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Article: Equivalence between Haseman-Elston and variance-components linkage analyses for sib pairs

TitleEquivalence between Haseman-Elston and variance-components linkage analyses for sib pairs
Authors
Issue Date2001
PublisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/
Citation
American Journal Of Human Genetics, 2001, v. 68 n. 6, p. 1527-1532 How to Cite?
AbstractThe Haseman-Elston regression method offers a simpler alternative to variance-components (VC) models, for the linkage analysis of quantitative traits. However, even the "revisited" method, which uses the cross-product - rather than the squared difference - in sib trait values, is, in general, less powerful than VC models. In this report, we clarify the relative efficiencies of existing Haseman-Elston methods and show how a new Haseman-Elston method can be constructed to have power equivalent to that of VC models. This method uses as the dependent variable a linear combination of squared sums and squared differences, in which the weights are determined by the overall trait correlation between sibs in a population. We show how this method can be used for both the selection of maximally informative sib pairs for genotyping and the subsequent analysis of such selected samples.
Persistent Identifierhttp://hdl.handle.net/10722/175840
ISSN
2015 Impact Factor: 10.794
2015 SCImago Journal Rankings: 8.769
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorSham, PCen_US
dc.contributor.authorPurcell, Sen_US
dc.date.accessioned2012-11-26T09:01:43Z-
dc.date.available2012-11-26T09:01:43Z-
dc.date.issued2001en_US
dc.identifier.citationAmerican Journal Of Human Genetics, 2001, v. 68 n. 6, p. 1527-1532en_US
dc.identifier.issn0002-9297en_US
dc.identifier.urihttp://hdl.handle.net/10722/175840-
dc.description.abstractThe Haseman-Elston regression method offers a simpler alternative to variance-components (VC) models, for the linkage analysis of quantitative traits. However, even the "revisited" method, which uses the cross-product - rather than the squared difference - in sib trait values, is, in general, less powerful than VC models. In this report, we clarify the relative efficiencies of existing Haseman-Elston methods and show how a new Haseman-Elston method can be constructed to have power equivalent to that of VC models. This method uses as the dependent variable a linear combination of squared sums and squared differences, in which the weights are determined by the overall trait correlation between sibs in a population. We show how this method can be used for both the selection of maximally informative sib pairs for genotyping and the subsequent analysis of such selected samples.en_US
dc.languageengen_US
dc.publisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/en_US
dc.relation.ispartofAmerican Journal of Human Geneticsen_US
dc.subject.meshChi-Square Distributionen_US
dc.subject.meshChromosome Mapping - Methods - Statistics & Numerical Dataen_US
dc.subject.meshComputer Simulationen_US
dc.subject.meshGenetic Linkage - Geneticsen_US
dc.subject.meshGenotypeen_US
dc.subject.meshHumansen_US
dc.subject.meshMatched-Pair Analysisen_US
dc.subject.meshNuclear Familyen_US
dc.subject.meshQuantitative Trait, Heritableen_US
dc.subject.meshRegression Analysisen_US
dc.titleEquivalence between Haseman-Elston and variance-components linkage analyses for sib pairsen_US
dc.typeArticleen_US
dc.identifier.emailSham, PC: pcsham@hku.hken_US
dc.identifier.authoritySham, PC=rp00459en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1086/320593en_US
dc.identifier.pmid11353401-
dc.identifier.scopuseid_2-s2.0-0034987802en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0034987802&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume68en_US
dc.identifier.issue6en_US
dc.identifier.spage1527en_US
dc.identifier.epage1532en_US
dc.identifier.isiWOS:000169094600025-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridSham, PC=34573429300en_US
dc.identifier.scopusauthoridPurcell, S=7005489464en_US

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