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Article: Powerful regression-based quantitative-trait linkage analysis of general pedigrees

TitlePowerful regression-based quantitative-trait linkage analysis of general pedigrees
Authors
Issue Date2002
PublisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/
Citation
American Journal Of Human Genetics, 2002, v. 71 n. 2, p. 238-253 How to Cite?
AbstractWe present a new method of quantitative-trait linkage analysis that combines the simplicity and robustness of regression-based methods and the generality and greater power of variance-components models. The new method is based on a regression of estimated identity-by-descent (IBD) sharing between relative pairs on the squared sums and squared differences of trait values of the relative pairs. The method is applicable to pedigrees of arbitrary structure and to pedigrees selected on the basis of trait value, provided that population parameters of the trait distribution can be correctly specified. Ambiguous IBD sharing (due to incomplete marker information) can be accommodated in the method by appropriate specification of the variance-covariance matrix of IBD sharing between relative pairs. We have implemented this regression-based method and have performed simulation studies to assess, under a range of conditions, estimation accuracy, type I error rate, and power. For normally distributed traits and in large samples, the method is found to give the correct type I error rate and an unbiased estimate of the proportion of trait variance accounted for by the additive effects of the locus - although, in cases where asymptotic theory is doubtful, significance levels should be checked by simulations. In large sibships, the new method is slightly more powerful than variance-components models. The proposed method provides a practical and powerful tool for the linkage analysis of quantitative traits.
Persistent Identifierhttp://hdl.handle.net/10722/143697
ISSN
2014 Impact Factor: 10.931
2014 SCImago Journal Rankings: 7.223
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorSham, PCen_HK
dc.contributor.authorPurcell, Sen_HK
dc.contributor.authorCherny, SSen_HK
dc.contributor.authorAbecasis, GRen_HK
dc.date.accessioned2011-12-16T08:09:35Z-
dc.date.available2011-12-16T08:09:35Z-
dc.date.issued2002en_HK
dc.identifier.citationAmerican Journal Of Human Genetics, 2002, v. 71 n. 2, p. 238-253en_HK
dc.identifier.issn0002-9297en_HK
dc.identifier.urihttp://hdl.handle.net/10722/143697-
dc.description.abstractWe present a new method of quantitative-trait linkage analysis that combines the simplicity and robustness of regression-based methods and the generality and greater power of variance-components models. The new method is based on a regression of estimated identity-by-descent (IBD) sharing between relative pairs on the squared sums and squared differences of trait values of the relative pairs. The method is applicable to pedigrees of arbitrary structure and to pedigrees selected on the basis of trait value, provided that population parameters of the trait distribution can be correctly specified. Ambiguous IBD sharing (due to incomplete marker information) can be accommodated in the method by appropriate specification of the variance-covariance matrix of IBD sharing between relative pairs. We have implemented this regression-based method and have performed simulation studies to assess, under a range of conditions, estimation accuracy, type I error rate, and power. For normally distributed traits and in large samples, the method is found to give the correct type I error rate and an unbiased estimate of the proportion of trait variance accounted for by the additive effects of the locus - although, in cases where asymptotic theory is doubtful, significance levels should be checked by simulations. In large sibships, the new method is slightly more powerful than variance-components models. The proposed method provides a practical and powerful tool for the linkage analysis of quantitative traits.en_HK
dc.publisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/en_HK
dc.relation.ispartofAmerican Journal of Human Geneticsen_HK
dc.titlePowerful regression-based quantitative-trait linkage analysis of general pedigreesen_HK
dc.typeArticleen_HK
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.emailCherny, SS: cherny@hku.hken_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.identifier.authorityCherny, SS=rp00232en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1086/341560en_HK
dc.identifier.pmid12111667en_HK
dc.identifier.scopuseid_2-s2.0-0036077215en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036077215&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume71en_HK
dc.identifier.issue2en_HK
dc.identifier.spage238en_HK
dc.identifier.epage253en_HK
dc.identifier.isiWOS:000176977700003-
dc.publisher.placeUnited Statesen_HK
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dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.scopusauthoridPurcell, S=7005489464en_HK
dc.identifier.scopusauthoridCherny, SS=7004670001en_HK
dc.identifier.scopusauthoridAbecasis, GR=6604013253en_HK

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