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)

Creating dot plots for alignment visualizations

Dot plots of pairs of aligned sequences are possibly the oldest alignment visualization. In these plots, the positions of two sequences are plotted on the x axis and y axis, and for every coordinate in that space, a point is drawn if the letters (nucleotides or amino acids) correspond at that (x,y) coordinate. Since the plot can show regions that match that aren’t generally in the same region of the two sequences (as lines away from the diagonal), the plot is a good way to visually spot insertions and deletions and structural rearrangements in the two sequences. In this recipe, we’ll look at a speedy method for constructing a dot plot using the dotplot package and a bit of code for getting a grid plot of all pairwise dot plots for sequences in a file.

Getting ready

We’ll need the bhlh.fa file, which contains three basic helix-loop-helix (bHLH) transcription factor sequences from pea, soy, and lotus. The file...