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. 2015 Jun 30;2015:7. doi: 10.1186/s13637-015-0025-6

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© Ayati et al. 2015

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited.

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Fig. 2 — Statistical significance of subnetworks. Statistical significance of high-scoring subnetworks identified using NODE-BASED scoring (first column), LINEAR COMBINATION of node scores and edge scores (second column), and MODULARITY-BASED (MOBAS) scoring (third column). The highest scoring 20 subnetworks identified using each scoring scheme are shown. The x-axis shows the rank of each subnetwork according to their score, and the y-axis shows its score. The blue curve shows the scores of the subnetworks identified on the WTCCC-T2D dataset. For each i on the x-axis, the red (green) curve and error bar in the first (second) row show the distribution of the scores of i highest scoring subnetworks in 100 datasets obtained by permuting the genotypes of the samples (permuting the interactions in the PPI networks while preserving node degrees)