This book covers the statistical models and methods that are used to
understand human genetics, following the historical and recent
developments of human genetics. Starting with Mendel's first experiments
to genome-wide association studies, the book describes how genetic
information can be incorporated into statistical models to discover
disease genes. All commonly used approaches in statistical genetics
(e.g. aggregation analysis, segregation, linkage analysis, etc), are
used, but the focus of the book is modern approaches to association
analysis. Numerous examples illustrate key points throughout the text,
both of Mendelian and complex genetic disorders. The intended audience
is statisticians, biostatisticians, epidemiologists and quantitatively-
oriented geneticists and health scientists wanting to learn about
statistical methods for genetic analysis, whether to better analyze
genetic data, or to pursue research in methodology. A background in
intermediate level statistical methods is required. The authors include
few mathematical derivations, and the exercises provide problems for
students with a broad range of skill levels. No background in genetics
is assumed.