clusterAlgorithmKmeans-class {goCluster} | R Documentation

## Class "clusterAlgorithmKmeans", provides kmeans clustering for goCluster.

### Description

This can be used to group a dataset according to kmeans. The resulting gene groups can subsequently be analysed for significant enrichment of specific annotations.

### Details

The class provides a wrapper around the `clusterkmeans` function. Please read the corresponding documentation for further details.

### Slots

`repeats`:
  Object of class `"numeric"`, specifies how often the clustering should be repeated to account for the statistical variability of the clustering.
`clusters`:
  Object of class `"numeric"`, determines the number of clusters the kmeans clustering will identify.

Additional slots are described in the documentation of the `clusterAlgorithm-class` and `clusterModule-class`.

### Extends

Class `"clusterAlgorithm"`, directly. Class `"clusterModule"`, by class `"clusterAlgorithm"`.

### Methods

config
  `signature(object = "clusterModule")`: interactive setup of the class. You will be asked to specify the number of clusters the kmeans clustering should result in and how often the clustering should be repeated.
setup
  `signature(object = "clusterModule")`: returns the configuration of the object as a list. This list can again be used for the non-interactive setup of the class.
setup<-
  `signature(object = "clusterModule")`: non-interactive setup of the class. The options are specified using a list.
execute
  `signature(object = "clusterModule")`: run the clustering.
reset
  `signature(object = "clusterModule")`: remove all cluster data so that the `execute` function can be run again.

### Author(s)

Gunnar Wrobel, http://www.gunnarwrobel.de.

### See Also

`clusterkmeans`, `goCluster-class`, `clusterModule-class`, `clusterAlgorithm-class`, `clusterAlgorithmKmeans-class`, `clusterAlgorithmClara-class`, `clusterAlgorithmPam-class`

### Examples

    ## Predefined setup for goCluster
    data(benomylsetup)

    ## Change the setup to
    ## hierarchical clustering
    benomylsetup$classalgo <- "clusterAlgorithmKmeans"
    benomylsetup$algo$repeats   <- 10

    ## Setup a new goCluster object
    test <- new("goCluster")
    setup(test) <- benomylsetup

    ## Retrieve annotation
    test@data <- execute(test@data, test)

    ## Cluster the dataset
    test@algo <- execute(test@algo, test)

[Package goCluster version 1.0.0 Index]