splitscale-class {flowCore} | R Documentation |
The split scale transformation class defines a transformation that has a logarithmic scale at high values and a linear scale at low values. The transition points are chosen so that the slope of the trasformation is continuos at the transition points.
The split scale transformation is defined by the function
f(parameter,r,maxValue,transitionChannel)= a*parameter+ b ~~~~parameter<=t
log_{10}(c*parameter)*frac{r}{d} ~~~~parameter > t
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 can be created by calls to the constructor
splitscale(parameters,r,maxValue,transitionChannel,transformationId)
.Data
:"function"
~~ r
:"numeric"
-a positive value indicating the range of the logarithmical
part of the display maxValue
:"numeric"
-a positive value indicating the maximum value the transformation
is applied totransitionChannel
:"numeric"
-non negative value that indicates where to
split the linear vs. logarithmical transformationparameters
:"transformation"
- flow parameter to be transformed transformationId
:"character"
-unique ID to reference the transformation
Class "singleParameterTransform"
, directly.
Class "transform"
, by class "singleParameterTransform", distance 2.
Class "transformation"
, by class "singleParameterTransform", distance 3.
Class "characterOrTransformation"
, by class "singleParameterTransform", distance 4.
No methods defined with class "splitscale" in the signature.
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)
Gopalakrishnan N, F.Hahne
Gating-ML Candidate Recommendation for Gating Description in Flow Cytometry
invsplitscale
dat <- read.FCS(system.file("extdata","0877408774.B08",package="flowCore")) sp1<-splitscale("FSC-H",r=768,maxValue=10000,transitionChannel=256) transOut<-eval(sp1)(exprs(dat))