A multilocus extension of the affected-pedigree-member method of linkage analysis.
A multilocus extension of the affected-pedigree-member method of linkage analysis.
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DOI：
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发表时间：
1992-04
影响因子：
9.8
通讯作者：
Daniel E. Weeks;Kenneth Lange
中科院分区：
文献类型：
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作者：
Daniel E. Weeks;Kenneth Lange
连锁分析的受影响谱系成员（APM）方法旨在检测疾病和标记表型独立分离的偏离。APM方法的基本统计量对由谱系内受影响的标记表型所暗示的身份-状态关系进行操作。在这里，我们将APM统计推广到多个连锁标记。这种推广依赖于递归计算的两个位点的亲属关系系数的算法汤普森。在一个真实的和一个人工数据集的背景下，扩展APM统计量的分布特性进行了理论研究和模拟。在这两个例子中，多位点统计倾向于拒绝，比单位点统计更强烈，疾病位点和标记位点之间的独立分离的零假设。
The affected-pedigree-member (APM) method of linkage analysis is designed to detect departures from independent segregation of disease and marker phenotypes. The underlying statistic of the APM method operates on the identity-by-state relations implied by the marker phenotypes of the affected within a pedigree. Here we generalize the APM statistic to multiple linked markers. This generalization relies on recursive computation of two-locus kinship coefficients by an algorithm of Thompson. The distributional properties of the extended APM statistic are investigated theoretically and by simulation in the context of one real and one artificial data set. In both examples, the multilocus statistic tends to reject, more strongly than the single-locus statistics do, the null hypothesis of independent segregation between the disease locus and the marker loci.