Figure 1.
Figure 1. Identification of consensus clusters. (A) Left panels: Consensus matrices produced by hierarchical clustering (HC, K = 3), self-organizing maps (SOM, K = 3), and probabilistic clustering (PC). Right panels: Comparisons of the cluster assignments of the different algorithms (PC vs HC, HC vs SOM, and PC vs SOM). More than 84% of DLBCLs were assigned to the same clusters by any 2 algorithms. (B) Left panel: Consensus matrix comparing the assignments made by all 3 clustering algorithms (Meta Consensus [PC vs HC] vs [PC vs SOM]). Right panel: Comparisons of the meta-consensus cluster assignments. Of the 176 tumors, 141 were assigned to the same clusters by all 3 algorithms. (C) Expression profiles of the 3 DLBCL clusters. The top 50 genes associated with each DLBCL cluster are shown. Each column is a sample, and each row is a gene. Color scale at bottom indicates relative expression and standard deviations from the mean. Red indicates high-level expression; blue, low-level expression.

Identification of consensus clusters. (A) Left panels: Consensus matrices produced by hierarchical clustering (HC, K = 3), self-organizing maps (SOM, K = 3), and probabilistic clustering (PC). Right panels: Comparisons of the cluster assignments of the different algorithms (PC vs HC, HC vs SOM, and PC vs SOM). More than 84% of DLBCLs were assigned to the same clusters by any 2 algorithms. (B) Left panel: Consensus matrix comparing the assignments made by all 3 clustering algorithms (Meta Consensus [PC vs HC] vs [PC vs SOM]). Right panel: Comparisons of the meta-consensus cluster assignments. Of the 176 tumors, 141 were assigned to the same clusters by all 3 algorithms. (C) Expression profiles of the 3 DLBCL clusters. The top 50 genes associated with each DLBCL cluster are shown. Each column is a sample, and each row is a gene. Color scale at bottom indicates relative expression and standard deviations from the mean. Red indicates high-level expression; blue, low-level expression.

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