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Article: Robust tests for matched case-control genetic association studies

TitleRobust tests for matched case-control genetic association studies
Authors
Issue Date2010
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenet/
Citation
Bmc Genetics, 2010, v. 11 How to Cite?
AbstractBackground: The Cochran-Armitage trend test (CATT) is powerful in detecting association between a susceptible marker and a disease. This test, however, may suffer from a substantial loss of power when the underlying genetic model is unknown and incorrectly specified. Thus, it is useful to derive tests obtaining the plausible power against all common genetic models. For this purpose, the genetic model selection (GMS) and genetic model exclusion (GME) methods were proposed recently. Simulation results showed that GMS and GME can obtain the plausible power against three common genetic models while the overall type I error is well controlled.Results: Although GMS and GME are powerful statistically, they could be seriously affected by known confounding factors such as gender, age and race. Therefore, in this paper, via comparing the difference of Hardy-Weinberg disequilibrium coefficients between the cases and the controls within each sub-population, we propose the stratified genetic model selection (SGMS) and exclusion (SGME) methods which could eliminate the effect of confounding factors by adopting a matching framework. Our goal in this paper is to investigate the robustness of the proposed statistics and compare them with other commonly used efficiency robust tests such as MAX3 and χ2 with 2 degrees of freedom (df) test in matched case-control association designs through simulation studies.Conclusion: Simulation results showed that if the mean genetic effect of the heterozygous genotype is between those of the two homozygous genotypes, then the proposed tests and MAX3 are preferred. Otherwise, χ2 with 2 df test may be used. To illustrate the robust procedures, the proposed tests are applied to a real matched pair case-control etiologic study of sarcoidosis. © 2010 Zang and Fung; licensee BioMed Central Ltd.
Persistent Identifierhttp://hdl.handle.net/10722/137543
ISSN
2015 Impact Factor: 2.152
2015 SCImago Journal Rankings: 1.185
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
China Natural Science Foundation10701067
HKU
Funding Information:

The research of Y. Zang was partially supported by the China Natural Science Foundation grant 10701067 and the research of W. K. Fung was partially supported by the HKU Research Output Prize Funding.

References

 

DC FieldValueLanguage
dc.contributor.authorZang, Yen_HK
dc.contributor.authorFung, WKen_HK
dc.date.accessioned2011-08-26T14:27:40Z-
dc.date.available2011-08-26T14:27:40Z-
dc.date.issued2010en_HK
dc.identifier.citationBmc Genetics, 2010, v. 11en_HK
dc.identifier.issn1471-2156en_HK
dc.identifier.urihttp://hdl.handle.net/10722/137543-
dc.description.abstractBackground: The Cochran-Armitage trend test (CATT) is powerful in detecting association between a susceptible marker and a disease. This test, however, may suffer from a substantial loss of power when the underlying genetic model is unknown and incorrectly specified. Thus, it is useful to derive tests obtaining the plausible power against all common genetic models. For this purpose, the genetic model selection (GMS) and genetic model exclusion (GME) methods were proposed recently. Simulation results showed that GMS and GME can obtain the plausible power against three common genetic models while the overall type I error is well controlled.Results: Although GMS and GME are powerful statistically, they could be seriously affected by known confounding factors such as gender, age and race. Therefore, in this paper, via comparing the difference of Hardy-Weinberg disequilibrium coefficients between the cases and the controls within each sub-population, we propose the stratified genetic model selection (SGMS) and exclusion (SGME) methods which could eliminate the effect of confounding factors by adopting a matching framework. Our goal in this paper is to investigate the robustness of the proposed statistics and compare them with other commonly used efficiency robust tests such as MAX3 and χ2 with 2 degrees of freedom (df) test in matched case-control association designs through simulation studies.Conclusion: Simulation results showed that if the mean genetic effect of the heterozygous genotype is between those of the two homozygous genotypes, then the proposed tests and MAX3 are preferred. Otherwise, χ2 with 2 df test may be used. To illustrate the robust procedures, the proposed tests are applied to a real matched pair case-control etiologic study of sarcoidosis. © 2010 Zang and Fung; licensee BioMed Central Ltd.en_HK
dc.languageengen_US
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcgenet/en_HK
dc.relation.ispartofBMC Geneticsen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong Licenseen_US
dc.subject.meshCase-Control Studies-
dc.subject.meshGenetic Association Studies-
dc.subject.meshImmunoglobulins - genetics-
dc.subject.meshModels, Genetic-
dc.subject.meshPolymorphism, Genetic-
dc.titleRobust tests for matched case-control genetic association studiesen_HK
dc.typeArticleen_HK
dc.identifier.emailFung, WK: wingfung@hku.hken_HK
dc.identifier.authorityFung, WK=rp00696en_HK
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1186/1471-2156-11-91en_HK
dc.identifier.pmid20937159-
dc.identifier.pmcidPMC2964553-
dc.identifier.scopuseid_2-s2.0-77957737930en_HK
dc.identifier.hkuros189429en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77957737930&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume11en_HK
dc.identifier.isiWOS:000283495600001-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridZang, Y=16053902200en_HK
dc.identifier.scopusauthoridFung, WK=13310399400en_HK
dc.identifier.citeulike8025952-

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