Book Image

R Bioinformatics Cookbook - Second Edition

By : Dan MacLean
Book Image

R Bioinformatics Cookbook - Second Edition

By: Dan MacLean

Overview of this book

The updated second edition of R Bioinformatics Cookbook takes a recipe-based approach to show you how to conduct practical research and analysis in computational biology with R. You’ll learn how to create a useful and modular R working environment, along with loading, cleaning, and analyzing data using the most up-to-date Bioconductor, ggplot2, and tidyverse tools. This book will walk you through the Bioconductor tools necessary for you to understand and carry out protocols in RNA-seq and ChIP-seq, phylogenetics, genomics, gene search, gene annotation, statistical analysis, and sequence analysis. As you advance, you'll find out how to use Quarto to create data-rich reports, presentations, and websites, as well as get a clear understanding of how machine learning techniques can be applied in the bioinformatics domain. The concluding chapters will help you develop proficiency in key skills, such as gene annotation analysis and functional programming in purrr and base R. Finally, you'll discover how to use the latest AI tools, including ChatGPT, to generate, edit, and understand R code and draft workflows for complex analyses. By the end of this book, you'll have gained a solid understanding of the skills and techniques needed to become a bioinformatics specialist and efficiently work with large and complex bioinformatics datasets.
Table of Contents (16 chapters)

Comparing changes in distributions with ggridges

Ridge plots, also known as joyplots, are a visualization tool that allows for the clear comparison of multiple distributions in a single plot. The ggridges R package provides an easy-to-use implementation of ridge plots, allowing for the clear comparison of multiple distributions of a single variable by superimposing them on top of each other in a single plot. The package also allows for easy customization of plot features such as color, fill, and theme. The ggridges package is particularly useful for comparing the distribution of a single variable across multiple groups or categories. In this recipe, we will look at implementing some useful ridge plots.

Getting ready

We will need the ggplot2, ggridges, and palmerpenguins packages.

How to do it…

We can look at the changes in distributions using the following steps:

  1. Plot overlapping distributions:
    library(ggplot2)library(ggridges)library(palmerpenguins)ggplot...