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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

Plotting features on genetic maps with karyoploteR

One of the most rewarding and insightful things we can do is visualize data. Very often, we want to see where some features lie concerning others on a chromosome or genetic map. These are sometimes called chromosome plots or ideograms. In this recipe, we’ll learn how to create one of these using the karyoploteR package. This package takes the familiar GRanges objects as input and creates detailed plots from the configuration. We’ll take a quick look at some different plot styles and configuration options for ironing out the bumps in your plots when labels spill off the page or overlap each other.

Getting ready

For this recipe, you’ll need karyoploteR installed. All of the data we’ll use will be generated within the recipe itself.

How to do it…

Plotting features on genetic maps with karyoploteR can be done by performing the following steps:

  1. First, load the necessary libraries:
    library...
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