Holdings: Handbook of statistical genetics

Handbook of statistical genetics: 2

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Bibliographic Details
Format:	Book
Language:	English
Published:	Chichester, West Sussex, England John Wiley & Sons 2007
Edition:	3. ed.
Subjects:	Genetik Statistik Methode
Online Access:	Inhaltsverzeichnis
Physical Description:	LII S., S. 755-1392, LXXXIV S.
ISBN:	0470058307 9780470058305

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adam_text	VOLUME 2 List of Contributors xxix Editor s Preface to the Third Edition xxxv Glossary of Terms xxxvii Abbreviations and Acronyms xlix Part 5 POPULATION GENETICS 753 22 Mathematical Models in Population Genetics 755 C. Neuhauser 22.1 A Brief History of The Role of Selection 755 xvjü _________________________________________ CONTENTS 22.2 Mutation, Random Genetic Drift, and Selection 756 22.2.1 Mutation 757 22.2.2 Random Genetic Drift 757 22.2.3 Selection 759 22.2.4 The Wright-Fisher Model 759 22.3 The Diffusion Approximation 760 22.3.1 Fixation 763 22.3.2 The Kolmogorov Forward Equation 764 22.3.3 Random Genetic Drift Versus Mutation and Selection 764 22.4 The Infinite Alíele Model 765 22.4.1 The Infinite Alíele Model with Mutation 766 22.4.2 Ewens s Sampling Formula 767 22.4.3 The Infinite Alíele Model with Selection and Mutation 767 22.5 Other Models of Mutation and Selection 768 22.5.1 The Infinitely Many Sites Model 768 22.5.2 Frequency-dependent Selection 768 22.5.3 Overlapping Generations 769 22.6 Coalescent Theory 769 22.6.1 The Neutral Coalescent 769 22.6.2 The Ancestral Selection Graph 771 22.6.3 Varying Population Size 774 22.7 Detecting Selection 775 Acknowledgments 777 References 777 23 Inference, Simulation and Enumeration of Genealogies 781 С Cannings and A. Thomas 23.1 Genealogies as Graphs 781 23.2 Relationships 782 23.2.1 The Algebra of Pairwise Relationships 782 23.2.2 Measures of Genetic Relationship 785 23.2.3 Identity States for Two Individuals 786 23.2.4 More Than Two Individuals 787 23.2.5 Example: Two Siblings Given Parental States 789 23.3 The Identity Process Along a Chromosome 790 23.3.1 Theory of Junctions 790 23.3.2 Random Walks 791 23.3.3 Other Methods 791 23.4 State Space Enumeration 792 23.4.1 Applying the Peeling Method 792 23.4.2 Recursions 793 23.4.3 More Complex Linear Systems 795 23.4.4 A Non-linear System 796 23.5 Marriage Node Graphs 796 23.5.1 Drawing Marriage Node Graphs 796 23.5.2 Zero-loop Pedigrees 798 CONTENTS xix 23.6 Moral Graphs 801 23.6.1 Significance for Computation 801 23.6.2 Derivation from Marriage Node Graphs 802 23.6.3 Four Colourability and Triangulation 804 References 805 24 Graphical Models in Genetics 808 S.L. Lauritzen and N.S. Sheehan 24.1 Introduction 808 24.2 Bayesian Networks and Other Graphical Models 809 24.2.1 Graph Terminology 809 24.2.2 Conditional Independence 809 24.2.3 Elements of Bayesian Networks 810 24.2.4 Object-oriented Specification of Bayesian Networks 810 24.3 Representation of Pedigree Information 811 24.3.1 Graphs for Pedigrees 811 24.3.2 Pedigrees and Bayesian Networks 812 24.4 Peeling and Related Algorithms 816 24.4.1 Compilation 817 24.4.2 Propagation 821 24.4.3 Random and Other Propagation Schemes 823 24.4.4 Computational Shortcuts 824 24.5 Pedigree Analysis and Beyond 824 24.5.1 Single-point Linkage Analysis 824 24.5.2 QTL Mapping 825 24.5.3 Pedigree Uncertainty 827 24.5.4 Forensic Applications 829 24.5.5 Bayesian Approaches 832 24.6 Causal Inference 832 24.6.1 Causal Concepts 833 24.6.2 Mendelian Randomisation 833 24.7 Other Applications 836 24.7.1 Graph Learning for Genome-wide Associations 836 24.7.2 Gene Networks 838 References 838 25 Coalescent Theory 843 M. Nordborg 25.1 Introduction 843 25.2 The coalescent 844 25.2.1 The Fundamental Insights 844 25.2.2 The Coalescent Approximation 847 25.3 Generalizing the Coalescent 850 25.3.1 Robustness and Scaling 850 25.3.2 Variable Population Size 851 25.3.3 Population Structure on Different Time Scales 853 XX CONTENTS 25.4 Geographical Structure 854 25.4.1 The Structured Coalescent 855 25.4.2 The Strong-migration Limit 856 25.5 Segregation 857 25.5.1 Hermaphrodites 857 25.5.2 Males and Females 859 25.6 Recombination 859 25.6.1 The Ancestral Recombination Graph 860 25.6.2 