HCL: Hierarchical Clustering
Parameter Information
Tree Selection
These checkboxes are used to indicate whether to construct trees for
genes, samples, or both.
Leaf Order Optimization
These checkboxes are used to indicate whether to use an algorithm that will rearrange the
analysis to optimize the sum of similarities between all adjacent leaves on the tree. This
algorithm is memory intensive and will increase the calculation time over the arbitrary ordering
technique. Depending on the size of your data set this option may not be available due to Java
memory constraints.
Distance Metric Selection
This area allows the selection of the metric to be used to assess gene-to-gene
or sample-to-sample distances. The initial metric displayed (choosen) corresponds to the global
setting in the Multiple Array Viewer's 'Metrics' menu. Alterations to the
chosen metric in this dialog will only alter the metric used for the current
algorithm run. The global setting in the main 'Metrics' menu will remain unchanged.
Euclidean Distance and Pearson Correllation tend to be the most frequently used options.
An appendix in the MeV manual describes the distance metrics offered in MeV.
Linkage Method Selection
This parameter is used to indicate the convention
used for determining cluster-to-cluster distances
when constructing the hierarchical tree. Just as distance metrics define
gene-to-gene or sample-to-sample distances the Linkage methods
are employed to determine cluster-to-cluster distances.
Single Linkage: The distances are measured between
each member of one cluster each member of the other
cluster. The minimum of these distances is considered
the cluster-to-cluster distance.
Average Linkage: The average distance of each member of
one cluster to each member of the other cluster is used
as a measure of cluster-to-cluster distance.
Complete Linkage: The distances are measured between
each member of one cluster each member of the other
cluster. The maximum of these distances is considered
the cluster-to-cluster distance.