normalizer normalizes any data set using a chosen method (see Details).
It may be used when the data from an experiment have considerable variation regarding the
background and plateau signal.
normalizer(y, method.norm = "none", qnL = 0.03)is a vector containing the fluorescence values.
is a argument to use a "none", "minm", "max", "luqn", or "zscore" normalization. See Details.
is the quantile to be used for the quantile normalization. Ignored if
method.norm is not equal to "luqn".
A vector of normalized fluorescence values.
The parameter qnL is
a user defined quantile which is used for the quantile normalization. A
quantile normalization herein refers to an approach which is less prone to
outliers than a normalization based on the minimum and the maximum of an
amplification curve.
minm does a min-max normalization between 0 and 1 (see Roediger et al.
2013 for explanation).
max does a normalization to the maximum value (MFI/max(MFI)).
luqn does a quantile normalization based on a symmetric proportion
as defined by the qnL parameter (e.g., qnL = 0.03 equals 3 and 97
percent quantiles).
zscore performs a z-score normalization with a mean of 0 and a
standard deviation of 1.
Surface Melting Curve Analysis with R. S. Roediger, A. Boehm and I. Schimke. The R Journal. 5(2):37--52, 2013. https://journal.r-project.org
# NOT RUN {
normalizer(C17[2L:50, 1], "minm")
# }
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