MetaClustering

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Description

Cluster data with automatic number of cluster determination for several algorithms

Usage

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

Arguments

data

Matrix containing the data to cluster

method

Clustering method to use

max

Maximum number of clusters to try out

...

Extra parameters to pass along

Value

Numeric array indicating cluster for each datapoint

See Also

metaClustering_consensus

Examples

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   # 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]]    

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