real.clusters <- sample2comp estimated.clusters <- sample2response(res, subnet.id, "hard") table(real.clusters, estimated.clusters)
After identifying the locally connected subnetworks, it is possible to search for features (genes) that are similar to a given subnetwork but not directly interacting with it. To order the remaining features in the input data based on similarity with the subnetwork, type
g <- find.similar.features(res, subnet.id = "Subnet-1") subset(g, delta < 0)
This gives a data frame which indicates similarity level with the subnetwork for each feature. The smaller, the more similar. Negative values of delta indicate the presence of coordinated responses, positive values of delta indicate independent responses. The data frame is ordered such that the features are listed by decreasing similarity.
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