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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.

News

  • Release of version 0.8.4 to CRAN
  • improved robustness and error checking of the "easylinear"" method
  • Corrected parametrization of Gompertz models (0.8.2)
  • Simplified handling of log-transformed parametric models (v. 0.8.1)
  • Several small changes and improvements
  • Added predict-methods
  • Presentation at the useR!2017 conference in Brussels

Overview

The package contains basically three methods:

  • fit a linear regression to a subset of data with the steepest log-linear increase (a method, similar to Hall et al., 2014),

  • fit parametric nonlinear models to the complete data set, where the model functions can be given either in closed form or as numerically solved (system of) differential equation(s),

  • use maximum of the 1st derivative of a smoothing spline with log-transformed y-values (similar to Kahm et al., 2010).

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.

Download and Installation of the release version (recommended)

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

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Version

Install

install.packages('growthrates')

Monthly Downloads

466

Version

0.8.4

License

GPL (>= 2)

Issues

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Maintainer

Last Published

October 3rd, 2022

Functions in growthrates (0.8.4)

all_growthmodels

Fit Nonlinear Growth Models to Data Frame
fit_easylinear

Fit Exponential Growth Model with a Heuristic Linear Method
antibiotic

Plate Reader Data of Bacterial Growth
extcoef_logistic

Extended Set of Coefficients of a Logistic Growth Model
all_splines

Fit Exponential Growth Model with Smoothing Spline
bactgrowth

Plate Reader Data of Bacterial Growth
grow_baranyi

The Baranyi and Roberts Growth Model
ode_genlogistic

Generalized Logistic Growth Model
grow_exponential

Exponential Growth Model
grow_huang

Growth Model According to Huang
rsquared

Additional Generic Functions
grow_gompertz

Growth Model According to Gompertz
function_growthmodel-class

Union Class of Growth Model or Function
grow_gompertz2

Growth Model According to Gompertz
fit_spline

Fit Exponential Growth Model with Smoothing Spline
grow_logistic

Logistic Growth Model
multisplit

Split Data Frame into Multiple Groups
grow_richards

Growth Model According to Richards
ode_twostep

Twostep Growth Model
rsquared,growthrates_fit-method

Accessor Methods of Package growthrates.
growthrates_fit-class

S4 Classes of Package growthrates
lm_or_NULL-class

Union Class of Linear Model or NULL
growthmodel

Create a User-defined Parametric Growth Model
growthmodel-class

Class of Growth Model Functions
lm_window

Fit Exponential Growth Model with a Heuristic Linear Method
growthrates-package

tools:::Rd_package_title("growthrates")
parse_formula_nonlin

Simple Formula Interface for Grouped Nonlinear Functions
names.growthmodel

Get Names Attributes of Growth Models
plot

Plot Model Fits
parse_formula

Simple Formula Interface
predict,growthrates_fit-method

Model Predictions for growthrates Fits
fit_growthmodel

Fit Nonlinear Parametric Growth Model
all_easylinear

Easy Growth Rates Fit to data Frame
[,multiple_fits,ANY,missing-method

Extract or Replace Parts of a 'multiple_fits' Object
cost

Cost Function for Nonlinear Fits