Book description
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.
