runClara {CytoTree} | R Documentation

## runClara

### Description

Clustering a data matrix into k clusters

### Usage

    runClara(
      object,
      k = 25,
      metric = c("euclidean", "manhattan", "jaccard"),
      stand = FALSE,
      samples = 5,
      scale = TRUE,
      trace = 0,
      verbose = FALSE,
      ...
    )

### Arguments

`object` | an CYT object
`k` | numeric. The number of clusters. It is required that 0 < k < n where n is the number of observations (i.e., n = nrow(x)).
`metric` | character. string specifying the metric to be used for calculating dissimilarities between observations.
`stand` | logical. Indicating if the measurements in x are standardized before calculating the dissimilarities.
`samples` | numeric. Say N, the number of samples to be drawn from the dataset. The default is N = 5,
`scale` | logical. Whether to use scaled data in kmeans.
`trace` | numberic. Indicating a trace level for diagnostic output during the algorithm
`verbose` | logical. Whether to print calculation progress.
`...` | Parameters passing to `clara` function

### Value

an CYT object with clara.id in meta.data

### See Also

`clara`

### Examples

    cyt.file <- system.file("extdata/cyt.rds", package = "CytoTree")
    cyt <- readRDS(file = cyt.file)

    cyt <- runClara(cyt, k = 25, verbose = TRUE)

[Package CytoTree version 1.4.0 Index]