical testing in R
- Executing basic data analysis workflows in R
- Basic Plotting
- Customizing plots
- Basic programming with if/else statements and for loops
- Creating reproducible reports in R
Learning Objectives
After this course you should be able to:
- Import data and plot graphs
- Perform statistical tests in R
- Create a documented and reproducible piece of R code
- Know how to develop your skills in R after the course
- Install and use Bioconductor packages
Links
Book Here
Timetable
Day 1 | |
9:30 - 11:00 | Introduction to R and its environment |
11:00 - 12:30 | Data Structures |
12:30 - 13:30 | Lunch |
13:30 - 15:00 | Data Analysis Example |
15:00 - 17:30 | Plotting in R |
Day 2 | |
9:30 - 11:00 | Further customisation of plots |
11:00 - 12:30 | Statistics |
12:30 - 13:30 | Lunch |
13:30 - 15:30 | Data Manipulation Techniques |
15:30 - 17:00 | Programming in R |
17:00 - 17:30 | Further report writing |