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)

Interpreting complicated code with ChatGPT assistance

ChatGPT can be used to interpret R code by leveraging its natural language processing capabilities and its understanding of the R programming language. It’s important to note that while ChatGPT can assist in interpreting and explaining R code, it’s still just an AI language model and may not have knowledge of the most recent updates or specific domain-specific intricacies. Double-checking information with official documentation and consulting experienced developers or experts is always necessary. It is massively useful for simplifying and getting a good first-level understanding in most cases.

In this recipe, we’ll look at how to take an arbitrary bit of complex code and explain it in plain English.

Getting ready

We need some code to interpret – we’ll use a function from the besthr Github hosted package at https://github.com/TeamMacLean/besthr/blob/master/R/functions.R and an account with...