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Genetics, Vol. 178, 2417-2427, April 2008, Copyright © 2008
doi:10.1534/genetics.107.085332
Exploring Population Genetic Models With Recombination Using Efficient Forward-Time Simulations
Badri Padhukasahasram*,1,
Paul Marjoram
,
Jeffrey D. Wall
,
Carlos D. Bustamante* and
Magnus Nordborg
* Biological Statistics and Computational Biology, Cornell University, Ithaca, New York 14850, Biostatistics Division, Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California 90089, Institute of Human Genetics, University of California, San Francisco, California 94143 and Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089
1 Corresponding author: Biological Statistics and Computational Biology, Room 169, Biotechnology Building, Cornell University, Ithaca, NY 14850.
E-mail: bp85{at}cornell.edu
We present an exact forward-in-time algorithm that can efficiently simulate the evolution of a finite population under the Wright–Fisher model. We used simulations based on this algorithm to verify the accuracy of the ancestral recombination graph approximation by comparing it to the exact Wright–Fisher scenario. We find that the recombination graph is generally a very good approximation for models with complete outcrossing, whereas, for models with self-fertilization, the approximation becomes slightly inexact for some combinations of selfing and recombination parameters.
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