Department of Epidemiology and Biostatistics, Case Western Reserve University Cleveland, OH, USA.
Front Genet. 2013 Nov 19;4:244. doi: 10.3389/fgene.2013.00244. eCollection 2013.
Olson's conditional-logistic model retains the nice property of the LOD score formulation and has advantages over other methods that make it an appropriate choice for complex trait linkage mapping. However, the asymptotic distribution of the conditional-logistic likelihood-ratio (CL-LR) statistic with genetic constraints on the model parameters is unknown for some analysis models, even in the case of samples comprising only independent sib pairs. We derive approximations to the asymptotic null distributions of the CL-LR statistics and compare them with the empirical null distributions by simulation using independent affected sib pairs. Generally, the empirical null distributions of the CL-LR statistics match well the known or approximated asymptotic distributions for all analysis models considered except for the covariate model with a minimum-adjusted binary covariate. This work will provide useful guidelines for linkage analysis of real data sets for the genetic analysis of complex traits, thereby contributing to the identification of genes for disease traits.
奥尔森条件逻辑模型保留了 LOD 评分公式的优良性质,并且优于其他方法,因此它是复杂性状连锁映射的合适选择。然而,对于某些分析模型,即使在仅包含独立同胞对的样本情况下,条件逻辑似然比(CL-LR)统计量的渐近分布也是未知的,这些模型的参数受到遗传限制。我们推导出 CL-LR 统计量的渐近零分布的逼近值,并通过使用独立受影响的同胞对进行模拟来将其与经验零分布进行比较。通常,除了具有最小调整二进制协变量的协变量模型之外,CL-LR 统计量的经验零分布与所有考虑的分析模型的已知或近似渐近分布匹配良好。这项工作将为复杂性状遗传分析的真实数据集的连锁分析提供有用的指导,从而有助于鉴定疾病性状的基因。