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Table 1 P-values of Wilcoxon test to determine significance of mean values of network centralities and semantic measures for subnetwork

From: An integrative approach for a network based meta-analysis of viral RNAi screens

 

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

  1. 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.
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Algorithms for Molecular Biology

ISSN: 1748-7188