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MORE ABOUT THIS BOOK
Main description:
This volume presents a valuable and readily reproducible collection of established and emerging techniques on modern genetic analyses. Chapters focus on statistical or data mining analyses, genetic architecture, the burden of multiple testing, genetic variance, measuring epistasis, multifactor dimensionality reduction, and ReliefF. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols, and key tips on troubleshooting and avoiding known pitfalls.
Authoritative and practical, Epistasis: Methods and Protocols aids scientists in continuing to study elucidate epistasis in the context of modern data availability.
Contents:
1. Long Term Selection Experiments: Epistasis and The Response To Selection
Charles Goodnight
2. Finding the Epistasis Needles in the Genome-Wide Haystack
Marylyn D. Ritchie
3. Biological Knowledge-Driven Analysis of Epistasis in Human GWAS with Application to Lipid Traits
Li Ma, Alon Keinan, and Andrew G. Clark
4. Epistasis for Quantitative Traits in Drosophila
Trudy F. C. Mackay
5. Epistasis In The Risk Of Human Neuropsychiatric Disease
Scott M Williams
6. On the Partitioning of Genetic Variance with Epistasis
Jose M Alvarez-Castro and Arnaud Le Rouzic
7. Measuring Gene Interactions
Thomas F. Hansen
8. Two Rules for the Detection and Quantification of Epistasis and other Interaction Effects
Gunter P. Wagner
9. Direct Approach to Modeling Epistasis
Rong-Cai Yang
10. Capacitating Epistasis - Detection and Role in the Genetic Architecture of Complex Traits
Mats E. Pettersson and OErjan Carlborg
11. Compositional Epistasis: An Epidemiologic Perspective
Etsuji Suzuki and Tyler J. VanderWeele
12. Identification Of Genome-Wide SNP-SNP and SNP-Clinical Boolean Interactions In Age-Related Macular Degeneration
Carlos Riveros, Renato Vimieiro, Elizabeth G. Holliday, Christopher Oldmeadow, Jie Jin Wang, Paul Mitchell, John Attia, Rodney J. Scott, and Pablo A. Moscato
13. Epistasis Analysis Using Information Theory
Jason H. Moore and Ting Hu
14. Genome-Wide Epistasis and Pleiotropy Characterized by the Bipartite Human Phenotype Network
Christian Darabos and Jason H. Moore
15. Network Theory for Data-Driven Epistasis Networks
Caleb A. Lareau and B. A. McKinney
16. Epistasis Analysis Using Multifactor Dimensionality Reduction
Jason H. Moore and Peter C. Andrews
17. Epistasis Analysis Using ReliefF
Jason H. Moore
18. Epistasis Analysis Using Artificial Intelligence
Jason H. Moore and Doug P. Hill
PRODUCT DETAILS
Publisher: Springer (Humana Press Inc.)
Publication date: November, 2014
Pages: 340
Weight: 9006g
Availability: Available
Subcategories: Genetics
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