Calculate the Consensus Clustering Result from Re-Sampled Clustering Experiments with the Option of Using Multiple Algorithms and Parameters
clusterCons contains functions for the calculation of robustness measures for clusters and cluster membership based on consensus matrices generated 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.
The package can be installed from either .tar.gz (*nix) or .ZIP (windows) executables via the release on the right hand side of this web-page. These can be installed using the usual methods for R package installation either at the command line or within R.
clusterCons has recently been updated to be compatible with R version 4.1.2 and is now available on the CRAN repository after an absence of a few years. You can access it directly here - https://cran.r-project.org/package=clusterCons