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Title: Introduction to Statistical Methods in Modern Genetics (Asian Mathematics) by Mark C. K. Yang ISBN: 9-0569913-4-5 Publisher: T&F STM Pub. Date: 01 February, 2000 Format: Hardcover Volumes: 1 List Price(USD): $79.95

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Average Customer Rating: 4 (1 review)

Rating: 4
Summary: nice introduction to stat methods in genetic research
Comment: Mark Yang is a University of Florida Professor of Statistics. He has a strong engineering background and good training in biology and biochemistry. This interest led him to a careful understanding of the subject and the modern methods that are employed which rely more and more on statistics.

What is particularly nice about the book is its simplicity. The study of genetics can be very complicated. Also various useful statistical tools including Markov chain Monte Carlo, bootstrap methods, the EM algorithm and multiple comparisons can be complex as well. But Professor Yang is careful to extract only the essentials to make both the statistics and teh genetics understandable to the layperson.

On the statistical side the emphasis is on the Hardy-Weinberg equilibrium and the likeihood equations in pedigree analysis. Rather than go through complicated Markov Chain theory to demonstrate the equilibrium result Professor Yang demonstrates using simple conditional probabilities. This approach works because the convergence occurs exactly after two steps.

For the benefit of the statistician who knows nothing about genetics Chapter 1 is a primer on molecular genetics that gives the essential to understand recombinant methods, recombination fraction, the Haldane distance mapping function, linkage, RFLP and PCR techniques needed for subsequent chapters.

Most of the work in genetic inference involves calcualting the formula for the likelihood equations. This involves basic discrete probability calculations and combinatorics for the main part.

Once we learn the basics we are ready to understand gentic fingerprinting which is used to establish paternity or identify criminals.

The book has interesting examples and exercises and many good references. The only major drawback to the book is that it does not cover microarray analysis.

However, I recently took a short course from Dr. Yang based on this book. In the course he spent a great deal of time on microarray technology by supplementing the text with some notes on microarrays and a recent paper he published on the reliabiity on the technique. The text certainly gives the reader the proper background for microarray analysis or other genetic developments.