Group 6: Pleiotropy and multivariate analysis
Group 6: Pleiotropy and multivariate analysis
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DOI：
10.1002/gepi.10284
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发表时间：
2003-01-01
影响因子：
2.1
通讯作者：
de Andrade, M
中科院分区：
文献类型：
--
作者：
Kraft, P;de Andrade, M
同时使用几个性状数据的分析技术使研究人员能够剖析影响相关性状的遗传结构，并可以增加检测多效性基因的能力，即影响两个或更多性状的基因。这个小组中的几篇来自基因分析研讨会13的论文提出了有希望的多个性状的单变量摘要，这些单变量摘要检测到了标准的单性状单变量方法无法检测到的连锁信号。其他论文发现了使用多变量技术的连锁信号，但单变量技术遗漏了这一点，尽管情况并不一致。一些论文还考虑了在不同年龄对单个性状进行测量的相关性，以评估该性状的遗传结构是否随着年龄的变化而变化。弗雷明翰心脏研究数据的应用确定了共同影响体重指数和高密度脂蛋白胆固醇、高密度脂蛋白胆固醇和甘油三酯、总胆固醇和甘油三酯的主要基因座，以及与代谢综合征有关的四个特征的各种组合。(C)2003年Wiley-Liss，Inc.
Analysis techniques using data on several traits simultaneously allow researchers to dissect the genetic architecture affecting correlated traits, and can increase the power to detect pleiotropic genes, i.e., genes that influence two or more traits. Several of the papers in this group from Genetic Analysis Workshop 13 presented promising univariate summaries of multiple traits that detected linkage signals that standard single-trait univariate methods did not. Other papers found linkage signals using multivariate techniques that univariate techniques missed, although this was not uniformly the case. Some papers also considered the correlation among measurements of a single trait taken at different ages to assess whether the genetic architecture of the trait changed over age. Applications of the Framingham Heart Study data identified major loci jointly influencing body mass index and high-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides, total cholesterol and triglycerides, and various combinations of four traits involved in metabolic syndrome. (C) 2003 Wiley-Liss, Inc.