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The resolution of genotype × environment interaction in segregation analysis of nuclear families

The resolution of genotype × environment interaction in segregation analysis of nuclear families A model is presented for the effects of one or two loci, a measured index of the environment and genotype × environment (G×E) interaction of risk for a discontinuous trait. Initial properties of the model are explored for the single locus case, with and without the effects of environment and G×E interaction. Seven data sets were simulated, each comprising 500 nuclear families on whom an environmental index has been measured. Maximum‐likelihood estimation procedures were used to obtain parameter estimates under seven models for each data set. Likelihood ratio tests were constructed, and in all cases it was possible to identify the “correct” model for the simulated data. The matrices of information realized showed that the parameters could be estimated with acceptable precision and that the effects of genes, environment, and G×E interaction could be resolved in the simulated populations. The effects on conventional segregation analysis of ignoring the environment and G×E are considered. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Genetic Epidemiology Wiley

The resolution of genotype × environment interaction in segregation analysis of nuclear families

Genetic Epidemiology , Volume 1 (3) – Jan 1, 1984

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References (22)

Publisher
Wiley
Copyright
Copyright © 1984 Wiley‐Liss, Inc., A Wiley Company
ISSN
0741-0395
eISSN
1098-2272
DOI
10.1002/gepi.1370010302
pmid
6544238
Publisher site
See Article on Publisher Site

Abstract

A model is presented for the effects of one or two loci, a measured index of the environment and genotype × environment (G×E) interaction of risk for a discontinuous trait. Initial properties of the model are explored for the single locus case, with and without the effects of environment and G×E interaction. Seven data sets were simulated, each comprising 500 nuclear families on whom an environmental index has been measured. Maximum‐likelihood estimation procedures were used to obtain parameter estimates under seven models for each data set. Likelihood ratio tests were constructed, and in all cases it was possible to identify the “correct” model for the simulated data. The matrices of information realized showed that the parameters could be estimated with acceptable precision and that the effects of genes, environment, and G×E interaction could be resolved in the simulated populations. The effects on conventional segregation analysis of ignoring the environment and G×E are considered.

Journal

Genetic EpidemiologyWiley

Published: Jan 1, 1984

Keywords: genotype × environment interaction; segregation analysis; simulation; nuclear family; likelihood; environmental index; nonadditive

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