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Article: Regression-based sib pair linkage analysis for binary traits

TitleRegression-based sib pair linkage analysis for binary traits
Authors
Issue Date2003
PublisherS Karger AG. The Journal's web site is located at http://www.karger.com/HHE
Citation
Human Heredity, 2003, v. 55 n. 2-3, p. 125-131 How to Cite?
AbstractThe Haseman-Elston (HE) regression method offers a mathematically and computationally simpler alternative to variance-components (VC) models for the linkage analysis of quantitative traits. However, current versions of HE regression and VC models are not optimised for binary traits. Here, we present a modified HE regression and a liability-threshold VC model for binary-traits. The new HE method is based on the regression of a linear combination of the trait squares and the trait cross-product on the proportion of alleles identical by descent (IBD) at the putative locus, for sibling pairs. We have implemented both the new HE regression-based method and have performed analytic and simulation studies to assess its type 1 error rate and power under a range of conditions. These studies showed that the new HE method is well-behaved under the null hypothesis in large samples, is more powerful than both the original and the revisited HE methods, and is approximately equivalent in power to the liability-threshold VC model. Copyright © 2003 S. Karger AG, Basel.
Persistent Identifierhttp://hdl.handle.net/10722/175893
ISSN
2015 Impact Factor: 1.539
2015 SCImago Journal Rankings: 0.942
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZeegers, MPAen_US
dc.contributor.authorRice, JPen_US
dc.contributor.authorRijsdijk, FVen_US
dc.contributor.authorAbecasis, GRen_US
dc.contributor.authorSham, PCen_US
dc.date.accessioned2012-11-26T09:02:13Z-
dc.date.available2012-11-26T09:02:13Z-
dc.date.issued2003en_US
dc.identifier.citationHuman Heredity, 2003, v. 55 n. 2-3, p. 125-131en_US
dc.identifier.issn0001-5652en_US
dc.identifier.urihttp://hdl.handle.net/10722/175893-
dc.description.abstractThe Haseman-Elston (HE) regression method offers a mathematically and computationally simpler alternative to variance-components (VC) models for the linkage analysis of quantitative traits. However, current versions of HE regression and VC models are not optimised for binary traits. Here, we present a modified HE regression and a liability-threshold VC model for binary-traits. The new HE method is based on the regression of a linear combination of the trait squares and the trait cross-product on the proportion of alleles identical by descent (IBD) at the putative locus, for sibling pairs. We have implemented both the new HE regression-based method and have performed analytic and simulation studies to assess its type 1 error rate and power under a range of conditions. These studies showed that the new HE method is well-behaved under the null hypothesis in large samples, is more powerful than both the original and the revisited HE methods, and is approximately equivalent in power to the liability-threshold VC model. Copyright © 2003 S. Karger AG, Basel.en_US
dc.languageengen_US
dc.publisherS Karger AG. The Journal's web site is located at http://www.karger.com/HHEen_US
dc.relation.ispartofHuman Heredityen_US
dc.subject.meshData Interpretation, Statisticalen_US
dc.subject.meshGenetic Linkageen_US
dc.subject.meshHumansen_US
dc.subject.meshRegression Analysisen_US
dc.subject.meshSiblingsen_US
dc.titleRegression-based sib pair linkage analysis for binary traitsen_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.doi10.1159/000072317en_US
dc.identifier.pmid12931051-
dc.identifier.scopuseid_2-s2.0-0042886971en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0042886971&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume55en_US
dc.identifier.issue2-3en_US
dc.identifier.spage125en_US
dc.identifier.epage131en_US
dc.identifier.isiWOS:000185279100007-
dc.publisher.placeSwitzerlanden_US
dc.identifier.scopusauthoridZeegers, MPA=7003691618en_US
dc.identifier.scopusauthoridRice, JP=35355165300en_US
dc.identifier.scopusauthoridRijsdijk, FV=6701830835en_US
dc.identifier.scopusauthoridAbecasis, GR=6604013253en_US
dc.identifier.scopusauthoridSham, PC=34573429300en_US

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