Properties and Effects of Recombination 863 25.7 Selection 865 25.7.1 Balancing Selection 865 25.7.2 Selective Sweeps 868 25.7.3 Background Selection 868 25.8 Neutral Mutations 869 25.9 Conclusion 870 25.9.1 The Coalescent and Classical Population Genetics 870 25.9.2 The Coalescent and Phylogenetics 870 25.9.3 Prospects 872 Acknowledgments 872 References 872 26 Inference Under the Coalescent 878 M. Stephens 26.1 Introduction 878 26.1.1 Likelihood-based Inference 879 26.2 The Likelihood and the Coalescent 883 26.3 Importance Sampling 885 26.3.1 Likelihood Surfaces 887 26.3.2 Ancestral Inference 888 26.3.3 Application and Assessing Reliability 888 26.4 Markov Chain Monte Carlo 889 26.4.1 Introduction 889 26.4.2 Choosing a Good Proposal Distribution 891 26.4.3 Likelihood Surfaces 891 26.4.4 Ancestral Inference 893 26.4.5 Example Proposal Distributions 894 26.4.6 Application and Assessing Reliability 897 26.4.7 Extensions to More Complex Demographic and Genetic Models 899 26.5 Other Approaches 900 26.5.1 Rejection Sampling and Approximate Bayesian Computation 900 26.5.2 Composite Likelihood Methods 902 26.5.3 Product of Approximate Conditionals (PAC) Models 903 26.6 Software and Web Resources 903 26.6.1 Population Genetic Simulations 904 26.6.2 Inference Methods 904 Acknowledgments 905 References 906 CONTENTS xxi 27 Linkage Disequilibrium, Recombination and Selection 909 G. McVean 27.1 What Is Linkage Disequilibrium? 909 27.2 Measuring Linkage Disequilibrium 911 27.2.1 Single-number Summaries of LD 913 27.2.2 The Spatial Distribution of LD 914 27.2.3 Various Extensions of Two-locus LD Measures 918 27.2.4 The Relationship between r2 and Power in Association Studies 919 27.3 Modelling LD and Genealogical History 922 27.3.1 A Historical Perspective 922 27.3.2 Coalescent Modelling 924 27.3.3 Relating Genealogical History to LD 930 27.4 Inference 932 27.4.1 Formulating the Hypotheses 932 27.4.2 Parameter Estimation 933 27.4.3 Hypothesis Testing 937 27.5 Prospects 938 Acknowledgments 939 Related Chapters 940 References 940 28 Inferences from Spatial Population Genetics 945 F. Rousset 28.1 Introduction 945 28.2 Neutral Models of Geographical Variation 946 28.2.1 Assumptions and Parameters 946 28.3 Methods of Inference 948 28.3.1 F-statistics 948 28.3.2 Likelihood Computations 952 28.4 Inference Under the Different Models 955 28.4.1 Migration-Matrix Models 955 28.4.2 Island Model 955 28.4.3 Isolation by Distance 956 28.4.4 Likelihood Inferences 959 28.5 Separation of Timescales 960 28.6 Other Methods 962 28.6.1 Assignment and Clustering 962 28.6.2 Inferences from Clines 964 28.7 Integrating Statistical Techniques into the Analysis of Biological 965 Processes Acknowledgments 966 Related Chapters 966 References 967 Appendix A: Analysis of Variance and Probabilities of Identity 972 Appendix B: Likelihood Analysis of the Island Model 977 xxii CONTENTS 29 Analysis of Population Subdivision 980 L. Excoffier 29.1 Introduction 98° 29.1.1 Effects of Population Subdivision 980 29.2 The Fixation Index F 982 29.3 Wright s F Statistics in Hierarchic Subdivisions 983 29.3.1 Multiple Alíeles 985 29.3.2 Sample Estimation of F Statistics 986 29.3.3 G Statistics 987 29.4 Analysis of Genetic Subdivision Under an Analysis of Variance 988 Framework 29.4.1 The Model 989 29.4.2 Estimation Procedure 991 29.4.3 Dealing with Mutation and Migration using Identity Coefficients 996 29.5 Relationship Between Different Definitions of Fixation Indexes 997 29.6 F Statistics and Coalescence Times 999 29.7 Analysis of Molecular Data: The Amova Framework 1001 29.7.1 Haplotypic Diversity 1001 29.7.2 Genotypie Data 1004 29.7.3 Multiallelic Molecular Data 1004 29.7.4 Dominant Data 1007 29.7.5 Relation of AMOVA with other Approaches 1008 29.8 Significance Testing 1009 29.8.1 Resampling Techniques 1009 29.9 Related and Remaining Problems 1011 29.9.1 Testing Departure from Hardy-Weinberg Equilibrium 1011 29.9.2 Detecting Loci under Selection 1012 29.9.3 What is the Underlying Genetic Structure of Populations? 