Model {PvSTATEM}R Documentation

Logistic regression model for the standard curve

Description

This model uses the nplr package to fit the model. The model is fitted using the formula:

y = B + \frac{T - B}{(1 + 10^{b \cdot (x_{mid} - x)})^s},

where:

This equation is referred to as the Richards' equation. More information about the model can be found in the nplr package documentation.

Public fields

analyte

(character(1))
Name of the analyte for which the model was fitted

dilutions

(numeric())
Dilutions used to fit the model

mfi

(numeric())
MFI values used to fit the model

mfi_min

(numeric(1))
Minimum MFI used for scaling MFI values to the range [0, 1]

mfi_max

(numeric(1))
Maximum MFI used for scaling MFI values to the range [0, 1]

model

(nplr)
Instance of the nplr model fitted to the data

log_dilution

(logical())
Indicator should the dilutions be transformed using the log10 function

log_mfi

(logical())
Indicator should the MFI values be transformed using the log10 function

scale_mfi

(logical())
Indicator should the MFI values be scaled to the range [0, 1]

Active bindings

top_asymptote

(numeric(1))
The top asymptote of the logistic curve

bottom_asymptote

(numeric(1))
The bottom asymptote of the logistic curve

Methods

Public methods


Method new()

Create a new instance of Model R6 class

Usage
Model$new(
  analyte,
  dilutions,
  mfi,
  npars = 5,
  verbose = TRUE,
  log_dilution = TRUE,
  log_mfi = TRUE,
  scale_mfi = TRUE,
  mfi_min = NULL,
  mfi_max = NULL
)
Arguments
analyte

(character(1))
Name of the analyte for which the model was fitted.

dilutions

(numeric())
Dilutions used to fit the model

mfi

MFI (numeric())
values used to fit the model

npars

(numeric(1))
Number of parameters to use in the model

verbose

(logical())
If TRUE prints messages, TRUE by default

log_dilution

(logical())
If TRUE the dilutions are transformed using the log10 function, TRUE by default

log_mfi

(logical())
If TRUE the MFI values are transformed using the log10 function, TRUE by default

scale_mfi

(logical())
If TRUE the MFI values are scaled to the range [0, 1], TRUE by default

mfi_min

(numeric(1))
Enables to set the minimum MFI value used for scaling MFI values to the range [0, 1]. Use values before any transformations (e.g., before the log10 transformation)

mfi_max

(numeric(1))
Enables to set the maximum MFI value used for scaling MFI values to the range [0, 1]. Use values before any transformations (e.g., before the log10 transformation)


Method predict()

Predict the dilutions from the MFI values

Usage
Model$predict(mfi)
Arguments
mfi

(numeric())
MFI values for which we want to predict the dilutions.

Returns

(data.frame())
Dataframe with the predicted dilutions, MFI values, and the 97.5% confidence intervals The columns are named as follows:


Method get_plot_data()

Data that can be used to plot the standard curve.

Usage
Model$get_plot_data()
Returns

(data.frame())
Prediction dataframe for scaled MFI (or logMFI) values in the range [0, 1]. Columns are named as in the predict method


Method print()

Function prints the basic information about the model such as the number of parameters or samples used

Usage
Model$print()

Method clone()

The objects of this class are cloneable with this method.

Usage
Model$clone(deep = FALSE)
Arguments
deep

Whether to make a deep clone.

Examples

plate_file <- system.file("extdata", "CovidOISExPONTENT.csv", package = "PvSTATEM")
layout_file <- system.file("extdata", "CovidOISExPONTENT_layout.csv", package = "PvSTATEM")
plate <- read_luminex_data(plate_file, layout_filepath = layout_file)
model <- create_standard_curve_model_analyte(plate, "S2", log_mfi = TRUE)
print(model)


[Package PvSTATEM version 0.0.4 Index]