Vieland Veronica J
Program in Public Health Genetics and Center for Statistical Genetics Research, University of Iowa Colleges of Public Health and Medicine, Iowa City, Iowa 52245, USA.
Genet Epidemiol. 2005;29 Suppl 1:S110-5. doi: 10.1002/gepi.20118.
This paper summarizes the contributions to Group 15 of Genetic Analysis Workshop (GAW) 14, which focused on methods for dealing with heterogeneity in linkage and association analysis. A variety of methods were employed, ranging from manipulation of the phenotype and/or identification of endophenotypes prior to analysis, to statistical methods allowing for heterogeneity in the analysis of simple dichotomous phenotypes as provided with the data. Overall, it was difficult to draw broad conclusions from these applications. Groups that focused on the simulated data had fairly consistent success in mapping the major genes (but not the two minor genes). However, this appeared to be the case regardless of whether heterogeneity was explicitly modeled, either at the phenotypic or statistical level, with relatively crude statistical methods applied to the simulated simple dichotomous trait Kofendrerd personality disorder also enjoying considerable success.
本文总结了遗传分析研讨会（GAW）14的第15组的研究成果，该组聚焦于处理连锁和关联分析中的异质性的方法。研究采用了多种方法，从分析前对表型的处理和/或内表型的识别，到对数据中提供的简单二分表型进行分析时考虑异质性的统计方法。总体而言，很难从这些应用中得出广泛的结论。专注于模拟数据的小组在定位主要基因（但不是两个次要基因）方面取得了相当一致的成功。然而，无论在表型还是统计层面是否明确建模异质性，情况似乎都是如此，应用于模拟简单二分性状“Kofendrerd人格障碍”的相对粗略的统计方法也取得了相当大的成功。
