SEGREGATION ANALYSIS OF HUMAN PEDIGREES USING ESTIMATING EQUATIONS

• 成果类型: Article
• 署名作者: ZHAO, LP
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• 发表日期: 1994
• 页码: 197209
• 关键词: complex segregation; models; traits

摘要

Studies in genetic epidemiology are generally required to collect phenotypes on subjects from human pedigrees that consist of blood relatives and their spouses. One of the main objectives in analyzing pedigree data is to study the segregation of underlying genes that may predispose certain phenotypes and thus cause phenotypic aggregation within pedigrees. Most classical segregation methods are maximum likelihood-based under highly specified distributional assumptions for phenotypes given underlying genes. The assumptions are usually not testable with available data, and their misspecification may affect estimation of and inference about parameters of interest. Following the conceptual framework of the classical segregation methods, this paper introduces an estimating equation-based method that requires no distributional assumption concerning the joint distribution of phenotypes given underlying genes. Moreover, manageable computation allows one to fit a general segregation model with subject-specific covariates and their interactions with underlying genes. The model admits both continuous and binary phenotypes. A strategy for segregation analysis and two relevant test statistics are described.