A Scalable Approach for Discovering Conserved Active Subnetworks across Species
Figure 2
Evaluation of conserved subnetworks.
(A) The cross-species algorithm mines subnetworks in the functional linkage network with a high density of differentially expressed genes. The network score of a subnetwork reflects the average differential activity of all genes in the network. The number of subnetworks identified at a network score threshold is plotted (solid line) and is compared to the number of subnetworks identified after differential expression scores were randomly shuffled (dotted line). The parameters for average clustering coefficient are 0.1 for mouse and 0.2 for human. (B) The number of conserved subnetworks discovered is plotted for a range of connectedness parameters (minimum clustering coefficient). All clustering coefficients noted are relative to the background, single-gene average clustering coefficient, which is 0.08 for mouse and 0.35 for human.