R Bioinformatics Cookbook : Utilize R packages for bioinformatics, genomics, data science, and machine learning, 2/e (Paperback)

Discover over 80 recipes for modeling and handling real-life biological data using modern libraries from the R ecosystem

Key Features:

• Apply modern R packages to process biological data using real-world examples
• Represent biological data with advanced visualizations and workflows suitable for research and publications
• Solve real-world bioinformatics problems such as transcriptomics, genomics, and phylogenetics
• Purchase of the print or Kindle book includes a free PDF eBook

Book Description:

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.

What You Will Learn:

• Set up a working environment for bioinformatics analysis with R
• Import, clean, and organize bioinformatics data using tidyr
• Create publication-quality plots, reports, and presentations using ggplot2 and Quarto
• Analyze RNA-seq, ChIP-seq, genomics, and next-generation genetics with Bioconductor
• Search for genes and proteins by performing phylogenetics and gene annotation
• Apply ML techniques to bioinformatics data using mlr3
• Streamline programmatic work using iterators and functional tools in the base R and purrr packages
• Use ChatGPT to create, annotate, and debug code and workflows

Who this book is for:

This book is for bioinformaticians, data analysts, researchers, and R developers who want to address intermediate-to-advanced biological and bioinformatics problems by learning via a recipe-based approach. Working knowledge of the R programming language and basic knowledge of bioinformatics are prerequisites.

發現超過80個使用R生態系統中現代庫來建模和處理真實生物數據的食譜

主要特點：

- 使用真實世界的例子，應用現代R包處理生物數據
- 使用適合研究和出版的高級可視化和工作流程來表示生物數據
- 解決真實的生物信息學問題，如轉錄組學、基因組學和親緣關係學
- 購買印刷版或Kindle書籍可獲得免費PDF電子書

書籍描述：

《R生物信息學食譜》第二版更新了食譜式的方法，向您展示如何使用R進行計算生物學的實際研究和分析。您將學習如何創建一個有用和模塊化的R工作環境，以及使用最新的Bioconductor、ggplot2和tidyverse工具來加載、清理和分析數據。

本書將引導您了解在RNA-seq和ChIP-seq、親緣關係學、基因組學、基因搜索、基因注釋、統計分析和序列分析中所需的Bioconductor工具。隨著您的進步，您將了解如何使用Quarto創建數據豐富的報告、演示文稿和網站，並清楚了解機器學習技術如何應用於生物信息學領域。最後幾章將幫助您掌握關鍵技能，例如基因注釋分析和purrr和base R中的函數編程。最後，您將發現如何使用最新的AI工具，包括ChatGPT，來生成、編輯和理解R代碼，並為複雜分析起草工作流程。

通過閱讀本書，您將獲得扎實的技能和技術，成為一名生物信息學專家，並有效地處理大型和複雜的生物信息學數據。

學到什麼：

- 為生物信息學分析設置工作環境
- 使用tidyr導入、清理和組織生物信息學數據
- 使用ggplot2和Quarto創建出版質量的圖表、報告和演示文稿
- 使用Bioconductor分析RNA-seq、ChIP-seq、基因組學和下一代遺傳學
- 通過執行親緣關係學和基因注釋來搜索基因和蛋白質
- 使用mlr3將機器學習技術應用於生物信息學數據
- 使用base R和purrr包中的迭代器和函數工具來簡化編程工作
- 使用ChatGPT創建、注釋和調試代碼和工作流程

適合對象：

本書適合生物信息學家、數據分析師、研究人員和R開發人員，他們希望通過基於食譜的方法解決中高級生物和生物信息學問題。需要具備R編程語言的工作知識和基本的生物信息學知識。