Figure 2.

Network properties of the correlation network (CN) and Gaussian graphical model (GGM) inferred from a targeted metabolomics population data set (1020 participants, 151 quantified metabolites). A+B: Graphical depiction of significantly positive edges in both networks, emphasizing local clustering structures. Each circle color represents a single metabolite class. C+D: Histograms of <a onClick="popup('','MathML',630,470);return false;" target="_blank" href="">View MathML</a> pairwise correlation coefficients (i.e. edge weights) for both networks. Green lines indicate the median values, red lines denote a significance level of 0.01 with Bonferroni correction. The CN displays a general bias towards positive correlations throughout all metabolites. For the GGM, the median value lies around zero and we observe a shift towards significantly positive values. E+F: Modularity between metabolite classes measured as the relative out-degree from each class (rows) to all other classes (columns). The GGM (right) shows a clear separation of metabolite classes, with some overlaps for the different phospholipid species diacyl-PCs, lyso-PCs, acyl-alkyl-PCs and sphingomyelins. Values range from white (0.0 out-degree towards this class) to black (1.0). PCs = phosphatidylcholines.

Krumsiek et al. BMC Systems Biology 2011 5:21   doi:10.1186/1752-0509-5-21
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