Forward-Time Population Genetics Simulations

The rapid increase of the power of personal computers has led to the use of serious simulation programs such as easy POP in genetic studies. This book summarizes recent advances in forward-time simulation methods and demonstrates their applications in population genetics and genetic epidemiology. The authors introduce commonly used forward-time population genetics simulation methods, including some new methods, and introduce a forward-time population genetics simulation environment, simuPOP, as a powerful and flexible tool to implement these simulations. Researchers and students in population and statistical genetics will find this book useful.

Bo Peng, PhD, is an assistant professor in the Department of Genetics at The University of Texas MD Anderson Cancer Center. With his degrees in applied mathematics and biostatistics, he is applying advanced computational techniques such as parallel computation and larger-scale simulations to research topics in population genetics, genetic epidemiology, and bioinformatics. Marek Kimmel, PhD, is Director of the Doctoral Program in Bioinformatics and Statistical Genetics and head of the Bioinformatics Group at Rice University. He holds joint appointments as Professor of Statistics at Rice University Professor of Biostatistics and Applied Mathematics at MD Anderson Cancer Center, and Professor of Biometry, at The University of Texas School of Public Health. Christopher I. Amos, PhD, is a professor, in the Department of Genetics at The University of Texas MD Anderson Cancer Center. He also holds adjunct appointments at Rice University and in the Department of Epidemiology at The University of Texas School of Public Health.

Preface	p. xiii
Acknowledgments	p. xvii
List of Examples	p. xix
Basic Concepts and Models	p. 1
Biological and Genetic Concepts	p. 2
Genome and Chromosomes	p. 2
Genes, Markers, Loci, and Alleles	p. 3
Recombination and Linkage	p. 4
Sex Chromosomes	p. 5
Mutation and Mutation Models	p. 5
Population and Evolutionary Genetics	p. 7
Population Variation and Mutation	p. 8
The Wright-Fisher Model and Random Mating	p. 8
The Hardy-Weinberg Equilibrium	p. 9
Genetic Drift and Effective Population Size	p. 10
Natural Selection	p. 10
Linkage Equilibrium	p. 13
Population Structure and Migration	p. 15
Demographic History of Human Populations	p. 16
Coalescent and Backward-Time Simulations	p. 17
Forward-Time Simulations	p. 20
Statistical Genetics and Genetic Epidemiology	p. 21
Penetrance Models	p. 21
Simple and Complex Genetic Diseases	p. 24
Phenotypic, Allelic, and Locus Heterogeneity	p. 24
Study Designs of Gene Mapping	p. 25
References	p. 27
Simulation of Population Genetics Models	p. 31
Random Genetic Drift	p. 31
Dynamics of Allele Frequency and Heterozygosity	p. 32
Persistence Time	p. 34
Demographic Models	p. 35
The Bottleneck Effect	p. 36
Mutation	p. 38
A Diallelic Mutation Model	p. 38
Multiallelic Mutation Models	p. 40
Migration	p. 42
An Island Model of Migration	p. 42
Recombination and Linkage Disequilibrium	p. 44
Natural Selection	p. 45
Single-Locus Diallelic Selection Models	p. 45
Multilocus Selection Models	p. 48
Genealogy of Forward-Time Simulations	p. 49
Genealogy of Haploid Simulations	p. 49
Genealogy of Diploid Simulations	p. 52
References	p. 53
Ascertainment Bias in Population Genetics	p. 55
Introduction	p. 55
Methods	p. 58
Evolution of a DNA Repeat Locus	p. 58
Conditional Distributions and Ascertainment Bias of Allele Sizes	p. 60
Simulation Method	p. 62
Results	p. 64
Summary of Modeling Results	p. 64
Comparisons of Empirical Statistics Derived from Human and Chimpanzee Microsatellite Data	p. 68
Discussion and Conclusions	p. 69
References	p. 71
Observing Properties of Evolving Populations	p. 73
Introduction	p. 74
Allelic Spectra of Complex Human Diseases	p. 74
An Evolutionary Model of Effective Number of Disease Alleles	p. 75
Simulation of the Evolution of n_e I	p. 76
Simulation of the Evolution of Allele Spectra	p. 77
Demographic Models	p. 77
Output Statistics	p. 80
Mutation Models	p. 84
Multilocus Selection Models	p. 84
Evolve!	p. 87
Validation of Theoretical Results	p. 89
Extensions to the Basic Model	p. 90
Impact of Demographic Models	p. 90
Impact of the Mutation Model	p. 92
Impact of Subpopulation Structure	p. 93
Impact of Migration	p. 94
Distribution of Equilibrium Disease Allele Frequency	p. 96
Varying Selection and Mutation Coefficients	p. 97
Evolution of Disease Predisposing Loci Under Weak Selection	p. 98
Discussion	p. 100
References	p. 102
Simulating Populations with Complex Human Diseases	p. 105
Introduction	p. 106
Controlling Disease Allele Frequencies at the Present Generation	p. 108
Introduction of Disease Alleles	p. 108
Trajectory of Disease Allele Frequency	p. 110
Forward-and Backward-Time Simulations	p. 111
Random Mating with Controlled Disease Allele Frequency	p. 117
Forward-Time Simulation of Realistic Samples	p. 120
Method	p. 121
Drawing Population and Family-Based Samples	p. 126
Example 1: Typical Simulations With or Without Scaling	p. 132
Example 2: A Genetic Disease with Two DPL	p. 134
Example 3: Simulations of Slow and Rapid Selective Sweep	p. 136
Discussion	p. 141
References	p. 143
Nonrandom Mating and its Applications	p. 147
Assortative Mating	p. 148
Genetic Architecture of Traits	p. 149
Mating Model	p. 151
Simulation of Assortative Mating	p. 156
More Complex Nonrandom Mating Schemes	p. 158
Customized Parent Choosing Scheme	p. 158
Example of a Nonrandom Mating in a Continuous Habitat	p. 161
Heterogeneous Mating Schemes	p. 164
Simulation of Population Admixture	p. 167
Simulation of Age-Structured Populations	p. 170
Simulation of Age-Structured Populations	p. 172
A Hypothetical Disease Model	p. 174
Evolution of an Age-Structured Population with Lung Cancer	p. 179
References	p. 182
Appendix: Forward-Time Simulations Using Simupop	p. 185
Introduction	p. 185
What is simuPOP?	p. 185
An Overview of simuPOP Concepts	p. 186
Population	p. 189
Creating a Population	p. 189
Genotype Structure of a Population	p. 192
Subpopulations and Virtual Subpopulations	p. 194
Accessing Individuals in a Population	p. 196
Population Variables	p. 198
Altering the Structure, Genotype, or Information Fields of a Population	p. 199
Multigeneration Populations and Parental Information	p. 202
Saving and Loading a Population	p. 204
Operators	p. 204
Applicable Generations	p. 205
Operator Output	p. 206
During-Mating Operators	p. 208
Function Form of Operators	p. 209
Operator Stat	p. 210
Hybrid and Python Operators	p. 212
Evolving One or More Populations	p. 215
Mating Scheme	p. 215
Conditionally Terminating an Evolutionary Process	p. 217
Evolving Several Populations Simultaneously	p. 218
A Complete simuPOP Script	p. 219
Reference	p. 226
Index	p. 227
Table of Contents provided by Ingram. All Rights Reserved.

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Forward-Time Population Genetics Simulations Methods, Implementation, and Applications

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