Academic Journal
Calculating the limit of detection for a dilution series.
| Τίτλος: | Calculating the limit of detection for a dilution series. |
|---|---|
| Συγγραφείς: | Sharp JL; Department of Statistics, Colorado State University, Fort Collins, USA. Electronic address: julia.l.sharp@gmail.com., Parker AE; Center for Biofilm Engineering, Montana State University, Bozeman, USA; Department of Mathematical Sciences, Montana State University, Bozeman, USA., Hamilton MA; Department of Mathematical Sciences, Montana State University, Bozeman, USA. |
| Πηγή: | Journal of microbiological methods [J Microbiol Methods] 2023 May; Vol. 208, pp. 106723. Date of Electronic Publication: 2023 Apr 07. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Biomedical Country of Publication: Netherlands NLM ID: 8306883 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1872-8359 (Electronic) Linking ISSN: 01677012 NLM ISO Abbreviation: J Microbiol Methods Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Amsterdam, The Netherlands : Elsevier Biomedical, c1983- |
| Ιατρικοί όροι (MeSH): | Bacteria* , Models, Statistical*, Limit of Detection |
| Περίληψη: | Aims: Microbial samples are often serially diluted to estimate the number of microbes in a sample, whether as colony-forming units of bacteria or algae, plaque forming units of viruses, or cells under a microscope. There are at least three possible definitions for the limit of detection (LOD) for dilution series counts in microbiology. The statistical definition that we explore is that the LOD is the number of microbes in a sample that can be detected with high probability (commonly 0.95). Methods and Results: Our approach extends results from the field of chemistry using the negative binomial distribution that overcomes the simplistic assumption that counts are Poisson. The LOD is a function of statistical power (one minus the rate of false negatives), the amount of overdispersion compared to Poisson counts, the lowest countable dilution, the volume plated, and the number of independent samples. We illustrate our methods using a data set from Pseudomonas aeruginosa biofilms. Conclusions: The techniques presented here can be applied to determine the LOD for any counting process in any field of science whenever only zero counts are observed. Significance and Impact of Study: We define the LOD when counting microbes from dilution experiments. The practical and accessible calculation of the LOD will allow for a more confident accounting of how many microbes can be detected in a sample. (Copyright © 2023 Elsevier B.V. All rights reserved.) |
| Competing Interests: | Declaration of Competing Interest No conflict of interest declared. |
| Contributed Indexing: | Keywords: Microbial counts; Negative binomial; Overdispersion; Poisson |
| Entry Date(s): | Date Created: 20230409 Date Completed: 20230519 Latest Revision: 20230625 |
| Update Code: | 20260130 |
| DOI: | 10.1016/j.mimet.2023.106723 |
| PMID: | 37031895 |
| Βάση Δεδομένων: | MEDLINE |
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