loq_derivatives: Limits of quantifications estimation using derivatives

In drLumi: Multiplex Immunoassays Data Analysis

Description

Estimates the limits of quantification based on the second order derivative of the functions.

Usage

loq_derivatives(x, subset.list = NULL, ...)

Arguments

x	a scluminex class object
subset.list	list of analytes to estimate. Default NULL (all analytes of the scluminex object)
...	further arguments to be passed to uniroot.all function.

Details

The limits of quantification are based on the maximum and minimum points of the second order derivative of the function. The solution is based on the specific expressions of the derivatives. The uniroot.all function is used in order to find the global maximum and minimum.

Value

Object of class loq.

References

Ritz C and Spiess AN (2008). qpcR: an R package for sigmoidal model selection in q uantitative real-time polymerase chain reaction analysis. Bioinformatics 24, 1549-51.

Examples

# Load data and estimate models
data(ecdata)
data(mfidata)

dat <- mfidata[mfidata$plate=="plate_1" & mfidata$analyte=="FGF",]

sdf <- data_selection(dat, ecdata)[[1]]

igmodels <- scluminex("plate_1",sdf$standard, sdf$background,
                lfct=c("SSl4", "SSl5"),
                bkg="ignore",
                fmfi="mfi",
                verbose=FALSE)

loq_derivatives(igmodels)

drLumi documentation built on May 2, 2019, 2:45 p.m.