Microbial lag calculator: A shiny‐based application and an R package for calculating the duration of microbial lag phase

Author:

Smug Bogna J.1ORCID,Opalek Monika2ORCID,Necki Maks3,Wloch‐Salamon Dominika2ORCID

Affiliation:

1. Malopolska Centre of Biotechnology Jagiellonian University Kraków Poland

2. Faculty of Biology, Institute of Environmental Sciences Jagiellonian University Krakow Poland

3. Department of Computational Biophysics and Bioinformatics, Faculty of Biochemistry, Biophysics and Biotechnology Jagiellonian University Krakow Poland

Abstract

Abstract The duration of lag phase can be used as an organismal fitness marker; however, it is often underreported as its estimation may be challenging and method and parameters dependent. Moreover, there are no publicly available tools to calculate lag duration by different methods. We developed a shiny‐based web application (https://microbialgrowth.shinyapps.io/lag_calulator/) where the lag duration can be calculated based on the user‐specified growth curve data, and for various explicitly specified methods, parameters and data preprocessing techniques. Additionally, we release an R package ‘miLAG’ that can be further customised and developed. We also describe in short the assumptions, advantages and disadvantages of the most popular lag calculation methods and propose a decision tree to choose a method most suited to one's data. Finally, we show some working examples of how to calculate lag duration using our shiny server.

Funder

Narodowa Agencja Wymiany Akademickiej

Narodowe Centrum Nauki

Uniwersytet Jagielloński w Krakowie

Publisher

Wiley

Subject

Ecological Modeling,Ecology, Evolution, Behavior and Systematics

Reference17 articles.

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2. Baty F. &Delignette‐Muller M.‐L.(2013).nlsMicrobio: Data sets and nonlinear regression models dedicated to predictive microbiology.

3. Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources

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