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)

Finding unannotated transcribed regions

Finding unannotated transcribed regions can be useful in several different genomics applications. One of the main use cases is identifying novel genes. Unannotated transcribed regions may represent novel genes that have not been previously identified.

By identifying these regions, researchers can gain a better understanding of the genome and potentially discover new biological pathways or proteins. Another use case is identifying alternative splicing events, where different exons are used to create different protein products. Identifying these events can provide insight into how the genome is regulated and how different proteins are produced from the same gene. Additionally, unannotated transcribed regions may include untranslated RNAs (UTRs), lncRNAs, miRNAs, and other types of non-coding RNAs, which can provide a more complete understanding of the functional elements in the genome and characterize the non-coding genome. Lastly, unannotated...