create model for standard curve of a certain antibody — create_standard_curve_model

function for now uses the nplr package to fit the model. The model is fitted using the formula:

$$y = B + \fracT - B(1 + 10^b*(x_mid - x))^s$$, where:

$y$ is the predicted value, MFI in our case,
$x$ is the independent variable, dilution in our case,
$B$ is the bottom plateau - the right horizontal asymptote,
$T$ is the top plateau - the left horizontal asymptote,
$b$ is the slope of the curve at the inflection point,
$x_mid$ is x-coordinate at the inflection point,
$s$ is the assymetric coefficient. This equation is refered as the Richards' equation. More information about the model can be found in the nplr package documentation. By default, nplr model transforms the x values using the log10 function.

create_standard_curve_model_antibody(
  plate,
  antibody_name,
  data_type = "Median",
  npars = 5,
  verbose = TRUE
)

Arguments

plate: Plate object
antibody_name: Name of the antibody for which we want to create the model
data_type: Data type of the value we want to use to fit the model - the same datatype as in the plate file. By default equals to Median
npars: Number of parameters to fit the model, by default 5 - the maximum value. npars also accepts a number of parameters to fit the model - an integer between 2 and 5, accepts also value "all", which chooses best models from those with different number of parameters.
verbose: If TRUE prints messages, TRUE by default

nplr object with the model