Human Population Biology Research Unit, Department of Anatomy and Anthropology, Tel Aviv University, Tel Aviv, Israel
Korostishevsky Michael, e-mail: korost@post.tau.ac.il.
We propose a statistical method of bivariate genetic analysis, designed to evaluate contribution of the DNA polymorphisms such as SNP and familial effects (additive genetic, common environment) to variation of two interrelated traits without predefined distribution (i.e. could be quantitative and/or qualitative phenotypes). Our approach is an alternative of the liability-threshold concept (Falconer, 1965), and it is based on the discrete models of genetic and familial effects. In order to take into account additive effect of the other genes on the traits’, we introduce three independent binary factors ZX, ZY, and ZXY. In our model they represent genetic factors affecting variation of each trait separately (ZX and ZY) and both traits simultaneously (ZXY), pleiotropic effect. Gene-independent effects, caused by random or common familial effects on the phenotype variation are also taken into account in the model. The model application to analysis muscular mass, metabolomics and genotyping data in a large sample of middle-aged UK female twins is exemplified.
muscular mass, metabolomics, GWAS, bivariate analysis, additive genetic and environmental factors
Цит.: Korostishevsky Michael, Malkin Ida, Livshits Gregory NOVEL MODEL OF BIVARIATE ANALYSIS FOR HUMAN GENETIC STUDY. APPLICATION TO MUSCULAR MASS AND METABOLITE LEVEL VARIATION // Вестник Московского университета. Серия XXIII. Антропология, 2014; 3/2014; с. 119-119
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