ArticleAnnals of human genetics2011
Tests for compositional epistasis under single interaction-parameter models.
Article in Annals of human genetics, 2011. 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.
- Unraveling Causality: Innovations in Epidemiologic Methods.JMA journal · 2025Article
- How to increase our belief in discovered statistical interactions via large-scale association studies?Human genetics · 2019Review
- Commentary: The formal approach to quantitative causal inference in epidemiology: misguided or misrepresented?International journal of epidemiology · 2016Article
- Genome-Wide Analysis of Gene-Gene and Gene-Environment Interactions Using Closed-Form Wald Tests.Genetic epidemiology · 2015Article
- Deep determinism and the assessment of mechanistic interaction.Biostatistics (Oxford, England) · 2013Article
- Causation and causal inference for genetic effects.Human genetics · 2012Review
- Article
- Article
- Adaptive tests for detecting gene-gene and gene-environment interactions.Human heredity · 2011Article
- Testing gene-gene interactions in the case-parents design.Human heredity · 2011Article
- Statistical analysis of genetic interactions.Genetics research · 2010Review
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Compositional epistasis is said to be present when the effect of a genetic factor at one locus is masked by a variant at another locus. Although such compositional epistasis is not equivalent to the presence of an interaction in a statistical model, non-standard tests can sometimes be used to detect compositional epistasis. In this paper we consider empirical tests for compositional epistasis under models for the joint effect of two genetic factors which place no restrictions on the main effects of each factor but constrain the interactive effects of the two factors so as to be captured by a single parameter in the model. We describe the implications of these tests for cohort, case-control, case-only and family-based study designs and we illustrate the methods using an example of gene-gene interaction already reported in the literature.
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