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Originally published as Genetics Published Articles Ahead of Print on June 11, 2007.
Genetics, Vol. 176, 2335-2342, August 2007, Copyright © 2007
doi:10.1534/genetics.106.063560
Incorporating Experimental Design and Error Into Coalescent/Mutation Models of Population History
Bjarne Knudsen1 and Michael M. Miyamoto
Department of Zoology, University of Florida, Gainesville, Florida 32611-8525
1 Corresponding author: CLC bio A/S, Gustav Wieds Vej 10 8000, Århus C, Denmark.
E-mail: bknudsen{at}clcbio.com
Coalescent theory provides a powerful framework for estimating the evolutionary, demographic, and genetic parameters of a population from a small sample of individuals. Current coalescent models have largely focused on population genetic factors (e.g., mutation, population growth, and migration) rather than on the effects of experimental design and error. This study develops a new coalescent/mutation model that accounts for unobserved polymorphisms due to missing data, sequence errors, and multiple reads for diploid individuals. The importance of accommodating these effects of experimental design and error is illustrated with evolutionary simulations and a real data set from a population of the California sea hare. In particular, a failure to account for sequence errors can lead to overestimated mutation rates, inflated coalescent times, and inappropriate conclusions about the population. This current model can now serve as a starting point for the development of newer models with additional experimental and population genetic factors. It is currently implemented as a maximum-likelihood method, but this model may also serve as the basis for the development of Bayesian approaches that incorporate experimental design and error.
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