Fits the logistic equation to
microbial growth curve data (e.g., repeated absorbance measurements
taken from a plate reader over time). From this fit, a variety of
metrics are provided, including the maximum growth rate,
the doubling time, the carrying capacity, the area under the logistic
curve, and the time to the inflection point. Method described in
Sprouffske and Wagner (2016)

Growthcurver is an R package that fits growth curve data to a standard form of the logistic equation common in ecology and evolution whose parameters (the growth rate, the initial population size, and the carrying capacity) provide meaningful population-level information with straight-forward biological interpretation.

You can install the latest released version from CRAN from within R with

`install.packages("growthcurver")`

You can install the latest development version from github with

`# install devtools first if you don't already have the packageinstall.packages("devtools") # then install growthcurverdevtools::install_github("sprouffske/growthcurver")`

The easiest way to get started with growthcurver is to work through the examples in the vignette. In the vignette, you can find information on

- What your input data should look like
- How to use growthcurver to get summary metrics on a single growth curve sample
- How to use growthcurver to get summary metrics on an entire plate of growth curves
- What those metrics mean and some best practices for quality control

You can find the vignette at bit.ly/1p7w6dJ.

This code loads the `growthcurver`

package and some sample data. Then, it calls `SummarizeGrowth`

to do the analysis.

`library(growthcurver) # load the packaged <- growthdata # load some sample, simulated datagc_fit <- SummarizeGrowth(d$time, d$A1) # do the analysisplot(gc_fit) # plot your data and the best fitgc_fit # view some returned metrics`