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Article: Linkage analysis of a common oligogenic disease using selected sib pairs

TitleLinkage analysis of a common oligogenic disease using selected sib pairs
Authors
Keywordsinterval mapping
QTL
sib pairs
Issue Date1995
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841
Citation
Genetic Epidemiology, 1995, v. 12 n. 6, p. 741-746 How to Cite?
AbstractSib pairs drawn from the simulated common oligogenic disease families were selected for extreme quantitative trait scores and analyzed using interval mapping and multipoint methods. Linkage analyses of 112 selected sib pairs, in which one or more members had trait values exceeding the disease threshold, were compared with analyses of the total unselected sib-pair sample (771 pairs). Selected sample regression models yielded comparable significance levels to those obtained from the unselected sample at most loci on the six simulated chromosomes, demonstrating the efficiency of selected sib-pair analysis for quantitative characters. Two of the three disease QTLs were detected in both selected and unselected samples. Interval mapping and multipoint analyses yielded location estimates close to the simulated positions of the QTLs. The combined strategy of using interval mapping and multipoint methods with selected sib pairs appears to provide improved accuracy and sensitivity over more traditional sib-pair methods for detecting quantitative trait loci.
Persistent Identifierhttp://hdl.handle.net/10722/143625
ISSN
2015 Impact Factor: 2.553
2015 SCImago Journal Rankings: 2.101
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCardon, LRen_HK
dc.contributor.authorFulker, DWen_HK
dc.contributor.authorCherny, SSen_HK
dc.date.accessioned2011-12-16T08:08:14Z-
dc.date.available2011-12-16T08:08:14Z-
dc.date.issued1995en_HK
dc.identifier.citationGenetic Epidemiology, 1995, v. 12 n. 6, p. 741-746en_HK
dc.identifier.issn0741-0395en_HK
dc.identifier.urihttp://hdl.handle.net/10722/143625-
dc.description.abstractSib pairs drawn from the simulated common oligogenic disease families were selected for extreme quantitative trait scores and analyzed using interval mapping and multipoint methods. Linkage analyses of 112 selected sib pairs, in which one or more members had trait values exceeding the disease threshold, were compared with analyses of the total unselected sib-pair sample (771 pairs). Selected sample regression models yielded comparable significance levels to those obtained from the unselected sample at most loci on the six simulated chromosomes, demonstrating the efficiency of selected sib-pair analysis for quantitative characters. Two of the three disease QTLs were detected in both selected and unselected samples. Interval mapping and multipoint analyses yielded location estimates close to the simulated positions of the QTLs. The combined strategy of using interval mapping and multipoint methods with selected sib pairs appears to provide improved accuracy and sensitivity over more traditional sib-pair methods for detecting quantitative trait loci.en_HK
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841en_HK
dc.relation.ispartofGenetic Epidemiologyen_HK
dc.subjectinterval mappingen_HK
dc.subjectQTLen_HK
dc.subjectsib pairsen_HK
dc.titleLinkage analysis of a common oligogenic disease using selected sib pairsen_HK
dc.typeArticleen_HK
dc.identifier.emailCherny, SS: cherny@hku.hken_HK
dc.identifier.authorityCherny, SS=rp00232en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1002/gepi.1370120635en_HK
dc.identifier.pmid8788002-
dc.identifier.scopuseid_2-s2.0-0029611015en_HK
dc.identifier.volume12en_HK
dc.identifier.issue6en_HK
dc.identifier.spage741en_HK
dc.identifier.epage746en_HK
dc.identifier.isiWOS:A1995TP13700033-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridCardon, LR=7005082964en_HK
dc.identifier.scopusauthoridFulker, DW=7005792286en_HK
dc.identifier.scopusauthoridCherny, SS=7004670001en_HK

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