splitScaleTransform: Compute the split-scale transformation describe by FL. Battye

Description

The split scale transformation described by Francis L. Battye [B15] (Figure 13) consists of a logarithmic scale at high values and a linear scale at low values with a fixed transition point chosen so that the slope (first derivative) of the transform is continuous at that point. The scale extends to the negative of the transition value that is reached at the bottom of the display.

Usage

splitScaleTransform(transformationId="defaultSplitscaleTransform", maxValue=1023, transitionChannel=64, r=192)

Arguments

transformationId

A name to assign to the transformation. Used by the transform/filter integration routines.

maxValue

Maximum value the transformation is applied to, e.g., 1023

transitionChannel

Where to split the linear versus the logarithmic transformation, e.g., 64

Range of the logarithm part of the display, ie. it may be expressed as the maxChannel - transitionChannel considering the maxChannel as the maximum value to be obtained after the transformation.

Value

Returns values giving the inverse of the biexponential within a certain tolerance. This function should be used with care as numerical inversion routines often have problems with the inversion process due to the large range of values that are essentially 0. Do not be surprised if you end up with population splitting about w and other odd artifacts.

References

Battye F.L. A Mathematically Simple Alternative to the Logarithmic Transform for Flow Cytometric Fluorescence Data Displays. http://www.wehi.edu.au/cytometry/Abstracts/AFCG05B.html.

Examples

Run this code


data(GvHD)
ssTransform  <- splitScaleTransform("mySplitTransform")
after.1 <- transform(GvHD, transformList('FSC-H', ssTransform))

opar = par(mfcol=c(2, 1))
plot(density(exprs(GvHD[[1]])[, 1]), main="Original")
plot(density(exprs(after.1[[1]])[, 1]), main="Split-scale Transform")