- Includes cutting-edge methods and protocols
- Provides step-by-step detail essential for reproducible results
- Contains key notes and implementation advice from the experts
Buy this book
- About this book
-
This volume explores methods and protocols for detecting epistasis from genetic data. Chapters provide methods and protocols demonstrating approaches to identify epistasis, genetic epistasis testing, genome-wide epistatic SNP networks, epistasis detection through machine learning, and complex interaction analysis using trigenic synthetic genetic array (τ-SGA). Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls.
Authoritative and cutting-edge, Epistasis: Methods and Protocols aims to ensure successful results in the further study of this vital field.
- Table of contents (23 chapters)
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Mass-Based Protein Phylogenetic Approach to Identify Epistasis
Pages 1-15
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SNPInt-GPU: Tool for Epistasis Testing with Multiple Methods and GPU Acceleration
Pages 17-35
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Epistasis-Based Feature Selection Algorithm
Pages 37-44
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W-Test for Genetic Epistasis Testing
Pages 45-53
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The Combined Analysis of Pleiotropy and Epistasis (CAPE)
Pages 55-67
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Table of contents (23 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Epistasis
- Book Subtitle
- Methods and Protocols
- Editors
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- Ka-Chun Wong
- Series Title
- Methods in Molecular Biology
- Series Volume
- 2212
- Copyright
- 2021
- Publisher
- Springer US
- Copyright Holder
- Springer Science+Business Media, LLC, part of Springer Nature
- eBook ISBN
- 978-1-0716-0947-7
- DOI
- 10.1007/978-1-0716-0947-7
- Hardcover ISBN
- 978-1-0716-0946-0
- Series ISSN
- 1064-3745
- Edition Number
- 1
- Number of Pages
- X, 402
- Number of Illustrations
- 82 b/w illustrations, 85 illustrations in colour
- Topics