Estimating recombination rates from population genetic data.
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 m...
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| Format: | Journal article |
| Language: | English |
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2001
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| _version_ | 1797094228845658112 |
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| author | Fearnhead, P Donnelly, P |
| author_facet | Fearnhead, P Donnelly, P |
| author_sort | Fearnhead, P |
| collection | OXFORD |
| description | 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. |
| first_indexed | 2024-03-07T04:11:11Z |
| format | Journal article |
| id | oxford-uuid:c7de614a-620e-40ae-a0d1-0a14e0bedbf9 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:11:11Z |
| publishDate | 2001 |
| record_format | dspace |
| spelling | oxford-uuid:c7de614a-620e-40ae-a0d1-0a14e0bedbf92022-03-27T06:48:20ZEstimating recombination rates from population genetic data.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c7de614a-620e-40ae-a0d1-0a14e0bedbf9EnglishSymplectic Elements at Oxford2001Fearnhead, PDonnelly, PWe 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. |
| spellingShingle | Fearnhead, P Donnelly, P Estimating recombination rates from population genetic data. |
| title | Estimating recombination rates from population genetic data. |
| title_full | Estimating recombination rates from population genetic data. |
| title_fullStr | Estimating recombination rates from population genetic data. |
| title_full_unstemmed | Estimating recombination rates from population genetic data. |
| title_short | Estimating recombination rates from population genetic data. |
| title_sort | estimating recombination rates from population genetic data |
| work_keys_str_mv | AT fearnheadp estimatingrecombinationratesfrompopulationgeneticdata AT donnellyp estimatingrecombinationratesfrompopulationgeneticdata |