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)

Using the devtools package to work with the latest non-CRAN packages

A source R package contains the plain text source code for an R package, which can be installed and built on the user’s machine. A binary R package, on the other hand, is a pre-built version of an R package that contains pre-compiled code and can be installed and used directly without the need to build the package from the source, and without needing all the tools and programs needed for the compilation progress. When we install packages from CRAN using install.packages(), we are typically getting a pre-compiled binary version of the code.

The devtools R package is a collection of tools that make it easier to develop R packages. It includes functions for creating and installing source packages, building and reloading package documentation, and more. Additionally, it also provides functionality to check packages, build documentation, manage package dependencies, and test package functionality. It allows users...