K-Means Clustering
Overview
This component provides an interface to running K-Means Clustering on a GenePattern server, and a viewer for the results.
As described in the GenePattern documentation (PDF):
"K-Means clustering is a clustering algorithm that classifies or groups objects into a specified number of clusters. Initially, k cluster centroids (centers) are randomly selected from the given data set and each data point is assigned to the cluster of the nearest cluster center. Each cluster center is then recalculated to be the mean value of its members and all data points are re-assigned to the cluster with the closest centroid. This process is repeated until the distance between consecutive cluster centers converges".
Prerequisites
The K-Means clustering analysis and viewer components must be loaded in the Component_Configuration_Manager
A gene expression dataset must be loaded in the Workspace.
Technical Note
The K-Means clustering component is found in the "gpmodule_v3_0" package in the geWorkbench component source tree.
References
- J. B. MacQueen (1967) Some Methods for classification and Analysis of Multivariate Observations. Proceedings of 5th Berkeley Symposium on Mathematical Statistics and Probability, Berkeley, University of California Press, 1:281-297
- GenePattern module descriptions