QurvE (version 1.1.1)

fl.drFit: Fit a biosensor model (Meyer et al., 2019) to response vs. concentration data

Description

Fit a biosensor model (Meyer et al., 2019) to response vs. concentration data

Usage

fl.drFit(
  flTable,
  control = fl.control(dr.method = "model", dr.parameter = "max_slope.spline")
)

Value

An object of class drFit.

raw.data

Data that passed to the function as flTable.

drTable

Dataframe containing condition identifiers, fit options, and results of the dose-response analysis.

drFittedModels

List of all drFitModel objects generated by the call of fl.drFitModel for each distinct experiment.

control

Object of class fl.control created with the call of fl.control.

Arguments

flTable

A dataframe containing the data for the dose-response model estimation. Such table of class flTable can be obtained by running flFit with dr.method = 'model' as argument in the fl.control object.

control

A fl.control object created with fl.control, defining relevant fitting options.

dr.method

(Character) Perform either a smooth spline fit on response parameter vs. concentration data ('spline') or fit a biosensor response model with 'model' (proposed by Meyer et al., 2019).

dr.parameter

(Character or numeric) The response parameter in the output table to be used for creating a dose response curve. See fl.drFit for further details. Default: 'max_slope.spline', which represents the maximum slope of the spline fit Typical options include: 'max_slope.linfit', 'dY.linfit', 'max_slope.spline', and 'dY.spline'.

Details

Common response parameters used in dose-response analysis:

Linear fit:
- max_slope.linfit: Fluorescence increase rate
- lambda.linfit: Lag time
- dY.linfit: Maximum Fluorescence - Minimum Fluorescence
- A.linfit: Maximum fluorescence

Spline fit:
- max_slope.spline: Fluorescence increase rate
- lambda.spline: Lag time
- dY.spline: Maximum Fluorescence - Minimum Fluorescence
- A.spline: Maximum fluorescence
- integral.spline: Integral

Parametric fit:
- max_slope.model: Fluorescence increase rate
- lambda.model: Lag time
- dY.model: Maximum Fluorescence - Minimum Fluorescence
- A.model: Maximum fluorescence
- integral.model: Integral'

References

Meyer, A.J., Segall-Shapiro, T.H., Glassey, E. et al. Escherichia coli “Marionette” strains with 12 highly optimized small-molecule sensors. Nat Chem Biol 15, 196–204 (2019). DOI: 10.1038/s41589-018-0168-3

Examples

# \donttest{
# Load example dataset
input <- read_data(data.fl = system.file('lac_promoters_fluorescence.txt', package = 'QurvE'),
                   csvsep.fl = "\t")

# Run fluorescence curve analysis workflow
fitres <- flFit(fl_data = input$fluorescence,
                time = input$time,
                parallelize = FALSE,
                control = fl.control(x_type = 'time', norm_fl = FALSE,
                                     suppress.messages = TRUE))

# Perform dose-response analysis
drFit <- fl.drFit(flTable = fitres$flTable,
                  control = fl.control(dr.method = 'model',
                                       dr.parameter = 'max_slope.linfit'))

# Inspect results
summary(drFit)
plot(drFit)
# }