mblrr: A function to perform a Local Robust Regression in Ranges...

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

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.

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

Value

gives a numeric (S3 class, type of double) as output for the regressed regions

Author(s)

Stefan Roediger, Michal Burdukiewcz

Examples

# 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)

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