Forward-Time Population Genetics Simulations: Methods, Implementation, and Applications

The only book available in the area of forward-time population genetics simulations—applicable to both biomedical and evolutionary studies

The rapid increase of the power of personal computers has led to the use of serious forward-time simulation programs in genetic studies. Forward-Time Population Genetics Simulations presents both new and commonly used methods, and introduces simuPOP, a powerful and flexible new program that can be used to simulate arbitrary evolutionary processes with unique features like customized chromosome types, arbitrary nonrandom mating schemes, virtual subpopulations, information fields, and Python operators.

The book begins with an overview of important concepts and models, then goes on to show how simuPOP can simulate a number of standard population genetics models—with the goal of demonstrating the impact of genetic factors such as mutation, selection, and recombination on standard Wright-Fisher models. The rest of the book is devoted to applications of forward-time simulations in various research topics.

Forward-Time Population Genetics Simulations includes:

• An overview of currently available forward-time simulation methods, their advantages, and shortcomings

• An overview and evaluation of currently available software

• A simuPOP tutorial

• Applications in population genetics

• Applications in genetic epidemiology, statistical genetics, and mapping complex human diseases

The only book of its kind in the field today, Forward-Time Population Genetics Simulations will appeal to researchers and students of population and statistical genetics.

Avainsanat: simulation programs, easy POP, genetic studies, forward-time simulation, forward-time simulation methods, forward-time population genetics, simulation environment, simuPOP, statistical genetics, population genetics, genetic epidemiology, Statistical Genetics / Microarray Analysis, Medical Statistics & Epidemiology, Statistical Genetics / Microarray Analysis, Medical Statistics & Epidemiology