title: Dissecting the correlation structure of a bivariate phenotype: common genes or shared environment?
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.
authors.affiliation: Human Genetics Unit, Indian Statistical Institute, 203 BT Road, Kolkata 700 108, India. saurabh@isical.ac.in
authors.forename: Saurabh
authors.initials: S
authors.lastname: Ghosh
mesh_terms: D000437:Alcoholism / Q000235:genetics; D002874:Chromosome Mapping; D004777:Environment; D006801:Humans; D008957:Models, Genetic; D009010:Monte Carlo Method; D010641:Phenotype; D040641:Quantitative Trait Loci