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Article: Bias and precision in QST estimates: Problems and some solutions

TitleBias and precision in Q<inf>ST</inf> estimates: Problems and some solutions
Authors
Issue Date2005
Citation
Genetics, 2005, v. 171, n. 3, p. 1331-1339 How to Cite?
AbstractComparison of population differentiation in neutral marker genes and in genes coding quantitative traits by means of FST and QST indexes has become commonplace practice. While the properties and estimation of FST have been the subject of much interest, little is known about the precision and possible bias in QST estimates. Using both simulated and real data, we investigated the precision and bias in QST estimates and various methods of estimating the precision. We found that precision of QST estimates for typical data sets (i.e., with <20 populations) was poor. Of the methods for estimating the precision, a simulation method, a parametric bootstrap, and the Bayesian approach returned the most precise estimates of the confidence intervals. Copyright © 2005 by the Genetics Society of America.
Persistent Identifierhttp://hdl.handle.net/10722/292568
ISSN
2023 Impact Factor: 3.3
2023 SCImago Journal Rankings: 1.917
PubMed Central ID
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorO'Hara, R. B.-
dc.contributor.authorMerilä, J.-
dc.date.accessioned2020-11-17T14:56:45Z-
dc.date.available2020-11-17T14:56:45Z-
dc.date.issued2005-
dc.identifier.citationGenetics, 2005, v. 171, n. 3, p. 1331-1339-
dc.identifier.issn0016-6731-
dc.identifier.urihttp://hdl.handle.net/10722/292568-
dc.description.abstractComparison of population differentiation in neutral marker genes and in genes coding quantitative traits by means of FST and QST indexes has become commonplace practice. While the properties and estimation of FST have been the subject of much interest, little is known about the precision and possible bias in QST estimates. Using both simulated and real data, we investigated the precision and bias in QST estimates and various methods of estimating the precision. We found that precision of QST estimates for typical data sets (i.e., with <20 populations) was poor. Of the methods for estimating the precision, a simulation method, a parametric bootstrap, and the Bayesian approach returned the most precise estimates of the confidence intervals. Copyright © 2005 by the Genetics Society of America.-
dc.languageeng-
dc.relation.ispartofGenetics-
dc.titleBias and precision in Q<inf>ST</inf> estimates: Problems and some solutions-
dc.typeArticle-
dc.description.naturelink_to_OA_fulltext-
dc.identifier.doi10.1534/genetics.105.044545-
dc.identifier.pmid16085700-
dc.identifier.pmcidPMC1456852-
dc.identifier.scopuseid_2-s2.0-32544451095-
dc.identifier.volume171-
dc.identifier.issue3-
dc.identifier.spage1331-
dc.identifier.epage1339-
dc.identifier.isiWOS:000233967200039-
dc.identifier.issnl0016-6731-

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