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| Contributors | |
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| Foreword | |
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| Acknowledgments | |
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| The Evolving Field of Genetic Epidemiology | |
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| Introduction | |
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| Assessing Genetic Influences on Disease, Human Genetics Concepts, and Genomic Technology | |
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| Family-based Study Designs: Linkage, Exome Sequencing and Case-Parent Trios | |
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| Genetic Association Studies of Common and Rare Variants, Large-scale Collaborations, and Population Stratification | |
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| Gene-Environment Interactions, Epistasis, and Non-Mendelian Genetics | |
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| Software and Data Resources | |
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| Ethical Issues and Translational Genetic Epidemiology | |
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| Conclusion | |
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| Assessing Genetic Influences on Diseases and Risk Factors | |
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| Introduction | |
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| Familial Aggregation Studies | |
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| Familial aggregation study designs | |
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| Heritability Analysis | |
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| Polygenic model | |
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| Estimating heritability using twins | |
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| Assumptions, biases, and misconceptions in heritability analysis | |
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| Conclusion: Heritability and the Polygenic Model in the Genomic Era | |
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| Genetic Concepts and Genomic Technology for Genetic Epidemiology | |
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| Introduction | |
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| Mendelian Inheritance and Complex Traits | |
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| Mendel's laws | |
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| Modes of inheritance for single genes | |
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| Online Mendelian Inheritance in Man (OMIM�) | |
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| Complex traits | |
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| Hardy-Weinberg Principle | |
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| Deviations from Hardy-Weinberg equilibrium | |
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| Genetic Code, Gene Structure, and Genetic Markers | |
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| Exons, introns, and untranslated regions | |
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| Single nucleotide polymorphisms (SNPs) and structural variations | |
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| Genetic Linkage and Linkage Disequilibrium | |
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| Genetic linkage and recombination | |
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| Linkage disequilibrium and haplotypes | |
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| Tag SNPs | |
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| SNP genotyping platforms | |
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| DNA Sequencing Technologies | |
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| Three generations of DNA sequencing | |
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| Exome sequencing | |
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| Study Designs for Common and Rare Genetic Variants | |
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| Conclusion | |
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| Family Studies in Genetic Epidemiology: From Linkage to Exome Sequencing | |
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| Linkage Analysis | |
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| Basics of LOD score linkage analysis | |
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| Non-parametric linkage analysis | |
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| Family-based Association Studies | |
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| Linkage and association in families | |
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| Case-parent trios and the transmission disequilibrium test (TDT) | |
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| Extensions of the TDT | |
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| Conclusion | |
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| Genetic Association Studies | |
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| Introduction to Genetic Association Studies | |
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| Study Designs for Candidate Gene Studies | |
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| Practical considerations for selecting candidate genes | |
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| Complexities of Interpreting Genetic Association Results | |
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| Direct, causal relationship | |
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| Indirect association due to linkage disequilibrium | |
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| False-positive associations | |
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| False-negative associations and power | |
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| Basics of Genome-wide Association Studies (GWAS) | |
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| GWAS case-control studies | |
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| Data analysis of GWAS | |
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| Large-scale Collaborations: The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium | |
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| The CHARGE Consortium | |
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| CHARGE goals and organization | |
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| Genome-wide genotyping methods | |
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| Design of CHARGE analyses | |
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| Phenotype working groups | |
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| Analysis methods | |
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| Productivity | |
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| Collaborations with non-CHARGE studies and other consortia | |
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| Working-group model as innovation | |
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| A new era of consortia | |
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| CHARGE: past, present, and future | |
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| Facilitating large-scale collaborations | |
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| Case-Parent Trio Designs in GWAS | |
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| Heritability and Allelic Architecture of Complex Traits | |
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| Missing heritability in GWAS | |
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| Study Designs and Statistical Analysis of DNA Sequencing Data | |
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| Study designs for rare genetic variants | |
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| Methods for detecting association with rare variants | |
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| Conclusion | |
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| Population Stratification in Genetic Association Studies | |
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| General Concepts | |
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| Rationale for GWAS | |
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| Population stratification confounding | |
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| Detecting Population Stratification | |
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| Statistical Methods to Adjust for Global Population Stratification Confounding | |
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| Genomic control | |
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| Ethnicity adjustment | |
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| Principal components adjustment | |
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| Estimated ancestry adjustment | |
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| Estimated correlation methods | |
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| Statistical Methods to Adjust for Local Population Stratification Confounding | |
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| Mixing of populations and local population structure | |
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| Lactase persistence gene | |
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| Controlling for local ancestry | |
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| Conclusion | |
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| Gene-Environment Interactions and Epistasis | |
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| Why Study Interaction? | |
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| Models of Interaction | |
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| Statistical Interaction and the Problem of Measurement Scale | |
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| Statistical analysis of interaction for cohort and case-control studies | |
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| Multiplicative and additive measurement scales | |
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| Causal modeling applied to interaction | |
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| Case-only Study Design | |
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| Considerations for case-only studies | |
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| Pharmacogenomics | |
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| Gene-Environment-wide Interaction Studies (GEW1S) | |
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| Harmonization of environmental data | |
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| GEWIS data analysis approaches | |
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| Epistasis: Interactions Between Genes | |
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| Conclusion | |
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| Non-Mendelian Genetics | |
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| Introduction | |
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| Mitochondrial Genetics | |
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| De Novo Variation | |
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| Parental and Parent-of-origin Effects | |
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| DNA Methylation: An Epigenetic Mechanism Underlying Phenotypic Variation | |
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| Conclusion | |
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| Software and Data Resources for Genetic Epidemiology Studies | |
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| Introduction | |
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| Software for Genetic Data Analysis | |
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| R software | |
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| PLINK | |
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| Software for association testing in samples from structured populations | |
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| Individual ancestry estimation software | |
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| Relatedness estimation software for GWAS | |
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| Software for power calculations in genetic association studies | |
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| Genotype imputation software | |
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| An alphabetical list of genetic analysis software | |
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| Human Reference Panels and Resources | |
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| International HapMap Project (HapMap) | |
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| 1000 Genomes Project | |
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| Human Generic Diversity Panel (HGDP) | |
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| Genome Variation Server | |
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| Genotype and Phenotype Repositories | |
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| Conclusion | |
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| Ethical Issues in Genetic Epidemiology | |
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| Introduction | |
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| Current Regulatory Environment | |
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| Trade-offs of Data De-identification | |
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| Informed Consent and Respect | |
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| Research Governance | |
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| Conclusion | |
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| Public Health and Clinical Applications of Genetic Epidemiology | |
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| Introduction | |
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| T1: From Discovery to Candidate Health Application | |
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| T2: From Health Application to Evidence-based Guidelines | |
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| T3: From Guidelines to Health Practice | |
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| T4: From Practice to Population Health Impact | |
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| Conclusion | |
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| Index | |