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Article: Simple algorithms to calculate asymptotic null distributions of robust tests in case-control genetic association studies in R

TitleSimple algorithms to calculate asymptotic null distributions of robust tests in case-control genetic association studies in R
Authors
KeywordsAlgorithm
Asymptotic Distributions
Dependence Of Trend Tests
Genetic Model Selection
Max3
Robust Tests
Issue Date2010
Citation
Journal Of Statistical Software, 2010, v. 33 n. 8, p. 1-24 How to Cite?
AbstractThe case-control study is an important design for testing association between genetic markers and a disease. The Cochran-Armitage trend test (CATT) is one of the most commonly used statistics for the analysis of case-control genetic association studies. The asymptotically optimal CATT can be used when the underlying genetic model (mode of inheritance) is known. However, for most complex diseases, the underlying genetic models are unknown. Thus, tests robust to genetic model misspecification are preferable to the model-dependant CATT. Two robust tests, MAX3 and the genetic model selection (GMS), were recently proposed. Their asymptotic null distributions are often obtained by Monte-Carlo simulations, because they either have not been fully studied or involve multiple integrations. In this article, we study how components of each robust statistic are correlated, and find a linear dependence among the components. Using this new finding, we propose simple algorithms to calculate asymptotic null distributions for MAX3 and GMS, which greatly reduce the computing intensity. Furthermore, we have developed the R package Rassoc implementing the proposed algorithms to calculate the empirical and asymptotic p values for MAX3 and GMS as well as other commonly used tests in case-control association studies. For illustration, Rassoc is applied to the analysis of case-control data of 17 most significant SNPs reported in four genome-wide association studies.
Persistent Identifierhttp://hdl.handle.net/10722/172471
ISSN
2015 Impact Factor: 2.379
2015 SCImago Journal Rankings: 2.970
References

 

DC FieldValueLanguage
dc.contributor.authorZang, Yen_US
dc.contributor.authorFung, WKen_US
dc.contributor.authorZheng, Gen_US
dc.date.accessioned2012-10-30T06:22:42Z-
dc.date.available2012-10-30T06:22:42Z-
dc.date.issued2010en_US
dc.identifier.citationJournal Of Statistical Software, 2010, v. 33 n. 8, p. 1-24en_US
dc.identifier.issn1548-7660en_US
dc.identifier.urihttp://hdl.handle.net/10722/172471-
dc.description.abstractThe case-control study is an important design for testing association between genetic markers and a disease. The Cochran-Armitage trend test (CATT) is one of the most commonly used statistics for the analysis of case-control genetic association studies. The asymptotically optimal CATT can be used when the underlying genetic model (mode of inheritance) is known. However, for most complex diseases, the underlying genetic models are unknown. Thus, tests robust to genetic model misspecification are preferable to the model-dependant CATT. Two robust tests, MAX3 and the genetic model selection (GMS), were recently proposed. Their asymptotic null distributions are often obtained by Monte-Carlo simulations, because they either have not been fully studied or involve multiple integrations. In this article, we study how components of each robust statistic are correlated, and find a linear dependence among the components. Using this new finding, we propose simple algorithms to calculate asymptotic null distributions for MAX3 and GMS, which greatly reduce the computing intensity. Furthermore, we have developed the R package Rassoc implementing the proposed algorithms to calculate the empirical and asymptotic p values for MAX3 and GMS as well as other commonly used tests in case-control association studies. For illustration, Rassoc is applied to the analysis of case-control data of 17 most significant SNPs reported in four genome-wide association studies.en_US
dc.languageengen_US
dc.relation.ispartofJournal of Statistical Softwareen_US
dc.subjectAlgorithmen_US
dc.subjectAsymptotic Distributionsen_US
dc.subjectDependence Of Trend Testsen_US
dc.subjectGenetic Model Selectionen_US
dc.subjectMax3en_US
dc.subjectRobust Testsen_US
dc.titleSimple algorithms to calculate asymptotic null distributions of robust tests in case-control genetic association studies in Ren_US
dc.typeArticleen_US
dc.identifier.emailFung, WK: wingfung@hku.hken_US
dc.identifier.authorityFung, WK=rp00696en_US
dc.description.naturelink_to_OA_fulltexten_US
dc.identifier.scopuseid_2-s2.0-77953172073en_US
dc.identifier.hkuros171325-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77953172073&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume33en_US
dc.identifier.issue8en_US
dc.identifier.spage1en_US
dc.identifier.epage24en_US
dc.identifier.scopusauthoridZang, Y=16053902200en_US
dc.identifier.scopusauthoridFung, WK=13310399400en_US
dc.identifier.scopusauthoridZheng, G=35265434100en_US

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