Statistical Genetics

Gene Mapping Through Linkage and Association

Benjamin Neale, Manuel Ferreira, Sarah Medland, Danielle Posthuma, Benjamin Neale, Manuel Ferreira, Sarah Medland, Danielle Posthuma

• Publisher: Taylor & Francis
• Year: 2007
• Print ISBN: 9780415410403
• eBook ISBN: 9781134129324
• Topic: Biological Sciences
• Subtopic: Biology
• Index: Biological Sciences

Statistical Genetics is an advanced textbook focusing on conducting genome-wide linkage and association analysis in order to identify the genes responsible for complex behaviors and diseases. Starting with an introductory section on statistics and quantitative genetics, it covers both established and new methodologies, providing the genetic and statistical theory on which they are based. Each chapter is written by leading researchers, who give the reader the benefit of their experience with worked examples, study design, and sources of error.

The text can be used in conjunction with an associated website (www.genemapping.org) that provides supplementary material and links to downloadable software.

Table of contents

• Cover
• Half-Title Page
• Title Page
• Copyright Page
• Table of Contents
• About the editors
• List of contributors
• Preface
• Acknowledgments
• Foreword
• Abbreviations
• Statistical symbols
• 1 Introduction
• 2 Basics of DNA and genotyping
• 3 Introduction to biometrical genetics
• 4 Introduction to statistics
• 5 Statistical power
• 6 Population genetics and its relevance to gene mapping
• 7 Principles of linkage analysis
• 8 Algorithms for IBD estimation
• 9 Regression methods for linkage analysis
• 10 Variance components linkage analysis for quantitative traits
• 11 Extensions to univariate linkage analysis
• 12 QTL detection in multivariate data from sibling pairs
• 13 Factors affecting type-I error and power of linkage analysis
• 14 Introduction to association
• 15 Single-locus association models
• 16 Analyzing genome-wide association study data: a tutorial using PLINK
• 17 Haplotype estimation
• 18 Regional multilocus association models
• 19 Linkage disequilibrium and tagging
• 20 Practical guide to linkage disequilibrium analysis and tagging using Haploview
• 21 Factors affecting power and type one error in association
• 22 Resampling approaches to statistical inference
• Appendix I: File formats
• Online resources
• Index