ArticleGenetic epidemiology2009
Restricted parameter space models for testing gene-gene interaction.
Article in Genetic epidemiology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Constrained Score Statistics Identify Genetic Variants Interacting with Multiple Risk Factors in Barrett's Esophagus.American journal of human genetics · 2016Article
- Genome-Wide Analysis of Gene-Gene and Gene-Environment Interactions Using Closed-Form Wald Tests.Genetic epidemiology · 2015Article
- Jackknife-based gene-gene interactiontests for untyped SNPs.BMC genetics · 2015Article
- Article
- Detection for gene-gene co-association via kernel canonical correlation analysis.BMC genetics · 2012Article
- Adaptive tests for detecting gene-gene and gene-environment interactions.Human heredity · 2011Article
- Relative efficiency of trend tests with misspecified genetic models in stratified analyses of case-control or cohort data.Human heredity · 2011Article
- Tests for compositional epistasis under single interaction-parameter models.Annals of human genetics · 2011Article
- Using principal components of genetic variation for robust and powerful detection of gene-gene interactions in case-control and case-only studies.American journal of human genetics · 2010Article
- Statistical tests of genetic association in the presence of gene-gene and gene-environment interactions.Human heredity · 2010Article
- Article
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Authors and funding
2 authors.
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Abstract
There is a growing recognition that interactions (gene-gene and gene-environment) can play an important role in common disease etiology. The development of cost-effective genotyping technologies has made genome-wide association studies the preferred tool for searching for loci affecting disease risk. These studies are characterized by a large number of investigated SNPs, and efficient statistical methods are even more important than in classical association studies that are done with a small number of markers. In this article we propose a novel gene-gene interaction test that is more powerful than classical methods. The increase in power is due to the fact that the proposed method incorporates reasonable constraints in the parameter space. The test for both association and interaction is based on a likelihood ratio statistic that has a x(2) distribution asymptotically. We also discuss the definitions used for "no interaction" and argue that tests for pure interaction are useful in genome-wide studies, especially when using two-stage strategies where the analyses in the second stage are done on pairs of loci for which at least one is associated with the trait.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.