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多变量定性和定量性状的联合多点连锁分析。I. 似然性公式及模拟结果。

Joint multipoint linkage analysis of multivariate qualitative and quantitative traits. I. Likelihood formulation and simulation results.

作者信息

Williams J T, Van Eerdewegh P, Almasy L, Blangero J

机构信息

Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX 78245-0549, USA.

出版信息

Am J Hum Genet. 1999 Oct;65(4):1134-47. doi: 10.1086/302570.

Abstract

We describe a variance-components method for multipoint linkage analysis that allows joint consideration of a discrete trait and a correlated continuous biological marker (e.g., a disease precursor or associated risk factor) in pedigrees of arbitrary size and complexity. The continuous trait is assumed to be multivariate normally distributed within pedigrees, and the discrete trait is modeled by a threshold process acting on an underlying multivariate normal liability distribution. The liability is allowed to be correlated with the quantitative trait, and the liability and quantitative phenotype may each include covariate effects. Bivariate discrete-continuous observations will be common, but the method easily accommodates qualitative and quantitative phenotypes that are themselves multivariate. Formal likelihood-based tests are described for coincident linkage (i.e., linkage of the traits to distinct quantitative-trait loci [QTLs] that happen to be linked) and pleiotropy (i.e., the same QTL influences both discrete-trait status and the correlated continuous phenotype). The properties of the method are demonstrated by use of simulated data from Genetic Analysis Workshop 10. In a companion paper, the method is applied to data from the Collaborative Study on the Genetics of Alcoholism, in a bivariate linkage analysis of alcoholism diagnoses and P300 amplitude of event-related brain potentials.

摘要

我们描述了一种用于多点连锁分析的方差成分法,该方法允许在任意大小和复杂度的家系中联合考虑离散性状和相关的连续生物学标记(例如疾病前体或相关风险因素)。假设连续性状在家族内呈多元正态分布,离散性状通过作用于潜在多元正态易患性分布的阈值过程进行建模。允许易患性与数量性状相关,并且易患性和数量表型均可包含协变量效应。双变量离散 - 连续观测很常见,但该方法可轻松处理本身为多元的定性和定量表型。针对重合连锁(即性状与恰好连锁的不同数量性状基因座[QTL]的连锁)和多效性(即同一QTL影响离散性状状态和相关连续表型)描述了基于似然的正式检验。通过使用遗传分析研讨会10的模拟数据展示了该方法的特性。在一篇配套论文中,该方法应用于酒精中毒遗传学合作研究的数据,用于酒精中毒诊断与事件相关脑电位P300振幅的双变量连锁分析。

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Bivariate quantitative trait linkage analysis: pleiotropy versus co-incident linkages.双变量数量性状连锁分析:多效性与巧合连锁
Genet Epidemiol. 1997;14(6):953-8. doi: 10.1002/(SICI)1098-2272(1997)14:6<953::AID-GEPI65>3.0.CO;2-K.

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