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.

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Yes, you can access Statistical Genetics by Benjamin Neale, Manuel Ferreira, Sarah Medland, Danielle Posthuma in PDF and/or ePUB format, as well as other popular books in Biological Sciences & Cell Biology. We have over one million books available in our catalogue for you to explore.

Information

Publisher

Taylor & Francis

Year

2007

ISBN

9781134129324

Edition

Topic

Biological Sciences

Subtopic

Cell Biology

Index

Biological Sciences

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