Genetic Data Analysis II: Methods for Discrete Population Genetic Data by Bruce S. Weir – A Statistical Genetics Textboo

Introduction

For students and researchers navigating the complex world of population genetics, having a reliable mathematical foundation is essential. Genetic Data Analysis II: Methods for Discrete Population Genetic Data by Bruce S. Weir stands as a definitive resource for understanding and applying statistical methods to discrete genetic data. This hardcover edition, published by Sinauer Associates (an imprint of Oxford University Press), builds upon the classic 1990 volume, incorporating user feedback and cutting-edge developments. Whether you are a postgraduate student in India or a practising biologist, this book equips you with the tools to analyse genetic variation with precision.

Book Overview

This second edition retains the rigorous approach of its predecessor while expanding into new territories. The book systematically covers the analysis of discrete genetic data—such as allele frequencies, genotype counts, and molecular markers—using sound statistical principles. With revised chapters, new material on linkage and individual identification, and an enhanced set of exercises, it bridges theory and practical application. The accompanying Windows-based programs (by Paul O. Lewis and Dmitri Zaykin) further empower readers to implement methods directly.

Key Highlights

• Updated Chapter on Phylogeny Reconstruction: Incorporates modern methods for building evolutionary trees.
• New Chapters on Linkage and Individual Identification: Addresses contemporary needs in forensic genetics and genome mapping.
• Expanded Exercises with Solutions: Over 100 problems with worked answers to reinforce learning.
• Comprehensive Reference List: Hundreds of citations to primary literature for deeper study.
• Windows-Based Software Suite: Practical tools for performing analyses covered in the book.

Inside the Book

The text is organised into twelve chapters, each building logically on the previous. Beginning with basic probability and statistics, it moves through gene frequency estimation, Hardy–Weinberg equilibrium testing, linkage disequilibrium, population subdivision, and finally phylogeny reconstruction and individual identification. Every concept is illustrated with real-world examples from human, animal, and plant populations. The writing is clear and mathematical without being opaque, making it accessible to those with a solid undergraduate background in statistics or genetics.

Key Topics

• Probability models for genetic data
• Estimation of allele and genotype frequencies
• Testing for Hardy–Weinberg equilibrium
• Measures of genetic diversity and differentiation
• Linkage disequilibrium and association mapping
• Population structure and F-statistics
• Phylogeny reconstruction methods (parsimony, distance, likelihood)
• Individual identification and forensic applications

Reader Benefits

• Master Statistical Rigour: Move beyond black-box software to understand the mathematics behind genetic analysis.
• Solve Real Problems: Work through exercises that mirror actual research challenges.
• Stay Current: Benefit from the latest methods in phylogenetics and linkage analysis.
• Build a Strong Foundation: Ideal for self-study or as a textbook for advanced courses.
• Practical Implementation: Use the included software to apply methods to your own data.

Learning Outcomes

After studying this book, readers will be able to: estimate genetic parameters from discrete data with confidence; test hypotheses about population genetic processes; interpret measures of population differentiation; construct and evaluate phylogenetic trees; and apply methods for individual identification and parentage analysis. The skills gained are directly transferable to fields such as conservation genetics, plant and animal breeding, human genetics, and evolutionary biology.

Who Should Read

• Graduate Students in genetics, bioinformatics, evolutionary biology, and statistics.
• Researchers in population genetics, conservation biology, and forensic science.
• Lecturers designing courses in genetic data analysis.
• Bioinformatics Professionals seeking a deeper understanding of discrete data methods.
• Indian Students preparing for competitive exams or research in genomics and breeding.

About the Author

Bruce S. Weir is a distinguished geneticist and Professor of Biostatistics at the University of Washington. A pioneer in statistical genetics, he has authored over 300 research articles and several seminal books. His work on F-statistics, population structure, and forensic DNA analysis has shaped modern genetics. Dr. Weir’s ability to communicate complex mathematical ideas with clarity makes this book a trusted companion for learners worldwide.

About the Publisher

Sinauer Associates, an imprint of Oxford University Press, is renowned for publishing high-quality textbooks and reference works in biology and genetics. With a legacy spanning decades, Sinauer titles are known for their authoritative content, rigorous peer review, and exceptional production standards. This partnership ensures that Genetic Data Analysis II meets the highest academic benchmarks.

Conclusion

Genetic Data Analysis II remains an indispensable guide for anyone working with discrete population genetic data. Its blend of theory, practical exercises, and software support makes it a complete learning package. Available now in hardcover from Bookshops.in, this is a long-term investment in your statistical and genetic literacy. Add it to your library today and gain the skills to analyse genetic variation with confidence.