Cluster detection searches for subtrees of the tree selected in the ARB_DIST main window, that form homologous groups of sequences.
The main prerequisite for cluster detection to work well is a good tree, preferable a tree optimized with ARB_PARSIMONY (since cluster detection uses the same distance function as ARB_PARSIMONY does).
You may control the distance calculation by selecting filter and/or weights in the ARB_DIST main window.
The following parameters define which subtrees will be reported as clusters
Max. distance inside each cluster (no two sequences in a cluster have bigger distance than specified). Specify the distance as percentage of mutations, 100 means every base differs, 0 means no base differs
Min cluster size (clusters below that size are ignored)
Press 'Detect clusters' to start the cluster detection..
The clusters matching the given parameters will be displayed in the list below. Each line contains the following information:
number of species in cluster
mean distance [min. - max.distance]
minimal bases used for distance calculation (weighted)
a generated cluster description
Each cluster contains one so called 'representative'. The representative is the species in the cluster with the least mean distance to all other cluster members.