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R Bioinformatics Cookbook

You're reading from   R Bioinformatics Cookbook Utilize R packages for bioinformatics, genomics, data science, and machine learning

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Product type Paperback
Published in Oct 2023
Publisher Packt
ISBN-13 9781837634279
Length 396 pages
Edition 2nd Edition
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Author (1):
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Dan MacLean Dan MacLean
Author Profile Icon Dan MacLean
Dan MacLean
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Table of Contents (16) Chapters Close

Preface 1. Chapter 1: Setting Up Your R Bioinformatics Working Environment 2. Chapter 2: Loading, Tidying, and Cleaning Data in the tidyverse FREE CHAPTER 3. Chapter 3: ggplot2 and Extensions for Publication Quality Plots 4. Chapter 4: Using Quarto to Make Data-Rich Reports, Presentations, and Websites 5. Chapter 5: Easily Performing Statistical Tests Using Linear Models 6. Chapter 6: Performing Quantitative RNA-seq 7. Chapter 7: Finding Genetic Variants with HTS Data 8. Chapter 8: Searching Gene and Protein Sequences for Domains and Motifs 9. Chapter 9: Phylogenetic Analysis and Visualization 10. Chapter 10: Analyzing Gene Annotations 11. Chapter 11: Machine Learning with mlr3 12. Chapter 12: Functional Programming with purrr and base R 13. Chapter 13: Turbo-Charging Development in R with ChatGPT 14. Index 15. Other Books You May Enjoy

Estimating the copy number at a locus of interest

We will often want to know how often a sequence occurs in a sample of interest – that is, to estimate whether in a given sample, a locus has been duplicated or its copy number has increased. The locus could be anything from a gene at a Kbp scale or a large section of DNA at a Mbp scale. Our approach in this recipe will be to use HTS read coverage after alignment to estimate a background level of coverage and then compare it to the coverage in a region of interest. The ratio will give us an estimate of the copy number of our region of interest. The recipe here is the first step. The background model we’ll use is very simple – we’ll only calculate a global mean, but we’ll discuss some alternatives later. This recipe does not cover ploidy – the number of genomes present in the whole cell. It is possible to estimate ploidy from similar data but it is a more involved pipeline. Take a look at the...

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