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)

Extracting and working with subtrees using ape

A common but often frustrating task is cropping trees to look at a section in a new, clearer context or combining them with another tree in order to present two distant clades more clearly. In this short recipe, we’ll look at how easy it can be to manipulate trees- specifically, how to pull out a subtree as a new object and how to combine trees into other trees. We’ll use the ape package, the phylogenetic workhorse in R that will give us functionality for completing those tasks easily.

Getting ready

We’ll need a single example tree – the mammal_tree.nwk file in the rbioinfcookbook package will be fine. All the functions we require can be found in the ape package.

How to do it…

Extracting and working with subtrees in ape can be executed using the following steps:

  1. Load the library and tree:
    library(ape)tree_file <- fs::path_package(  "extdata",  &quot...