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Cell fluorescense intensity transformation for FACS data. The user can use the transformation plots to check that the transformation looks correct. Ideally it should make the data look like a blob, if dots are aligned to the zero in either of the axis or are placed below zero would mean that the transformation is not separating the values properly and another transformation should be used.

Version 1.0
Bundle flowand
Categories FlowCytometry
Authors Julia Casado (julia.casado@helsinki.fi)
Requires R ; flowCore (R-bioconductor) ; openCyto (R-bioconductor)
Source files component.xml Transformation.r
Usage Example with default values


Name Type Mandatory Description
in Array<CSV> Mandatory An array of CSV files with all the data for a given experiment.


Name Type Description
out Array<CSV> Transformed data in a concatenated CSV file.


Name Type Default Description
channels string "*" A comma-separated list of channel numbers indicating which columns to transform. Antibody names that match partially the names of the columns. The default is for all. If empty, it will not do any transformation. If parameter 'negate' is true then all channels not in this list are transformed.
negate boolean false If true, the transformation will be applied to all channels except those defined in the 'channels' parameter.
transformation string "arcsinhTransform(transformationId='defaultArcsinhTransform', a=1, b=2)" The transformation method to apply, open definition of an object of type transform. Examples: linearTransform(transformationId="defaultLinearTransform", a = 1, b = 0) lnTransform(transformationId="defaultLnTransform", r=1, d=1) logicleTransform(transformationId="defaultLogicleTransform", w = 0.5, t = 262144, m = 4.5, a = 0) biexponentialTransform(transformationId="defaultBiexponentialTransform", a = 0.5, b = 1, c = 0.5, d = 1, f = 0, w = 0, tol = .Machine$double.eps^0.25, maxit = as.integer(5000)) arcsinhTransform(transformationId="defaultArcsinhTransform", a=1, b=1, c=0) quadraticTransform(transformationId="defaultQuadraticTransform", a = 1, b = 1, c = 0) logTransform(transformationId="defaultLogTransform", logbase=10, r=1, d=1) scaleTransform(transformationId="defaultScaleTransform", a, b) truncateTransform(transformationId="defaultTruncateTransform", a=1)

Test cases

Test case Parameters IN
case1 (missing) in out

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