fl.drFitModel: Perform a biosensor model fit on response vs. concentration...
In QurvE: Robust and User-Friendly Analysis of Growth and Fluorescence Curves

fl.drFitModel

R Documentation

Perform a biosensor model fit on response vs. concentration data of a single sample.

Description

fl.drFitModel fits the biosensor model proposed by Meyer et al. (2019) to the provided response (e.g., max_slope.spline vs. concentration data to determine the leakiness, sensitivity, induction fold-change, and cooperativity.

Usage

fl.drFitModel(conc, test, drID = "undefined", control = fl.control())

Arguments

`conc`	Vector of concentration values.
`test`	Vector of response parameter values of the same length as `conc`.
`drID`	(Character) The name of the analyzed condition
`control`	A `fl.control` object created with `fl.control`, defining relevant fitting options.

Value

A drFitFLModel object.

`raw.conc`	Raw data provided to the function as `conc`.
`raw.test`	Raw data for the response parameter provided to the function as `test`.
`drID`	(Character) Identifies the tested condition
`fit.conc`	Fitted concentration values.
`fit.test`	Fitted response values.
`model`	`nls` object generated by the `nlsLM` function.
`parameters`	List of parameters estimated from dose response curve fit.

yEC50: Response value related to EC50.
y.min: Minimum fluorescence ('leakiness', if lowest concentration is 0).
y.max: Maximum fluorescence.
fc: Fold change (y.max divided by y.min).
K: Concentration at half-maximal response ('sensitivity').
n: Cooperativity.
yEC50.orig: Response value for EC50 in original scale, if a transformation was applied.
K.orig: K in original scale, if a transformation was applied.
test.nm: Test identifier extracted from test.

`fitFlag`	(Logical) Indicates whether a spline could fitted successfully to data.
`reliable`	(Logical) Indicates whether the performed fit is reliable (to be set manually).
`control`	Object of class `fl.control` created with the call of `fl.control`.

Use plot.drFitModel to visualize the model fit.

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

# Create concentration values via a serial dilution
conc <- c(0, rev(unlist(lapply(1:18, function(x) 10*(2/3)^x))),10)

# Simulate response values via biosensor equation
response <- biosensor.eq(conc, y.min = 110, y.max = 6000, K = 0.5, n = 2) +
            0.01*6000*rnorm(10)

# Perform fit
TestRun <- fl.drFitModel(conc, response, drID = 'test', control = fl.control())

print(summary(TestRun))
plot(TestRun)

QurvE documentation built on May 29, 2024, 3 a.m.