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R package growthrates

Estimate Growth Rates from Experimental Data

The population growth rate is the main indicator of population fitness. This R package provides a collection of methods to determine growth rates from experimental data, in particular from batch experiments and microwell plate reader trials.

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Overview

The package contains basically three methods:

The package can fit data sets of single experiments or complete series containing multiple data sets. Included are functions for extracting estimates and for plotting. The package supports growth models given as numerically solved differential equations. Multi-core computation is used to speed up fitting of parametric models.

Install package from within R or RStudio like any other package, or with:

install.packages("growthrates")

Development version

Install with package devtools:

install.packages("devtools")
library(devtools)
install_github("tpetzoldt/growthrates")

Introduction to the main functions

Writing user defined functions

References

Hall, B. G., H. Acar, A. Nandipati, and M. Barlow. 2014. Growth Rates Made Easy. Mol. Biol. Evol. 31: 232-38. https://dx.doi.org/10.1093/molbev/mst187

Kahm, Matthias, Guido Hasenbrink, Hella Lichtenberg-Frate, Jost Ludwig, and Maik Kschischo. 2010. grofit: Fitting Biological Growth Curves with R. Journal of Statistical Software 33 (7): 1-21. https://dx.doi.org/10.18637/jss.v033.i07

R Core Team. 2015. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org/

Soetaert, Karline, and Thomas Petzoldt. 2010. Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME. Journal of Statistical Software 33 (3): 1-28. https://dx.doi.org/10.18637/jss.v033.i03

Soetaert, Karline, Thomas Petzoldt, and R. Woodrow Setzer. 2010. Solving Differential Equations in R: Package deSolve. Journal of Statistical Software 33 (9): 1-25. https://dx.doi.org/10.18637/jss.v033.i09

Original author

tpetzoldt