Program in Population Health Sciences, Research Institute, Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, M5G 1X8, Canada.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S59. doi: 10.1186/1471-2156-6-S1-S59.
Using the Genetic Analysis Workshop 14 simulated datasets we carried out nonparametric linkage analyses and applied a log-linear method for analysis of case-parent-triad data with stratification on parental mating type. We proposed and applied a random effect modelling approach to explore the impact of population heterogeneity on tests of association between genetic markers and disease status. The estimated genetic effect may appear to be strongly significant in one population but nonsignificant in another population, leading to confusion about interpretation. However, when results are interpreted in the light of a random effects model, both studies may be making similar statements about a genetic effect that varies depending on environment and background.
使用遗传分析工作坊 14 个模拟数据集，我们进行了非参数连锁分析，并应用对数线性方法对具有亲交配类型分层的病例-父母-三亲数据进行分析。我们提出并应用了一种随机效应建模方法来探索人群异质性对遗传标记与疾病状态之间关联检验的影响。在一个群体中，估计的遗传效应可能表现出很强的显著性，但在另一个群体中则不显著，从而导致对解释的混淆。然而，当根据随机效应模型解释结果时，这两项研究可能都对遗传效应做出了类似的表述，该遗传效应取决于环境和背景而有所不同。
