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Tabular Overview of Statistical Methods Proposed for the Analysis of Ames Salmonella Assay Data

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Statistical Methods in Toxicology

Part of the book series: Lecture Notes in Medical Informatics ((LNMED,volume 43))

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Abstract

The AMES Salmonella/Microsome assay has challenged considerable biometrical efforts for data analysis since its introduction to mutagenicity testing in 1975. Approaches proposed by various authors range from straightforward applications of classical linear models to more sophisticated statistical methods such as those of generalized linear models. The assay motivated the use of stochastic branching process theory for constructing the model equations to analyze mutagenicity data, and it is considered as an important example of the analysis of overdispersed count data. Non-parametric methods have also been applied with success.

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References

  • Alvord WG, Driver JH, Claxton L, Creason JP (1990) Methods for comparing Salmonella mutagenicity data sets using nonlinear models. Mutat. Res. 240: 177–194

    Google Scholar 

  • Andrews AW, Thibault LH, Ljinski W (1978) The relationship between carcinogenicity and mutagenicity of some polynuclear hydrocarbons. Mutat. Res. 51: 319–326

    Google Scholar 

  • Benedict WF, Baker MS, Haroun L, Choi W, Ames BN (1977) Mutagenicity of cancer chemotherapeutic agents in the Salmonella/microsome test. Cancer Res. 37: 2209–2213

    Google Scholar 

  • Bernstein L, Kaldor J, McCann J, Pike MC (1982) An empirical approach to the statistical analysis of mutagenesis data from the Salmonella test. Mutat. Res. 97: 267–281

    Google Scholar 

  • Breslow NE (1984) Extra-Poisson variation in log-linear models. Appl. Statist. 33: 38–44

    Article  Google Scholar 

  • Breslow NE (1990) Tests of hypotheses in overdispersed Poisson regression and other quasi-likelihood models. J. Amer Statist. Assoc. 85: 565–571

    Article  Google Scholar 

  • Breslow NE, Kaldor J (1986) Statistical analysis of data from in-vitro assays of mutagenesis. In Montesano R, Bartsch H, Vainio H, Wilbourn J, Yamasaki H (eds) Long-term and Short-term assays for Carcinogens: A Critical Appraisal. IARC Sci Publications, IARC Lyon, 457–481

    Google Scholar 

  • Brusick DJ (1977) In vitro mutagenesis assays as predictors of chemical carcinogenesis in mammals. Clin. Toxicol. 10: 79109

    Article  Google Scholar 

  • Chen JJ, Heflich RH, Hass BS (1989) A response-additive model for analyzing mixtures of two chemicals in the Salmonella reversion assay. Biom. J. 31: 495–503

    Google Scholar 

  • Chu KC, Patel KM, Lin AH, Tarone RE, Lin MS, Dunkel VC (1981) Evaluating statistical analyses and reproducibility of microbial mutagenicity assays. Mutat. Res. 85: 119–132

    Google Scholar 

  • Collings BJ, Margolin BH, Oehlert GW (1981) Analyses of binomial data with application to the fluctuation test for mutagenicity. Biometrics 37: 775–794

    Article  MathSciNet  MATH  Google Scholar 

  • Ehrenberg L (1977) Aspects of statistical inference in testing for genetic toxicity. In: Kilbey BJ, Legator M, Ramel C (eds) Handbook of Mutagenicity Test Procedures. Elsevier, Amsterdam, 419–459

    Google Scholar 

  • Katz AJ (1979) Design and analysis of experiments on mutagenicity H. Assays involving micro-organisms. Mutat. Res. 64, 61–77

    Article  Google Scholar 

  • Kirkland DJ (1989) Statistical Evaluation of Mutagenicity Test Data. Cambridge University Press, Cambridge

    Google Scholar 

  • Mahon GAT, Green MHL, Middleton B, Mitchell I de G, Robinson WD, Tweats DJ (1989) Analysis of data from microbial colony as-

    Google Scholar 

  • says. In: Kirkland DJ (ed) Statistical Evaluation of Mutagenicity Test Data. Cambridge University Press, Cambridge, 2665

    Google Scholar 

  • Margolin BH, Kaplan N, Zeiger E (1981) Statistical analysis of the Ames Salmonella/microsome test. Proc. Natl. Acad. Sci. 78: 3779–3783

    Google Scholar 

  • Mitchell I de G (1982) Establishment of stochastic significance in Ames tests and its relevance to genetical significance. Mutat. Res. 104: 25–28

