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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

Creating dot plots for alignment visualizations

Dot plots of pairs of aligned sequences are possibly the oldest alignment visualization. In these plots, the positions of two sequences are plotted on the x axis and y axis, and for every coordinate in that space, a point is drawn if the letters (nucleotides or amino acids) correspond at that (x,y) coordinate. Since the plot can show regions that match that aren’t generally in the same region of the two sequences (as lines away from the diagonal), the plot is a good way to visually spot insertions and deletions and structural rearrangements in the two sequences. In this recipe, we’ll look at a speedy method for constructing a dot plot using the dotplot package and a bit of code for getting a grid plot of all pairwise dot plots for sequences in a file.

Getting ready

We’ll need the bhlh.fa file, which contains three basic helix-loop-helix (bHLH) transcription factor sequences from pea, soy, and lotus. The file...

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