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)

Setting Up Your R Bioinformatics Working Environment

R is a powerful and versatile programming language that is widely used in bioinformatics, data science, and statistics. One of the key benefits of using R is its rich ecosystem of packages and libraries, which allows users to easily perform complex tasks and analyze large datasets – in particular, the tidyverse packages, which provide a lot of data science functionality, and the Bioconductor packages, which are state of the art in biological analysis, have provided great power. To get the best out of these and make sure that you are working in the most productive ways, it is important to use the best tools and employ a clear and organized project structure to ensure that your work is readable, maintainable, and reproducible.

One of the most important aspects of a good project structure is separating the different parts into different files and directories based on their purpose. For example, it is a good practice to keep...