Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletter Hub
Free Learning
Arrow right icon
timer SALE ENDS IN
0 Days
:
00 Hours
:
00 Minutes
:
00 Seconds
R Bioinformatics Cookbook
R Bioinformatics Cookbook

R Bioinformatics Cookbook: Utilize R packages for bioinformatics, genomics, data science, and machine learning , Second Edition

eBook
₹799.99 ₹2382.99
Paperback
₹2978.99
Subscription
Free Trial
Renews at ₹800p/m

What do you get with a Packt Subscription?

Free for first 7 days. ₹800 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing
Table of content icon View table of contents Preview book icon Preview Book

R Bioinformatics Cookbook

Loading, Tidying, and Cleaning Data in the tidyverse

Cleaning data is a crucial step in the data science process. It involves identifying and correcting errors, inconsistencies, and missing values in the data, as well as formatting and structuring the data in a way that makes it easy to work with. This allows the data to be used effectively for analysis, modeling, and visualization. The R tidyverse is a collection of packages designed for data science and includes tools for data manipulation, visualization, and modeling. The dplyr and tidyr packages are two of the most widely used packages within the tidyverse for data cleaning. dplyr provides a set of functions for efficiently manipulating large datasets, such as filtering, grouping, and summarizing data. tidyr is specifically designed for tidying (or restructuring) data, making it easier to work with. It provides functions for reshaping data, such as gathering and spreading columns, and allows for the creation of a consistent structure in the data. This makes it easier to perform data analysis and visualization. Together, these packages provide powerful tools for cleaning and manipulating data in R, making it a popular choice among data scientists. In this chapter, we will look at tools and techniques for preparing data in the tidyverse set of packages. You will learn how to deal with different formats and quickly interconvert them, merge different datasets, and summarize them. You will also learn how to bring data from outside sources not in handy files into your work.

In this chapter, we will cover the following recipes:

  • Loading data from files with readr
  • Tidying a wide format table into a tidy table with tidyr
  • Tidying a long format table into a tidy table with tidyr
  • Combining tables using join functions
  • Reformatting and extracting existing data into new columns using stringr
  • Computing new data columns from existing ones and applying arbitrary functions using mutate()
  • Using dplyr to summarize data in large tables
  • Using datapasta to create R objects from cut-and-paste data
Left arrow icon Right arrow icon

Key benefits

  • 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

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.

Who is this book 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.

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

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 31, 2023
Length: 396 pages
Edition : 2nd
Language : English
ISBN-13 : 9781837634279
Languages :
Concepts :
Tools :

What do you get with a Packt Subscription?

Free for first 7 days. ₹800 p/m after that. Cancel any time!
Product feature icon Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!
Product feature icon 50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.
Product feature icon Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.
Product feature icon Thousands of reference materials covering every tech concept you need to stay up to date.
Subscribe now
View plans & pricing

Product Details

Publication date : Oct 31, 2023
Length: 396 pages
Edition : 2nd
Language : English
ISBN-13 : 9781837634279
Languages :
Concepts :
Tools :

Packt Subscriptions

See our plans and pricing
Modal Close icon
₹800 billed monthly
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Simple pricing, no contract
₹4500 billed annually
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just ₹400 each
Feature tick icon Exclusive print discounts
₹5000 billed in 18 months
Feature tick icon Unlimited access to Packt's library of 7,000+ practical books and videos
Feature tick icon Constantly refreshed with 50+ new titles a month
Feature tick icon Exclusive Early access to books as they're written
Feature tick icon Solve problems while you work with advanced search and reference features
Feature tick icon Offline reading on the mobile app
Feature tick icon Choose a DRM-free eBook or Video every month to keep
Feature tick icon PLUS own as many other DRM-free eBooks or Videos as you like for just ₹400 each
Feature tick icon Exclusive print discounts

Frequently bought together


Stars icon
Total 11,022.97
Bioinformatics with Python Cookbook
₹4319.99
The Statistics and Machine Learning with R Workshop
₹3723.99
R Bioinformatics Cookbook
₹2978.99
Total 11,022.97 Stars icon

