Bayesian analysis of mutational spectra.

Journal Article (Journal Article)

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.

Full Text

Duke Authors

Cited Authors

  • Dunson, DB; Tindall, KR

Published Date

  • November 2000

Published In

Volume / Issue

  • 156 / 3

Start / End Page

  • 1411 - 1418

PubMed ID

  • 11063712

Pubmed Central ID

  • PMC1461324

Electronic International Standard Serial Number (EISSN)

  • 1943-2631

International Standard Serial Number (ISSN)

  • 0016-6731

Digital Object Identifier (DOI)

  • 10.1093/genetics/156.3.1411


  • eng