An Introduction to Solving Biological Problems with R

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.

The course website providing links to the course materials is here.

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 see the list of Related courses. 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.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

• Graduate students, Postdocs and Staff members from the University of Cambridge, Affiliated Institutions and other external Institutions or individuals
• Please be aware that these courses are only free for University of Cambridge students. All other participants will be charged a registration fee in some form. Registration fees and further details regarding the charging policy are available here.
• Further details regarding eligibility criteria are available here

• 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.

Number of sessions: 2

Bioinformatics, Biology, Data handling

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

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

Presentations, demonstrations and practicals

• Free for University of Cambridge students
• £ 50/day for all University of Cambridge staff, including postdocs, and participants from Affiliated Institutions. Please note that these charges are recovered by us at the Institutional level
• It remains the participant's responsibility to acquire prior approval from the relevant group leader, line manager or budget holder to attend the course. It is requested that people booking only do so with the agreement of the relevant party as costs will be charged back to your Lab Head or Group Supervisor.
• £ 50/day for all other academic participants from external Institutions and charitable organizations. These charges must be paid at registration
• £ 100/day for all Industry participants. These charges must be paid at registration
• Further details regarding the charging policy are available here

Participants may find it useful to look over this R tutorial

2

A number of times per year

• Data Manipulation and Visualisation in R
• Statistical Analysis using R
• Basic statistics and data handling
• An Introduction to Machine Learning (ONLINE LIVE TRAINING)
• R object-oriented programming and package development
• CRUK: Data Carpentry in R