createEnsemble {ddPCRclust} | R Documentation

## Create a cluster ensemble

### 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

    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

    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)

[Package ddPCRclust version 1.4.0 Index]