Li W, Reich J
Laboratory of Statistical Genetics, Rockefeller University, New York, NY 10021, USA.
Hum Hered. 2000 Nov-Dec;50(6):334-49. doi: 10.1159/000022939.
There are 512 two-locus, two-allele, two-phenotype, fully penetrant disease models. Using the permutation between two alleles, between two loci, and between being affected and unaffected, one model can be considered to be equivalent to another model under the corresponding permutation. These permutations greatly reduce the number of two-locus models in the analysis of complex diseases. This paper determines the number of nonredundant two-locus models (which can be 102, 100, 96, 51, 50, or 58, depending on which permutations are used, and depending on whether zero-locus and single-locus models are excluded). Whenever possible, these nonredundant two-locus models are classified by their property. Besides the familiar features of multiplicative models (logical AND), heterogeneity models (logical OR), and threshold models, new classifications are added or expanded: modifying-effect models, logical XOR models, interference and negative interference models (neither dominant nor recessive), conditionally dominant/recessive models, missing lethal genotype models, and highly symmetric models. The following aspects of two-locus models are studied: the marginal penetrance tables at both loci, the expected joint identity-by-descent (IBD) probabilities, and the correlation between marginal IBD probabilities at the two loci. These studies are useful for linkage analyses using single-locus models while the underlying disease model is two-locus, and for correlation analyses using the linkage signals at different locations obtained by a single-locus model.
有512种双基因座、双等位基因、双表型、完全显性的疾病模型。通过在两个等位基因之间、两个基因座之间以及患病与未患病之间进行排列,在相应排列下,一个模型可被视为与另一个模型等效。这些排列在复杂疾病分析中大大减少了双基因座模型的数量。本文确定了非冗余双基因座模型的数量(根据所使用的排列以及是否排除零基因座和单基因座模型,数量可能为102、100、96、51、50或58)。只要有可能,这些非冗余双基因座模型就按其性质进行分类。除了常见的乘法模型(逻辑与)、异质性模型(逻辑或)和阈值模型的特征外,还增加或扩展了新的分类:修饰效应模型、逻辑异或模型、干扰和负干扰模型(既非显性也非隐性)、条件显性/隐性模型、缺失致死基因型模型和高度对称模型。研究了双基因座模型的以下几个方面:两个基因座处的边际显性表、预期的联合同源性(IBD)概率以及两个基因座处边际IBD概率之间的相关性。这些研究对于在潜在疾病模型为双基因座时使用单基因座模型进行连锁分析,以及对于使用单基因座模型在不同位置获得的连锁信号进行相关性分析都很有用。