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Article: Robust tests for gene–environment interaction in case-control and case-only designs
Title | Robust tests for gene–environment interaction in case-control and case-only designs |
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Authors | |
Keywords | Case-control design Case-only design Genetic modelgene–environment interaction Robust test |
Issue Date | 2019 |
Publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csda |
Citation | Computational Statistics & Data Analysis, 2019, v. 129, p. 79-92 How to Cite? |
Abstract | The case-control and case-only designs are commonly used to detect the gene-environment (G-E) interaction. In principle, the tests based on these two designs require a pre-specified genetic model to achieve an expected power of detecting the G-E interaction. Unfortunately, for most complex diseases the underlying genetic models are unknown. It is well known that mis-specification of the genetic model can result in a substantial loss of power in the detection of the main genetic effect. However, limited effort has been dedicated to the study of G-E interaction. This issue has been investigated in this article with a conclusion that the genetic model mis-specification can not only undermine the power of detecting G-E interaction in both case-control and case-only designs but also distort the type I error rate in case-control design. To tackle this problem, a class of robust tests, namely MAX3, have been proposed for both the case-control and case-only designs. The proposed tests can well control the type I error rate and yield satisfactory power even when the genetic model is mis-specified. The asymptotic distribution and the p-value formula for MAX3 have also been derived. Comprehensive simulation studies and a real data application on the genome-wide association study (GWAS) have been conducted using these analytical tools and the results demonstrate desirable operating characteristics of the proposed robust tests. (C) 2018 Elsevier B.V. All rights reserved. |
Persistent Identifier | http://hdl.handle.net/10722/272974 |
ISSN | 2023 Impact Factor: 1.5 2023 SCImago Journal Rankings: 1.008 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zang, Y | - |
dc.contributor.author | Fung, TWK | - |
dc.contributor.author | Cao, S | - |
dc.contributor.author | Ng, HK | - |
dc.contributor.author | Zhang, C | - |
dc.date.accessioned | 2019-08-06T09:20:12Z | - |
dc.date.available | 2019-08-06T09:20:12Z | - |
dc.date.issued | 2019 | - |
dc.identifier.citation | Computational Statistics & Data Analysis, 2019, v. 129, p. 79-92 | - |
dc.identifier.issn | 0167-9473 | - |
dc.identifier.uri | http://hdl.handle.net/10722/272974 | - |
dc.description.abstract | The case-control and case-only designs are commonly used to detect the gene-environment (G-E) interaction. In principle, the tests based on these two designs require a pre-specified genetic model to achieve an expected power of detecting the G-E interaction. Unfortunately, for most complex diseases the underlying genetic models are unknown. It is well known that mis-specification of the genetic model can result in a substantial loss of power in the detection of the main genetic effect. However, limited effort has been dedicated to the study of G-E interaction. This issue has been investigated in this article with a conclusion that the genetic model mis-specification can not only undermine the power of detecting G-E interaction in both case-control and case-only designs but also distort the type I error rate in case-control design. To tackle this problem, a class of robust tests, namely MAX3, have been proposed for both the case-control and case-only designs. The proposed tests can well control the type I error rate and yield satisfactory power even when the genetic model is mis-specified. The asymptotic distribution and the p-value formula for MAX3 have also been derived. Comprehensive simulation studies and a real data application on the genome-wide association study (GWAS) have been conducted using these analytical tools and the results demonstrate desirable operating characteristics of the proposed robust tests. (C) 2018 Elsevier B.V. All rights reserved. | - |
dc.language | eng | - |
dc.publisher | Elsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csda | - |
dc.relation.ispartof | Computational Statistics & Data Analysis | - |
dc.subject | Case-control design | - |
dc.subject | Case-only design | - |
dc.subject | Genetic modelgene–environment interaction | - |
dc.subject | Robust test | - |
dc.title | Robust tests for gene–environment interaction in case-control and case-only designs | - |
dc.type | Article | - |
dc.identifier.email | Fung, TWK: wingfung@hkucc.hku.hk | - |
dc.identifier.authority | Fung, TWK=rp00696 | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.csda.2018.08.014 | - |
dc.identifier.scopus | eid_2-s2.0-85053005960 | - |
dc.identifier.hkuros | 300030 | - |
dc.identifier.volume | 129 | - |
dc.identifier.spage | 79 | - |
dc.identifier.epage | 92 | - |
dc.identifier.isi | WOS:000447571400006 | - |
dc.publisher.place | Netherlands | - |
dc.identifier.issnl | 0167-9473 | - |