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 an R project in a directory

R is a command-line tool, and historically, users would work at the command line in order to make use of the language, but as the complexity of a user’s tasks increases beyond running a few simple commands, then that interface becomes limiting, and more powerful and flexible tools are needed.

RStudio is an integrated development environment (IDE) for the R programming language. It provides a user-friendly interface for writing and running R code, as well as tools for data visualization and data manipulation. RStudio includes a variety of other tools, such as code completion, syntax highlighting, and error checking, which can help users to write and debug their code more efficiently. RStudio provides a powerful and flexible environment that can be customized to suit the needs of individual users. It provides many options for customizing the layout of the interface, including the ability to integrate with GitHub, render help and vignettes...