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)

Technical requirements

We will use renv to manage packages in a project-specific way. To use renv to install packages, you will first need to install the renv package. No specific R version seems to be needed for renv, though it’s a good idea to use the latest version of R. renv will automatically record the version of R that you used when you start working with it on a project. Note also that you shouldn’t use renv directly in the home directory, only in project-level directories. You can see more information on this working structure in the Setting up an R project directory and Using the renv package to create a project-specific set of packages recipes.

You can do this by running the following command in your R console:

  1. Install renv:
    install.packages("renv")
  2. Next, you will need to create a new renv environment for your project by running the following command:
    renv::init()

This will create a new directory called ".renv" in your...