createEnsemble: Create a cluster ensemble

Description Usage Arguments Value Examples

View source: R/ddPCRclust.R

Description

This function takes the three (or less) clustering approaches of the ddPCRclust package and combines them to one cluster ensemble. See cl_medoid for more information.

Usage

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createEnsemble(dens = NULL, sam = NULL, peaks = NULL, file)

Arguments

dens

The result of the flowDensity algorithm as a CLUE partition.

sam

The result of the samSPECTRAL algorithm as a CLUE partition.

peaks

The result of the flowPeaks algorithm as a CLUE partition.

file

The input data. More specifically, a data frame with two dimensions, each dimension representing the intensity for one color.

Value

data

The original input data minus the removed events (for plotting)

confidence

The agreement between the different clustering results in percent. If all algorithms calculated the same result, the clustering is likely to be correct, thus the confidence is high.

counts

The droplet count for each cluster.

Examples

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exampleFiles <- list.files(paste0(find.package('ddPCRclust'), '/extdata'), full.names = TRUE)
file <- read.csv(exampleFiles[3])
densResult <- runDensity(file = file, numOfMarkers = 4)
samResult <- runSam(file = file, numOfMarkers = 4)
peaksResult <- runPeaks(file = file, numOfMarkers = 4)

superResult <- createEnsemble(densResult, samResult, peaksResult, file)

ddPCRclust documentation built on Nov. 8, 2020, 6:06 p.m.