1012 Acknowledgments 1013 References 1013 30 Conservation Genetics 1021 M.A. Beaumont 30.1 Introduction 1021 30.2 Estimating Effective Population Size 1022 30.2.1 Estimating Ne Using Two Samples from the Same Population: 1023 The Temporal Method 30.2.2 Estimating Ne from Two Derived Populations 1025 30.2.3 Estimating JVe Using One Sample 1030 30.2.4 Inferring Past Changes in Population Size: 1033 Population Bottlenecks 30.2.5 Approximate Bayesian Computation 1040 30.3 Admixture 1041 30.4 Genotypie Modelling 1046 30.4.1 Assignment Testing 1046 30.4.2 Genetic Mixture Modelling and Clustering 1048 30.4.3 Hybridisation and the Use of Partially Linked Markers 1051 CONTENTS__________________________________________________________ xxiii 30.4.4 Inferring Current Migration Rates 1052 30.4.5 Spatial Modelling 1053 30.5 Relatedness and Pedigree Estimation 1054 Acknowledgments 1057 Related Chapters 1057 References 1058 31 Human Genetic Diversity and its History 1067 G. Barbujani and L, Chikhi 31.1 Introduction 1068 31.2 Human Genetic Diversity: Historical Inferences 1069 31.2.1 Some Data on Fossil Evidence 1069 31.2.2 Models of Modern Human Origins 1070 31.2.3 Methods for Inferring Past Demography 1071 31.2 A Reconstructing Past Human Migration and Demography 1075 31.3 Human Genetic Diversity: Geographical Structure 1081 31.3.1 Catalogues of Humankind 1081 31.3.2 Methods for Describing Population Structure 1084 31.3.3 Identifying the Main Human Groups 1087 31.3.4 Continuous versus Discontinuous Models of Human Variation 1091 31.4 Final Remarks 1092 Acknowledgments 1096 References 1096 Part 6 GENETIC EPIDEMIOLOGY 1109 32 Epidemiology and Genetic Epidemiology 1111 P.R. Burton, J.M. Bowden and M.D. Tobin 32.1 Introduction 1111 32.2 Descriptive Epidemiology 1112 32.2.1 Incidence and Prevalence 1114 32.2.2 Modelling Correlated Responses 1115 32.3 Descriptive Genetic Epidemiology 1117 32.3.1 Is There Evidence of Phenotypic Aggregation within Families? 1117 32.3.2 Is the Pattern of Correlation Consistent with a Possible 1118 Effect of Genes? 32.3.3 Segregation Analysis 1126 32.3.4 Ascertainment 1127 32.4 Studies Investigating Specific Aetiological Determinants 1130 32.5 The Future П31 Acknowledgments 1132 References 1132 33 Linkage Analysis 1141 E.A. Thompson 33.1 Introduction 1141 xxjy CONTENTS 33.2 The Early Years 1142 33.3 The Development of Human Genetic Linkage Analysis 1144 33.4 The Pedigree Years; Segregation and Linkage Analysis 1146 33.5 Likelihood and Location Score Computation 1149 33.6 Monte Carlo Multipoint Linkage Likelihoods 1151 33.7 Linkage Analysis of Complex Traits 1155 33.8 Map Estimation, Map Uncertainty, and The Meiosis Model 1158 33.9 The Future 1162 Acknowledgments 1163 References 1163 34 Non-parametric Linkage 1168 P. Holmans 34.1 Introduction 1168 34.2 Pros and Cons of Model-free Methods 1169 34.3 Model-free Methods for Dichotomous Traits 1171 34.3.1 Affected Sib-pair Methods 1171 34.3.2 Parameter Estimation and Power Calculation Using 1172 Affected Sib Pairs 34.3.3 Typing Unaffected Relatives in Sib-pair Analyses 1173 34.3.4 Application of Sib-pair Methods to Multiplex Sibships 1174 34.3.5 Methods for Analysing Larger Pedigrees 1175 34.3.6 Extensions to Multiple Marker Loci 1176 34.3.7 Multipoint Analysis with Tightly Linked Markers 1177 34.3.8 Inclusion of Covariates 1177 34.3.9 Multiple Disease Loci 1179 34.3.10 Significance Levels for Genome Scans 1180 34.3.11 Meta-analysis of Genome Scans 1180 34.4 Model-free Methods for Analysing Quantitative Traits 1181 34.5 Conclusions 1182 Related Chapters 1182 References 1183 35 Population Admixture and Stratification in Genetic 1190 Epidemiology P.M. McKeigue 35.1 Background 1191 35.2 Admixture Mapping Ц92 35.2.1 Basic Principles Ц92 35.2.2 Statistical Power and Sample Size 1194 35.2.3 Distinguishing between Genetic and Environmental 1196 Explanations for Ethnic Variation in Disease Risk 35.3 Statistical Models 1198 35.3.1 Modelling Admixture 1198 35.3.2 Modelling Stratification 1199 35.3.3 Modelling Alíele Frequencies 1201 CONTENTS__________________________________________________________________________________________xxv 35.3.4 Fitting the Statistical Model 1202 35.3.5 Model Comparison 1203 35.3.6 Assembling and Evaluating Panels of Ancestry-informative 1204 Marker Loci 35.4 Testing For Linkage With Locus Ancestry 1205 35.4.1 Modelling Population Stratification 1207 35.5 Conclusions 1212 References 1213 36 Population Association 1216 D. Clayton 36.1 