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 AnnoDB packages for genome annotation

Bioconductor AnnoDB packages provide a set of software tools and resources for the annotation and functional analysis of genomic data, including DNA sequences, microarray data, and high throughput sequencing data. These packages are designed to help researchers in the field of genomics to better understand the biological significance of their data by providing them with access to a comprehensive database of biological annotations and functional annotations, such as GO pathway analysis, and functional enrichment analysis.

The Bioconductor AnnoDB packages are designed to work with a wide range of genomic data types from various organisms and are regularly updated to include the latest annotations and functional information. Some of the key features of these packages include tools for mapping genomic data to annotated genomic features, tools for retrieving functional annotations for specific genomic regions, and tools for performing various...