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)

Retrieving gene and genome annotations from BioMart

Once a draft of a genome sequence is prepared, a lot of bioinformatics work goes into finding the genes and other functional features or important loci that are in a genome. These are numerous, difficult to perform and verify, typically take lots of expertise and time, and are not something we would want to repeat. Genome project consortia will typically share their annotations in some way, often through public databases of some sort. BioMart is a common data structure and computational interface through which annotation data is made available. In this recipe, we’ll look at how to programmatically access such databases so we can get annotations for genes that we are interested in.

Getting ready

For this recipe, we’ll need the biomaRt Bioconductor package and a working internet connection. We’ll also need to know the BioMart server to connect to – there are about 40 worldwide, providing information...