Literature DB >> 18832356

A simple formula for obtaining markedly improved mutation rate estimates.

Philip Gerrish1.   

Abstract

In previous work by M. E. Jones and colleagues, it was shown that mutation rate estimates can be improved and corresponding confidence intervals tightened by following a very easy modification of the standard fluctuation assay: cultures are grown to a larger-than-usual final density, and mutants are screened for in only a fraction of the culture. Surprisingly, this very promising development has received limited attention, perhaps because there has been no efficient way to generate the predicted mutant distribution to obtain non-moment-based estimates of the mutation rate. Here, the improved fluctuation assay discovered by Jones and colleagues is made amenable to quantile-based, likelihood, and other Bayesian methods by a simple recursion formula that efficiently generates the entire mutant distribution after growth and dilution. This formula makes possible a further protocol improvement: grow cultures as large as is experimentally possible and severely dilute before plating to obtain easily countable numbers of mutants. A preliminary look at likelihood surfaces suggests that this easy protocol adjustment gives markedly improved mutation rate estimates and confidence intervals.

Mesh:

Year:  2008        PMID: 18832356      PMCID: PMC2581975          DOI: 10.1534/genetics.108.091777

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


  21 in total

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Authors:  M E Jones; S M Thomas; K Clarke
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Authors:  F M Stewart
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Authors:  F M Stewart; D M Gordon; B R Levin
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8.  An algorithm accounting for plating efficiency in estimating spontaneous mutation rates.

Authors:  M E Jones
Journal:  Comput Biol Med       Date:  1993-11       Impact factor: 4.589

9.  Luria-Delbrück fluctuation experiments; accounting simultaneously for plating efficiency and differential growth rate.

Authors:  M E Jones
Journal:  J Theor Biol       Date:  1994-02-07       Impact factor: 2.691

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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