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Article: SPS: a simulation tool for calculating power of set-based genetic association tests

TitleSPS: a simulation tool for calculating power of set-based genetic association tests
Authors
KeywordsComplex disease
Meta-analysis
Power
Set-based association test
Simulation
Issue Date2015
PublisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841
Citation
Genetic Epidemiology, 2015, v. 39 n. 5, p. 395-397 How to Cite?
AbstractSet-based association tests, combining a set of single-nucleotide polymorphisms into a unified test, have become important approaches to identify weak-effect or low-frequency risk loci of complex diseases. However, there is no comprehensive and user-friendly tool to estimate power of set-based tests for study design. We developed a simulation tool to estimate statistical power of multiple representative set-based tests (SPS). SPS has a graphic interface to facilitate parameter settings and result visualization. Advanced functions include loading real genotypes to define genetic architecture, set-based meta-analysis for risk loci with or without heterogeneity, and parallel simulations. In proof-of-principle examples, SPS took no more than 3 sec on average to estimate the power in a conventional setting. The SPS has been integrated into a user-friendly software tool (KGG) as an independent functional module and it is freely available at http://statgenpro.psychiatry.hku.hk/limx/kgg/. © 2015 WILEY PERIODICALS, INC.
DescriptionBrief Report
Persistent Identifierhttp://hdl.handle.net/10722/210226
ISSN
2015 Impact Factor: 2.553
2015 SCImago Journal Rankings: 2.101
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLi, J-
dc.contributor.authorSham, PC-
dc.contributor.authorSong, Y-
dc.contributor.authorLi, M-
dc.date.accessioned2015-05-29T01:48:40Z-
dc.date.available2015-05-29T01:48:40Z-
dc.date.issued2015-
dc.identifier.citationGenetic Epidemiology, 2015, v. 39 n. 5, p. 395-397-
dc.identifier.issn0741-0395-
dc.identifier.urihttp://hdl.handle.net/10722/210226-
dc.descriptionBrief Report-
dc.description.abstractSet-based association tests, combining a set of single-nucleotide polymorphisms into a unified test, have become important approaches to identify weak-effect or low-frequency risk loci of complex diseases. However, there is no comprehensive and user-friendly tool to estimate power of set-based tests for study design. We developed a simulation tool to estimate statistical power of multiple representative set-based tests (SPS). SPS has a graphic interface to facilitate parameter settings and result visualization. Advanced functions include loading real genotypes to define genetic architecture, set-based meta-analysis for risk loci with or without heterogeneity, and parallel simulations. In proof-of-principle examples, SPS took no more than 3 sec on average to estimate the power in a conventional setting. The SPS has been integrated into a user-friendly software tool (KGG) as an independent functional module and it is freely available at http://statgenpro.psychiatry.hku.hk/limx/kgg/. © 2015 WILEY PERIODICALS, INC.-
dc.languageeng-
dc.publisherJohn Wiley & Sons, Inc. The Journal's web site is located at http://www3.interscience.wiley.com/cgi-bin/jhome/35841-
dc.relation.ispartofGenetic Epidemiology-
dc.rightsGenetic Epidemiology. Copyright © John Wiley & Sons, Inc.-
dc.subjectComplex disease-
dc.subjectMeta-analysis-
dc.subjectPower-
dc.subjectSet-based association test-
dc.subjectSimulation-
dc.titleSPS: a simulation tool for calculating power of set-based genetic association tests-
dc.typeArticle-
dc.identifier.emailSham, PC: pcsham@hku.hk-
dc.identifier.emailSong, Y: songy@hku.hk-
dc.identifier.emailLi, M: mxli@hku.hk-
dc.identifier.authoritySham, PC=rp00459-
dc.identifier.authoritySong, Y=rp00488-
dc.identifier.authorityLi, M=rp01722-
dc.identifier.doi10.1002/gepi.21898-
dc.identifier.pmid25995121-
dc.identifier.scopuseid_2-s2.0-84934441755-
dc.identifier.hkuros246407-
dc.identifier.isiWOS:000356363800008-
dc.publisher.placeUnited States-

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