A Bayesian two-level model for fluctuation assay. Academic Article

abstract

• The fluctuation experiment is an essential tool for measuring microbial mutation rates in the laboratory. When inferring the mutation rate from an experiment, one assumes that the number of mutants in each test tube follows a common distribution. This assumption conceptually restricts the scope of applicability of fluctuation assay. We relax this assumption by proposing a Bayesian two-level model, under which an experiment-wide average mutation rate can be defined. The new model suggests a gamma mixture of the Luria-Delbrck distribution, which coincides with a recently discovered discrete distribution. While the mixture model is of considerable independent interest in fluctuation assay, it also offers a practical Markov chain Monte Carlo method for estimating mutation rates. We illustrate the Bayesian approach with a detailed analysis of an actual fluctuation experiment.

authors

• Zheng, Qi

published proceedings

• Genetica

author list (cited authors)

• Zheng, Q. i.

citation count

• 3

complete list of authors

• Zheng, Qi

publication date

• January 2011

publisher

• Springer Nature  Publisher

published in

• Genetica  Journal

keywords

• Algorithms
• Bayes Theorem
• Models, Genetic
• Models, Statistical
• Mutation Rate

Digital Object Identifier (DOI)

• 10.1007/s10709-012-9639-8

start page

• 1409

end page

• 1416

volume

• 139

issue

• 11-12

URL

• https://www.scopus.com/inward/record.uri?eid=2-s2.0-84860998296&partnerID=40&md5=065f37ce2d95d6204d162d88c220e956