plot_net {dSimer} | R Documentation |
plot a network/graph of a symmetric disease similarity matrix, note that a unsymmetric matrix can't be visualized into a network by this method.
plot_net(simmat, cutoff = 1, vertex.label.font = 2, vertex.label.dist = 0.5, vertex.label.color = "black", vertex.label.cex = 0.8, vertex.shape = "circle", vertex.color = "paleturquoise", vertex.size = 20, edge.color = "red", layout = layout.fruchterman.reingold)
simmat |
a symmetric similarity matrix |
cutoff |
a cutoff value, only disease pairs have similarity scores no less than cutoff will be visualized in the network |
vertex.label.font |
label text font |
vertex.label.dist |
label text dist |
vertex.label.color |
label text color |
vertex.label.cex |
label text cex |
vertex.shape |
vertex shape |
vertex.color |
vertex color |
vertex.size |
vertex size |
edge.color |
edge color |
layout |
layout |
an igraph plot object
Peng Ni, Min Li
data(d2g_separation) data(interactome) graph_interactome<-graph.data.frame(interactome,directed=FALSE) ds<-c("myocardial ischemia","myocardial infarction","coronary artery disease", "cerebrovascular disorders","arthritis, rheumatoid","diabetes mellitus, type 1", "autoimmune diseases of the nervous system","demyelinating autoimmune diseases, cns", "respiratory hypersensitivity","asthma","retinitis pigmentosa", "retinal degeneration","macular degeneration") sep<-Separation(ds,ds,d2g_separation,graph_interactome) sim<-Separation2Similarity(sep) plot_net(sim,cutoff=0.2)