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)

Index

As this ebook edition doesn't have fixed pagination, the page numbers below are hyperlinked for reference only, based on the printed edition of this book.

Symbols

3D structure protein alignment

predicting, in bio3d 231-233

A

AllelicImbalance

used, for finding allele-specific expression (ASE) 166-169

analysis of variance (ANOVA) 97

using, to compare multiple groups in multiple variable 111-114

using, to compare multiple groups in single variable 108-110

AnnoDB packages

using, for genome annotation 272-274

ape package 238

tree formats, reading and writing 239, 240

used, for extracting and working with subtrees 249-251

apply() functions

using 327-329

arbitrary functions

applying, using mutate() function 36-38

autoplot() function 294

B

base R objects

making tidy 322, 323

basic helix-loop-helix (bHLH) 252

batch effects

estimating, with SVA 164-166

bio3d

3D structure protein alignment...