SummarizeGrowthByPlate: Summarize Growth Curves
In growthcurver: Simple Metrics to Summarize Growth Curves

Description Usage Arguments Details Value See Also Examples

View source: R/summarize-growth-by-plate.R

This function finds the parameters that describe the input data's growth for a plate of growth curves. It does so by fitting the logistic curve to your growth curve measurements.

SummarizeGrowthByPlate(
  plate,
  t_trim = 0,
  bg_correct = "min",
  plot_fit = FALSE,
  plot_file = "growthcurver.pdf"
)

`plate`	A data.table with at least two columns. One column contains timepoints that measurements were taken (e.g., hours) and must be named "time". An optional column can be included called "blank" that contains the blank readings for background correction (make sure to select the "blank" bg_correct option if you provide a blank column). Each remaining column contains the absorbance readings from a single well in a plate.
`t_trim`	Measurements taken after this time should not be included in fitting the curve. If stationary phase is variable, this may give you a better fit. A value of 0 means no trimming. Defaults to no trimming (0).
`bg_correct`	The background correction method to use. No background correction is performed for "none". Specifying "min" subtracts the smallest value in a column from all the rows in that column, and specifying "blank" subtracts the values from the blank vector from the data_n vector.
`plot_fit`	TRUE if you want to generate a pdf file that plots all columns provided in the plate along with the growthcurver's fit. The default value is FALSE, which generates no plots.
`plot_file`	The name of the file to save the plots to if you set plot_fit to TRUE. The default file is called "growthcurver.pdf".

The logistic curve equation is

N_t = N_0 K / (N_0 + (K - N_0) exp(-rt))

where N_t is the number of cells (or the absorbance reading) at time t, N_0 is the initial cell count (or absorbance reading), K is the carrying capacity, and r is the growth rate.

The fitness proxies returned are the parameters of the logistic equation and the area under the curve (a measure that integrates the effects of N_0, K, and r). See gcfit for more documentation on these.

This method expects that your data adhere to a particular format.

The data are provided in a data.frame
One column in the data.frame is named "time" and contains the time measurements (e.g., hours).
Each remaining column contains the readings from a single well in a plate reader. The name of the column will be used to identify the sample in the output data.
There are no missing values or non-numeric data in the data.frame.

A data.table containing the summary metrics and residual error from the fit of the logistic curve to the data. The names of the input columns are used to identify each well (or sample).

See the accompanying Vignette for an example of how to use and interpret SummarizeGrowthByPlate. https://CRAN.R-project.org/package=growthcurver/vignettes/Growthcurver-vignette.html

#Get the summary metrics for the entire plate of sample data provided
#with the Growthcurver package

#First, load the example data provided with Growthcurver. Note that there is
#a column named "time" -- this is necessary for Growthcurver to know which
#column contains the time measurements. In this dataset, the repeated
#measurements from a single well in a plate are given in a column of data.

myPlate <- growthdata
names(myPlate)

#Next, do the analysis for all the columns.
summary_plate <- SummarizeGrowthByPlate(plate = myPlate)

#The output is a data frame that contains the information on the best
#fit for each column of data.
head(summary_plate)      # Use head to display just the first few rows