Bioconductor
Bioconductor
An Introduction to Core Technologies
About the Book
The Bioconductor project is a widely used open source and open development platform for software for computational biology. It is a leading platform for doing data science in Genomics. This book covers the core functionality needed to deploy Bioconductor on modern datasets, and will lay the foundation for you to learn and explore parts of the project devoted to specific application domains.
You will learn about the core data classes in Bioconductor, tools for manipulating genomic intervals and genome sequences, tools for getting your data into Bioconductor and for accessing online annotation data. Finally, the book concludes with a number of short introductions to standard analysis packages.
License
About the Author
Packages
The Book
PDF
EPUB
MOBI
WEB
English
The Book + Lecture Videos
This package includes the book as well as high-definition lecture videos (6 hours in total). The videos are licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 license.
Includes:
Instructional videos
Instructional videos associated with the book, for a total of more than 35 videos with a total length of 6 hours. The file format is mp4 and the total size is almost 8 GB. These videos have no subtitles. The audio is in english; note that the author does not have english as a first language.
PDF
EPUB
MOBI
WEB
English
Table of Contents
- Preface
-
1. What is Bioconductor
- 1.1 What is this book
-
2. Installing Bioconductor
- 2.1 Installing Bioconductor
-
3. Online Resources for Bioconductor
- 3.1 Overview
- 3.2 Bioconductor packages and documentation
- 3.3 The Bioconductor site
- 3.4 Other resources
-
4. An overview of base types in R
- 4.1 Dependencies
- 4.2 Overview
- 4.3 Atomic Vectors
- 4.4 Matrices
- 4.5 Lists
- 4.6 Data frames
- 4.7 Conversion
- 4.8 Other Resources
-
5. IRanges - Basic Usage
- 5.1 Dependencies
- 5.2 Overview
- 5.3 Basic IRanges
- 5.4 Normal IRanges
- 5.5 Disjoin
- 5.6 Manipulating IRanges, intra-range
- 5.7 Manipulating IRanges, as sets
- 5.8 Finding Overlaps
- 5.9 Counting Overlaps
- 5.10 Finding nearest IRanges
- 5.11 Other Resources
-
6. GenomicRanges - GRanges
- 6.1 Dependencies
- 6.2 GRanges
- 6.3 GRanges, seqinfo
- 6.4 Other Resources
- 6.5 References
-
7. GenomicRanges - Basic GRanges Usage
- 7.1 Dependencies
- 7.2 DataFrame
- 7.3 GRanges, metadata
- 7.4 findOverlaps
- 7.5 subsetByOverlaps
- 7.6 makeGRangesFromDataFrame
- 7.7 Biology usecase I
- 7.8 Biology usecase II
- 7.9 Other Resources
- 7.10 References
-
8. GenomicRanges - More on seqinfo
- 8.1 Dependencies
- 8.2 Overview
- 8.3 Drop and keep seqlevels
- 8.4 Changing style
- 8.5 Using information from BSgenome packages
- 8.6 Other Resources
-
9. AnnotationHub
- 9.1 Dependencies
- 9.2 Overview
- 9.3 Usage
- 9.4 Other Resources
- 9.5 References
-
10. Usecase - Basic GRanges and AnnotationHub
- 10.1 Dependencies
- 10.2 Overview
- 10.3 Accomplishing our goals
-
11. Biostrings
- 11.1 Dependencies
- 11.2 Overview
- 11.3 Representing sequences
- 11.4 Basic functionality
- 11.5 Biological functionality
- 11.6 Counting letters
- 11.7 References
-
12. BSgenome
- 12.1 Dependencies
- 12.2 Overview
- 12.3 Genomes
-
13. Biostrings - Matching
- 13.1 Dependencies
- 13.2 Overview
- 13.3 Pattern matching
- 13.4 Specialized alignments
- 13.5 References
-
14. BSgenome - Views
- 14.1 Dependencies
- 14.2 Overview
- 14.3 Views
-
15. GenomicRanges - Rle
- 15.1 Dependencies
- 15.2 Overview
- 15.3 Coverage
- 15.4 Rle
- 15.5 Useful functions for Rle
- 15.6 Views and Rles
- 15.7 RleList
- 15.8 Rles and GRanges
- 15.9 Biology Usecase
-
16. GenomicRanges - Lists
- 16.1 Dependencies
- 16.2 Overview