Introduction 1216 36.2 Measures of Association 1217 36.3 Case-Control Studies 1219 36.4 Tests For Association 1221 36.5 Logistic Regression And Log-Linear Models 1225 36.6 Stratification And Matching 1227 36.7 Unmeasured Confounding 1230 36.8 Multiple Alíeles 1232 36.9 Multiple Loci 1234 36.10 Discussion 1236 Acknowledgments 1236 References 1236 37 Whole Genome Association 1238 A.P. Morris and L.R. Cardon 37.1 Introduction 1238 37.1.1 Linkage Disequilibrium and Tagging 1239 37.1.2 Current WGA Studies 1240 37.2 Genotype Quality Control 1242 37.3 Single-Locus Analysis 1245 37.3.1 Logistic Regression Modelling Framework 1247 37.3.2 Interpretation of Results and Correction for Multiple Testing 1249 37.4 Population Structure 1250 37.5 Multi-Locus Analysis 1251 37.5.1 Haplotype-based Analyses 1252 37.5.2 Haplotype Clustering Techniques 1253 37.6 Epistasis 1254 37.7 Replication 1256 37.8 Prospects for Whole-Genome Association Studies 1257 References 1258 38 Family-based Association 1264 F. Dudbridge 38.1 Introduction 1264 38.2 Transmission/Disequilibrium Test 1266 xxvi _________________________________________________________________________CONTENTS 38.3 Logistic Regression Models 1268 38.4 Haplotype Analysis 1271 38.5 General Pedigree Structures 1273 38.6 Quantitative Traits 1276 38.7 Association in the Presence of Linkage 1278 38.8 Conclusions 1281 References 1282 39 Cancer Genetics I286 M.D. Teare 39.1 Introduction 1286 39.2 Armitage-Doll Models of Carcinogenesis 1287 39.2.1 The Multistage Model 1287 39.2.2 The Two-stage Model 1289 Electronic Resources 1298 References 1298 40 Epigenetics 1301 K.D. Siegmund and S. Lin 40.1 A Brief Introduction 1301 40.2 Technologies for CGI Methylation Interrogation 1303 40.2.1 MethyLight 1304 40.2.2 Methylation Microarrays 1304 40.3 Modeling Human Cell Populations 1305 40.3.1 Background 1305 40.3.2 Methylation Patterns 1305 40.3.3 Modeling Human Colon Crypts 1306 40.3.4 Summary 1307 40.4 Mixture Modeling 1307 40.4.1 Cluster Analysis 1308 40.4.2 Modeling Exposures for Latent Disease Subtypes 1310 40.4.3 Differential Methylation with Single-slide Data 1311 40.5 Recapitulation of Tumor Progression Pathways 1313 40.5.1 Background 1313 40.5.2 Heritable Clustering 1313 40.5.3 Further Comments 1315 40.6 Future Challenges 1316 Acknowledgments 1316 References 1317 Part 7 SOCIAL AND ETHICAL ASPECTS 1323 41 Ethics Issues in Statistical Genetics 1325 R.E. Ashcroft 41.1 Introduction: Scope of This Chapter 1325 41.1.1 What is Ethics ? 1326 CONTENTS xxvji 41.1.2 Models for Analysing the Ethics of Population Genetic Research 1327 41.2 A Case Study in Ethical Regulation of Population Genetics Research: 1329 UK Biobank s Ethics and Governance Framework 41.2.1 The Scientific and Clinical Value of the Research 1330 41.2.2 Recruitment of Participants 1332 41.2.3 Consent 1334 41.2.4 Confidentiality and Security 1339 41.3 Stewardship 1339 41.3.1 Benefit Sharing 1340 41.3.2 Community Involvement 1341 41.4 Wider Social Issues 1341 41.4.1 Geneticisation 1341 41.4.2 Race, Ethnicity and Genetics 1342 41.5 Conclusions 1343 Acknowledgments 1343 References 1343 42 Insurance 1346 A.S. Macdonald 42.1 Principles of Insurance 1346 42.1.1 Long-term Insurance Pricing 1346 42.1.2 Life Insurance Underwriting 1348 42.1.3 Familial and Genetic Risk Factors 1349 42.1.4 Adverse Selection 1349 42.1.5 Family Medical Histories 1350 42.1.6 Legislation and Regulation 1351 42.1.7 Quantitative Questions 1352 42.2 Actuarial Modelling 1352 42.2.1 Actuarial Models for Life and Health Insurance 1352 42.2.2 Parameterising Actuarial Models 1354 42.2.3 Market Models and Missing Information 1355 42.2.4 Modelling Strategies 1357 42.2.5 Statistical Issues 1358 42.2.6 Economics Issues 1359 42.3 Examples and Conclusions 1359 42.3.1 Single-gene Disorders 1359 42.3.2 Multifactorial Disorders 1361 References 1365 43 Forensics 1368 B.S. Weir 43.1 Introduction 1368 43.2 Principles of Interpretation 1369 43.3 Profile Probabilities 1371 43.3.1 Allelic Independence 1371 43.3.2 Alíele Frequencies 1373 xxviii CONTENTS 43.3.3 Joint Profile Probabilities 1375 43.4 Parentage Issues 1377 43.5 Identification of Remains 1379 43.6 Mixtures 1379 43.7 Sampling Issues 1383 43.7.1 Alíele Probabilities 1383 43.7.2 Coancestry 1384 43.8 Other Forensic Issues 1385 43.8.1 Common Fallacies 1385 43.8.2 Relevant Population 1385 43.8.3 Database Searches 1386 43.8.4 Uniqueness of Profiles 1386 43.8.5 Assigning Individuals to Phenotypes, Populations or Families 1388 43.8.6 Hierarchy of Propositions 1389 43.9 Conclusions 1390 References 1390 Reference Author Index I Subject Index LXIII
