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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

Setting Up Your R Bioinformatics Working Environment

R is a powerful and versatile programming language that is widely used in bioinformatics, data science, and statistics. One of the key benefits of using R is its rich ecosystem of packages and libraries, which allows users to easily perform complex tasks and analyze large datasets – in particular, the tidyverse packages, which provide a lot of data science functionality, and the Bioconductor packages, which are state of the art in biological analysis, have provided great power. To get the best out of these and make sure that you are working in the most productive ways, it is important to use the best tools and employ a clear and organized project structure to ensure that your work is readable, maintainable, and reproducible.

One of the most important aspects of a good project structure is separating the different parts into different files and directories based on their purpose. For example, it is a good practice to keep...

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