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)

Selecting and classifying variants with VariantAnnotation

In variant calling pipelines, we’ll often want to do subsequent analysis steps that need further filtering or classification based on the features of the individual variants, such as the depth of coverage in the alternative allele. This is best done from a VCF file, and a common protocol is to save a VCF of all variants found and experiment with filtering that. In this recipe, we’ll look at taking an input VCF and filtering it to retain variants in which the alternative allele is the major allele in the sample.

Getting ready

We’ll need a tabix index VCF file; one is provided in the rbioinfcookbook package. To extract it, we’ll use the fs package. For analysis, we shall use the VariantAnnotation Bioconductor package.

How to do it…

Selecting and classifying variants with VariantAnnotation can be done as follows:

  1. Create a prefilter function:
    library(VariantAnnotation)is_not_microsat...