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Unbiased Estimation of Mutation Rates under Fluctuating Final Counts

Estimation methods for mutation rates (or probabilities) in Luria-Delbrück fluctuation analysis usually assume that the final number of cells remains constant from one culture to another. We show that this leads to systematically underestimate the mutation rate. Two levels of information on final nu...

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Autores principales: Ycart, Bernard, Veziris, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4079557/
https://www.ncbi.nlm.nih.gov/pubmed/24988217
http://dx.doi.org/10.1371/journal.pone.0101434
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author Ycart, Bernard
Veziris, Nicolas
author_facet Ycart, Bernard
Veziris, Nicolas
author_sort Ycart, Bernard
collection PubMed
description Estimation methods for mutation rates (or probabilities) in Luria-Delbrück fluctuation analysis usually assume that the final number of cells remains constant from one culture to another. We show that this leads to systematically underestimate the mutation rate. Two levels of information on final numbers are considered: either the coefficient of variation has been independently estimated, or the final number of cells in each culture is known. In both cases, unbiased estimation methods are proposed. Their statistical properties are assessed both theoretically and through Monte-Carlo simulation. As an application, the data from two well known fluctuation analysis studies on Mycobacterium tuberculosis are reexamined.
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spelling pubmed-40795572014-07-08 Unbiased Estimation of Mutation Rates under Fluctuating Final Counts Ycart, Bernard Veziris, Nicolas PLoS One Research Article Estimation methods for mutation rates (or probabilities) in Luria-Delbrück fluctuation analysis usually assume that the final number of cells remains constant from one culture to another. We show that this leads to systematically underestimate the mutation rate. Two levels of information on final numbers are considered: either the coefficient of variation has been independently estimated, or the final number of cells in each culture is known. In both cases, unbiased estimation methods are proposed. Their statistical properties are assessed both theoretically and through Monte-Carlo simulation. As an application, the data from two well known fluctuation analysis studies on Mycobacterium tuberculosis are reexamined. Public Library of Science 2014-07-02 /pmc/articles/PMC4079557/ /pubmed/24988217 http://dx.doi.org/10.1371/journal.pone.0101434 Text en © 2014 Ycart, Veziris http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Ycart, Bernard
Veziris, Nicolas
Unbiased Estimation of Mutation Rates under Fluctuating Final Counts
title Unbiased Estimation of Mutation Rates under Fluctuating Final Counts
title_full Unbiased Estimation of Mutation Rates under Fluctuating Final Counts
title_fullStr Unbiased Estimation of Mutation Rates under Fluctuating Final Counts
title_full_unstemmed Unbiased Estimation of Mutation Rates under Fluctuating Final Counts
title_short Unbiased Estimation of Mutation Rates under Fluctuating Final Counts
title_sort unbiased estimation of mutation rates under fluctuating final counts
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4079557/
https://www.ncbi.nlm.nih.gov/pubmed/24988217
http://dx.doi.org/10.1371/journal.pone.0101434
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