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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

Reading and writing varied tree formats with ape and treeio

Phylogenetic analysis is a cornerstone of biology and bioinformatics. The programs are diverse and complex, the computations are long-running, and the datasets are often large. Many programs are standalone and many have proprietary input and output formats. This has created a very complex ecosystem that we must navigate when dealing with phylogenetic data, meaning that, often, the simplest strategy is to use combinations of tools to load, convert, and save the results of analyses in order to be able to use them in different packages. In this recipe, we'll look at dealing with phylogenetic tree data in R. To date, R support for the wide range of tree formats is restricted, but a few core packages have sufficient standardized objects such that workflows can focus on a few types and conversion to those types is streamlined...

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