Table of Contents

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

Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.7
(3 Ratings)
5 star 66.7%
4 star 33.3%
3 star 0%
2 star 0%
1 star 0%
Rudrendu Kumar Paul Nov 04, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The R Bioinformatics Cookbook by Dan MacLean is a practical, comprehensive guide aimed at bioinformaticians looking to expand their data analysis skills using R and Bioconductors. With the author's extensive background in genomics, molecular biology, and bioinformatics, readers can trust that the book provides authoritative content.A major strength of the cookbook format is it supplies readers with recipe-based solutions to tackle common bioinformatics challenges. Rather than just theory, professionals get hands-on guidance to put concepts into practice. The book spans a versatile range of topics - from the initial setup of the R environment to sophisticated methods like machine learning. This ensures readers can find both introductory building blocks as well as more advanced techniques to round out their skills.Notably, the book thoroughly covers specialized packages and frameworks within the R ecosystem that are tailored for bioinformatics. Readers are immersed in the diverse capabilities of Bioconductor along with packages like ggplot2 for publication-quality graphics and mlr3 for machine learning. The focus on R capabilities designed for biological data analysis is a distinguishing factor.The content covers crucial bioinformatics techniques such as RNA-seq analysis, variant calling from DNA sequencing data, statistical modeling, and phylogenetic approaches. There is also a significant emphasis on data visualization and interpretation - essential skills for research. Interactive elements utilizing Shiny and Quarto demonstrate new avenues for impactful data presentation.While the book is geared towards those with some existing R familiarity, beginners may need help due to the assumed knowledge and density of information spanning many techniques. However, intermediate to advanced R users in bioinformatics will find an invaluable guide for expanding their toolkit in a hands-on manner. They can level up skills in both fundamental and cutting-edge data analysis areas.Additional topics could potentially enhance the book even further. As biological datasets explode in size, guidance on leveraging cloud computing could prove useful. More coverage of sophisticated machine learning methods like deep learning would keep readers abreast of the latest techniques for modeling complex data. Single-cell sequencing and metagenomics represent rapidly growing areas where extra content would make this guide more comprehensive for the field.The R Bioinformatics Cookbook is a practical, authoritative resource for bioinformaticians looking to hone their R skills for impactful data analysis. The hands-on solutions, specialized coverage of R packages, and techniques like statistical modeling and visualization make it a robust guide for intermediate to advanced practitioners seeking to expand their toolkits. While beginners may need more foundational content, the book's recipe-based approach helps professionals readily apply concepts to real-world biological studies.
Amazon Verified review Amazon
Amazon Customer Nov 04, 2023
Full star icon Full star icon Full star icon Full star icon Full star icon 5
AI practitioners looking to upgrade their data analysis skills with R, the R Bioinformatics Cookbook by Dan MacLean offers an authoritative, practical guide. True to its name, the cookbook format provides proven recipes to solve common challenges faced in biological research. Rather than just theory, professionals get hands-on solutions readily applicable to real-world work.The book strikes an effective balance between breadth and depth across two dimensions. First, it spans a diverse range of topics - from R environment setup to advanced machine learning. Second, it delves deeply into specialized R packages tailored for bioinformatics within the expansive Bioconductor ecosystem. Readers tour the diverse landscape of tools designed specifically for genomics and computational biology.Notably, the book moves beyond just core techniques to incorporate cutting-edge methods poised to shape the future. The coverage of sophisticated machine learning using mlr3 and interactive dashboards with Shiny/Quarto keeps readers ahead of the curve. While leveraging time-tested tools like ggplot2 for publication-quality graphics, the book also showcases next-gen avenues for analysis and communication.The content is firmly rooted in the practical needs of bioinformaticians. Crucial workflows like sequencing data analysis, statistical modeling, and phylogenetics all receive thorough treatment. Each chapter focuses on a single technique, ensuring digestible depth. And code is structured to promote understanding and extensibility rather than just solutions.For readers with some existing R familiarity, the book serves as an invaluable springboard to enhanced productivity. It provides building blocks to level up both fundamental and advanced skills. However, complete beginners may need supplementary learning first to establish core competencies before benefiting fully. The assumed knowledge makes this more suited for intermediate learners onward.To make this comprehensive guide even more holistic, additional topics on large-scale cloud computing, deep learning for omics data, and single-cell analysis could prove valuable amendments. As data complexity escalates, guidance on these emerging fronts would increase the book's utility for tackling real-world biological complexities.The practitioners seeking to expand their R toolkit in order to derive greater insights from modern molecular datasets, the R Bioinformatics Cookbook hits the sweet spot between theory and practice. Its competent stewardship of both foundational and innovative R-based techniques makes it a recipe for success in bioinformatics.
Amazon Verified review Amazon
Om S Nov 09, 2023
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
In the second edition of the "R Bioinformatics Cookbook," readers are taken on a hands-on journey through over 80 recipes, providing a practical guide to conducting research and analysis in computational biology using the R ecosystem. The book emphasizes real-world applications, offering a treasure trove of modern R packages for processing biological data with tangible examples. From setting up a functional R working environment to analyzing RNA-seq, ChIP-seq, genomics, and more, each chapter introduces essential tools and techniques for bioinformatics enthusiasts.The book's strength lies in its recipe-based approach, allowing bioinformaticians, data analysts, researchers, and R developers to tackle intermediate-to-advanced biological problems effectively. Notably, the inclusion of Bioconductor, ggplot2, and Quarto tools enhances the reader's ability to represent biological data through advanced visualizations suitable for research and publication. The concluding chapters delve into machine learning with mlr3 and harnessing the power of ChatGPT for code generation and workflow understanding. With a clear structure and a focus on practical applications, this cookbook equips readers to become proficient bioinformatics specialists, navigating the complexities of large and intricate biological datasets.
Amazon Verified review Amazon
Get free access to Packt library with over 7500+ books and video courses for 7 days!
Start Free Trial

FAQs

What is included in a Packt subscription? Chevron down icon Chevron up icon

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription? Chevron down icon Chevron up icon

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits? Chevron down icon Chevron up icon

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled? Chevron down icon Chevron up icon

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title? Chevron down icon Chevron up icon

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team. 

Can I download the code files for Early Access titles? Chevron down icon Chevron up icon

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date? Chevron down icon Chevron up icon

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready? Chevron down icon Chevron up icon

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access? Chevron down icon Chevron up icon

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered? Chevron down icon Chevron up icon

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content? Chevron down icon Chevron up icon

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access? Chevron down icon Chevron up icon

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.