Estimation of 2N(e)s from temporal allele frequency data

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Estimation of 2N(e)s from temporal allele frequency data. / Bollback, Jonathan Paul; York, Thomas L.; Nielsen, Rasmus.

In: Genetics, Vol. 179, 2008, p. 497-502.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Bollback, JP, York, TL & Nielsen, R 2008, 'Estimation of 2N(e)s from temporal allele frequency data', Genetics, vol. 179, pp. 497-502. https://doi.org/10.1534/genetics.107.085019

APA

Bollback, J. P., York, T. L., & Nielsen, R. (2008). Estimation of 2N(e)s from temporal allele frequency data. Genetics, 179, 497-502. https://doi.org/10.1534/genetics.107.085019

Vancouver

Bollback JP, York TL, Nielsen R. Estimation of 2N(e)s from temporal allele frequency data. Genetics. 2008;179:497-502. https://doi.org/10.1534/genetics.107.085019

Author

Bollback, Jonathan Paul ; York, Thomas L. ; Nielsen, Rasmus. / Estimation of 2N(e)s from temporal allele frequency data. In: Genetics. 2008 ; Vol. 179. pp. 497-502.

Bibtex

@article{392f3100e6eb11ddbf70000ea68e967b,
title = "Estimation of 2N(e)s from temporal allele frequency data",
abstract = "We develop a new method for estimating effective population sizes, Ne, and selection coefficients, s, from time-series data of allele frequencies sampled from a single diallelic locus. The method is based on calculating transition probabilities, using a numerical solution of the diffusion process, and assuming independent binomial sampling from this diffusion process at each time point. We apply the method in two example applications. First, we estimate selection coefficients acting on the CCR5-{Delta}32 mutation on the basis of published samples of contemporary and ancient human DNA. We show that the data are compatible with the assumption of s = 0, although moderate amounts of selection acting on this mutation cannot be excluded. In our second example, we estimate the selection coefficient acting on a mutation segregating in an experimental phage population. We show that the selection coefficient acting on this mutation is ~0.43.",
author = "Bollback, {Jonathan Paul} and York, {Thomas L.} and Rasmus Nielsen",
year = "2008",
doi = "10.1534/genetics.107.085019",
language = "English",
volume = "179",
pages = "497--502",
journal = "Genetics",
issn = "1943-2631",
publisher = "The Genetics Society of America (GSA)",

}

RIS

TY - JOUR

T1 - Estimation of 2N(e)s from temporal allele frequency data

AU - Bollback, Jonathan Paul

AU - York, Thomas L.

AU - Nielsen, Rasmus

PY - 2008

Y1 - 2008

N2 - We develop a new method for estimating effective population sizes, Ne, and selection coefficients, s, from time-series data of allele frequencies sampled from a single diallelic locus. The method is based on calculating transition probabilities, using a numerical solution of the diffusion process, and assuming independent binomial sampling from this diffusion process at each time point. We apply the method in two example applications. First, we estimate selection coefficients acting on the CCR5-{Delta}32 mutation on the basis of published samples of contemporary and ancient human DNA. We show that the data are compatible with the assumption of s = 0, although moderate amounts of selection acting on this mutation cannot be excluded. In our second example, we estimate the selection coefficient acting on a mutation segregating in an experimental phage population. We show that the selection coefficient acting on this mutation is ~0.43.

AB - We develop a new method for estimating effective population sizes, Ne, and selection coefficients, s, from time-series data of allele frequencies sampled from a single diallelic locus. The method is based on calculating transition probabilities, using a numerical solution of the diffusion process, and assuming independent binomial sampling from this diffusion process at each time point. We apply the method in two example applications. First, we estimate selection coefficients acting on the CCR5-{Delta}32 mutation on the basis of published samples of contemporary and ancient human DNA. We show that the data are compatible with the assumption of s = 0, although moderate amounts of selection acting on this mutation cannot be excluded. In our second example, we estimate the selection coefficient acting on a mutation segregating in an experimental phage population. We show that the selection coefficient acting on this mutation is ~0.43.

U2 - 10.1534/genetics.107.085019

DO - 10.1534/genetics.107.085019

M3 - Journal article

C2 - 18493066

VL - 179

SP - 497

EP - 502

JO - Genetics

JF - Genetics

SN - 1943-2631

ER -

ID: 9855393