caa a22 4500 445845783 CHVBK 20180317145358.0 cr unu---uuuuu 170323e20111201xx s 000 0 eng 10.1007/s10709-012-9639-8 doi (NATIONALLICENCE)springer-10.1007/s10709-012-9639-8 Zheng Qi Department of Epidemiology and Biostatistics, School of Rural Public Health, Texas A&M Health Science Center, 77843, College Station, TX, USA aut A Bayesian two-level model for fluctuation assay [Elektronische Daten] [Qi Zheng] 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. Springer Science+Business Media B.V., 2012 Mutation rate nationallicence Fluctuation experiment nationallicence Bayesian model nationallicence Genetica Springer Netherlands 139/11-12(2011-12-01), 1409-1416 0016-6707 139:11-12<1409 2011 139 10709 https://doi.org/10.1007/s10709-012-9639-8 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10709-012-9639-8 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Zheng Qi Department of Epidemiology and Biostatistics, School of Rural Public Health, Texas A&M Health Science Center, 77843, College Station, TX, USA aut NATIONALLICENCE 773 0- Genetica Springer Netherlands 139/11-12(2011-12-01), 1409-1416 0016-6707 139:11-12<1409 2011 139 10709 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer