KMS: K-Means/K-Medians Support

Parameter Information


Sample Selection

The sample selection option indicates whether to cluster genes or experiments.

Distance Metric Selection

This area allows the selection of the metric to be used to assess gene-to-gene or sample-to-sample distances. The initial metric displayed (choosen) corresponds to the global setting in the Multiple Array Viewer's 'Metrics' menu. Alterations to the chosen metric in this dialog will only alter the metric used for the current algorithm run. The global setting in the main 'Metrics' menu will remain unchanged.

An appendix in the MeV manual describes the distance metrics offered in MeV.

Means/Medians option

The Means or Medians option indicates whether each cluster's centroid vector should be calculated a mean or a median of the member expression patterns.

Number of k-means/k-medians runs

This integer value indicates how many times KMC should be run.

Threshold % of occurrence in same cluster

This parameter indicates the minimum percentage of times that two elements should cluster together in order consider the two elements in a cluster. For instance, if 10 KMC runs were run, and the percentage was 80% then a pair of expression elements found together at least 8 times would be considered to pass a criteria to be included in a cluster.

Number of Clusters (K)

This positive integer value indicates the number of clusters to be created during each KMC run. Note that for K-Means support the final number may turn out to be slightly smaller or larger than this entered value depending on the nature of the input data and the appropriate selection of K (number of clusters to create). Note that FOM can be used to estimate an appropriate value for K.

Number of Iterations

This positive integer value is the maximum number of times that all the elements in the data set will be tested for cluster fit. On each iteration each element is associated with the cluster with the closest mean (or median).

Note that a KMC run will terminate when either no elements require migration (reassignment) to new clusters or when the maximum number of iterations has been reached.

Hierarchical Clustering

This check box selects whether to perform hierarchical clustering on the elements in each cluster created.