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Overall similarities in gene expression across all samples were first computed by means of supervised hierarchical clustering using Cluster (uncentered correlation, average linkage) and the corresponding dendogram was generated using TreeView [ 51].

The dendrogram generated by supervised hierarchical clustering shows a clear separation between fed and fasted conditions.

To highlight the differences in gene expression a supervised hierarchical clustering was performed on the set of differentially expressed genes.

These were analyzed by supervised hierarchical clustering of samples using z-scored normalized data with a Pearson correlation (uncentered) similarity metric and average linkage clustering using CLUSTER and TREEVIEW software [ 45].

The differentially expressed miRNAs of all three data sets were identified and summarized (Supporting Table 1), and two distinctive expression clusters of miRNAs were obtained by supervised hierarchical clustering analysis in each data set (Fig. 1C-E).

NKAIN1 was also an essential classifier in supervised hierarchical clustering analysis.

Genes that were expressed at significantly different levels between patients and controls were analyzed by supervised hierarchical clustering (uncentered correlation, complete linkage) [25] to visualize the correlation of co-expressed genes in Treeview (available at http://rana.lbl.gov/EisenSoftware.htm).htm

Differential DNA methylation segregated PPR from PGR by supervised hierarchical clustering and may serve as potential biomarkers for prednisolone response.

With the aid of agglomerative hierarchical cluster analysis, we categorized subjects into major clusters, which were found to have significantly different distributions of β2-AR Arg16Gly genotype.

Analysis of the data using a supervised hierarchical clustering method identified a gene expression pattern that was unique and consistent among NPC fibroblasts (Figure 1A).

Differential expression of the chosen genes across the treatment groups was assessed using supervised hierarchical clustering [ 14] that measures the proximity of distribution of samples and genes.