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:
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An overview of currently available forward-time simulation methods, their advantages, and shortcomings
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An overview and evaluation of currently available software
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A simuPOP tutorial
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Applications in population genetics
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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.
Bo Peng, PHD, is an assistant professor in the Department of Genetics at The University of Texas MD Anderson Cancer Center. With his degrees in applied mathematics and biostatistics, he is applying advanced computational techniques such as parallel computation and large-scale simulations to research topics in population genetics, genetic epidemiology, and bioinformatics.
Marek Kimmel, PHD, is Director of the Doctoral Program in Bioinformatics and Statistical Genetics and head of the Bioinformatics Group at Rice University. He holds joint appointments as Professor of Statistics at Rice University, Professor of Biostatistics and Applied Mathematics at MD Anderson Cancer Center, and Professor of Biometry at The University of Texas School of Public Health.
Christopher I. Amos, PHD, is a professor in the Department of Genetics at The University of Texas MD Anderson Cancer Center. He also holds adjunct appointments at Rice University and in the Department of Epidemiology at The University of Texas School of Public Health.
