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Analysis of Complex Disease Association Studies - A Practical Guide
Eleftheria Zeggini, Andrew Morris
Verlag Elsevier Reference Monographs, 2010
ISBN 9780123751430 , 353 Seiten
Format PDF, ePUB, OL
Kopierschutz DRM
Geräte
Front Cover
1
Analysis of Complex Disease Association Studies
4
Copyright
5
Table of Contents
6
List of Contributors
8
Chapter 1 Genetic Architecture ofComplex Diseases
10
Introduction
10
Genetic Modeling: Twin, Adoption andFamily Studies
11
Disease Gene Mapping: Linkage Studies
14
Disease Gene Mapping: Association Studies
16
Conclusion
19
References
20
Chapter 2 Population Genetics and Linkage Disequilibrium
24
The Origin and Structure of Variation inThe Human Genome
24
Pair-Wise Measurement of LD
26
Predicted and Observed Patterns ofRecombination
28
The International HapMap Project
30
Conclusion
31
References
32
Chapter 3 Genetic Association Study Design
34
Concepts and Scope of Association Studies
35
Population-Based Study Designs
39
Conclusions
52
References
53
Chapter 4 Tag SNP Selection
58
Introduction
58
Approaches
60
Tools
69
Genotyping Platforms
72
References
74
Chapter 5 Genotype Calling
78
Bias and Error in Genotype Calling
78
Genotyping Platforms
79
Normalization Algorithms
80
Genotype Calling From a Single Array
83
Genotype Calling of Multiple Arrays Simultaneously
86
Other Genotype Calling Algorithms
91
References
94
Chapter 6 Data Handling
96
References
103
Chapter 7 Data Quality Control
104
Introduction
105
Sample-based QC
107
Marker-based QC
113
Family-based Studies
115
Post-analysis QC
115
Summary
116
References
116
Chapter 8 Single-locus Tests of Association for Population-based Studies
118
Introduction
119
Genetic Models
121
Covariates
122
Genome - wide Associations Studies and General Interpretation
126
Quantitative Traits
128
Conclusion
130
References
130
Chapter 9 Effects of Population Structure in Genome-wide Association Studies
132
Introduction
133
Genetic Structure of Populations
134
Effects of Population Structure on Standard Tests for Association
143
Analysis of Structured Populations
154
LINKS
163
References
164
Chapter 10 Genotype Imputation
166
Uses of Imputation
168
Genotype Imputation Methods
170
SNP Tagging-Based Approaches
171
Hidden Markov Model-Based Approaches
171
Perspectives and Future Directions
180
References
181
Chapter 11 Haplotype Methods for Population-based Association Studies
186
Haplotype Reconstruction in Population-Based Association Studies
188
Population-Based Haplotype Association Analysis
197
Summary
201
References
202
Chapter 12 Gene-Gene Interaction and Epistasis
206
Introduction
207
What is ``Epistasis''?
207
``Biological'' Epistasis
208
Statistical Epistasis
208
Two-Locus Quantitative Trait Models Incorporating Epistatic Interactions
210
Test for Association Incorporating Interactions
212
Two-Locus Binary Models Incorporating Interaction
215
Why Model Epistasis?
215
Strategies for Detecting Epistasis in Genome-WideAssociation Studies
216
Two-Stage Strategies to Detect Epistasis
218
Other Simple Tests for Gene-Gene Interaction
218
Higher-Order Interactions
219
More Sophisticated Approaches to Modeling and Detecting Interactions
220
Conclusions
220
Reference
220
Chapter 13 Copy Number Variant Association Studies
224
Introduction
224
The Value of CNV Association Studies
226
Differences Between SNP and CNV Association Studies
227
Normalization of CNV Intensity Data
229
Normalization of SNP Genotyping Data forCNV Studies
230
Effect of SNPS on CNV Probes
231
Association Tests and Software for CNV Data
232
Differential Bias and The Advantage ofUsing Trio Data
233
Summarizing Signal Across Multiple Probes
234
References
238
Chapter 14 Family-based Association Methods
240
FBATs
241
Genetic Data
246
Phenotypes
249
Multivariate Phenotypes and Genotypes
252
Testing Strategies for Large-Scale Association Studies
252
Gene-Environment Interaction
255
Software
255
Discussion
255
References
257
Chapter 15 Bioinformatics Approaches
260
Prioritizing Association Signals forFollow-Up
260
Using Linkage Disequilibrium (LD) to Define Regions SurroundingSignals
261
Sources of Bioinformation
262
Tools for Annotating Bioinformation
262
References
268
Chapter 16 Interpreting Association Signals
270
Introduction
271
The Importance and Definition ofReplication
271
Power of Replication Studies
274
Guidelines for Reporting Association Results
279
Follow-Up of Associations
280
Conclusions
283
References
284
Chapter 17 Delineating Signals from Association Studies
286
Introduction
287
Locus Fine-Mapping: Design and a Case Study
291
Delineating Association Signals in the Future
295
Concluding Remarks
299
World Wide Web Url Links
299
References
299
Chapter 18 A Genome-wide Association Case Study on Obesity
304
References
312
Chapter 19 Case Study on Rheumatoid Arthritis
316
Candidate Gene on Studies
317
Genome-Wide Association Studies
319
Future Studies
327
Overall Conclusion
328
References
328
Index
334
Color Plates
344
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