Literature DB >> 22395601

A Bayesian two-level model for fluctuation assay.

Qi Zheng1.   

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-Delbrück 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.

Mesh:

Year:  2012        PMID: 22395601     DOI: 10.1007/s10709-012-9639-8

Source DB:  PubMed          Journal:  Genetica        ISSN: 0016-6707            Impact factor:   1.082


  13 in total

Review 1.  Progress of a half century in the study of the Luria-Delbrück distribution.

Authors:  Q Zheng
Journal:  Math Biosci       Date:  1999 Nov-Dec       Impact factor: 2.144

Review 2.  Determining mutation rates in bacterial populations.

Authors:  W A Rosche; P L Foster
Journal:  Methods       Date:  2000-01       Impact factor: 3.608

3.  Statistical and algorithmic methods for fluctuation analysis with SALVADOR as an implementation.

Authors:  Qi Zheng
Journal:  Math Biosci       Date:  2002-04       Impact factor: 2.144

4.  Methods for determining spontaneous mutation rates.

Authors:  Patricia L Foster
Journal:  Methods Enzymol       Date:  2006       Impact factor: 1.600

5.  Mutations of Bacteria from Virus Sensitivity to Virus Resistance.

Authors:  S E Luria; M Delbrück
Journal:  Genetics       Date:  1943-11       Impact factor: 4.562

6.  A modified Luria-Delbrück fluctuation assay for estimating and comparing mutation rates.

Authors:  G J Crane; S M Thomas; M E Jones
Journal:  Mutat Res       Date:  1996-07-22       Impact factor: 2.433

7.  Bayesian procedures for the estimation of mutation rates from fluctuation experiments.

Authors:  G Asteris; S Sarkar
Journal:  Genetics       Date:  1996-01       Impact factor: 4.562

8.  The distribution of the numbers of mutants in bacterial populations.

Authors:  D E LEA; C A COULSON
Journal:  J Genet       Date:  1949-12       Impact factor: 1.166

9.  Modeling and measurement of the spontaneous mutation rate in mammalian cells.

Authors:  T G Rossman; E I Goncharova; A Nádas
Journal:  Mutat Res       Date:  1995-04       Impact factor: 2.433

10.  Luria-Delbrück fluctuation experiments: design and analysis.

Authors:  M E Jones; S M Thomas; A Rogers
Journal:  Genetics       Date:  1994-03       Impact factor: 4.562

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