title: Statistical methods for the Ames Salmonella assay: a review.
abstract: The Ames Salmonella assay remains the most widely used in vitro genotoxicity assay. Several statistical methods have been proposed for its analysis [B.H. Margolin, N. Kaplan, E. Zeiger, Statistical analysis of the Ames Salmonella/microsome test, Proc. Natl. Acad. Sci., 78 (1981) 3779-3783; L.E. Myers, N.H. Saxton, L.I. Southerland, T.J. Wolff, Regression analysis of Ames test data, Environ. Mol. Mutagen., 3 (1981) 575-586; A.G. Stead, V. Hasselblad, J.P. Creason, L. Claxton, Modelling the Ames test, Mutation Res., 85 (1981) 13-27; L. Bernstein, J. Kaldor, J. McCaan, M.C. Pike, An empirical approach to the statistical analysis of mutagenesis data from the Salmonella test, Mutation Res., 97 (1982) 267-281; N.E. Breslow, Extra-Poisson variation in log-linear models, Appl. Stat., 33 (1984) 38-44; J. Wahrendorf, G.A.T. Mahon, M. Schumacher, A nonparametric approach to the statistical analysis of mutagenicity data, Mutation Res., 147 (1985) 5-13; D.G. Simpson, B.H. Margolin, Recursive nonparametric testing for dose-response relationships subject to downturns at high doses, Biometrika, 73 (1986) 589-596; D.G. Simpson, B.H. Margolin, Nonparametric testing for dose-response curves subject to downturns: Asymptotic power considerations, Annals Stat., 18 (1990) 373-390.]. In this paper we review recent literature to see what statistical methods are in fact employed for the analysis of the Ames assay. We then note that these methods can be classified into a common category in the framework of Haynes and Eckardt's mutation induction kinetics model [R.H. Haynes, F. Eckardt, Mathematical analysis of mutation induction kinetics, in: F.J. de Serres, A. Hollaender (Eds. ), Chemical Mutagens, Principles and Methods for Their Detection, Vol. 6, Plenum, New York, 1980, pp. 271-307]. The value in knowing this is that most methods of analysis considered here will likely exhibit common statistical behavior. These analyses are computationally intensive, e.g., [B.H. Margolin, N. Kaplan, E. Zeiger, Statistical analysis of the Ames Salmonella/microsome test, Proc. Nat. Acad. Sci., 78 (1981) 3779-3783], hence the ready availability of computer programs is essential if biologists are to use these methods. We briefly review two statistical software programs that are available in the public domain, and describe in detail a third program, Salm, [B.H. Margolin, N. Kaplan, E. Zeiger, Statistical analysis of the Ames Salmonella/microsome test, Proc. Nat. Acad. Sci., 78 (1981) 3779-3783; B.H. Margolin, B.S. Kim, K. Risko, The Ames Salmonella/microsome assay: Issues of inference and validation, J. Amer. Stat. Assoc., 84 (1989) 651-661]. The Salm program is obtainable through the file transfer protocol (ftp) or using a WWW browser. Finally, we discuss two statistical consequences of naively applying the two-fold rule, a method of analysis employed by a number of researchers.
authors.affiliation: Department of Applied Statistics, Yonsei University, Seoul, 120-749, South Korea.bskim@bubble.yonsei.ac.kr
authors.forename: B S
authors.initials: BS
authors.lastname: Kim
authors.forename: B H
authors.initials: BH
authors.lastname: Margolin
mesh_terms: D004305:Dose-Response Relationship, Drug; D008957:Models, Genetic; D009152:Mutagenicity Tests / Q000145:classification / Q000706:statistics & numerical data*; D012475:Salmonella / Q000235:genetics*; D012984:Software