The Statistics of Gene Mapping

Background and Preparations.- Background in Statistics.- to Experimental Genetics.- Fundamentals of Genetics: Inbreeding, Recombination, Random Mating, and Identity by Descent.- Experimental Genetics.- Testing for Linkage with a Single Marker.- Whole Genome Scans: The Significance Level.- Statistical Power and Confidence Regions.- Missing Data and Interval Mapping.- Advanced Topics.- Human Genetics.- Mapping Qualitative Traits in Humans Using Affected Sib Pairs.- Admixture Mapping.- Mapping Complex and Quantitative Traits with Data from Human Pedigrees.- Association Studies.- Inferring Haplotypes from Genotypes and Testing Association.

From the reviews:

"The Statistics of Gene Mapping...is a welcome addition to the statistical genetics literature, that in fact includes a very small number of textbooks. ...The exercises at the end of the chapters will provide a useful pedagogical tool, with their mix of computer implementation and conceptual questions. ...[This book] provides the reader with clar, concises introduction to a number of important topics and I think it will prove to be a useful teaching instrument." Chiara Sabatti, Journal of Statistical Software, August 2007, Vol. 21

"The book is an excellent addition to the statistics-for-biology and health book series. It is also a very good textbook is statistical genetics. All statistical models and methods in the book are illustrated and simulated using R Language. ... Overall, the book covers both classical and up-to-date important topics in statistical genetics. It is a well-written book for both researchers and graduate students in statistics, biostatistics, statistical genetics, and other related fields." (Xianggui Qu, Technometrics, Vol. 50 (1), 2008)

"This book presents an excellent introduction to the basic statistical principles used in gene mapping. ... Computer algorithms are given ... . There are numerous challenging problems. ... This is a rewarding read ... . those that work through the book will gain a deep understanding of the statistical challenges of the field. With this knowledge they would be prepared for more encyclopedic or data analytic works. I recommend the book to any graduate student who might consider contributing to the field." (David F. Andrews, International Statistical Review, Vol. 75 (2), 2007)