Fit input data to a logistic growth function

Source: R/estimate_growth_rate.R

estimate_growth_rate fits the input OD data to a logistic growth function. It differs from growthcurver by fitting the logged data and function. It can also subtract an estimated value for blank wells (taking the minimum across all readings), and takes into account measurements only after t_start.

estimate_growth_rate(
  OD_data,
  t_start = 0,
  t_col = "time",
  blank_tf = T,
  verbose = T
)

Arguments

OD_data

Dataframe of OD data. Expects a column for the time (t_col), and will interpret all other columns as OD data for different samples (identified by their column name).
t_start

Earliest possible time point from which to start the fit.
t_col

Name of the time column (defaults to 'time').
blank_tf

Boolean. Should a blank value be subtracted?
verbose

Boolean. Should warnings be returned?

Value

Dataframe of estimated growth parameters. Contains columns name, carrying_cap, growth_rate, N0, t_min and t_stat.

Details

*Note*: this function is not as thoroughly tested as those to estimate conjugation rates, and is primarily included for convenience. We generally recommend using a dedicated package to estimate growth rates.

See also

Other growth rate functions: .logist(), get_growth_fit_for_plot()

Examples

estimate_growth_rate(growth_example, t_start = 1, t_col = 'Time_h')

#>           name carrying_cap growth_rate      N0 t_min t_stat
#> 1     Donor_OD       0.2903      0.4903 0.08252 1.297  3.863
#> 2 Recipient_OD       0.1613      1.6970 0.03780 1.297  2.152