Statistical Genetics
eBook - ePub

Statistical Genetics

Gene Mapping Through Linkage and Association

  1. 608 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

About this book

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

Information

Table of contents

  1. Cover
  2. Half-Title Page
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. About the editors
  7. List of contributors
  8. Preface
  9. Acknowledgments
  10. Foreword
  11. Abbreviations
  12. Statistical symbols
  13. 1 Introduction
  14. 2 Basics of DNA and genotyping
  15. 3 Introduction to biometrical genetics
  16. 4 Introduction to statistics
  17. 5 Statistical power
  18. 6 Population genetics and its relevance to gene mapping
  19. 7 Principles of linkage analysis
  20. 8 Algorithms for IBD estimation
  21. 9 Regression methods for linkage analysis
  22. 10 Variance components linkage analysis for quantitative traits
  23. 11 Extensions to univariate linkage analysis
  24. 12 QTL detection in multivariate data from sibling pairs
  25. 13 Factors affecting type-I error and power of linkage analysis
  26. 14 Introduction to association
  27. 15 Single-locus association models
  28. 16 Analyzing genome-wide association study data: a tutorial using PLINK
  29. 17 Haplotype estimation
  30. 18 Regional multilocus association models
  31. 19 Linkage disequilibrium and tagging
  32. 20 Practical guide to linkage disequilibrium analysis and tagging using Haploview
  33. 21 Factors affecting power and type one error in association
  34. 22 Resampling approaches to statistical inference
  35. Appendix I: File formats
  36. Online resources
  37. Index