clusterCons: Calculate the consensus clustering result from re-sampled clustering experiments with the option of using multiple algorithms and parameter

clusterCons is a package containing functions that generate robustness measures for clusters and cluster membership based on generating consensus matrices from bootstrapped clustering experiments in which a random proportion of rows of the data set are used in each individual clustering. This allows the user to prioritise clusters and the members of clusters based on their consistency in this regime. The functions allow the user to select several algorithms to use in the re-sampling scheme and with any of the parameters that the algorithm would normally take.

Downloads: