Quantification of type I error probabilities for heterogeneity LOD scores
Quantification of type I error probabilities for heterogeneity LOD scores
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DOI：
10.1002/gepi.0155
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发表时间：
2002-02-01
影响因子：
2.1
通讯作者：
Greenberg, DA
中科院分区：
文献类型：
--
作者：
Abreu, PC;Hodge, SE;Greenberg, DA
基因座的异质性是连锁分析中的一个主要混杂因素，当不存在连锁的先验知识时，人们的目标是同时检测连锁和异质性，经典的对数似然比分布理论不成立。尽管对这个问题进行了一些理论研究，但没有普遍接受的实践指南。也没有人严格地检验连锁和异质性测试的综合效果，并同时最大化两种遗传模型（显性，隐性）。连接相位的影响是另一个未研究的问题。使用计算机模拟，我们研究了“混合物”异质性LOD（HLOD）评分的I型错误（P值），即，LOD得分在重组分数0和混合参数α两者上最大化并且我们将其与仅相对于0最大化时的P值进行比较（即，标准LOD评分）。我们生成的数据集阶段已知和未知的核心家庭，大小k = 2，4，和6个孩子，火种完全外显常染色体显性遗传。我们分析了这些数据集：（1）假设单一遗传模型，并最大化theta和alpha上的HLOD，以及（2）最大化另外两个显性模型（显性与隐性）上的HLOD，然后减去0.3校正。对于（1）和（2），P值随家庭规模k增加而增加;相位未知家庭的P值比相位已知家庭的P值增加得少，随着k的增加，前者接近后者;并且没有超过单侧混合分布xi =（1/2）chi（1）（2）+（1/2）chi（2）（2）。因此，在0和a上最大化HLOD似乎比相关的chi（1）（2）分布增加的额外自由度少得多。最后，我们提出了联系调查人员的实用指南。Genet.流行病学22：156-169，2002. (C)2002 Wiley-Liss，Inc.
Locus heterogeneity is a major confounding factor in linkage analysis, When no prior knowledge of linkage exists, and one aims to detect linkage and heterogeneity simultaneously, classical distribution theory of log-likelillood ratios does not hold. Despite some theoretical work on this problem, no generally accepted practical guidelines exist. Nor has anyone rigorously examined the combined effect of testing for linkage and heterogeneity and simultaneously maximizing over two genetic models (dominant, recessive). The effect of linkage phase represents another uninvestigated issue. Using computer simulation, we investigated type I error (P value) of the "admixture" heterogeneity LOD (HLOD) score, i.e., the LOD score maximized over both recombination fraction 0 and admixture parameter a and we compared this with the P values when one maximizes only with respect to 0 (i.e., the standard LOD score). We generated datasets of phase-known and -unknown nuclear families, sizes k = 2, 4, and 6 children, tinder fully penetrant autosomal dominant inheritance. We analyzed these datasets ( I) assuming a single genetic model, and maximizing the HLOD over theta and alpha and (2) maximizing the HLOD additionally over two dominance models (dominant vs. recessive), then subtracting a 0.3 correction. For both (1) and (2), P values increased with family size k; rose less for phase-unknown families than for phase-known ones, with the former approaching the latter as k increased; and did not exceed the one-sided mixture distribution xi = (1/2) chi(1)(2)+ (1/2) chi(2)(2). Thus, maximizing the HLOD over 0 and a appears to add considerably less than an additional degree of freedom to the associated chi(1)(2) distribution. We conclude with practical guidelines for linkage investigators. Genet. Epidemiol. 22:156-169, 2002. (C) 2002 Wiley-Liss, Inc.