Estimating recombination rates from population genetic data.

School Of Mathematical Sciences

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Estimating recombination rates from population genetic data. / Fearnhead, Paul; Donnelly, Peter.
In: Genetics, Vol. 159, No. 3, 11.2001, p. 1299-1318.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Author

Fearnhead, Paul ; Donnelly, Peter. / Estimating recombination rates from population genetic data. In: Genetics. 2001 ; Vol. 159, No. 3. pp. 1299-1318.

Bibtex

@article{1438f67c02e144cdacaba7937058a69a,

title = "Estimating recombination rates from population genetic data.",

abstract = "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.",

author = "Paul Fearnhead and Peter Donnelly",

note = "RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research",

year = "2001",

month = nov,

language = "English",

volume = "159",

pages = "1299--1318",

journal = "Genetics",

issn = "0016-6731",

publisher = "Genetics Society of America",

number = "3",

}

RIS

TY - JOUR

T1 - Estimating recombination rates from population genetic data.

AU - Fearnhead, Paul

AU - Donnelly, Peter

N1 - RAE_import_type : Journal article RAE_uoa_type : Statistics and Operational Research

PY - 2001/11

Y1 - 2001/11

N2 - 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.

AB - 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.

M3 - Journal article

VL - 159

SP - 1299

EP - 1318

JO - Genetics

JF - Genetics

SN - 0016-6731

IS - 3

ER -

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