Genetics and Analysis of Quantitative Traits

Genetics and Analysis of Quantitative Traits

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Description

The authors bring together a diverse array of theoretical and empirical applications of quantitative genetics in this comprehensive work designed to be accessible to anyone with a rudimentary understanding of statistics and genetics. Central concepts are developed from first principles and are illustrated with examples. The book reflects the recent influx of quantitative-genetic thinking into evolutionary biology and includes the techniques for QTL (quantitative-trait loci) analysis. Although written as a general text in quantitative genetics, the book should also serve as a basic reference for the professional.

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Product details

  • Hardback | 803 pages
  • 188 x 236.2 x 48.3mm | 1,973.15g
  • Sinauer Associates Inc.,U.S.
  • Sunderland, United States
  • English
  • 0878934812
  • 9780878934812
  • 517,733

Table of contents

I. The Genetic Basis of Quantitative Variation - An Overview of Quantitative Genetics - Properties of Distributions - Covariance, Regression, and Correlation - Properties of Single Loci - Sources of Genetic Variation for Multilocus Traits - Sources of Environmental Variation - Resemblance Between Relatives - Introduction to Matrix Algebra and Linear Models - Analysis of Line Crosses - Inbreeding Depression - Matters of Scale - II. Quantitative-Trait Loci - Polygenes and Polygenic Mutation - Detecting Major Genes - Basic Concepts of Marker-Based Analysis - Mapping and Characterizing QTLs: Inbred-Line Crosses - Mapping and Characterizing QTLs: Outbred Populations - III. Estimation Procedures - Parent-Offspring Regression - Sib AnalysisTwins and Clones - Cross-Classified Designs - Correlations Between Characters - Genotype x Environment Interaction - Maternal Effects Sex Linkage and Sexual Dimorphism - Threshold Characters - Estimation of Breeding Values - Variance-Component Estimation with Complex Pedigrees - Appendices - Expectations, Variances and Covariances of Compound Variables - Path Analysis - Matrix Algebra and Linear Models - Maximum Likelihood Estimation and Likelihood-Ratio Tests - Estimation of Power of Statistical Tests -

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