MetaClustering {FlowSOM} | R Documentation

## MetaClustering

### Description

Cluster data with automatic number of cluster determination for several algorithms

### Usage

    MetaClustering(data, method, max = 20, nClus = NULL, ...)

### Arguments

`data` | Matrix containing the data to cluster
`method` | Clustering method to use, given as a string. Options are metaClustering_consensus,metaClustering_hclust, metaClustering_kmeans,metaClustering_som
`max` | Maximum number of clusters to try out
`nClus` | Exact number of clusters to use. If not NULL, max will be ignored.
`...` | Extra parameters to pass along

### Value

Numeric array indicating cluster for each datapoint

### See Also

`metaClustering_consensus`

### Examples

       # Read from file, build self-organizing map and minimal spanning tree
       fileName <- system.file("extdata","lymphocytes.fcs",package="FlowSOM")
       flowSOM.res <- ReadInput(fileName, compensate=TRUE,transform=TRUE,
                                scale=TRUE)
       flowSOM.res <- BuildSOM(flowSOM.res,colsToUse=c(9,12,14:18))
       flowSOM.res <- BuildMST(flowSOM.res)

       # Apply metaclustering
       metacl <- MetaClustering(flowSOM.res$map$codes,
                                "metaClustering_consensus",
                                max=10)

       # Get metaclustering per cell
       flowSOM.clustering <- metacl[flowSOM.res$map$mapping[,1]]

[Package FlowSOM version 1.12.0 Index]