mblrr: A function to perform a Local Robust Regression in Ranges defined by Qunantile-filtering
Description
mblrr is a function to perform the Median based Local Robust Regression (mblrr)
from a quantitative PCR experiment. In detail, this function attempts to break the
amplification curve in two parts (head (~background) and tail (~plateau)).
Subsequent, a robust linear regression analysis (lmrob) is
preformed individually on both parts. The rational behind this analysis is
that the slope and intercept of an amplification curve differ in the
background and plateau region.
Usage
mblrr(x, y, sig.level = 0.01, normalize = FALSE)
Arguments
x
is the cycle numbers (x-axis).
y
is the cycle dependent fluorescence amplitude (y-axis).
sig.level
is the significance level for the correlation test.
normalize
is a logical parameter, which indicates if the amplification curve
data should be normalized to the 99 percent quantile of the amplification curve.
Value
gives a numeric (S3 class, type of double) as output
for the regressed regions
Details
mblrr_intercept_bg is the intercept of the head region,
mblrr_slope_bg is the slope of the head region,
mblrr_cor_bg is the coefficient of correlation of the head region,
mblrr_intercept_pt is the intercept of the tail region,
mblrr_intercept_pt is the slope of the tail region,
mblrr_cor_pt is the coefficient of correlation of the tail region
# NOT RUN {# Perform an mblrr analysis on noise (negative) amplification data of qPCR data# with 35 cycles.library(qpcR)
mblrr(x=boggy[, 1], y=boggy[, 2], normalize=TRUE)
# }