Böhm U, Dahm P F, McAllister B F, Greenbaum I F
Department of Statistics, Texas A & M University, College Station 77843.
Hum Genet. 1995 Mar;95(3):249-56. doi: 10.1007/BF00225189.
The inability to identify fragile sites from data for single individuals remains the major obstacle to determining whether these chromosomal loci are predisposed to cancer-causing and evolutionary rearrangements. We describe a novel statistical model that is amenable to data from single individuals and that establishes site-specific chromosomal breakage as nonrandom with respect to the distribution of total breakage. Our method tests incrementally smaller subsets of the data for homogeneity under a multinomial model that assigns equal probabilities to a maximal set of nonfragile sites and unrestricted probabilities to the remaining fragile sites with significantly higher numbers of breaks. We show how standardized Pearson's chi-square (X2) and likelihood-ratio (G2) statistics can be appropriately used to measure goodness-of-fit for sparse contingency (individual-based) data in this model. A sample application of this approach indicates extensive variation in fragile sites among individuals and marked differences in fragile-site inferences from pooled as opposed to per-individual data.
无法从单个个体的数据中识别脆性位点仍然是确定这些染色体位点是否易于发生致癌和进化重排的主要障碍。我们描述了一种新颖的统计模型,该模型适用于单个个体的数据,并将位点特异性染色体断裂确定为相对于总断裂分布而言是非随机的。我们的方法在多项模型下逐步测试数据的更小子集的同质性,该模型为最大的非脆性位点集分配相等的概率,并为具有明显更多断裂的其余脆性位点分配无限制的概率。我们展示了标准化的皮尔逊卡方(X2)和似然比(G2)统计量如何能够适当地用于测量该模型中稀疏列联(基于个体)数据的拟合优度。这种方法的一个示例应用表明个体之间脆性位点存在广泛差异,并且与汇总数据相比,从个体数据推断脆性位点存在显著差异。