ArticleAmerican journal of human genetics2003
Two-locus heterogeneity cannot be distinguished from two-locus epistasis on the basis of affected-sib-pair data.
Article in American journal of human genetics, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- The PPLD has advantages over conventional regression methods in application to moderately sized genome-wide association studies.PloS one · 2021Article
- Epi2Loc: an R package to investigate two-locus epistatic models.Twin research and human genetics : the official journal of the International Society for Twin Studies · 2014Article
- Causal models for investigating complex disease: I. A primer.Human heredity · 2011Article
- KELVIN: a software package for rigorous measurement of statistical evidence in human genetics.Human heredity · 2011Article
- Causal models for investigating complex genetic disease: II. what causal models can tell us about penetrance for additive, heterogeneity, and multiplicative two-locus models.Human heredity · 2011Article
- Increasing genotype-phenotype model determinism: application to bivariate reading/language traits and epistatic interactions in language-impaired families.Human heredity · 2010Article
- Comparison of affected sibling-pair linkage methods to identify gene x gene interaction in GAW15 simulated data.BMC proceedings · 2007Article
- Exploiting gene x gene interaction in linkage analysis.BMC proceedings · 2007Article
- Article
- Mathematical assumptions versus biological reality: myths in affected sib pair linkage analysis.American journal of human genetics · 2005Article
- Affected-sib-pair data can be used to distinguish two-locus heterogeneity from two-locus epistasis.American journal of human genetics · 2003Article
- Reports of the death of the epistasis model are greatly exaggerated.American journal of human genetics · 2003Article
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Abstract
The observation of multiple linkage signals in the course of conducting genome screens for complex disorders raises the question of whether distinct genes represent independent causes of disease (heterogeneity) or whether they interact to produce the phenotype of interest (epistasis); and there has been a corresponding interest in statistical methods for detecting and/or exploiting the distinction between these two possibilities. At the same time, researchers are increasingly relying on affected-sib-pair (ASP) data. Here, we demonstrate an apparently unrecognized fact about two-locus (2L) models and ASP data, namely, 2L heterogeneity and 2L epistasis cannot, in general, be distinguished from one another on the basis of ASP marker data, as a matter of mathematical principle and therefore regardless of sample size. By the same token, correlations across ASPs in single-locus LOD scores or other measures also cannot be used to distinguish 2L heterogeneity from 2L epistasis. This raises questions about the measurement of gene-gene interactions in terms of patterns of correlation in marker data. Portions of our results carry over to larger pedigree structures as well, as long as only affected individuals are included in analyses; the extent to which our overall findings apply to general pedigrees (including unaffected individuals) remains to be investigated.
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