clusterAlgorithmClara-class {goCluster}R Documentation

Class "clusterAlgorithmClara", provides partitioning around medoids of large datasets

Description

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

Details

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

Slots

clusters:
Object of class "numeric", determines the number of clusters the partitioning around medoids will identify.
repeats:
Object of class "numeric", specifies how often the clustering is repeated in case clara is not run with a fixed initialization.
fixed:
Object of class "logical", if true, a fixed seed will be used for the partitioning around medoids.
distance:
Object of class "character", specifies the distance matrix that will be used.

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 = "clusterAlgorithmClara"): interactive setup of the class. You will be asked to specify the number of clusters clara clustering should result in and whether a fixed seed should be used. If not the class offers to repeat the clustering. In addition the distance matrix needs to be defined.
setup
signature(object = "clusterAlgorithmClara"): 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 = "clusterAlgorithmClara"): non-interactive setup of the class. The options are specified using a list.
execute
signature(object = "clusterAlgorithmClara"): run the clustering.
reset
signature(object = "clusterAlgorithmClara"): remove all cluster data so that the execute function can be run again.
print
signature(object = "clusterAlgorithmClara"): This function prints some basic information about the content of this object.

Author(s)

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

See Also

clusterclara, goCluster-class, clusterModule-class, clusterAlgorithm-class, clusterAlgorithmKmeans-class, clusterAlgorithmPam-class, clusterAlgorithmHclust-class, .

Examples

## Predefined setup for goCluster
## (This configuration selects the
## clara clustering)
data(benomylsetup)

## 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 1.0.3 Index]