Rabinowitz D, Laird N
Department of Statistics, Columbia University, New York, N.Y., USA.
Hum Hered. 2000 Jul-Aug;50(4):211-23. doi: 10.1159/000022918.
A general approach to family-based examinations of association between marker alleles and traits is proposed. The approach is based on computing p values by comparing test statistics for association to their conditional distributions given the minimal sufficient statistic under the null hypothesis for the genetic model, sampling plan and population admixture. The approach can be applied with any test statistic, so any kind of phenotype and multi-allelic markers may be examined, and covariates may be included in analyses. By virtue of the conditioning, the approach results in correct type I error probabilities regardless of population admixture, the true genetic model and the sampling strategy. An algorithm for computing the conditional distributions is described, and the results of the algorithm for configurations of nuclear families are presented. The algorithm is applicable with all pedigree structures and all patterns of missing marker allele information.
本文提出了一种基于家系的标记等位基因与性状关联检验的通用方法。该方法基于在零假设下，根据遗传模型、抽样计划和群体混合情况，通过将关联检验统计量与其最小充分统计量的条件分布进行比较来计算p值。该方法可应用于任何检验统计量，因此可以检验任何类型的表型和多等位基因标记，并且分析中可以纳入协变量。由于进行了条件设定，无论群体混合情况、真实遗传模型和抽样策略如何，该方法都能产生正确的I型错误概率。文中描述了一种计算条件分布的算法，并给出了该算法在核心家庭配置下的结果。该算法适用于所有系谱结构和所有标记等位基因信息缺失模式。
