Description Usage Arguments Value Author(s) Examples
Compute the local density of observation and incorporate the result as a new parameter to the FCS file. The local density is modeled as an integer count of the number of other observations within a specified distance of the observation.
1 | SPADE.addDensityToFCS(infilename, outfilename, cols = NULL, arcsinh_cofactor=NULL, transforms=flowCore::arcsinhTransform(a=0, b=0.2), kernel_mult = 5, apprx_mult = 1.5, med_samples = 2000, comp=TRUE)
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infilename |
Name of the input FCS file |
outfilename |
Name of the output FCS file |
cols |
Usually a vector of strings specifying the columns to be used in the density calculation, e.g., c("(Cd110)D","(Cs111)D"). Strings will be matched against the parameter names extracted from the FCS file. The default=NULL will use all parameters. |
arcsinh_cofactor |
DEPRECATED. Cofactor used in arcsinh transform |
transforms |
Transform object to apply to data. A single transform object will be applied to all channels. To apply different transforms to specific channels use a named vector of transform objects (where names are parameter names). |
kernel_mult |
Multiplier of the minimum median distance within which other observations are counted towards the density |
apprx_mult |
Multiplier of the minimum median distance within which observations are approximated to have the same density |
med_samples |
Number of observations used to estimate the minimum median distance |
comp |
Apply compensation matrix if present in SPILL or SPILLOVER keywords |
The name of the written file is returned
Michael Linderman
1 2 3 4 5 6 7 8 9 | # Not run
## Load two-parameters sample data included in package
#data_file_path = paste(installed.packages()["spade","LibPath"],"spade","extdata","SimulatedRawData.fcs",sep=.Platform$file.sep)
#
#output_dir <- tempdir()
#
## Compute and annotate FCS file with density
#density_file_path <- paste(output_dir,.Platform$file.sep,basename(data_file_path),".density.fcs",sep="")
#SPADE.addDensityToFCS(data_file_path, density_file_path, cols=c("marker1","marker2"))
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