A COMPARISON OF LINKAGE DISEQUILIBRIUM MEASURES FOR FINE-SCALE MAPPING
A COMPARISON OF LINKAGE DISEQUILIBRIUM MEASURES FOR FINE-SCALE MAPPING
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DOI：
10.1006/geno.1995.9003
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发表时间：
1995-09-20
期刊：
影响因子：
4.4
通讯作者：
RISCH, N
中科院分区：
文献类型：
--
作者：
DEVLIN, B;RISCH, N
连锁作图通常将疾病基因定位于染色体的1至2 cM区域。理论上，进一步精确定位可以通过基于群体的疾病位点等位基因与相邻标记等位基因之间的连锁不平衡研究来实现。定位的一种方法，称为简单不平衡作图，是通过将不平衡值与标记位置作图来确定疾病位点的相对位置。我们调查了简单的映射性质的五个不平衡措施，相关系数三角洲，Lewontin的D '，强大的制定人口归因风险三角洲，Yule的Q，卡普兰和威尔的比例差D疾病和标记位点之间的初始完全不平衡的假设下。研究表明，δ是一个上级措施精细定位，因为它是直接相关的疾病和标记基因座之间的重组分数，它是不变的，当疾病单倍型的采样率高于他们的人口频率，在病例对照研究。D'产生的结果在许多现实环境中与delta的结果相当。在剩下的三个度量Q、Delta和d中，Q产生最好的结果。从短期进化的模拟，所有的措施都显示出一定的敏感性标记等位基因频率，然而，如分析结果预测，Q，Delta和d表现出最大的敏感性标记等位基因频率的变化在基因座。(C)出版社：Academic Press
Linkage mapping generally localizes disease genes to 1- to 2-cM regions of chromosomes. In theory, further refinement of location can be achieved by population-based studies of linkage disequilibrium between disease locus alleles and alleles at adjacent markers. One approach to localization, dubbed simple disequilibrium mapping, is to determine the relative location of the disease locus by plotting disequilibrium values against marker locations. We investigate the simple mapping properties of five disequilibrium measures, the correlation coefficient Delta, Lewontin's D', the robust formulation of the population attributable risk delta, Yule's Q, and Kaplan and Weir's proportional difference d under the assumption of initial complete disequilibrium between disease and marker loci. The studies indicate that delta is a superior measure for fine mapping because it is directly related to the recombination fraction between the disease and the marker loci, and it is invariant when disease haplotypes are sampled at a rate higher than their population frequencies, as in a case-control study. D' yields results comparable to those of delta in many realistic settings. Of the remaining three measures, Q, Delta, and d, Q yields the best results. From simulations of short-term evolution, all measures show some sensitivity to marker allele frequencies; however, as predicted by analytic results, Q, Delta, and d exhibit the greatest sensitivity to variation in marker allele frequencies across loci. (C) 1995 Academic Press, Inc.