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Originally published as Genetics Published Articles Ahead of Print on October 18, 2007.
Genetics, Vol. 177, 1725-1731, November 2007, Copyright © 2007
doi:10.1534/genetics.106.069088
Sequence-Level Population Simulations Over Large Genomic Regions
Clive J. Hoggart*,1,2,
Marc Chadeau-Hyam*,1,
Taane G. Clark*,3,
Riccardo Lampariello
,
John C. Whittaker
,
Maria De Iorio* and
David J. Balding*
* Department of Epidemiology and Public Health, Imperial College, London W2 1PG, United Kingdom, Serono International, CH-1211 Geneva 20, Switzerland and Noncommunicable Disease Epidemiology Unit, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom
2 Corresponding author: Department of Epidemiology and Public Health, Imperial College, St. Mary's Campus, Norfolk Place, London W2 1PG, United Kingdom.
E-mail: c.hoggart{at}imperial.ac.uk
Simulation is an invaluable tool for investigating the effects of various population genetics modeling assumptions on resulting patterns of genetic diversity, and for assessing the performance of statistical techniques, for example those designed to detect and measure the genomic effects of selection. It is also used to investigate the effectiveness of various design options for genetic association studies. Backward-in-time simulation methods are computationally efficient and have become widely used since their introduction in the 1980s. The forward-in-time approach has substantial advantages in terms of accuracy and modeling flexibility, but at greater computational cost. We have developed flexible and efficient simulation software and a rescaling technique to aid computational efficiency that together allow the simulation of sequence-level data over large genomic regions in entire diploid populations under various scenarios for demography, mutation, selection, and recombination, the latter including hotspots and gene conversion. Our forward evolution of genomic regions (FREGENE) software is freely available from www.ebi.ac.uk/projects/BARGEN together with an ancillary program to generate phenotype labels, either binary or quantitative. In this article we discuss limitations of coalescent-based simulation, introduce the rescaling technique that makes large-scale forward-in-time simulation feasible, and demonstrate the utility of various features of FREGENE, many not previously available.
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