1st Edition

# Introduction to Statistical Methods in Modern Genetics

By

## M.C. Yang

ISBN 9780367398903
Published September 5, 2019 by CRC Press
247 Pages

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## Book Description

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 entrĂ©e into the rapidly expanding world of genetic data analysis.

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
Basic Concepts in Pedigree Analysis
Incomplete Penetrance and Sibling Studies
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
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