Applied Mathematics and Statistics Department, Stony Brook University, Stony Brook, New York 11794, USA.
BMC Genet. 2005 Dec 30;6 Suppl 1(Suppl 1):S47. doi: 10.1186/1471-2156-6-S1-S47.
In this paper we investigate the power of finding linkage to a disease locus through analysis of the disease-related traits. We propose two family-based gene-model-free linkage statistics. Both involve considering the distribution of the number of alleles identical by descent with the proband and comparing siblings with the disease-related trait to those without the disease-related-trait. The objective is to find linkages to disease-related traits that are pleiotropic for both the disease and the disease-related-traits. The power of these statistics is investigated for Kofendrerd Personality Disorder-related traits a (Joining/founding cults) and trait b (Fear/discomfort with strangers) of the simulated data. The answers were known prior to the execution of the reported analyses. We find that both tests have very high power when applied to the samples created by combining the data of the three cities for which we have nuclear family data.
在本文中，我们通过分析与疾病相关的特征来研究发现与疾病基因座连锁的能力。我们提出了两种基于家系的、无需基因模型的连锁统计方法。这两种方法都涉及考虑与先证者相同的遗传等位基因的数量分布，并将有疾病相关特征的兄弟姐妹与没有疾病相关特征的兄弟姐妹进行比较。目的是发现与疾病相关特征的连锁，这些特征对疾病和疾病相关特征都是多效的。对于模拟数据中的科芬德人格障碍相关特征 a（加入/创立邪教）和特征 b（对陌生人的恐惧/不适），我们研究了这些统计方法的功效。在执行报告的分析之前，答案是已知的。我们发现，当应用于我们具有核家庭数据的三个城市的数据组合创建的样本时，这两种检验都具有很高的功效。
