Table 1.
HIV | HCV | Combined | |||||
---|---|---|---|---|---|---|---|
Centrality measure | s66 | s52 | s43 | s64 | s46 | s52 | s239 |
Betweenness | < 0.0001 | 0.0131 | 0.0247 | 0.0005 | 0.0131 | 0.0131 | 0.0040 |
Closeness | <0.0001 | 0.0131 | 0.0247 | 0.0005 | 0.0131 | 0.0131 | 0.0040 |
Clustering Coefficient | < 0.0001 | 0.0247 | 0.0001 | 0.0005 | 0.0131 | 0.0131 | 0.0040 |
Eigenvector Centrality | < 0.0001 | 0.0131 | 1 | 1 | 1 | 0.0057 | 0.0057 |
Node Degree | < 0.0001 | 1 | 0.0247 | 0.0005 | 0.0211 | 0.0131 | 0.0040 |
Path Length | < 0.0001 | 0.0131 | 0.0247 | 0.0002 | 0.0131 | 0.0131 | 0.0040 |
Dice Similarity | < 0.0001 | 0.0131 | 0.0247 | 0.0005 | 0.0131 | 0.0131 | 0.0040 |
Wang Sim. (GO.BP) | 0.0004 | 0.0286 | 0.5926 | 0.6009 | 0.0284 | 0.0286 | 0.0136 |
Wang Sim. (GO.CC) | 0.0004 | 0.0286 | 0.5926 | 0.0315 | 0.0284 | 0.0286 | 0.0136 |
Wang Sim. (GO.MF) | 0.0004 | 0.0286 | 0.0498 | 0.7713 | 1 | 0.3429 | 0.1077 |
A Wilcoxon test was used to determine the significance of network centrality measures and semantic similarity measures of subnetworks significantly enriched with RNAi screening hits. Average similarity measures over all nodes in a given enriched cluster were tested against non-enriched subnetworks of comparable size, using a Wilcoxon test to assess significance of the differences between the means for each of the given network centrality and semantic similarity measures. Shown are resulting p-values for two clusters for HIV, two clusters for HCV, and three combined clusters.