adam_txt	VOLUME 2 List of Contributors xxix Editor's Preface to the Third Edition xxxv Glossary of Terms xxxvii Abbreviations and Acronyms xlix Part 5 POPULATION GENETICS 753 22 Mathematical Models in Population Genetics 755 C. Neuhauser 22.1 A Brief History of The Role of Selection 755 xvjü _ CONTENTS 22.2 Mutation, Random Genetic Drift, and Selection 756 22.2.1 Mutation 757 22.2.2 Random Genetic Drift 757 22.2.3 Selection 759 22.2.4 The Wright-Fisher Model 759 22.3 The Diffusion Approximation 760 22.3.1 Fixation 763 22.3.2 The Kolmogorov Forward Equation 764 22.3.3 Random Genetic Drift Versus Mutation and Selection 764 22.4 The Infinite Alíele Model 765 22.4.1 The Infinite Alíele Model with Mutation 766 22.4.2 Ewens's Sampling Formula 767 22.4.3 The Infinite Alíele Model with Selection and Mutation 767 22.5 Other Models of Mutation and Selection 768 22.5.1 The Infinitely Many Sites Model 768 22.5.2 Frequency-dependent Selection 768 22.5.3 Overlapping Generations 769 22.6 Coalescent Theory 769 22.6.1 The Neutral Coalescent 769 22.6.2 The Ancestral Selection Graph 771 22.6.3 Varying Population Size 774 22.7 Detecting Selection 775 Acknowledgments 777 References 777 23 Inference, Simulation and Enumeration of Genealogies 781 С Cannings and A. Thomas 23.1 Genealogies as Graphs 781 23.2 Relationships 782 23.2.1 The Algebra of Pairwise Relationships 782 23.2.2 Measures of Genetic Relationship 785 23.2.3 Identity States for Two Individuals 786 23.2.4 More Than Two Individuals 787 23.2.5 Example: Two Siblings Given Parental States 789 23.3 The Identity Process Along a Chromosome 790 23.3.1 Theory of Junctions 790 23.3.2 Random Walks 791 23.3.3 Other Methods 791 23.4 State Space Enumeration 792 23.4.1 Applying the Peeling Method 792 23.4.2 Recursions 793 23.4.3 More Complex Linear Systems 795 23.4.4 A Non-linear System 796 23.5 Marriage Node Graphs 796 23.5.1 Drawing Marriage Node Graphs 796 23.5.2 Zero-loop Pedigrees 798 CONTENTS xix 23.6 Moral Graphs 801 23.6.1 Significance for Computation 801 23.6.2 Derivation from Marriage Node Graphs 802 23.6.3 Four Colourability and Triangulation 804 References 805 24 Graphical Models in Genetics 808 S.L. Lauritzen and N.S. Sheehan 24.1 Introduction 808 24.2 Bayesian Networks and Other Graphical Models 809 24.2.1 Graph Terminology 809 24.2.2 Conditional Independence 809 24.2.3 Elements of Bayesian Networks 810 24.2.4 Object-oriented Specification of Bayesian Networks 810 24.3 Representation of Pedigree Information 811 24.3.1 Graphs for Pedigrees 811 24.3.2 Pedigrees and Bayesian Networks 812 24.4 Peeling and Related Algorithms 816 24.4.1 Compilation 817 24.4.2 Propagation 821 24.4.3 Random and Other Propagation Schemes 823 24.4.4 Computational Shortcuts 824 24.5 Pedigree Analysis and Beyond 824 24.5.1 Single-point Linkage Analysis 824 24.5.2 QTL Mapping 825 24.5.3 Pedigree Uncertainty 827 24.5.4 Forensic Applications 829 24.5.5 Bayesian Approaches 832 24.6 Causal Inference 832 24.6.1 Causal Concepts 833 24.6.2 Mendelian Randomisation 833 24.7 Other Applications 836 24.7.1 Graph Learning for Genome-wide Associations 836 24.7.2 Gene Networks 838 References 838 25 Coalescent Theory 843 M. Nordborg 25.1 Introduction 843 25.2 The coalescent 844 25.2.1 The Fundamental Insights 844 25.2.2 The Coalescent Approximation 847 25.3 Generalizing the Coalescent 850 25.3.1 Robustness and Scaling 850 25.3.2 Variable Population Size 851 25.3.3 Population Structure on Different Time Scales 853 XX CONTENTS 25.4 Geographical Structure 854 25.4.1 The Structured Coalescent 855 25.4.2 The Strong-migration Limit 856 25.5 Segregation 857 25.5.1 Hermaphrodites 857 25.5.2 Males and Females 859 25.6 Recombination 859 25.6.1 The Ancestral Recombination Graph 860 25.6.2 Properties and Effects of Recombination 863 25.7 Selection 865 25.7.1 Balancing Selection 865 25.7.2 Selective Sweeps 868 25.7.3 Background Selection 868 25.8 Neutral Mutations 869 