Class "invsplitscale"

Description

The inverse split scale transformation is defined by the function

f(parameter,r,maxValue,transitionChannel)= \frac{(parameter-b)}{a} ~~~~parameter<=t*a + b

\frac{10^{parameter*\frac{d}{r}}}{c} ~~~~ parameter > t*a+b

where,

b=\frac{transitionChannel}{2}

d=\frac{2*log_{10}(e)*r}{transitionChannel} + log_{10}(maxValue)

t=10^{log_{10}t}

a= \frac{transitionChannel}{2*t}

log_{10}ct=\frac{(a*t+b)*d}{r}

c=10^{log_{10}ct}

Objects from the Class

Objects can be created by calls to the constructor invsplitscale(parameters,r,maxValue,transitionChannel,transformationId)

Slots

.Data:

Object of class "function" ~~

r:

Object of class "numeric" -a positive value indicating the range of the logarithmic part of the display

maxValue:

Object of class "numeric" -a positive value indicating the maximum value the transformation is applied to

transitionChannel:

Object of class "numeric" -non negative value that indicates where to split the linear vs. logarithmic transformation

parameters:

Object of class "transformation" - flow parameter to be transformed

transformationId:

Object of class "character" -unique ID to reference the transformation

Extends

Class "singleParameterTransform", directly. Class "transform", by class "singleParameterTransform", distance 2. Class "transformation", by class "singleParameterTransform", distance 3. Class "characterOrTransformation", by class "singleParameterTransform", distance 4.

Methods

No methods defined with class "invsplitscale" in the signature.

Note

The transformation object can be evaluated using the eval method by passing the data frame as an argument.The transformed parameters are returned as a matrix with a single column. (See example below)

Author(s)

Gopalakrishnan N,F.Hahne

References

Gating-ML Candidate Recommendation for Gating Description in Flow Cytometry

See Also

splitscale

Examples

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  dat <- read.FCS(system.file("extdata","0877408774.B08",package="flowCore"))
  sp1<-invsplitscale("FSC-H",r=512,maxValue=2000,transitionChannel=512)
  transOut<-eval(sp1)(exprs(dat))

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