trans.ApplyToData: immunoClust asinh-Transformation

In immunoClust: immunoClust - Automated Pipeline for Population Detection in Flow Cytometry

Description

Applies the transformation information of the immunoClust object to the raw observed FC dataset.

Usage

trans.ApplyToData(x, data, add.param=c(), max.decade=attr(x,"trans.decade"), 
    lin.scale=attr(x,"trans.scale") )

Arguments

x	The immunoClust object containing the estimators for the transformation trans.a and trans.b.
data	The numeric matrix, data frame of observations, or object of class flowFrame.
add.param	A list of additional parameters in the flowFrame, which are not used for clustering but should be included in the final transformed resulting flowFrame.
max.decade	A numeric scale for the maximum transformed observation value; if missing or below 0, no scaling of the transformed values is apllied, which is the default in immunoClust.
lin.scale	A numeric scaling factor for the linear, i.e. not transformed, parameters; if missing no scaling, i.e. lin.scale=1, is applied, which is the default in immunoClust.

Details

In immunoClust an asinh-transformation h(y)=asinh(a*y + b) is applied to the fluorescence parameter in the observed data. The scatter parameter are assumed to be linear.

Value

A matrix or flowFrame with replaced transformed oberservation values.

Author(s)

Till Sörensen [e-mail]

References

Sörensen, T., Baumgart, S., Durek, P., Grützkau, A. and Häupl, T. immunoClust - an automated analysis pipeline for the identification of immunophenotypic signatures in high-dimensional cytometric datasets. Cytometry A (accepted).

See Also

immunoClust, trans.FitToData, cell.process

Examples

data(dat.fcs)
data(dat.exp)
dat.trans <- trans.ApplyToData(dat.exp[[1]], dat.fcs)
#
#plot(dat.exp[[1]], data=dat.trans)
#

immunoClust documentation built on Nov. 8, 2020, 5:19 p.m.