25.9 Conclusion 870 25.9.1 The Coalescent and 'Classical' Population Genetics 870 25.9.2 The Coalescent and Phylogenetics 870 25.9.3 Prospects 872 Acknowledgments 872 References 872 26 Inference Under the Coalescent 878 M. Stephens 26.1 Introduction 878 26.1.1 Likelihood-based Inference 879 26.2 The Likelihood and the Coalescent 883 26.3 Importance Sampling 885 26.3.1 Likelihood Surfaces 887 26.3.2 Ancestral Inference 888 26.3.3 Application and Assessing Reliability 888 26.4 Markov Chain Monte Carlo 889 26.4.1 Introduction 889 26.4.2 Choosing a Good Proposal Distribution 891 26.4.3 Likelihood Surfaces 891 26.4.4 Ancestral Inference 893 26.4.5 Example Proposal Distributions 894 26.4.6 Application and Assessing Reliability 897 26.4.7 Extensions to More Complex Demographic and Genetic Models 899 26.5 Other Approaches 900 26.5.1 Rejection Sampling and Approximate Bayesian Computation 900 26.5.2 Composite Likelihood Methods 902 26.5.3 Product of Approximate Conditionals (PAC) Models 903 26.6 Software and Web Resources 903 26.6.1 Population Genetic Simulations 904 26.6.2 Inference Methods 904 Acknowledgments 905 References 906 CONTENTS xxi 27 Linkage Disequilibrium, Recombination and Selection 909 G. McVean 27.1 What Is Linkage Disequilibrium? 909 27.2 Measuring Linkage Disequilibrium 911 27.2.1 Single-number Summaries of LD 913 27.2.2 The Spatial Distribution of LD 914 27.2.3 Various Extensions of Two-locus LD Measures 918 27.2.4 The Relationship between r2 and Power in Association Studies 919 27.3 Modelling LD and Genealogical History 922 27.3.1 A Historical Perspective 922 27.3.2 Coalescent Modelling 924 27.3.3 Relating Genealogical History to LD 930 27.4 Inference 932 27.4.1 Formulating the Hypotheses 932 27.4.2 Parameter Estimation 933 27.4.3 Hypothesis Testing 937 27.5 Prospects 938 Acknowledgments 939 Related Chapters 940 References 940 28 Inferences from Spatial Population Genetics 945 F. Rousset 28.1 Introduction 945 28.2 Neutral Models of Geographical Variation 946 28.2.1 Assumptions and Parameters 946 28.3 Methods of Inference 948 28.3.1 F-statistics 948 28.3.2 Likelihood Computations 952 28.4 Inference Under the Different Models 955 28.4.1 Migration-Matrix Models 955 28.4.2 Island Model 955 28.4.3 Isolation by Distance 956 28.4.4 Likelihood Inferences 959 28.5 Separation of Timescales 960 28.6 Other Methods 962 28.6.1 Assignment and Clustering 962 28.6.2 Inferences from Clines 964 28.7 Integrating Statistical Techniques into the Analysis of Biological 965 Processes Acknowledgments 966 Related Chapters 966 References 967 Appendix A: Analysis of Variance and Probabilities of Identity 972 Appendix B: Likelihood Analysis of the Island Model 977 xxii CONTENTS 29 Analysis of Population Subdivision 980 L. Excoffier 29.1 Introduction 98° 29.1.1 Effects of Population Subdivision 980 29.2 The Fixation Index F 982 29.3 Wright's F Statistics in Hierarchic Subdivisions 983 29.3.1 Multiple Alíeles 985 29.3.2 Sample Estimation of F Statistics 986 29.3.3 G Statistics 987 29.4 Analysis of Genetic Subdivision Under an Analysis of Variance 988 Framework 29.4.1 The Model 989 29.4.2 Estimation Procedure 991 29.4.3 Dealing with Mutation and Migration using Identity Coefficients 996 29.5 Relationship Between Different Definitions of Fixation Indexes 997 29.6 F Statistics and Coalescence Times 999 29.7 Analysis of Molecular Data: The Amova Framework 1001 29.7.1 Haplotypic Diversity 1001 29.7.2 Genotypie Data 1004 29.7.3 Multiallelic Molecular Data 1004 29.7.4 Dominant Data 1007 29.7.5 Relation of AMOVA with other Approaches 1008 29.8 Significance Testing 1009 29.8.1 Resampling Techniques 1009 29.9 Related and Remaining Problems 1011 29.9.1 Testing Departure from Hardy-Weinberg Equilibrium 1011 29.9.2 Detecting Loci under Selection 1012 29.9.3 What is the Underlying Genetic Structure of Populations? 