mbqnGetThreshold: Calculates the rank invariance threshold from which on MBQN...

In arianeschad/mbqn: Mean/Median-balanced quantile normalization

Calculates the rank invariance threshold from which on MBQN should be used instead of 'classical' QN

Description

Calculates the rank invariance threshold from which on MBQN should be used instead of 'classical' QN

Usage

mbqnGetThreshold(mtx, meanMedian = "mean", plot = TRUE)

Arguments

mtx	Matrix with samples in columns and features in rows
meanMedian	Offset function for the MBQN calculation
plot	Boolean values if logistic regression curves that are used to calculate intersection point should be plotted

Value

threshold value

Examples

set.seed(30)
n <- 20
m <- 20
mtx <- matrix(rnorm(m * n), m, n)
mbqnGetThreshold(mtx)

arianeschad/mbqn documentation built on March 29, 2022, 6:56 p.m.