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Dissecting the correlation structure of a bivariate phenotype: common genes or shared environment?
Article in English | IMSEAR | ID: sea-114442
ABSTRACT
High correlations between two quantitative traits may be either due to common genetic factors or common environmental factors or a combination of both. In this study, we develop statistical methods to extract the genetic contribution to the total correlation between the components of a bivariate phenotype. Using data on bivariate phenotypes and marker genotypes for sib-pairs, we propose a test for linkage between a common QTL and a marker locus based on the conditional cross-sib trait correlations (trait 1 of sib 1 - trait 2 of sib 2 and conversely) given the identity-by-descent (i.b.d.) sharing at the marker locus. We use Monte-Carlo simulations to evaluate the performance of the proposed test under different trait parameters and quantitative trait distributions. An application of the method is illustrated using data on two alcohol-related phenotypes from a project on the collaborative study on the genetics of alcoholism.
Subject(s)
Full text: Available Index: IMSEAR (South-East Asia) Main subject: Phenotype / Humans / Monte Carlo Method / Chromosome Mapping / Quantitative Trait Loci / Alcoholism / Environment / Models, Genetic Type of study: Health economic evaluation / Prognostic study Language: English Year: 2005 Type: Article

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Full text: Available Index: IMSEAR (South-East Asia) Main subject: Phenotype / Humans / Monte Carlo Method / Chromosome Mapping / Quantitative Trait Loci / Alcoholism / Environment / Models, Genetic Type of study: Health economic evaluation / Prognostic study Language: English Year: 2005 Type: Article