File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Haplotype Association Analysis of Discrete and Continuous Traits Using Mixture of Regression Models

TitleHaplotype Association Analysis of Discrete and Continuous Traits Using Mixture of Regression Models
Authors
Issue Date2004
PublisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0001-8244
Citation
Behavior Genetics, 2004, v. 34 n. 2, p. 207-214 How to Cite?
AbstractWe present a regression-based method of haplotype association analysis for quantitative and dichotomous traits in samples consisting of unrelated individuals. The method takes account of uncertain phase by initially estimating haplotype frequencies and obtaining the posterior probabilities of all possible haplotype combinations in each individual, then using these as weights in a finite mixture of regression models. Using this method, different combinations of marker loci can be modeled, to find a parsimonious set of marker loci that are most predictive and therefore most likely to be closely associated with the a quantitative trait locus. The method has the additional advantage of being able to use individuals with some missing genotype data, by considering all possible genotypes at the missing markers. We have implemented this method using the SNPHAP and Mx programs and illustrated its use on published data on idiopathic generalized epilepsy.
Persistent Identifierhttp://hdl.handle.net/10722/175908
ISSN
2015 Impact Factor: 3.268
2015 SCImago Journal Rankings: 1.457
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorSham, PCen_US
dc.contributor.authorRijsdijk, FVen_US
dc.contributor.authorKnight, Jen_US
dc.contributor.authorMakoff, Aen_US
dc.contributor.authorNorth, Ben_US
dc.contributor.authorCurtis, Den_US
dc.date.accessioned2012-11-26T09:02:22Z-
dc.date.available2012-11-26T09:02:22Z-
dc.date.issued2004en_US
dc.identifier.citationBehavior Genetics, 2004, v. 34 n. 2, p. 207-214en_US
dc.identifier.issn0001-8244en_US
dc.identifier.urihttp://hdl.handle.net/10722/175908-
dc.description.abstractWe present a regression-based method of haplotype association analysis for quantitative and dichotomous traits in samples consisting of unrelated individuals. The method takes account of uncertain phase by initially estimating haplotype frequencies and obtaining the posterior probabilities of all possible haplotype combinations in each individual, then using these as weights in a finite mixture of regression models. Using this method, different combinations of marker loci can be modeled, to find a parsimonious set of marker loci that are most predictive and therefore most likely to be closely associated with the a quantitative trait locus. The method has the additional advantage of being able to use individuals with some missing genotype data, by considering all possible genotypes at the missing markers. We have implemented this method using the SNPHAP and Mx programs and illustrated its use on published data on idiopathic generalized epilepsy.en_US
dc.languageengen_US
dc.publisherSpringer New York LLC. The Journal's web site is located at http://springerlink.metapress.com/openurl.asp?genre=journal&issn=0001-8244en_US
dc.relation.ispartofBehavior Geneticsen_US
dc.subject.meshChromosome Mapping - Statistics & Numerical Dataen_US
dc.subject.meshEpilepsy, Generalized - Geneticsen_US
dc.subject.meshGene Frequency - Geneticsen_US
dc.subject.meshGenetic Markers - Geneticsen_US
dc.subject.meshGenetics, Populationen_US
dc.subject.meshGenotypeen_US
dc.subject.meshHaplotypes - Geneticsen_US
dc.subject.meshHumansen_US
dc.subject.meshLogistic Modelsen_US
dc.subject.meshMathematical Computingen_US
dc.subject.meshModels, Geneticen_US
dc.subject.meshModels, Statisticalen_US
dc.subject.meshPhenotypeen_US
dc.subject.meshProbabilityen_US
dc.subject.meshQuantitative Trait Loci - Geneticsen_US
dc.subject.meshSoftwareen_US
dc.titleHaplotype Association Analysis of Discrete and Continuous Traits Using Mixture of Regression Modelsen_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.doi10.1023/B:BEGE.0000013734.39266.a3en_US
dc.identifier.pmid14755185-
dc.identifier.scopuseid_2-s2.0-1442332571en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-1442332571&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume34en_US
dc.identifier.issue2en_US
dc.identifier.spage207en_US
dc.identifier.epage214en_US
dc.identifier.isiWOS:000189303800010-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridSham, PC=34573429300en_US
dc.identifier.scopusauthoridRijsdijk, FV=6701830835en_US
dc.identifier.scopusauthoridKnight, J=13002769800en_US
dc.identifier.scopusauthoridMakoff, A=7006063526en_US
dc.identifier.scopusauthoridNorth, B=7005058731en_US
dc.identifier.scopusauthoridCurtis, D=14633020700en_US
dc.identifier.citeulike5422923-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats