Fluctuation analysis: can estimates be trusted?
Open accessAbstract
The estimation of mutation rates and relative fitnesses in fluctuation analysis is based on the unrealistic hypothesis that the single-cell times to division are exponentially distributed. Using the classical Luria-Delbrück distribution outside its modelling hypotheses induces an important bias on the estimation of the relative fitness. The model is extended here to any division time distribution. Mutant counts follow a generalization of the Luria-Delbrück distribution, which depends on the mean number of mutations, the relative fitness of normal cells compared to mutants, and the division time distribution of mutant cells. Empirical probability generating function techniques yield precise estimates both of the mean number of mutations and the relative fitness of normal cells compared to mutants. In the case where no information is available on the division time distribution, it is shown that the estimation procedure using constant division times yields more reliable results. Numerical results both on observed and simulated data are reported.
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Ycart (2013) suggested using a cell life distribution derived from a particular yeast study as a universal cell life distribution.
“Still, Ycart (2013) suggested using a cell life distribution derived from a particular yeast study as a universal cell life distribution.”
From rSalvador: An R Package for the Fluctuation Experiment (2017) · cites this paper as Ycart 2013
The Introduction (page not supplied) explicitly rejects a universal division-time distribution, saying it depends on species, strain, and experimental conditions. Ycart fitted three distributions to observations of Bacterium aerogenes, not yeast, and used them as simulation benchmarks—not as a universal cell-life distribution. (LLM, conf=0.92)
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Experimental — accuracy not yet measuredA simulation study by Ycart (2013) reached essentially the same conclusion.
“A simulation study by Ycart (2013) reached essentially the same conclusion.”
From rSalvador: An R Package for the Fluctuation Experiment (2017) · cites this paper as Ycart 2013
The Results > Simulation experiments section describes a simulation study and concludes that the exponential model overestimates ρ while the Dirac model estimates it more accurately; both estimate α correctly. The citing sentence does not identify the earlier conclusion, so whether Ycart reached essentially the same one cannot be verified from the claim provided. (LLM, conf=0.78)
Experimental — accuracy not yet measuredIn the reanalysis of the experiments of Luria and Delbrück (1943), Hamon and Ycart (2012, Table 1) and Ycart (2013, Table 3) ignored the effects of partial plating.
“For example, in the reanalysis of the experiments of Luria and Delbrück (1943), Hamon and Ycart (2012, Table 1) and Ycart (2013, Table 3) ignored the effects of partial plating.”
From rSalvador: An R Package for the Fluctuation Experiment (2017) · cites this paper as Ycart (2013)
The Results section (‘Published data sets’; page unavailable) confirms that Ycart reanalysed Luria and Delbrück’s experiments and reported the results in Table 3. It says the estimates used exponential and Dirac models, but our copy does not explicitly state whether the analysis accounted for partial plating; that part of the claim is not established. (LLM, conf=0.78)
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References 59 · Cited by 15
- Authors
- Ycart, B.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Ycart, Bernard
- Venue
- PLoS ONE
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-12-09
- Volume
- 8
- Issue
- 12
- Pages
- e80958
- ISSN
- 1932-6203 (ISSN-L)
- PMC
- PMC3857183
- OpenAlex
- W1970489379
- Cited by
- 15
- References
- 59
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2021: 1 · 2018: 2 · 2017: 5 · 2015: 2 · 2014: 2
- FWCI
- 0.88
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS ONE (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- HAL (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Funders
- Agence Nationale de la Recherche (ANR-11-LABX-0068)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Physical Sciences › Mathematics › Mathematical Physics › Stochastic processes and statistical mechanics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mathematical and Theoretical Epidemiology and Ecology Models
- Keywords
- fluctuation analysis, mutation rate estimation, probability generating function, estimation bias
- MeSH terms
- Algorithms, Models, Theoretical, Mutation
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