Cover -- Title page -- Contents -- Foreword to the First Edition -- Foreword to the Second Edition -- Preface -- Acknowledgments -- 1 Molecular Genetics -- 1.1 Genetic information -- 1.1.1 Location of genetic information -- 1.1.2 Interpretation of genetic information -- 1.1.3 Translation of genetic information -- 1.2 Transmission of genetic information -- 1.3 Variations in genetic information -- 1.3.1 Individual differences in genetic information -- 1.3.2 Detection of variations -- 1.3.3 Probability for detection of variations -- 1.4 Problems -- 2 Formal Genetics -- 2.1 Mendel and his laws -- 2.2 Segregation patterns -- 2.2.1 Autosomal dominant inheritance -- 2.2.2 Autosomal recessive inheritance -- 2.2.3 X-chromosomal dominant inheritance -- 2.2.4 X-chromosomal recessive inheritance -- 2.2.5 Y-chromosomal inheritance -- 2.3 Complications of Mendelian segregation -- 2.3.1 Variable penetrance and expression -- 2.3.2 Age-dependent penetrance -- 2.3.3 Imprinting -- 2.3.4 Phenotypic and genotypic heterogeneity -- 2.3.5 Complex diseases -- 2.4 Hardy-Weinberg law -- 2.5 Problems -- 3 Genetic Markers -- 3.1 Properties of genetic markers -- 3.2 Types of genetic markers -- 3.2.1 Short tandem repeats -- 3.2.2 Single nucleotide polymorphisms (SNPs) -- 3.3 Genotyping methods for SNPs -- 3.3.1 Restriction fragment length polymorphism analysis -- 3.3.2 Real-time polymerase chain reaction -- 3.3.3 Matrix assisted laser desorption/ionization time of flight genotyping -- 3.3.4 Chip-based genotyping -- 3.3.5 Choice of genotyping method -- 3.4 Problems -- 4 Data Quality -- 4.1 Pedigree errors -- 4.2 Genotyping errors in pedigrees -- 4.2.1 Frequency of genotyping errors -- 4.2.2 Reasons for genotyping errors -- 4.2.3 Mendel checks -- 4.2.4 Checks for double recombinants -- 4.3 Genotyping errors and Hardy-Weinberg equilibrium (HWE).

4.3.1 Causes of deviations from HWE -- 4.3.2 Tests for deviation from HWE for SNPs -- 4.3.3 Tests for deviation from HWE for STRs -- 4.3.4 Measures for deviation from HWE -- 4.3.5 Tests for compatibility with HWE for SNPs -- 4.4 Quality control in high-throughput studies -- 4.4.1 Sample quality control -- 4.4.2 SNP quality control -- 4.5 Cluster plot checks and internal validity -- 4.5.1 Cluster compactness measures -- 4.5.2 Cluster connectedness measures -- 4.5.3 Cluster separation measures -- 4.5.4 Genotype stability measures -- 4.5.5 Combinations of criteria -- 4.6 Problems -- 5 Genetic Map Distances -- 5.1 Physical distance -- 5.2 Map distance -- 5.2.1 Distance -- 5.2.2 Specific map functions -- 5.2.3 Correspondence between physical distance and map distance -- 5.2.4 Multilocus feasibility -- 5.3 Linkage disequilibrium distance -- 5.4 Problems -- 6 Family Studies -- 6.1 Family history method and family study method -- 6.2 Familial correlations and recurrence risks -- 6.2.1 Familial resemblance -- 6.2.2 Recurrence risk ratios -- 6.3 Heritability -- 6.3.1 The simple Falconer model -- 6.3.2 The general Falconer model -- 6.3.3 Kinship coefficient and Jacquard's Δ7 coefficient -- 6.4 Twin and adoption studies -- 6.4.1 Twin studies -- 6.4.2 Adoption studies -- 6.5 Critique on investigating familial resemblance -- 6.6 Segregation analysis -- 6.7 Problems -- 7 Model-Based Linkage Analysis -- 7.1 Linkage analysis between two genetic markers -- 7.1.1 Linkage analysis in phase-known pedigrees -- 7.1.2 Linkage analysis in phase-unknown pedigrees -- 7.1.3 Linkage analysis in pedigrees with missing genotypes -- 7.2 Linkage analysis between a genetic marker and a disease -- 7.2.1 Linkage analysis between a genetic marker and a disease in phase-known pedigrees -- 7.2.2 Linkage analysis between a genetic marker and a disease in general cases.

