title: Detecting interactions between gene, site, and environmental variables using GAP.
abstract: Regressive models that incorporate measured variables and assumed genetic parameters were used to detect interactions between gene, research site, and environmental variables in GAW11 Problem 2. Replicates 1 to 5 were used in the analyses. Significant three-way gene x environment x site interactions were seen for all models, regardless of what assumptions were made about genetic transmission. Therefore, regressive models within each of the four sites were examined for significant gene x environment interactions. At one site, there was a pattern of gene x environment interaction that was consistent in most of the genetic models assumed. Joint and separate segregation and linkage analyses were compared in this site. No patterns of gene x environment interaction were seen in the other sites. Results from this analysis show that regressive modeling can identify complex interactions in data from heterogeneous populations even when ascertainment assumptions are violated.
authors.affiliation: Department of Public Health Sciences, University of Toronto, Ontario, Canada.
authors.forename: J
authors.initials: J
authors.lastname: Shin
authors.forename: M
authors.initials: M
authors.lastname: Corey
mesh_terms: D002874:Chromosome Mapping; D004777:Environment; D005799:Genes, Dominant; D005808:Genes, Recessive; D008040:Genetic Linkage; D005820:Genetic Testing; D006801:Humans; D008957:Models, Genetic; D012044:Regression Analysis