earlyreg: A function to calculate the slope and intercept of an...

In devSJR/PCRedux: Quantitative Polymerase Chain Reaction (qPCR) Data Mining and Machine Learning Toolkit

A function to calculate the slope and intercept of an amplification curve data from a quantitative PCR experiment.

Description

earlyreg is a function to calculate the slope and intercept of an amplification curve data from a quantitative PCR experiment. The number of cycles to be analyzed is defined by the user (default 6 cycles). The output contains the Maximal Information Coefficient (MIC), which can be interpreted as a correlation measure with a range of [0,1]. A value of 0 mean statistically independent data and 1 approaches in "probability for noiseless functional relationships" (see original study by Reshef, D. N. et al. Detecting novel associations in large data sets. Science, 334, 1518-1524 (2011)).

Usage

earlyreg(x, y, range = 5, normalize = FALSE)

Arguments

x	is the cycle numbers (x-axis).
y	is the cycle dependent fluorescence amplitude (y-axis).
range	is the number of cycles to be used for the regression.
normalize	is a logical parameter which indicates if the amplification curve data should be normalized to the 99 percent percentile of the amplification curve.

Value

gives a numeric vector (S3 class, type of double) as output for local regression

Author(s)

Stefan Roediger, Michal Burdukiewcz

See Also

lmrob stats::coefficients()

Examples

# Calculate slope and intercept on noise (negative) amplification curve data
# for the cycles 2 to 7 for the C316.amp data set
library(chipPCR)
data(C316.amp)

# Plot the data
plot(C316.amp[, 2], y=C316.amp[, 3], xlab="Cycle", ylab="RFU",
     main="C316.amp data set", lty=1, type="l")
res <- earlyreg(x=C316.amp[, 2], y=C316.amp[, 3], range=5)
res

devSJR/PCRedux documentation built on Aug. 3, 2022, 1:34 p.m.