- 16.3 Why
- 16.4 GrangesList
- 16.5 Other Lists
-
17. GenomicFeatures
- 17.1 Dependencies
- 17.2 Overview
- 17.3 Examples
- 17.4 Caution: Terminology
- 17.5 Gene, exons and transcripts
- 17.6 Other Resources
-
18. Using the rtracklayer package for data import
- 18.1 Dependencies
- 18.2 Overview
- 18.3 The import function
- 18.4 BED files
- 18.5 BigWig files
- 18.6 Other file formats
- 18.7 Extensive example
- 18.8 LiftOver
- 18.9 Importing directly from UCSC
- 18.10 Tabix indexing
- 18.11 Other Resources
-
19. ExpressionSet
- 19.1 Dependencies
- 19.2 Overview
- 19.3 Data Containers
- 19.4 The structure of an ExpressionSet
- 19.5 Example
- 19.6 Subsetting
- 19.7 featureData and annotation
- 19.8 Note: phenoData and pData
- 19.9 The eSet class
- 19.10 Other Resources
-
20. SummarizedExperiment
- 20.1 Dependencies
- 20.2 Overview
- 20.3 Details
-
21. GEOquery
- 21.1 Dependencies
- 21.2 Overview
- 21.3 NCBI GEO
- 21.4 GEOquery
- 21.5 Other packages
- 21.6 Other Resources
-
22. biomaRt
- 22.1 Dependencies
- 22.2 Overview
- 22.3 Specifiying a mart and a dataset
- 22.4 Building a query
- 22.5 Other Resources
-
23. R - S4 Classes and Methods
- 23.1 Dependencies
- 23.2 Overview
- 23.3 S3 and S4 classes
- 23.4 Constructors and getting help
- 23.5 Slots and accessor functions
- 23.6 Class inheritance
- 23.7 Outdated S4 classes
- 23.8 S4 Methods
-
24. Getting Data into Bioconductor
- 24.1 Dependencies
- 24.2 Overview
- 24.3 Application Area
- 24.4 File types
- 24.5 Get data from databases of publicly available data
-
25. ShortRead
- 25.1 Dependencies
- 25.2 Overview
- 25.3 ShortRead
- 25.4 Reading FASTQ files
- 25.5 A word on quality scores
- 25.6 Reading alignment files
- 25.7 Other Resources
-
26. Rsamtools
- 26.1 Dependencies
- 26.2 Overview
- 26.3 Rsamtools
- 26.4 The BAM / SAM file format
- 26.5 scanBam
- 26.6 Reading in parts of the file
- 26.7 BAM summary
- 26.8 Other functionality from Rsamtools
- 26.9 Other Resources
-
27. The oligo package
- 27.1 Dependencies
- 27.2 Overview
- 27.3 Getting the data
- 27.4 Normalization
- 27.5 Other Resources
-
28. limma
- 28.1 Dependencies
- 28.2 Overview
- 28.3 Analysis Setup and Design
- 28.4 A two group comparison
- 28.5 More on the design
- 28.6 Background: Data representation in limma
- 28.7 Background: The targets file
- 28.8 Other Resources
-
29. Analysis of 450k DNA methylation data with minfi
- 29.1 Dependencies
- 29.2 Overview
- 29.3 DNA methylation
- 29.4 Array Design
- 29.5 Data
- 29.6 Preprocessing
- 29.7 Differential Methylation
- 29.8 Other Resources
-
30. Count Based RNA-seq analysis
- 30.1 Dependencies
- 30.2 Overview
- 30.3 RNA-seq count data
- 30.4 Statistical issues
- 30.5 The Data
- 30.6 edgeR
- 30.7 DESeq2
- 30.8 Comments
- 30.9 Other Resources
- Details on R and Bioconductor
- About the Author
The Leanpub 60-day 100% Happiness Guarantee
Within 60 days of purchase you can get a 100% refund on any Leanpub purchase, in two clicks.
See full terms
Do Well. Do Good.
Authors have earned$11,714,583writing, publishing and selling on Leanpub, earning 80% royalties while saving up to 25 million pounds of CO2 and up to 46,000 trees.
Learn more about writing on Leanpub
Free Updates. DRM Free.
If you buy a Leanpub book, you get free updates for as long as the author updates the book! Many authors use Leanpub to publish their books in-progress, while they are writing them. All readers get free updates, regardless of when they bought the book or how much they paid (including free).
Most Leanpub books are available in PDF (for computers), EPUB (for phones and tablets) and MOBI (for Kindle). The formats that a book includes are shown at the top right corner of this page.
