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Figure 2 | Genome Medicine

Figure 2

From: The `dnet’ approach promotes emerging research on cancer patient survival

Figure 2

Performance evaluation in identifying the patient-survival gene network. The performance of the dent method is compared against a popular and commonly used method called `jActiveModules’ and its extensions. A two-sample Kolmogorov-Smirnov (KS) test is used to assess the significance (P value) of the differential distributions. (A) Boxplot displays the distribution of Cox hazard ratio (HR) for network genes. Also illustrated on the left are 46 genes in the consensus network identified by jActiveModules. This consensus is reached based on results from four different annealing options as indicated. (B) Gene set enrichment analysis (GSEA) of network genes. GSEA is used to examine the extent to which genes in a network are rank-enriched towards the highest Cox HR. The plots show the running enrichment score and a peak (circled in blue) with a normalised enrichment score (NES). Genes in the survival network are indicated with red lines. (C) Comparisons of survival genes identified by both methods. Left panel: Venn diagram illustrating the differences and intersections of survival genes. Right panel: boxplot illustrating the distribution of Cox HR grouped according to the Venn diagram.

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