Book Image

R Bioinformatics Cookbook - Second Edition

By : Dan MacLean
Book Image

R Bioinformatics Cookbook - Second Edition

By: Dan MacLean

Overview of this book

The updated second edition of R Bioinformatics Cookbook takes a recipe-based approach to show you how to conduct practical research and analysis in computational biology with R. You’ll learn how to create a useful and modular R working environment, along with loading, cleaning, and analyzing data using the most up-to-date Bioconductor, ggplot2, and tidyverse tools. This book will walk you through the Bioconductor tools necessary for you to understand and carry out protocols in RNA-seq and ChIP-seq, phylogenetics, genomics, gene search, gene annotation, statistical analysis, and sequence analysis. As you advance, you'll find out how to use Quarto to create data-rich reports, presentations, and websites, as well as get a clear understanding of how machine learning techniques can be applied in the bioinformatics domain. The concluding chapters will help you develop proficiency in key skills, such as gene annotation analysis and functional programming in purrr and base R. Finally, you'll discover how to use the latest AI tools, including ChatGPT, to generate, edit, and understand R code and draft workflows for complex analyses. By the end of this book, you'll have gained a solid understanding of the skills and techniques needed to become a bioinformatics specialist and efficiently work with large and complex bioinformatics datasets.
Table of Contents (16 chapters)

Writing unit tests for R functions with ChatGPT

ChatGPT is beneficial for generating R unit tests because of its knowledge of programming patterns and best practices. It can understand code snippets, including functions and their expected behaviors, and generate relevant unit tests. By leveraging its training on diverse programming contexts, ChatGPT can assist in creating comprehensive test cases that cover different scenarios and edge cases. It helps ensure code correctness, identify potential bugs, and improve code reliability. ChatGPT’s ability to generate unit tests saves developers time and effort, promotes software quality, and contributes to building robust and well-tested R code. In this recipe, we’ll learn how to get ChatGPT to do the tedious work of generating test cases for code that we are working on.

Getting ready

We just need a ChatGPT account: https://chat.openai.com/.

How to do it…

To write unit tests for an R function with ChatGPT,...