invsplitscale-class {flowCore} | R Documentation |
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 can be created by calls to the constructor
invsplitscale(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 transformedtransformationId
:"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 "invsplitscale" 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
splitscale
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))