Data Manipulation and Visualisation

  • Sheffield - 3rd March 2020
  • 09:30am - 5pm

Overview

As the data generated from high-throughput biological experiments increase in volume and become more complex, the ability to manipulate and visualise data is a highly-desirable skill in academia and industry. Whilst familiar tools such as Excel allow basic manipulations, they are often not scalable to larger datasets and are not ameanable to reproducible analysis.

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 visualise tabular data.

After the course you should feel confident to start exploring your own dataset using the materials and references provided.

Course Data

  • Please download and extract (un-zip) this zip file into the directory on your computer that you wish to work in

Materials

Timetable (provisional)

  • 09:30 - 11:00 R basics
  • 11:00 - 12:30 Dealing with Data
  • 12:30 - 13:30 LUNCH (not provided)
  • 13:30 - 14:30 Dealing with Data (continued)
  • 14:30 - 16:00 Plotting
  • 16:00 - 17:00 Summarising and joining

Feedback

Please give us feedback for the course using this form. This will help us improve the course for the future.

Who should attend this course?

Researchers in life sciences who want to get manipulate and visualise their data more efficiently

Objectives:- After this course you should be able to:

  • Import data and plot graphs in R
  • Create a documented and reproducible piece of R code
  • Know how to develop your skills in R after the course

Aims:- 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 with dplyr
  • Using in-built functions
  • Basic Plotting in ggplot2
  • Customizing plots
  • Creating reproducible reports in R

Prerequisites

  • No prior programming experience is required

Software installation

You will need to bring an internet-enabled laptop to the course and install the latest versions of both R and RStudio before coming to the course

Windows

Install R by downloading and running this .exe file from CRAN. Also, please install the RStudio IDE. Note that if you have separate user and admin accounts, you should run the installers as administrator (right-click on .exe file and select “Run as administrator” instead of double-clicking). Otherwise problems may occur later, for example when installing R packages.

Mac

Install R by downloading and running this .pkg file from CRAN. Also, please install the free RStudio IDE

Linux

You can download the binary files for your distribution from CRAN. Or you can use your package manager (e.g. for Debian/Ubuntu run sudo apt-get install r-base and for Fedora run sudo yum install R). Also, please install free the RStudio IDE.

Instructors

  • Mark Dunning, Bioinformatics Core Director
  • Emily Chambers, Bioinformatics Core Analyst
  • Aya Elwazir, PhD Student

References