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R Bioinformatics Cookbook - Second Edition

You're reading from  R Bioinformatics Cookbook - Second Edition

Product type Book
Published in Oct 2023
Publisher Packt
ISBN-13 9781837634279
Pages 396 pages
Edition 2nd Edition
Languages
Author (1):
Dan MacLean Dan MacLean
Profile icon Dan MacLean
Toc

Table of Contents (16) Chapters close

Preface 1. Chapter 1: Setting Up Your R Bioinformatics Working Environment 2. Chapter 2: Loading, Tidying, and Cleaning Data in the tidyverse 3. Chapter 3: ggplot2 and Extensions for Publication Quality Plots 4. Chapter 4: Using Quarto to Make Data-Rich Reports, Presentations, and Websites 5. Chapter 5: Easily Performing Statistical Tests Using Linear Models 6. Chapter 6: Performing Quantitative RNA-seq 7. Chapter 7: Finding Genetic Variants with HTS Data 8. Chapter 8: Searching Gene and Protein Sequences for Domains and Motifs 9. Chapter 9: Phylogenetic Analysis and Visualization 10. Chapter 10: Analyzing Gene Annotations 11. Chapter 11: Machine Learning with mlr3 12. Chapter 12: Functional Programming with purrr and base R 13. Chapter 13: Turbo-Charging Development in R with ChatGPT 14. Index 15. Other Books You May Enjoy

Customizing plots with ggeasy

One of the key aspects of customizing plots in ggplot2 is the theme() function, which allows users to customize elements of the plot’s overall appearance. Customizing plots in ggplot2 can be a little unintuitive. Although the theme() function is powerful, it does require the user to manually specify each element of the plot, such as axis labels, titles, colors, and shapes. The ggeasy package, built on top of ggplot2, aims to make plot customization more accessible by providing a simpler, more intuitive syntax for many common customization tasks. ggeasy provides a set of simple wrapper functions around theme() that make the important things a lot easier to remember. With this recipe, we’ll look at customizing labels, legends, and axes in a plot created initially in ggplot2.

Getting ready

We’ll need the ggplot2, ggeasy, and palmerpenguins packages.

How to do it…

We can customize a plot as follows.

Make a base plot...

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