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R Bioinformatics Cookbook

You're reading from   R Bioinformatics Cookbook Use R and Bioconductor to perform RNAseq, genomics, data visualization, and bioinformatic analysis

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Product type Paperback
Published in Oct 2019
Publisher Packt
ISBN-13 9781789950694
Length 316 pages
Edition 1st Edition
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Authors (2):
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Dr Dan Maclean Dr Dan Maclean
Author Profile Icon Dr Dan Maclean
Dr Dan Maclean
Dan MacLean Dan MacLean
Author Profile Icon Dan MacLean
Dan MacLean
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Toc

Table of Contents (13) Chapters Close

Preface 1. Performing Quantitative RNAseq 2. Finding Genetic Variants with HTS Data FREE CHAPTER 3. Searching Genes and Proteins for Domains and Motifs 4. Phylogenetic Analysis and Visualization 5. Metagenomics 6. Proteomics from Spectrum to Annotation 7. Producing Publication and Web-Ready Visualizations 8. Working with Databases and Remote Data Sources 9. Useful Statistical and Machine Learning Methods 10. Programming with Tidyverse and Bioconductor 11. Building Objects and Packages for Code Reuse 12. Other Books You May Enjoy

Phylogenetic Analysis and Visualization

The comparison of sequences in order to infer evolutionary relationships is a fundamental technique of bioinformatics. It has a long history in R, too. There are many packages outside of Bioconductor for evolutionary analysis. In the recipes in this chapter, we will take a good look at how to work with tree formats from a variety of sources. A key focus will be how to manipulate trees to focus on particular parts and work with visualizations based on the new ggplot-based tree visualization packages, and the latter's usefulness in terms of viewing and annotating large trees.

The following recipes will be covered in this chapter:

  • Reading and writing varied tree formats with ape and treeio
  • Visualizing trees of many genes quickly with ggtree
  • Quantifying distances between trees with treespace
  • Extracting and working with subtrees using...
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