Shoukri M M, Lathrop G M
Department of Population Medicine, University of Guelph, Ontario, Canada.
Biometrics. 1993 Mar;49(1):151-61.
Recent advances in human genetics have led to a renewed interest in statistical methods for the detection of linkage from family data--for example, between marker loci and disease traits. Statistical analysis of linkage between two loci is carried out almost exclusively by means of the lod (log-odds) score test, equivalent to a likelihood ratio test. The current practice is to declare genetic linkage between loci when the maximum lod score exceeds 3. As will be discussed here, the lod-score approach is not appropriate for the detection of linkage from heterogeneous data, e.g., when families consist of a mixture of linked and unlinked types. Heterogeneity may arise, for example, when rare mutations at different genetic loci are responsible for the same disease trait. As an alternative approach to account for possible heterogeneity in the detection of linkage, we propose the application of large-sample test statistics that are members of Neyman's class of C(alpha), or partial score tests. The convergence of the proposed test statistics to their asymptotic distributions is investigated via Monte Carlo simulation for typical study designs applicable in human genetics.
人类遗传学的最新进展引发了人们对利用家族数据检测连锁关系（例如标记位点与疾病性状之间的连锁关系）的统计方法的新兴趣。两个位点之间连锁关系的统计分析几乎完全通过对数优势（lod）分数检验来进行，这等同于似然比检验。当前的做法是，当最大lod分数超过3时，宣布位点之间存在遗传连锁。正如本文将要讨论的，lod分数方法不适用于从异质性数据中检测连锁关系，例如当家族由连锁和非连锁类型混合组成时。例如，当不同基因位点的罕见突变导致相同的疾病性状时，就可能出现异质性。作为在连锁检测中考虑可能存在的异质性的一种替代方法，我们建议应用属于奈曼C(α)类的大样本检验统计量，即部分分数检验。通过蒙特卡罗模拟，针对人类遗传学中适用的典型研究设计，研究了所提出的检验统计量向其渐近分布的收敛情况。
