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Article: Robust association tests under different genetic models, allowing for binary or quantitative traits and covariates

TitleRobust association tests under different genetic models, allowing for binary or quantitative traits and covariates
Authors
KeywordsAssociation
Genetic models
Genome-wide association studies
Issue Date2011
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, 2011, v. 41 n. 5, p. 768-775 How to Cite?
AbstractThe association of genetic variants with outcomes is usually assessed under an additive model, for example by the trend test. However, misspecification of the genetic model will lead to a reduction in power. More robust tests for association might therefore be preferred. A useful approach is to consider the maximum of the three test statistics under additive, dominant and recessive models (MAX3). The p-value however has to be adjusted to maintain the type I error rate. Previous studies and software on robust association tests have focused on binary traits without covariates. In this study we developed an analytic approach to robust association tests using MAX3, allowing for quantitative or binary traits as well as covariates. The p-values from our theoretical calculations match very well with those from a bootstrap resampling procedure. The methodology is implemented in the R package RobustSNP which is able to handle both small-scale studies and GWAS. The package and documentation are available at http://sites.google.com/ site/honcheongso/software/robustsnp. © The Author(s) 2011.
Persistent Identifierhttp://hdl.handle.net/10722/144964
ISSN
2015 Impact Factor: 3.268
2015 SCImago Journal Rankings: 1.457
PubMed Central ID
ISI Accession Number ID
Funding AgencyGrant Number
Hong Kong Research Grants CouncilHKU 766906M
HKU 774707M
University of Hong Kong Strategic Research Theme of Genomics
Croucher Foundation
Funding Information:

The work was supported by the Hong Kong Research Grants Council General Research Fund grants HKU 766906M and HKU 774707M and the University of Hong Kong Strategic Research Theme of Genomics. Hon-Cheong So was supported by a Croucher Foundation Scholarship.

References
Grants

 

DC FieldValueLanguage
dc.contributor.authorSo, HCen_HK
dc.contributor.authorSham, PCen_HK
dc.date.accessioned2012-02-21T05:42:37Z-
dc.date.available2012-02-21T05:42:37Z-
dc.date.issued2011en_HK
dc.identifier.citationBehavior Genetics, 2011, v. 41 n. 5, p. 768-775en_HK
dc.identifier.issn0001-8244en_HK
dc.identifier.urihttp://hdl.handle.net/10722/144964-
dc.description.abstractThe association of genetic variants with outcomes is usually assessed under an additive model, for example by the trend test. However, misspecification of the genetic model will lead to a reduction in power. More robust tests for association might therefore be preferred. A useful approach is to consider the maximum of the three test statistics under additive, dominant and recessive models (MAX3). The p-value however has to be adjusted to maintain the type I error rate. Previous studies and software on robust association tests have focused on binary traits without covariates. In this study we developed an analytic approach to robust association tests using MAX3, allowing for quantitative or binary traits as well as covariates. The p-values from our theoretical calculations match very well with those from a bootstrap resampling procedure. The methodology is implemented in the R package RobustSNP which is able to handle both small-scale studies and GWAS. The package and documentation are available at http://sites.google.com/ site/honcheongso/software/robustsnp. © The Author(s) 2011.en_HK
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_HK
dc.relation.ispartofBehavior Geneticsen_HK
dc.rightsThe Author(s)en_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong Licenseen_US
dc.subjectAssociationen_HK
dc.subjectGenetic modelsen_HK
dc.subjectGenome-wide association studiesen_HK
dc.subject.meshComputational Biology - methods-
dc.subject.meshGenetic Variation-
dc.subject.meshGenome-Wide Association Study - methods-
dc.subject.meshModels, Genetic-
dc.subject.meshPolymorphism, Single Nucleotide-
dc.titleRobust association tests under different genetic models, allowing for binary or quantitative traits and covariatesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4551/resserv?sid=springerlink&genre=article&atitle=Robust Association Tests Under Different Genetic Models, Allowing for Binary or Quantitative Traits and Covariates&title=Behavior Genetics&issn=00018244&date=2011-09-01&volume=41&issue=5& spage=768&authors=Hon-Cheong So, Pak C. Shamen_US
dc.identifier.emailSham, PC: pcsham@hku.hken_HK
dc.identifier.authoritySham, PC=rp00459en_HK
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1007/s10519-011-9450-9en_HK
dc.identifier.pmid21305351-
dc.identifier.pmcidPMC3162964-
dc.identifier.scopuseid_2-s2.0-80054763270en_HK
dc.identifier.hkuros189864-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80054763270&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume41en_HK
dc.identifier.issue5en_HK
dc.identifier.spage768en_HK
dc.identifier.epage775en_HK
dc.identifier.eissn1573-3297en_US
dc.identifier.isiWOS:000294297200015-
dc.publisher.placeUnited Statesen_HK
dc.description.otherSpringer Open Choice, 21 Feb 2012en_US
dc.relation.projectGenome-wide association study of schizophrenia-
dc.identifier.scopusauthoridSo, HC=37031934700en_HK
dc.identifier.scopusauthoridSham, PC=34573429300en_HK
dc.identifier.citeulike8832775-

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