Finally, Leanpub books don't have any DRM copy-protection nonsense, so you can easily read them on any supported device.
Learn more about Leanpub's ebook formats and where to read them
Top Books
- #1
Recipes for Decoupling
Matthias NobackWrite software that survives
- #2
OpenIntro Statistics
David Diez, Christopher Barr, Mine Cetinkaya-Rundel, and OpenIntroA complete foundation for Statistics, also serving as a foundation for Data Science.
Leanpub revenue supports OpenIntro (US-based nonprofit) so we can provide free desk copies to teachers interested in using OpenIntro Statistics in the classroom and expand the project to support free textbooks in other subjects.
More resources: openintro.org.
- #3
C++20 - The Complete Guide
Nicolai M. JosuttisAll new language and library features of C++20 (for those who know previous C++ versions).
The book presents all new language and library features of C++20. Learn how this impacts day-to-day programming, to benefit in practice, to combine new features, and to avoid all new traps.
Buy early, pay less, free updates.
Other books:
- #4
CQRS by Example
Carlos Buenosvinos, Christian Soronellas, and Keyvan Akbary- Leverage your Software Architecture skills by learning everything about CQRS in detail with lots of examples
- Develop faster applications by applying CQRS and fostering Read Models and Projections
- Learn how to apply CQRS into a brownfield project from a pragmatic approach
- #5
Ansible for DevOps
Jeff GeerlingAnsible is a simple, but powerful, server and configuration management tool. Learn to use Ansible effectively, whether you manage one server—or thousands.
- #6
Maîtriser Apache JMeter
Philippe Mouawad, Bruno Demion (Milamber), and Antonio Gomes RodriguesToute la puissance d'Apache JMeter expliquée par ses commiteurs et utilisateurs experts. De l'intégration continue en passant par le Cloud, vous découvrirez comment intégrer JMeter à vos processus "Agile" et Devops.
If you're looking for the newer english version of this book, go to Master JMeter : From load testing to DevOps
- #7
Jetpack Compose internals
Jorge CastilloJetpack Compose is the future of Android UI. Master how it works internally and become a more efficient developer with it. You'll also find it valuable if you are not an Android dev. This book provides all the details to understand how the Compose compiler & runtime work, and how to create a client library using them.
- #8
The PowerShell Scripting and Toolmaking Book
Don Jones and Jeff HicksLearn the patterns, practices, and details of PowerShell Scripting and Toolmaking from the industry's two most recognized experts on the subject.
- #9
Mastering STM32 - Second Edition
Carmine NovielloWith more than 1200 microcontrollers, STM32 is probably the most complete ARM Cortex-M platform on the market. This book aims to be the most complete guide around introducing the reader to this exciting MCU portfolio from ST Microelectronics and its official CubeHAL and STM32CubeIDE development environment.
- #10
Introduction to Data Science
Rafael A IrizarryThe demand for skilled data science practitioners in industry, academia, and government is rapidly growing. This book introduces concepts from probability, statistical inference, linear regression and machine learning and R programming skills. Throughout the book we demonstrate how these can help you tackle real-world data analysis challenges.
Top Bundles
- #1
Software Architecture
2 Books
"Software Architecture for Developers" is a practical and pragmatic guide to modern, lightweight software architecture, specifically aimed at developers. You'll learn:The essence of software architecture.Why the software architecture role should include coding, coaching and collaboration.The things that you really need to think about before... - #2
CCIE Service Provider Ultimate Study Bundle
2 Books
Piotr Jablonski, Lukasz Bromirski, and Nick Russo have joined forces to deliver the only CCIE Service Provider training resource you'll ever need. This bundle contains a detailed and challenging collection of workbook labs, plus an extensively detailed technical reference guide. All of us have earned the CCIE Service Provider certification... - #4
Pattern-Oriented Memory Forensics and Malware Detection
2 Books
This training bundle for security engineers and researchers, malware and memory forensics analysts includes two accelerated training courses for Windows memory dump analysis using WinDbg. It is also useful for technical support and escalation engineers who analyze memory dumps from complex software environments and need to check for possible... - #6
All the Books of The Medical Futurist
6 Books
We put together the most popular books from The Medical Futurist to provide a clear picture about the major trends shaping the future of medicine and healthcare. Digital health technologies, artificial intelligence, the future of 20 medical specialties, big pharma, data privacy, digital health investments and how technology giants such as Amazon...