1012 Acknowledgments 1013 References 1013 30 Conservation Genetics 1021 M.A. Beaumont 30.1 Introduction 1021 30.2 Estimating Effective Population Size 1022 30.2.1 Estimating Ne Using Two Samples from the Same Population: 1023 The Temporal Method 30.2.2 Estimating Ne from Two Derived Populations 1025 30.2.3 Estimating JVe Using One Sample 1030 30.2.4 Inferring Past Changes in Population Size: 1033 Population Bottlenecks 30.2.5 Approximate Bayesian Computation 1040 30.3 Admixture 1041 30.4 Genotypie Modelling 1046 30.4.1 Assignment Testing 1046 30.4.2 Genetic Mixture Modelling and Clustering 1048 30.4.3 Hybridisation and the Use of Partially Linked Markers 1051 CONTENTS_ xxiii 30.4.4 Inferring Current Migration Rates 1052 30.4.5 Spatial Modelling 1053 30.5 Relatedness and Pedigree Estimation 1054 Acknowledgments 1057 Related Chapters 1057 References 1058 31 Human Genetic Diversity and its History 1067 G. Barbujani and L, Chikhi 31.1 Introduction 1068 31.2 Human Genetic Diversity: Historical Inferences 1069 31.2.1 Some Data on Fossil Evidence 1069 31.2.2 Models of Modern Human Origins 1070 31.2.3 Methods for Inferring Past Demography 1071 31.2 A Reconstructing Past Human Migration and Demography 1075 31.3 Human Genetic Diversity: Geographical Structure 1081 31.3.1 Catalogues of Humankind 1081 31.3.2 Methods for Describing Population Structure 1084 31.3.3 Identifying the Main Human Groups 1087 31.3.4 Continuous versus Discontinuous Models of Human Variation 1091 31.4 Final Remarks 1092 Acknowledgments 1096 References 1096 Part 6 GENETIC EPIDEMIOLOGY 1109 32 Epidemiology and Genetic Epidemiology 1111 P.R. Burton, J.M. Bowden and M.D. Tobin 32.1 Introduction 1111 32.2 Descriptive Epidemiology 1112 32.2.1 Incidence and Prevalence 1114 32.2.2 Modelling Correlated Responses 1115 32.3 Descriptive Genetic Epidemiology 1117 32.3.1 Is There Evidence of Phenotypic Aggregation within Families? 1117 32.3.2 Is the Pattern of Correlation Consistent with a Possible 1118 Effect of Genes? 32.3.3 Segregation Analysis 1126 32.3.4 Ascertainment 1127 32.4 Studies Investigating Specific Aetiological Determinants 1130 32.5 The Future П31 Acknowledgments 1132 References 1132 33 Linkage Analysis 1141 E.A. Thompson 33.1 Introduction 1141 xxjy CONTENTS 33.2 The Early Years 1142 33.3 The Development of Human Genetic Linkage Analysis 1144 33.4 The Pedigree Years; Segregation and Linkage Analysis 1146 33.5 Likelihood and Location Score Computation 1149 33.6 Monte Carlo Multipoint Linkage Likelihoods 1151 33.7 Linkage Analysis of Complex Traits 1155 33.8 Map Estimation, Map Uncertainty, and The Meiosis Model 1158 33.9 The Future 1162 Acknowledgments 1163 References 1163 34 Non-parametric Linkage 1168 P. Holmans 34.1 Introduction 1168 34.2 Pros and Cons of Model-free Methods 1169 34.3 Model-free Methods for Dichotomous Traits 1171 34.3.1 Affected Sib-pair Methods 1171 34.3.2 Parameter Estimation and Power Calculation Using 1172 Affected Sib Pairs 34.3.3 Typing Unaffected Relatives in Sib-pair Analyses 1173 34.3.4 Application of Sib-pair Methods to Multiplex Sibships 1174 34.3.5 Methods for Analysing Larger Pedigrees 1175 34.3.6 Extensions to Multiple Marker Loci 1176 34.3.7 Multipoint Analysis with Tightly Linked Markers 1177 34.3.8 Inclusion of Covariates 1177 34.3.9 Multiple Disease Loci 1179 34.3.10 Significance Levels for Genome Scans 1180 34.3.11 Meta-analysis of Genome Scans 1180 34.4 Model-free Methods for Analysing Quantitative Traits 1181 34.5 Conclusions 1182 Related Chapters 1182 References 1183 35 Population Admixture and Stratification in Genetic 1190 Epidemiology P.M. McKeigue 35.1 Background 1191 35.2 Admixture Mapping Ц92 35.2.1 Basic Principles Ц92 35.2.2 Statistical Power and Sample Size 1194 35.2.3 Distinguishing between Genetic and Environmental 1196 Explanations for Ethnic Variation in Disease Risk 35.3 Statistical Models 1198 35.3.1 Modelling Admixture 1198 35.3.2 Modelling Stratification 1199 35.3.3 Modelling Alíele Frequencies 1201 CONTENTS_xxv 35.3.4 Fitting the Statistical Model 1202 35.3.5 Model Comparison 1203 35.3.6 Assembling and Evaluating Panels of Ancestry-informative 1204 Marker Loci 35.4 Testing For Linkage With Locus Ancestry 1205 35.4.1 Modelling Population Stratification 1207 35.5 Conclusions 1212 References 1213 36 Population Association 1216 D. Clayton 36.1 Introduction 1216 36.2 Measures of Association 1217 36.3 Case-Control Studies 1219 36.4 Tests For Association 1221 36.5 Logistic Regression And Log-Linear Models 1225 36.6 Stratification And Matching 1227 36.7 Unmeasured Confounding 1230 36.8 Multiple Alíeles 1232 36.9 Multiple Loci 1234 36.10 Discussion 1236 Acknowledgments 