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)

Using Markdown and Quarto for literate computation

A very common task in bioinformatics is writing up our results in order to communicate them to colleagues or to have a good record in our laboratory books (electronic or otherwise). A key skill is to make the work as reproducible as possible so that we can rerun it ourselves when we need to revisit it or when someone else needs to replicate the process. One very popular way to solve this problem is to use literate programming techniques and executable notebooks that are a mixture of human-readable text, analytical code, and computational output rolled into a single document. In R, the R Markdown extension of the Markdown syntax and the Quarto command-line tool (and R package) allow us to combine code and text in this way and create output documents in a variety of formats. In this recipe, we’ll look at the large-scale structure of a typical document that can be rendered into multiple formats with Quarto.

Getting ready

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