Optimised consensus clustering of one or more heterogeneous datasets. It encapsulates the Bi-CoPaM and the M-N scatter plots methods in addition to pre-processing steps and very important post-processing cluster optimisation and completion steps.
Clust is freely available as a package that can be straightforwardly installed and used. A full description of how to install and use Clust is available at:
Here is an overview of the pipeline of steps that Clust undergoes: