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. 2000 Nov;156(3):1411–1418. doi: 10.1093/genetics/156.3.1411

Bayesian analysis of mutational spectra.

D B Dunson 1, K R Tindall 1
PMCID: PMC1461324  PMID: 11063712

Abstract

Studies that examine both the frequency of gene mutation and the pattern or spectrum of mutational changes can be used to identify chemical mutagens and to explore the molecular mechanisms of mutagenesis. In this article, we propose a Bayesian hierarchical modeling approach for the analysis of mutational spectra. We assume that the total number of independent mutations and the numbers of mutations falling into different response categories, defined by location within a gene and/or type of alteration, follow binomial and multinomial sampling distributions, respectively. We use prior distributions to summarize past information about the overall mutation frequency and the probabilities corresponding to the different mutational categories. These priors can be chosen on the basis of data from previous studies using an approach that accounts for heterogeneity among studies. Inferences about the overall mutation frequency, the proportions of mutations in each response category, and the category-specific mutation frequencies can be based on posterior distributions, which incorporate past and current data on the mutant frequency and on DNA sequence alterations. Methods are described for comparing groups and for assessing dose-related trends. We illustrate our approach using data from the literature.

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Selected References

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  1. Adams W. T., Skopek T. R. Statistical test for the comparison of samples from mutational spectra. J Mol Biol. 1987 Apr 5;194(3):391–396. doi: 10.1016/0022-2836(87)90669-3. [DOI] [PubMed] [Google Scholar]
  2. Cariello N. F., Douglas G. R., Dycaico M. J., Gorelick N. J., Provost G. S., Soussi T. Databases and software for the analysis of mutations in the human p53 gene, the human hprt gene and both the lacI and lacZ gene in transgenic rodents. Nucleic Acids Res. 1997 Jan 1;25(1):136–137. doi: 10.1093/nar/25.1.136. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Carr G. J., Gorelick N. J. Mutational spectra in transgenic animal research: data analysis and study design based upon the mutant or mutation frequency. Environ Mol Mutagen. 1996;28(4):405–413. doi: 10.1002/(SICI)1098-2280(1996)28:4<405::AID-EM15>3.0.CO;2-J. [DOI] [PubMed] [Google Scholar]
  4. Carr G. J., Gorelick N. J. Statistical design and analysis of mutation studies in transgenic mice. Environ Mol Mutagen. 1995;25(3):246–255. doi: 10.1002/em.2850250311. [DOI] [PubMed] [Google Scholar]
  5. Carr G. J., Gorelick N. J. Statistical tests of significance in transgenic mutation assays: considerations on the experimental unit. Environ Mol Mutagen. 1994;24(4):276–282. doi: 10.1002/em.2850240404. [DOI] [PubMed] [Google Scholar]
  6. Foster P. L., Eisenstadt E., Cairns J. Random components in mutagenesis. Nature. 1982 Sep 23;299(5881):365–367. doi: 10.1038/299365a0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Fung K. Y., Krewski D., Rao J. N., Scott A. J. Tests for trend in developmental toxicity experiments with correlated binary data. Risk Anal. 1994 Aug;14(4):639–648. doi: 10.1111/j.1539-6924.1994.tb00277.x. [DOI] [PubMed] [Google Scholar]
  8. Fung K. Y., Lin X., Krewski D. Use of generalized linear mixed models in analyzing mutant frequency data from the transgenic mouse assay. Environ Mol Mutagen. 1998;31(1):48–54. doi: 10.1002/(sici)1098-2280(1998)31:1<48::aid-em7>3.0.co;2-7. [DOI] [PubMed] [Google Scholar]
  9. Haseman J. K., Huff J., Boorman G. A. Use of historical control data in carcinogenicity studies in rodents. Toxicol Pathol. 1984;12(2):126–135. doi: 10.1177/019262338401200203. [DOI] [PubMed] [Google Scholar]
  10. Nishino H., Schaid D. J., Buettner V. L., Haavik J., Sommer S. S. Mutation frequencies but not mutant frequencies in Big Blue mice fit a Poisson distribution. Environ Mol Mutagen. 1996;28(4):414–417. doi: 10.1002/(SICI)1098-2280(1996)28:4<414::AID-EM16>3.0.CO;2-I. [DOI] [PubMed] [Google Scholar]
  11. Piegorsch W. W., Bailer A. J. Statistical approaches for analyzing mutational spectra: some recommendations for categorical data. Genetics. 1994 Jan;136(1):403–416. doi: 10.1093/genetics/136.1.403. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Piegorsch W. W., Lockhart A. C., Carr G. J., Margolin B. H., Brooks T., Douglas G. R., Liegibel U. M., Suzuki T., Thybaud V., van Delft J. H. Sources of variability in data from a positive selection lacZ transgenic mouse mutation assay: an interlaboratory study. Mutat Res. 1997 Feb 14;388(2-3):249–289. doi: 10.1016/s1383-5718(96)00123-4. [DOI] [PubMed] [Google Scholar]
  13. Piegorsch W. W., Lockhart A. M., Margolin B. H., Tindall K. R., Gorelick N. J., Short J. M., Carr G. J., Thompson E. D., Shelby M. D. Sources of variability in data from a lacI transgenic mouse mutation assay. Environ Mol Mutagen. 1994;23(1):17–31. doi: 10.1002/em.2850230105. [DOI] [PubMed] [Google Scholar]
  14. Prentice R. L., Smythe R. T., Krewski D., Mason M. On the use of historical control data to estimate dose response trends in quantal bioassay. Biometrics. 1992 Jun;48(2):459–478. [PubMed] [Google Scholar]
  15. Roff D. A., Bentzen P. The statistical analysis of mitochondrial DNA polymorphisms: chi 2 and the problem of small samples. Mol Biol Evol. 1989 Sep;6(5):539–545. doi: 10.1093/oxfordjournals.molbev.a040568. [DOI] [PubMed] [Google Scholar]
  16. de Boer J. G., Mirsalis J. C., Provost G. S., Tindall K. R., Glickman B. W. Spectrum of mutations in kidney, stomach, and liver from lacI transgenic mice recovered after treatment with tris(2,3-dibromopropyl)phosphate. Environ Mol Mutagen. 1996;28(4):418–423. doi: 10.1002/(SICI)1098-2280(1996)28:4<418::AID-EM17>3.0.CO;2-I. [DOI] [PubMed] [Google Scholar]

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