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Article: Application of multi-locus analytical methods to identify interacting loci in case-control studies

TitleApplication of multi-locus analytical methods to identify interacting loci in case-control studies
Authors
KeywordsCase-control study
Epistasis
Logic regression
Logistic regression
MDR
Set association method
Issue Date2007
PublisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/AHG
Citation
Annals Of Human Genetics, 2007, v. 71 n. 5, p. 689-700 How to Cite?
AbstractTo identify interacting loci in genetic epidemiological studies the application of multi-locus methods of analysis is warranted. Several more advanced classification methods have been developed in the past years, including multiple logistic regression, sum statistics, logic regression, and the multifactor dimensionality reduction method. The objective of our study was to apply these four multi-locus methods to simulated case-control datasets that included a variety of underlying statistical two-locus interaction models, in order to compare the methods and evaluate their strengths and weaknesses. The results showed that the ability to identify the interacting loci was generally good for the sum statistic method, the logic regression and MDR. The performance of the logistic regression was more dependent on the underlying model and multiple comparison adjustment procedure. However, identification of the interacting loci in a model with two two-locus interactions of common disease alleles with relatively small effects was impaired in all methods. Several practical and methodological issues that can be considered in the application of these methods, and that may warrant further research, are identified and discussed. © 2007 The Authors Journal compilation © 2007 University College London.
Persistent Identifierhttp://hdl.handle.net/10722/81460
ISSN
2015 Impact Factor: 1.889
2015 SCImago Journal Rankings: 1.191
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorVermeulen, SHHMen_HK
dc.contributor.authorDen Heijer, Men_HK
dc.contributor.authorSham, Pen_HK
dc.contributor.authorKnight, Jen_HK
dc.date.accessioned2010-09-06T08:18:01Z-
dc.date.available2010-09-06T08:18:01Z-
dc.date.issued2007en_HK
dc.identifier.citationAnnals Of Human Genetics, 2007, v. 71 n. 5, p. 689-700en_HK
dc.identifier.issn0003-4800en_HK
dc.identifier.urihttp://hdl.handle.net/10722/81460-
dc.description.abstractTo identify interacting loci in genetic epidemiological studies the application of multi-locus methods of analysis is warranted. Several more advanced classification methods have been developed in the past years, including multiple logistic regression, sum statistics, logic regression, and the multifactor dimensionality reduction method. The objective of our study was to apply these four multi-locus methods to simulated case-control datasets that included a variety of underlying statistical two-locus interaction models, in order to compare the methods and evaluate their strengths and weaknesses. The results showed that the ability to identify the interacting loci was generally good for the sum statistic method, the logic regression and MDR. The performance of the logistic regression was more dependent on the underlying model and multiple comparison adjustment procedure. However, identification of the interacting loci in a model with two two-locus interactions of common disease alleles with relatively small effects was impaired in all methods. Several practical and methodological issues that can be considered in the application of these methods, and that may warrant further research, are identified and discussed. © 2007 The Authors Journal compilation © 2007 University College London.en_HK
dc.languageengen_HK
dc.publisherBlackwell Publishing Ltd. The Journal's web site is located at http://www.blackwellpublishing.com/journals/AHGen_HK
dc.relation.ispartofAnnals of Human Geneticsen_HK
dc.rightsAnnals of Human Genetics. Copyright © Blackwell Publishing Ltd.en_HK
dc.subjectCase-control studyen_HK
dc.subjectEpistasisen_HK
dc.subjectLogic regressionen_HK
dc.subjectLogistic regressionen_HK
dc.subjectMDRen_HK
dc.subjectSet association methoden_HK
dc.titleApplication of multi-locus analytical methods to identify interacting loci in case-control studiesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0003-4800&volume=71&spage=689&epage=700&date=2007&atitle=Application+of+multi-locus+analytical+methods+to+identify+interacting+loci+in+case-control+studiesen_HK
dc.identifier.emailSham, P: pcsham@hku.hken_HK
dc.identifier.authoritySham, P=rp00459en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1111/j.1469-1809.2007.00360.xen_HK
dc.identifier.pmid17425620-
dc.identifier.scopuseid_2-s2.0-34447620856en_HK
dc.identifier.hkuros151797en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34447620856&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume71en_HK
dc.identifier.issue5en_HK
dc.identifier.spage689en_HK
dc.identifier.epage700en_HK
dc.identifier.isiWOS:000248121700013-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridVermeulen, SHHM=12799125300en_HK
dc.identifier.scopusauthoridDen Heijer, M=7003691185en_HK
dc.identifier.scopusauthoridSham, P=34573429300en_HK
dc.identifier.scopusauthoridKnight, J=13002769800en_HK
dc.identifier.citeulike1468537-

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