Lange K, Matthysse S
Department of Biomathematics, School of Medicine, University of California, Los Angeles 90024.
Am J Hum Genet. 1989 Dec;45(6):959-70.
A random walk method, based on the Metropolis algorithm, is developed for simulating the distribution of trait and linkage marker genotypes in pedigrees where trait phenotypes are already known. The method complements techniques suggested by Ploughman and Boehnke and by Ott that are based on sequential sampling of genotypes within a pedigree. These methods are useful for estimating the power of linkage analysis before complete study of a pedigree is undertaken. We apply the random walk technique to a partially penetrant disease, schizophrenia, and to a recessive disease, ataxia-telangiectasia. In the first case we show that accessory phenotypes with higher penetrance than that of schizophrenia itself may be crucial for effective linkage analysis, and in the second case we show that impressionistic selection of informative pedigrees may be misleading.
基于梅特罗波利斯算法开发了一种随机游走方法,用于模拟家系中性状和连锁标记基因型的分布,其中性状表型是已知的。该方法补充了普劳曼和博恩克以及奥特提出的基于家系内基因型顺序抽样的技术。这些方法对于在对家系进行全面研究之前估计连锁分析的效能很有用。我们将随机游走技术应用于一种部分显性疾病——精神分裂症,以及一种隐性疾病——共济失调毛细血管扩张症。在第一种情况下,我们表明具有比精神分裂症本身更高外显率的辅助表型对于有效的连锁分析可能至关重要,而在第二种情况下,我们表明凭印象选择信息丰富的家系可能会产生误导。