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Fit curves

Source: R/fit_curves.R
fit_curves.Rd

Fit GR and RV curves from a data.table.

Usage

fit_curves(
  df_,
  series_identifiers,
  e_0 = 1,
  GR_0 = 1,
  n_point_cutoff = 4,
  range_conc = c(0.005, 5),
  force_fit = FALSE,
  pcutoff = 0.05,
  cap = 0.1,
  normalization_type = c("GR", "RV")
)

Arguments

df_

data.table containing data to fit. See details.

series_identifiers

character vector of the column names in data.table whose combination represents a unique series for which to fit curves.

e_0

numeric value representing the x_0 value for the RV curve. Defaults to 1.

GR_0

numeric value representing the x_0 value for the GR curve. Defaults to 1.

n_point_cutoff

integer of how many points should be considered the minimum required to try to fit a curve. Defaults to 4.

range_conc

numeric vector of length 2 indicating the lower and upper concentration ranges. Defaults to c(5e-3, 5). See details.

force_fit

boolean indicating whether or not to force a constant fit. Defaults to FALSE.

pcutoff

numeric of pvalue significance threshold above or equal to which to use a constant fit. Defaults to 0.05.

cap

numeric value capping norm_values to stay below (x_0 + cap). Defaults to 0.1.

normalization_type

character vector of types of curves to fit. Defaults to c("GR", "RV").

Value

data.table of fit parameters as specified by the normalization_type.

Details

The df_ expects the following columns:

  • RelativeViability normalized relative viability values (if normalization_type includes "RV")

  • GRvalue normalized GR values (if normalization_type includes "GR")

The range_conc is used to calculate the x_AOC_range statistic. The purpose of this statistic is to enable comparison across different experiments with slightly different concentration ranges.

Examples

df_ <- data.table::data.table(Concentration = c(0.001, 0.00316227766016838, 
0.01, 0.0316227766016838),
x_std = c(0.1, 0.1, 0.1, 0.1), normalization_types = c("RV", "RV", "RV", "RV"),
x = c(0.9999964000144, 0.999964001439942, 0.999640143942423, 0.996414342629482))

fit_curves(df_, "Concentration", normalization_type = "RV")
#>       x_mean        x_AOC x_AOC_range  xc50     x_max      ec50     x_inf   x_0
#>        <num>        <num>       <num> <num>     <num>     <num>     <num> <num>
#> 1: 0.9994663 0.0005336782  0.07214082   Inf 0.9964143 0.2030077 0.8446057     1
#>           h    r2      p_value          rss x_sd_avg               fit_type
#>       <num> <num>        <num>        <num>    <num>                 <char>
#> 1: 2.014503     1 3.799066e-08 3.425795e-13      0.1 DRC3pHillFitModelFixS0
#>    maxlog10Concentration N_conc normalization_type fit_source
#>                    <num>  <int>             <char>     <char>
#> 1:                  -1.5      4                 RV        gDR