7.2.3 Gain in information by genotyping additional individuals -- power calculations -- 7.3 Significance levels in linkage analysis -- 7.4 Problems -- 8 Model-Free Linkage Analysis -- 8.1 The principle of similarity -- 8.2 Mathematical foundation of affected sib-pair analysis -- 8.3 Common tests for affected sib-pair analysis -- 8.3.1 The maximum LOD score and the triangle test -- 8.3.2 Score- and Wald-type 1 degree of freedom tests -- 8.3.3 Affected sib-pair tests using alleles shared identical by state -- 8.4 Properties of affected sib-pair tests -- 8.5 Sample size and power calculations for affected sib-pair studies -- 8.5.1 Functional relation between identical by descent probabilities and recurrence risk ratios -- 8.5.2 Sample size and power calculations for the mean test using recurrence risk ratios -- 8.6 Extensions to multiple marker loci -- 8.7 Extension to large sibships -- 8.8 Extension to large pedigrees -- 8.9 Extensions of the affected sib-pair approach -- 8.9.1 Covariates in affected sib-pair analyses -- 8.9.2 Multiple disease loci in affected sib-pair analyses -- 8.9.3 Estimating the position of the disease locus in affected sib-pair analyses -- 8.9.4 Typing unaffected relatives in sib-pair analyses -- 8.10 Problems -- 9 Quantitative Traits -- 9.1 Quantitative versus qualitative traits -- 9.2 The Haseman-Elston method -- 9.2.1 The expected squared phenotypic difference at the trait locus -- 9.2.2 The expected squared phenotypic difference at the marker locus -- 9.3 Extensions of the Haseman-Elston method -- 9.3.1 Double squared trait difference -- 9.3.2 Extension to large sibships -- 9.3.3 Haseman-Elston revisited and the new Haseman-Elston method -- 9.3.4 Power and sample size calculations -- 9.4 Variance components models -- 9.4.1 The univariate variance components model -- 9.4.2 The multivariate variance components model.

9.5 Random sib-pairs, extreme probands and extreme sib-pairs -- 9.6 Empirical determination of p-values -- 9.7 Problems -- 10 Fundamental Concepts of Association Analyses -- 10.1 Introduction to association -- 10.1.1 Principles of association -- 10.1.2 Study designs for association -- 10.2 Linkage disequilibrium -- 10.2.1 Allelic linkage disequilibrium -- 10.2.2 Genotypic linkage disequilibrium -- 10.2.3 Extent of linkage disequilibrium -- 10.3 Problems -- 11 Association Analysis in Unrelated Individuals -- 11.1 Selection of cases and controls -- 11.2 Tests, estimates, and a comparison -- 11.2.1 Association tests -- 11.2.2 Choice of a test in applications -- 11.2.3 Effect measures -- 11.2.4 Selection of the genetic model -- 11.2.5 Association tests for the X chromosome -- 11.3 Sample size calculation -- 11.4 Population stratification -- 11.4.1 Testing for population stratification -- 11.4.2 Structured association -- 11.4.3 Genomic control -- 11.4.4 Comparison of structured association and genomic control -- 11.4.5 Principal components analysis -- 11.5 Gene-gene and gene-environment interaction -- 11.5.1 Classical examples for gene-gene and gene-environment interaction -- 11.5.2 Coat color in the Labrador retriever -- 11.5.3 Concepts of interaction -- 11.5.4 Statistical testing of gene-environment interactions -- 11.5.5 Statistical testing of gene-gene interactions -- 11.5.6 Multifactor dimensionality reduction -- 11.6 Problems -- 12 Family-based Association Analysis -- 12.1 Haplotype relative risk -- 12.2 Transmission disequilibrium test (TDT) -- 12.3 Risk estimates for trio data -- 12.4 Sample size and power calculations for the TDT -- 12.5 Alternative test statistics -- 12.6 TDT for multiallelic markers -- 12.6.1 Test of single alleles -- 12.6.2 Global test statistics -- 12.7 TDT type tests for different family structures.

12.7.1 TDT type tests for missing parental data -- 12.7.2 TDT type tests for sibship data -- 12.7.3 TDT type tests for extended pedigrees -- 12.8 Association analysis for quantitative traits -- 12.9 Problems -- 13 Haplotypes in Association Analyses -- 13.1 Reasons for studying haplotypes -- 13.2 Inference of haplotypes -- 13.2.1 Algorithms for haplotype assignment -- 13.2.2 Algorithms for estimating haplotype probabilities -- 13.3 Association tests using haplotypes -- 13.4 Haplotype blocks and tagging SNPs -- 13.4.1 Selection of markers by haplotypes or linkage disequilibrium -- 13.4.2 Evaluation of marker selection approaches -- 13.5 Problems -- 14 Genome-wide Association (GWA) Studies -- 14.1 Design options in GWA studies -- 14.2 Genotype imputation -- 14.2.1 Imputation algorithms -- 14.2.2 Quality of imputation -- 14.3 Statistical analysis of GWA studies -- 14.4 Multiple testing -- 14.4.1 Region-wide multiple testing adjustment by simulation -- 14.4.2 Genome-wide multiple testing adjustment by simulation -- 14.4.3 Multiple testing adjustment by effective number of tests -- 14.5 Analysis of accumulating GWA data -- 14.5.1 Multistage designs for GWA studies -- 14.5.2 Replication in GWA studies -- 14.5.3 Meta-analysis of GWA studies -- 14.6 Clinical impact of a GWA study -- 14.6.1 Evaluation of a genetic predictive test -- 14.6.2 Clinical validity of a single genetic marker -- 14.6.3 Clinical validity of multiple genetic markers -- 14.7 Outlook -- 14.8 Problems -- Appendix -- Algorithms Used in Linkage Analyses -- A.1 The Elston-Stewart algorithm -- A.1.1 The fundamental ideas of the Elston-Stewart algorithm -- A.1.2 The Elston-Stewart algorithm for a trait and a linked marker locus -- A.2 The Lander-Green algorithm -- A.2.1 The inheritance vector at a single genetic marker -- A.2.2 The inheritance distribution given all genetic markers.

A.3 The Cardon-Fulker algorithm.