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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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Toc

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

Finding GO enrichment in an Ontology Conditional way with topGO

The GO is a hierarchical ontology that describes the biological processes, molecular functions, and cellular components of gene products in a standardized way. The ontology is structured as a directed acyclic graph (DAG) with three main categories: Biological Process (BP), Molecular Function (MF), and Cellular Component (CC).

Higher in the GO hierarchy, there are broader terms; for example, in the BP category, terms such as biological regulation and cellular process exist. As we move down the hierarchy, the terms become more specific and narrower in scope, and regulation of gene expression or protein localization to organelle are more specific terms within the BP category. Each term has parent terms and child terms.

The hierarchical nature of the GO allows researchers to perform analyses at different levels of specificity. A common need is to collapse similar terms into a higher, more general term that captures them...

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