GeneCluster 1.0 provides the ability to filter and preprocess data in a variety of ways, cluster expression profiles using the SOM algorithm, and view the results.

GeneCluster 2.0 expands the data analysis capabilities of GeneCluster 1.0 by adding supervised classification, gene selection and permutation test methods. It includes algorithms for building and testing supervised models using weighted voting (WV) and k-nearest neighbors (KNN) algorithms. It enhances the clustering capabilities of GeneCluster 1.0 by adding a module for batch SOM clustering, and also includes a marker gene finder based on a KNN analysis and a visualization module.

This tool can be found in Lille and Toulouse.