    Article  Google Scholar 

  • Moore D, Felton JS (1983) A microcomputer program for analyzing Ames test data. Mutat. Res. 119: 95–102

    Google Scholar 

  • Myers LE, Sexton NH, Southerland LI, Wolff TJ (1981) Regression

    Google Scholar 

  • analysis of Ames test data. Environ. Mutagen. 3: 575–586

    Google Scholar 

  • Piegorsch WW, Margolin (1989) Quantitative methods for assessing a synergistic or potentiated genotoxic response. Mutat. Res. 216: 1–8

    Google Scholar 

  • Schmoor C, Schumacher M (1988) Adaptive statistical procedures for the analysis of mutagenicity data. Institute of Medical Biometry and Informatics, University of Freiburg. December 1988

    Google Scholar 

  • Schumacher M (1985) Statistische Analyse des Ames Tests. Universitaet Dortmund, Arbeitsberichte der Abt. Statistik No. 18

    Google Scholar 

  • Simpson DG, Margolin BH (1986) Recursive nonparametric testing for dose-response relationships subject to downturns at high doses. Biometrika 73: 589–596

    MathSciNet  MATH  Google Scholar 

  • Simpson DG, Margolin BH (1990) Nonparametric testing for dose-response curves subject to downturns: asymptotic power considerations. Ann. Statist. 18: 373–390

    Google Scholar 

  • Snee RD, Irr JD (1984) A procedure for the statistical evaluation of Ames Salmonella assay results: comparison of results among four laboratories. Mutat. Res. 128: 115–125

    Google Scholar 

  • Stead AG, Hasselblad V, Creason JP, Claxton L (1981) Modeling the Ames test. Mutat. Res. 85: 13–27.

    Google Scholar 

  • Venitt S (1982) UKEMS collaborative genotoxicity trial - bacterial mutation tests of 4-chloromethylbiphenyl, 4-hydroxymeth-

    Google Scholar 

  • ylbiphenyl and benzyl chloride; analysis of data from 17 laboratories. Mutat. Res. 100: 91–109

    Google Scholar 

  • Vollmar J (1981): Statistical problems in the Ames test. In: Kappas A (ed) Progress in Mutation Research. Elsevier, Amsterdam, 179–186

    Google Scholar 

  • Vollmar J (1985) Nichtparametrische Trendtests in der Mutagenitaetspruefung. Kolloquium “Statistische Methoden in der experimentellen Forschung”, TU Berlin

    Google Scholar 

  • Wahrendorf J, Mahon GAT, Schumacher M (1985) A nonparametric approach to the statistical analysis of mutagenicity data. Mu-tat. Res. 147: 5–13

    Google Scholar 

  • Waters MD, Stack HF, Brady AL, Lohmann, PHM, Haroun L, Vainio H (1987) Activity profiles for genetic and related tests. In: IARC Monographs on the Evaluation of Carcinogenic Risks to Humans. Genetic and Related Effects: An Updating of Selected IARC Monographs from Volumes 1–42. Supplement 6. IARC Lyon, Appendix 1, 687–696

    Google Scholar 

  • Weinstein D, Lewinson TM (1978) A statistical treatment of the Ames mutagenicity assay. Mutat. Res. 51: 433–434

    Google Scholar 

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Author information

Authors and Affiliations

  1. Boehringer Mannheim GmbH, D-6800, Mannheim, Germany

    Joachim Vollmar & Lutz Edler

  2. National Institute of Environmental Health Sciences, Research Triangle Park, NC, 27709, USA

    Joachim Vollmar & Lutz Edler

Authors
  1. Joachim Vollmar
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  2. Lutz Edler
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Editor information

Editors and Affiliations

  1. Institute of Epidemiology and Biometry, German Cancer Research Center Heidelberg, Im Neuenheimer Feld 280, 6900, Heidelberg, Germany

    Ludwig Hothorn

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© 1991 Springer-Verlag Berlin Heidelberg

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Vollmar, J., Edler, L. (1991). Tabular Overview of Statistical Methods Proposed for the Analysis of Ames Salmonella Assay Data. In: Hothorn, L. (eds) Statistical Methods in Toxicology. Lecture Notes in Medical Informatics, vol 43. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-48736-1_6

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  • DOI: https://doi.org/10.1007/978-3-642-48736-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-53621-5

  • Online ISBN: 978-3-642-48736-1

  • eBook Packages: Springer Book Archive

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