Introduction to Statistical Methods in Modern Genetics

About this book

Although the basic statistical theory behind modern genetics is not very difficult, most statistical genetics papers are not easy to read for beginners in the field, and formulae quickly become very tedious to fit a particular area of application. "Introduction to Statistical Methods in Modern Genetics" distinguishes between the necessary and unnecessary complexity in a presentation designed for graduate-level statistics students. The author keeps derivations simple, but does so without losing the mathematical details. He also provides the required background in modern genetics for those looking forward to entering this arena. Along with some of the statistical tools important in genetics applications, students will learn: How a gene is found; How scientists have separated the genetic and environmental aspects of a person's intelligence; How genetics are used in agriculture to improve crops and domestic animals; What a DNA fingerprint is and why there are controversies about it. Although the author assumes students have a foundation in basic statistics, an appendix provides the necessary background beyond the elementary, including multinomial distributions, inference on frequency tables, and discriminant analysis. With clear explanations, a multitude of figures, and exercise sets in each chapter, this text forms an outstanding entre into the rapidly expanding world of genetic data analysis.

Contents

BACKGROUND TO MODERN STATISTICAL GENETICS Introduction: Where is the Gene? Function of Genes in Reproduction Some Facts in Molecular Genetics Tools in Molecular Genetics Genetic Engineering Exercise 1 LINKAGE ANALYSIS WITH QUALITATIVE TRAIT Basic Concepts in Pedigree Analysis Linkage analysis for Large Pedigrees Incomplete Penetrance and Sibling Studies Designs in Linkage Analysis Exercise 2 GENETICS OF QUANTITATIVE TRAIT Quantitative Trait Locus (QTL) Based on Sibpairs Interval Mapping of Quantitative Trait Loci Heritability Estimation Breeding Value Evaluation Models Exercise 3 SPECIAL TOPICS Small Area Gene Mapping by Linkage Disequilibrium Gene, Exon, and Intron Identification Reconstruction of Evolutionary Path Forensic Evidence Using Genetic Markers Exercise 4 APPENDIX A: STATISTICAL RESULTS USEFUL IN GENETICS Multivariate Analysis and Regression Likelihood Ratio Test and General Linear Models Multinomial Distribution Inference on Frequency Tables Discriminant Analysis and Neural Network APPENDIX B: SELECTED PUBLIC DOMAIN COMPUTER PROGRAMS FOR GENETIC DATA ANALYSIS A Teaching Linkage Analysis Program for Two Generation Families A Simulation Program to Computer ELOD and Var(LOD) for Two Generation Families Liped and Programs Described in Terwilliger and Ott's Handbook Simlink - Power Prediction for Given Pedigress SIB-PAIR; A Nonparametric Linkage Software MAPMAKER/SIBS, MAPMAKER/QTL, Genehunter, GAS A SAS Program to Computer Kinships Coefficients Using SAS-IML to Solve Handerson's Equation ETDT GeneBank and Genetic Data Sources Answers or Hints to Exercises Bibliography

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