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Article: Powerful regression-based quantitative-trait linkage analysis of general pedigrees
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TitlePowerful regression-based quantitative-trait linkage analysis of general pedigrees
 
AuthorsSham, PC1
Purcell, S1
Cherny, SS1
Abecasis, GR1
 
Issue Date2002
 
PublisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/
 
CitationAmerican Journal Of Human Genetics, 2002, v. 71 n. 2, p. 238-253 [How to Cite?]
DOI: http://dx.doi.org/10.1086/341560
 
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.
 
ISSN0002-9297
2012 Impact Factor: 11.202
2012 SCImago Journal Rankings: 6.230
 
DOIhttp://dx.doi.org/10.1086/341560
 
ISI Accession Number IDWOS:000176977700003
 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorSham, PC
 
dc.contributor.authorPurcell, S
 
dc.contributor.authorCherny, SS
 
dc.contributor.authorAbecasis, GR
 
dc.date.accessioned2011-12-16T08:09:35Z
 
dc.date.available2011-12-16T08:09:35Z
 
dc.date.issued2002
 
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.
 
dc.description.natureLink_to_subscribed_fulltext
 
dc.identifier.citationAmerican Journal Of Human Genetics, 2002, v. 71 n. 2, p. 238-253 [How to Cite?]
DOI: http://dx.doi.org/10.1086/341560
 
dc.identifier.doihttp://dx.doi.org/10.1086/341560
 
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dc.identifier.isiWOS:000176977700003
 
dc.identifier.issn0002-9297
2012 Impact Factor: 11.202
2012 SCImago Journal Rankings: 6.230
 
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dc.identifier.pmid12111667
 
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dc.identifier.urihttp://hdl.handle.net/10722/143697
 
dc.identifier.volume71
 
dc.publisherCell Press. The Journal's web site is located at http://www.cell.com/AJHG/
 
dc.publisher.placeUnited States
 
dc.relation.ispartofAmerican Journal of Human Genetics
 
dc.relation.referencesReferences in Scopus
 
dc.titlePowerful regression-based quantitative-trait linkage analysis of general pedigrees
 
dc.typeArticle
 
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Author Affiliations
  1. King's College London