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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

Adding interactivity with Shiny

Shiny is an R package that allows users to build interactive web applications and dashboards with R code. The package provides a framework for building user interfaces (UIs) using R functions and allows users to write server-side logic to respond to user input and update the UI in real time.

The basic structure of a Shiny application consists of two main components: the UI and the server-side logic. The UI is built using R functions that define the layout and structure of the web page, including input controls and output elements. The server-side logic is written in R code and runs on the server in response to user input. When a user interacts with the web page, the input is sent to the server, which processes the input and updates the UI in real time.

Shiny elements can be incorporated into R Markdown documents alongside other text and R code, enabling us to make our analyses interactive if needed. Quarto can render and serve these documents....

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