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Estimating recombination rates from population genetic data.

Research output: Contribution to journalJournal article


<mark>Journal publication date</mark>11/2001
Number of pages20
<mark>Original language</mark>English


We introduce a new method for estimating recombination rates from population genetic data. The method uses a computationally intensive statistical procedure (importance sampling) to calculate the likelihood under a coalescent-based model. Detailed comparisons of the new algorithm with two existing methods (the importance sampling method of Griffiths and Marjoram and the MCMC method of Kuhner and colleagues) show it to be substantially more efficient. (The improvement over the existing importance sampling scheme is typically by four orders of magnitude.) The existing approaches not infrequently led to misleading results on the problems we investigated. We also performed a simulation study to look at the properties of the maximum-likelihood estimator of the recombination rate and its robustness to misspecification of the demographic model.

Bibliographic note

RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research