The second step in an AHC analysis is specifying how dissimilarity is computed between clusters, and this is independent of the method selected for measuring pairwise dissimilarities between objects (described previously). As described in , there are several "linkage" methods for describing the dissimilarity between clusters. For example, we can approximate the dissimilarity between two clusters based on the average dissimilarity between all objects in clusters, commonly referred to as a Group Average or Unweighted Pair Group Method with Arithmetic mean (UPGMA) . In this study, we consider a "complete link" method which means the dissimilarity between clusters is approximated by the maximum dissimilarity between objects in the clusters, thus we guarantee that the maximum dissimilarity between any two objects in a cluster created at a specified dissimilarity cutoff level will always be bounded by the cutoff level value itself.