Clusternomics: Integrative context-dependent clustering for heterogeneous datasets
Fig 2
Example of the simulated data for p = 0 and p = 0.5, which show different degrees of dependence.
The x axis corresponds to the data in the first dataset (context), the y axis represents the data in the second dataset (context). The two subfigures show the two extreme situations: (a) For p = 0, we get two global clusters. Cluster membership is fully dependent on each other in both datasets. (b) For p = 0.5, we get four global clusters, where cluster membership in one dataset is fully independent on cluster membership in the second dataset.