1236 References 1236 37 Whole Genome Association 1238 A.P. Morris and L.R. Cardon 37.1 Introduction 1238 37.1.1 Linkage Disequilibrium and Tagging 1239 37.1.2 Current WGA Studies 1240 37.2 Genotype Quality Control 1242 37.3 Single-Locus Analysis 1245 37.3.1 Logistic Regression Modelling Framework 1247 37.3.2 Interpretation of Results and Correction for Multiple Testing 1249 37.4 Population Structure 1250 37.5 Multi-Locus Analysis 1251 37.5.1 Haplotype-based Analyses 1252 37.5.2 Haplotype Clustering Techniques 1253 37.6 Epistasis 1254 37.7 Replication 1256 37.8 Prospects for Whole-Genome Association Studies 1257 References 1258 38 Family-based Association 1264 F. Dudbridge 38.1 Introduction 1264 38.2 Transmission/Disequilibrium Test 1266 xxvi _CONTENTS 38.3 Logistic Regression Models 1268 38.4 Haplotype Analysis 1271 38.5 General Pedigree Structures 1273 38.6 Quantitative Traits 1276 38.7 Association in the Presence of Linkage 1278 38.8 Conclusions 1281 References 1282 39 Cancer Genetics I286 M.D. Teare 39.1 Introduction 1286 39.2 Armitage-Doll Models of Carcinogenesis 1287 39.2.1 The Multistage Model 1287 39.2.2 The Two-stage Model 1289 Electronic Resources 1298 References 1298 40 Epigenetics 1301 K.D. Siegmund and S. Lin 40.1 A Brief Introduction 1301 40.2 Technologies for CGI Methylation Interrogation 1303 40.2.1 MethyLight 1304 40.2.2 Methylation Microarrays 1304 40.3 Modeling Human Cell Populations 1305 40.3.1 Background 1305 40.3.2 Methylation Patterns 1305 40.3.3 Modeling Human Colon Crypts 1306 40.3.4 Summary 1307 40.4 Mixture Modeling 1307 40.4.1 Cluster Analysis 1308 40.4.2 Modeling Exposures for Latent Disease Subtypes 1310 40.4.3 Differential Methylation with Single-slide Data 1311 40.5 Recapitulation of Tumor Progression Pathways 1313 40.5.1 Background 1313 40.5.2 Heritable Clustering 1313 40.5.3 Further Comments 1315 40.6 Future Challenges 1316 Acknowledgments 1316 References 1317 Part 7 SOCIAL AND ETHICAL ASPECTS 1323 41 Ethics Issues in Statistical Genetics 1325 R.E. Ashcroft 41.1 Introduction: Scope of This Chapter 1325 41.1.1 What is Ethics'? 1326 CONTENTS xxvji 41.1.2 Models for Analysing the Ethics of Population Genetic Research 1327 41.2 A Case Study in Ethical Regulation of Population Genetics Research: 1329 UK Biobank's Ethics and Governance Framework 41.2.1 The Scientific and Clinical Value of the Research 1330 41.2.2 Recruitment of Participants 1332 41.2.3 Consent 1334 41.2.4 Confidentiality and Security 1339 41.3 Stewardship 1339 41.3.1 Benefit Sharing 1340 41.3.2 Community Involvement 1341 41.4 Wider Social Issues 1341 41.4.1 Geneticisation 1341 41.4.2 Race, Ethnicity and Genetics 1342 41.5 Conclusions 1343 Acknowledgments 1343 References 1343 42 Insurance 1346 A.S. Macdonald 42.1 Principles of Insurance 1346 42.1.1 Long-term Insurance Pricing 1346 42.1.2 Life Insurance Underwriting 1348 42.1.3 Familial and Genetic Risk Factors 1349 42.1.4 Adverse Selection 1349 42.1.5 Family Medical Histories 1350 42.1.6 Legislation and Regulation 1351 42.1.7 Quantitative Questions 1352 42.2 Actuarial Modelling 1352 42.2.1 Actuarial Models for Life and Health Insurance 1352 42.2.2 Parameterising Actuarial Models 1354 42.2.3 Market Models and Missing Information 1355 42.2.4 Modelling Strategies 1357 42.2.5 Statistical Issues 1358 42.2.6 Economics Issues 1359 42.3 Examples and Conclusions 1359 42.3.1 Single-gene Disorders 1359 42.3.2 Multifactorial Disorders 1361 References 1365 43 Forensics 1368 B.S. Weir 43.1 Introduction 1368 43.2 Principles of Interpretation 1369 43.3 Profile Probabilities 1371 43.3.1 Allelic Independence 1371 43.3.2 Alíele Frequencies 1373 xxviii CONTENTS 43.3.3 Joint Profile Probabilities 1375 43.4 Parentage Issues 1377 43.5 Identification of Remains 1379 43.6 Mixtures 1379 43.7 Sampling Issues 1383 43.7.1 Alíele Probabilities 1383 43.7.2 Coancestry 1384 43.8 Other Forensic Issues 1385 43.8.1 Common Fallacies 1385 43.8.2 Relevant Population 1385 43.8.3 Database Searches 1386 43.8.4 Uniqueness of Profiles 1386 43.8.5 Assigning Individuals to Phenotypes, Populations or Families 1388 43.8.6 Hierarchy of Propositions 1389 43.9 Conclusions 1390 References 1390 Reference Author Index I Subject Index LXIII
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