Decision tree-based method for integrating gene expression, demographic, and clinical data to determine disease endotypes

Table 4 Top ranking gene expression clustering methods from clusterSim

Index metric	Index value	Distance measure	Clustering method	No. of clusters
Silhouette	0.6325	Manhattan	Hierarchical – Single linkage	2
Baker & Hubert	1	Manhattan	Hierarchical – Single linkage	2
Hubert & Levine	0.0615	Generalized Distance Measure	Hierarchical – Complete linkage	50
		Generalized Distance Measure	Hierarchical - Complete linkage	14
		Generalized Distance Measure	Hierarchical - Complete linkage	12

The optimal distance measure and clustering method using three separate indices are shown along with the associated index value in each case. Where no index metric or value is given, an attempt was made to create more informative clusters rather than optimize a clustering index.

ISSN: 1752-0509