Mercurial > repos > bornea > network_attributes
changeset 1:e4a55256547a draft
Uploaded
author | bornea |
---|---|
date | Wed, 18 Oct 2017 15:23:06 -0400 |
parents | c8a8a1e90a9d |
children | 40339590a08d |
files | Calculate_attributes.R |
diffstat | 1 files changed, 30 insertions(+), 0 deletions(-) [+] |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/Calculate_attributes.R Wed Oct 18 15:23:06 2017 -0400 @@ -0,0 +1,30 @@ +library(igraph) +library(dplyr) +library(ggplot2) + +NetworkAttributes <- function(edges,centrality = "eigenvector",community="fast.greedy") { + "This function takes in a SIF formatted dataframe and returns a node attribute dataframe." + "It performs community optimization and calculates a centrality metric." + nodes <- data.frame(V1 = unique(c(as.character(edges[,1]),as.character(edges[,2])))) + graph <- graph.data.frame(edges, directed = FALSE, vertices = nodes) + graph = simplify(graph) + if(community == "optimal"){V(graph)$comm <- membership(optimal.community(graph))} # computationally intensive + if(community == "fast.greedy"){V(graph)$comm <- membership(fastgreedy.community(graph))} # for larger datasets\ + if(community == "edge.betweenness"){V(graph)$comm <- membership(edge.betweenness.community(graph))} + if(community == "walk.trap"){V(graph)$comm <- membership(walktrap.community(graph))} + if(community == "spin.glass"){V(graph)$comm <- membership(spinglass.community(graph))} + if(community == "leading.eigenvector"){V(graph)$comm <- membership(leading.eigenvector.community(graph))} + if(community == "label.propagation"){V(graph)$comm <- membership(label.propagation.community(graph))} + if(community == "multilevel"){V(graph)$comm <- membership(multilevel.community(graph))} + + if(centrality == "closeness"){V(graph)$closeness <- centralization.closeness(graph)$res} + if(centrality == "betweenness"){V(graph)$betweenness <- centralization.betweenness(graph)$res} + if(centrality == "eigenvector"){V(graph)$eigen <- centralization.evcent(graph)$vector} + if(centrality == "PageRank"){V(graph)$page <- page_rank(graph)$vector} + + return(get.data.frame(graph, what = "vertices")) +} +#calculate_attributes(nodes,edgelist,centrality = "betweenness",community="fastgreedy") +args <- commandArgs(trailingOnly = TRUE) +edgelist <- read.table(file=as.character(args[1]), stringsAsFactors = FALSE,sep="\t",header=FALSE) +write.table(NetworkAttributes(edgelist,args[2],args[3]),"node_attr.txt",sep="\t",quote=FALSE,row.names=FALSE)