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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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Concepts
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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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Professor Dan MacLean has a PhD in molecular biology from the University of Cambridge and gained postdoctoral experience in genomics and bioinformatics at Stanford University in California. Dan is now an honorary professor at the School of Computing Sciences at the University of East Anglia. He has worked in bioinformatics and plant pathogenomics, specializing in R and Bioconductor, and has developed analytical workflows in bioinformatics, genomics, genetics, image analysis, and proteomics at the Sainsbury Laboratory since 2006. Dan has developed and published software packages in R, Ruby, and Python, with over 100,000 downloads combined.
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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

Who this book is for

This book is for bioinformaticians, data analysts, researchers, and R developers who want to address intermediate to advanced biological and bioinformatics problems by learning through a recipe-based approach. Working knowledge of the R programming language and basic knowledge of bioinformatics are prerequisites.

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Authors (2)

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Profile icon MacLean
MacLean
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Professor Dan MacLean has a PhD in molecular biology from the University of Cambridge and gained postdoctoral experience in genomics and bioinformatics at Stanford University in California. Dan is now an honorary professor at the School of Computing Sciences at the University of East Anglia. He has worked in bioinformatics and plant pathogenomics, specializing in R and Bioconductor, and has developed analytical workflows in bioinformatics, genomics, genetics, image analysis, and proteomics at the Sainsbury Laboratory since 2006. Dan has developed and published software packages in R, Ruby, and Python, with over 100,000 downloads combined.
Read more
See other products by MacLean
Profile icon Dan MacLean
Dan MacLean
Professor Dan MacLean has a PhD in molecular biology from the University of Cambridge and gained postdoctoral experience in genomics and bioinformatics at Stanford University in California. Dan is now an honorary professor at the School of Computing Sciences at the University of East Anglia. He has worked in bioinformatics and plant pathogenomics, specializing in R and Bioconductor, and has developed analytical workflows in bioinformatics, genomics, genetics, image analysis, and proteomics at the Sainsbury Laboratory since 2006. Dan has developed and published software packages in R, Ruby, and Python, with over 100,000 downloads combined.
Read more
See other products by Dan MacLean
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