Show simple item record

dc.contributor.authorLawless, Jerald F.
dc.date.accessioned2016-10-24 15:50:56 (GMT)
dc.date.available2016-10-24 15:50:56 (GMT)
dc.date.issued2012
dc.identifier.urihttp://dx.doi.org/10.1002/gepi.21689
dc.identifier.urihttp://hdl.handle.net/10012/11011
dc.descriptionThis is the peer reviewed version of the following article: ``Derkach, A., Lawless, J.F. and Sun, L. (2013). Robust and powerful tests for rare variants using Fisher's method to combine evidence of association from two or more complementary tests. Genetic Epidemiology, 37 (1), 110--121", which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/gepi.21689/full DOI: 10.1002/gepi.21689. This article may be used for non-commercial purposes in accordance with http://olabout.wiley.com/WileyCDA/Section/id-828039.html. Wiley Terms and Conditions for Self-Archiving.en
dc.description.abstractMany association tests have been proposed for rare variants, but the choice of a powerful test is uncertain when there is limited information on the underlying genetic model. Proposed methods use either linear statistics, which are powerful when most variants are causal and have the same direction of effect, or quadratic statistics, which are more powerful in other scenarios. To achieve robustness, it is natural to combine the evidence of association from two or more complementary tests. To this end, we consider the minimum-p and Fisher’s methods of combining P-values from linear and quadratic statistics. Extensive simulation studies show that both methods are robust across models with varying proportions of causal, deleterious, and protective rare variants, allele frequencies, and effect sizes. When the majority (>75%) of the causal effects are in the same direction (deleterious or protective), Fisher’s method consistently outperforms the minimum-p and the individual linear and quadratic tests, as well as the optimal sequence kernel association test, SKAT-O. When the individual test has moderate power, Fisher’s test has improved power for 90% of the 5000 models considered, with >20% relative efficiency gain for 40% of the models. The maximum absolute power loss is 8% for the remaining 10% of the models. An application to the GAW17 quantitative trait Q2 data based on sequence data of the 1000 Genomes Project shows that, compared with linear and quadratic tests, Fisher’s test has comparable power for all 13 functional genes and provides the best power for more than half of them.en
dc.description.sponsorshipNatural Sciences and Engineering Research Council of Canada || (JFL RGPIN 8597)en
dc.language.isoenen
dc.publisherWileyen
dc.relation.ispartofseriesGenetic Epidemiology;37 (1)en
dc.subjectRobust methodsen
dc.subjectFisher’s methoden
dc.subjectRare variantsen
dc.subjectComplex traitsen
dc.subjectNext-generation sequencingen
dc.subject1000 genome projecten
dc.titleRobust and Powerful Tests for Rare Variants Using Fishers Method to Combine Evidence of Association From Two or More Complementary Testsen
dc.title.alternativeRobust and Powerful Tests for Rare Variants Using Fisher’s Method ...en
dc.typeArticleen
dcterms.bibliographicCitationDerkach, Andriy, Jerry F. Lawless, and Lei Sun. "Robust and powerful tests for rare variants using Fisher's method to combine evidence of association from two or more complementary tests." Genetic epidemiology 37.1 (2013): 110-121.en
uws.contributor.affiliation1Faculty of Mathematicsen
uws.contributor.affiliation2Statistics and Actuarial Scienceen
uws.typeOfResourceTexten
uws.peerReviewStatusRevieweden
uws.scholarLevelFacultyen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record


UWSpace

University of Waterloo Library
200 University Avenue West
Waterloo, Ontario, Canada N2L 3G1
519 888 4883

All items in UWSpace are protected by copyright, with all rights reserved.

DSpace software

Service outages