Data Analysis and Visualisation in R - Bite-size edition

TinyURL https://tinyurl.com/bs-intR

Description:

It has been said that 80% of data analysis is spent on the process of cleaning and preparing the data. In this course we introduce a suite or R packages collectively known as the tidyverse; this includes the packages tidyr, dplyr, ggplot2 and stringr. In combination these provide a powerful toolkit to make the process of manipulating and visualising data easy and intuitive.

This material is normally taught in an intensive 1 day course, however, in this series it is presented as six 1.5 hour sessions (with homework!).
This format will enable you to:

• Fit in wet-lab work around your dry-science training.
• Consolidate your learning gradually through practive between teaching sessions.
• Allow a more leisurely and flexible training schedule.

Course Prerequisites

• This is an intermediate-level R course aimed at students and research scientists who are already comfortable using R, but who are either not familiar with, or would like to improve their skills in, plotting using ggplot2 and data manipulation using the dplyr and tidyr.
• We will be using RStudio, so if you are not already using RStudio to write R code, it would be helpful to spend some time familiarizing yourself with RStudio.

Objectives

After this course you should be able to:

• Create reproducible documents
• Import and tidy and datasets into R
• Use dplyr to explore a dataset interactively
• Produce simple analysis workflows in R
• Make publication-ready graphics using ggplot2

Aims

During this course you will learn about:

• How R enables reproducible research
• What constitues a tidy dataset
• “Piping” commands together to form a workflow
• Subseting and filtering datasets using dplyr
• Producing summary statistics from a dataset
• Joining datasets using dplyr
• The grammar of graphics approach to plotting used in ggplot2

Trainers

Matt Eldridge (CRUK-CI Bioinformatics Core).
Ashley Sawle (CRUK-CI Bioinformatics Core).

Course outline

Homework Exercises

Session 1

• Exercises
• Answer Template
• Solutions

Session 2

• Exercises
• Answer Template
• Solutions

Session 3

• Exercise and Answer Template
• Solutions - see Exercise 1 in Session 4

Session 4

• Exercise and Answer Template
• Solutions

Session 5

• Exercise and Answer Template
• Solution

Session 6

• Exercises
• Answer Template
• Solution