This timely text presents a comprehensive guide to genetic association, a new and rapidly expanding field that aims to elucidate how our genetic code (genotypes) influences the traits we possess (phenotypes). The book provides a detailed review of methods of gene mapping used in association with experimental crosses, as well as genome-wide association studies. Emphasis is placed on model selection procedures for analyzing data from large-scale genome scans based on specifically designed modifications of the Bayesian information criterion. Topics and features: Presents a thorough introduction to the theoretical background to studies of genetic association (both genetic and statistical) Reviews the latest advances in the field, highlighting the advantages and shortcomings of the currently most commonly used methods Illustrates the properties of methods for mapping quantitative trait loci using computer simulations and the analysis of real data Discusses open challenges that remain to be solved in the future Includes an extensive statistical appendix as a reference for those who are not totally familiar with the fundamentals of statistics This important work is essential reading for researchers and graduate students wishing to enter the field of statistical genetics and/or interested in statistical issues related to the analysis of high-dimensional data. No prior background knowledge of genetics is required, although some basic mathematical and computer science skills are assumed. Dr. Florian Frommlet is a researcher in the Center for Medical Statistics, Informatics, and Intelligent Systems at the Medical University of Vienna, Austria. Dr. Małgorzata Bogdan is an Associate Professor in the Institute of Mathematics at Wrocław University, Poland. Dr. David Ramsey is a Senior Lecturer in the Department of Operations Research at Wrocław University of Technology, Poland.