Piegorsch W W, Bailer A J
Department of Statistics, University of South Carolina, Columbia 29208.
Genetics. 1994 Jan;136(1):403-16. doi: 10.1093/genetics/136.1.403.
In studies examining the patterns or spectra of mutational damage, the primary variables of interest are expressed typically as discrete counts within defined categories of damage. Various statistical methods can be applied to test for heterogeneity among the observed spectra of different classes, treatment groups and/or doses of a mutagen. These are described and compared via computer simulations to determine which are most appropriate for practical use in the evaluation of spectral data. Our results suggest that selected, simple modifications of the usual Pearson X2 statistic for contingency tables provide stable false positive error rates near the usual alpha = 0.05 level and also acceptable sensitivity to detect differences among spectra. Extensions to the problem of identifying individual differences within and among mutant spectra are noted.
在研究突变损伤的模式或谱时，主要关注的变量通常表示为特定损伤类别内的离散计数。可以应用各种统计方法来检验不同类别、治疗组和/或诱变剂剂量的观察谱之间的异质性。通过计算机模拟对这些方法进行描述和比较，以确定哪些方法最适合实际用于评估谱数据。我们的结果表明，对列联表常用的Pearson X2统计量进行选定的简单修改，可在通常的α = 0.05水平附近提供稳定的假阳性错误率，并且对检测谱之间的差异也具有可接受的敏感性。文中还提到了识别突变谱内和谱间个体差异问题的扩展。
