Gene Mapping Through Linkage and Association
Edited by Benjamin Neale, Manuel Ferreira, Sarah Medland, Danielle Posthuma
Published December 6th 2007 by Taylor & Francis – 332 pages
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.
"…well organized and is written and edited by enthusiastic experts. This will be a great starting place for anyone who wants to understand and, hopefully, get involved with research on the genetics of human complex traits." Twin Research and Human Genetics
1. Introduction 2. DNA 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. 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. Genome-wide Association 17. Haplotype Estimation 18. Multi-locus Association Models 19. Linkage Disequilibrium and Tagging 20. Haploview 21. Factors Affecting Type I Error and Power in Association 22. Resampling Approaches to Statistical Interference