Provides the facility to calculate the Brainerd-Robinson similarity coefficient for the rows of an input table, and to calculate the significance of each coefficient based on a permutation approach; a heatmap is produced to visually represent the similarity matrix. Optionally, hierarchical agglomerative clustering can be performed and the silhouette method is used to identify an optimal number of clusters; the results of the clustering can be optionally used to sort the heatmap.