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Perform a smooth spline fit on response vs. concentration data of a single sample to determine the EC50.

Source: R/dose-response-analysis.R
growth.drFitSpline.Rd

growth.drFitSpline performs a smooth spline fit determines the EC50 as the concentration at the half-maximum value of the response parameter of the spline.

Usage

growth.drFitSpline(conc, test, drID = "undefined", control = growth.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 grofit.control object created with growth.control, defining relevant fitting options.

Value

A drFitSpline 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.

spline

smooth.spline object generated by the smooth.spline function.

spline.low

x and y values of lowess spline fit on raw data. Used to call smooth.spline.

parameters

List of parameters estimated from dose response curve fit.

  • EC50: Concentration at half-maximal response.

  • yEC50: Response value related to EC50.

  • EC50.orig: EC50 value in original scale, if a transformation was applied.

  • yEC50.orig: Response value for EC50 in original scale, if a transformation was applied.

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 grofit.control containing list of options passed to the function as control.

Use plot.drFitSpline to visualize the spline fit.

Details

During the spline fit with smooth.spline, higher weights are assigned to data points with a concentration value of 0, as well as to x-y pairs with a response parameter value of 0 and pairs at concentration values before zero-response parameter values.

References

Matthias Kahm, Guido Hasenbrink, Hella Lichtenberg-Frate, Jost Ludwig, Maik Kschischo (2010). grofit: Fitting Biological Growth Curves with R. Journal of Statistical Software, 33(7), 1-21. DOI: 10.18637/jss.v033.i07

Christian Ritz, Florent Baty, Jens C. Streibig, Daniel Gerhard (2015). Dose-Response Analysis Using R. PLoS ONE 10(12): e0146021. DOI: 10.1371/journal.pone.0146021

See also

Other dose-response analysis functions: flFit(), growth.drBootSpline(), growth.gcFit(), growth.workflow()

Examples

conc <- c(0, rev(unlist(lapply(1:18, function(x) 10*(2/3)^x))),10)
response <- c(1/(1+exp(-0.7*(4-conc[-20])))+rnorm(19)/50, 0)

TestRun <- growth.drFitSpline(conc, response, drID = 'test',
              control = growth.control(log.x.dr = TRUE, smooth.dr = 0.8))
#> 
#> 
#> === Dose response curve estimation ================
#> --- EC 50 -----------------------------------------
#> --> test
#> xEC50 1.60819803080571 yEC50 0.483098138259066
#> --> Original scale 
#> xEC50 3.99380443353629 yEC50 0.483098138259066
#> 
#> 

print(summary(TestRun))
#>       EC50     yEC50 EC50.orig yEC50.orig test
#> 1 1.608198 0.4830981  3.993804  0.4830981   NA

plot(TestRun)