title: Statistical approaches for analyzing mutational spectra: some recommendations for categorical data.
abstract: 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.
authors.affiliation: Department of Statistics, University of South Carolina, Columbia 29208.
authors.forename: W W
authors.initials: WW
authors.lastname: Piegorsch
authors.forename: A J
authors.initials: AJ
authors.lastname: Bailer
mesh_terms: D001483:Base Sequence; D003062:Codon; D003198:Computer Simulation; D004926:Escherichia coli / Q000235:genetics; D008433:Mathematics; D008957:Models, Genetic; D015233:Models, Statistical; D009154:Mutation; D017354:Point Mutation
chemical_list: D003062:Codon