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)

ggplot2 and Extensions for Publication Quality Plots

Clear and informative data visualizations are the most important tool that bioinformaticians have to effectively communicate complex data and findings to other scientists in the field. They allow for easy and efficient exploration and understanding of large and complex datasets. The process of creating a good visualization is very iterative, and many drafts of a visualization are discarded before a final one is settled on, so it is important that we have plotting tools that allow for quick and easy plot creation and customization.

ggplot2 is a popular data visualization library in R that provides an elegant solution for bioinformaticians. It is based on the Grammar of Graphics, a principle that allows users to easily create complex and customizable visualizations by breaking them down into small, modular components, defined by a consistent interface. These make ggplot2 highly flexible and allow for the creation of a wide variety...