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R Bioinformatics Cookbook - Second Edition

You're reading from R Bioinformatics Cookbook - Second Edition

Product type Book

Published in Oct 2023

Publisher Packt

ISBN-13 9781837634279

Pages 396 pages

Edition 2nd Edition

Languages

Concepts

Author (1):

Dan MacLean

Table of Contents (16) Chapters

Preface

1. Chapter 1: Setting Up Your R Bioinformatics Working Environment

2. Chapter 2: Loading, Tidying, and Cleaning Data in the tidyverse

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

Why subscribe?

15. Other Books You May Enjoy

Writing documentation for R functions with ChatGPT

ChatGPT is valuable for generating R documentation because it has been trained on a wide range of text sources, including programming documentation. It can understand user queries related to R functions, packages, and concepts, and generate informative and accurate documentation snippets. With its language understanding capabilities, ChatGPT can provide descriptions, parameter details, usage examples, and even explanations of complex concepts in R. This assists developers in quickly accessing relevant information, clarifying doubts, and understanding the functionality of R functions or packages. ChatGPT serves as a handy tool for enhancing the accessibility and comprehensibility of R documentation, supporting users in their programming and analysis tasks.

In this recipe, we’ll use ChatGPT to help us with the normally very tedious task of generating documentation and examples for our own function.

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Authors (1)

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.

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