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R Bioinformatics Cookbook

You're reading from   R Bioinformatics Cookbook Utilize R packages for bioinformatics, genomics, data science, and machine learning

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781837634279
Length 396 pages
Edition 2nd Edition
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Author (1):
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Dan MacLean Dan MacLean
Author Profile Icon Dan MacLean
Dan MacLean
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Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Setting Up Your R Bioinformatics Working Environment 2. Chapter 2: Loading, Tidying, and Cleaning Data in the tidyverse FREE CHAPTER 3. Chapter 3: ggplot2 and Extensions for Publication Quality Plots 4. Chapter 4: Using Quarto to Make Data-Rich Reports, Presentations, and Websites 5. Chapter 5: Easily Performing Statistical Tests Using Linear Models 6. Chapter 6: Performing Quantitative RNA-seq 7. Chapter 7: Finding Genetic Variants with HTS Data 8. Chapter 8: Searching Gene and Protein Sequences for Domains and Motifs 9. Chapter 9: Phylogenetic Analysis and Visualization 10. Chapter 10: Analyzing Gene Annotations 11. Chapter 11: Machine Learning with mlr3 12. Chapter 12: Functional Programming with purrr and base R 13. Chapter 13: Turbo-Charging Development in R with ChatGPT 14. Index 15. Other Books You May Enjoy

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...
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