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 DNA motifs with universalmotif

A very common task when working with DNA sequences is finding instances of motifs – a short-defined sequence – within a longer sequence. These could represent protein-DNA binding sites such as transcription factor binding sites in a gene promoter or enhancer region. There are two starting points for this analysis – you either have a database of motifs that you want to use to scan target DNA sequences and extract wherever the motif occurs or you have just the sequences of interest and you want to find out whether there are any repeating motifs in there. We’ll look at ways of doing both of these things in this recipe.

Getting ready

For this recipe, we need a matrix describing the motif (a position-specific weight matrix or PWSM) and a set of sequences from upstream of transcriptional start sites. These are provided in the rbioinfcookbok package. We’ll use the universalmotif package to work with motifs and...