# HG changeset patch
# User bornea
# Date 1508354586 14400
# Node ID e4a55256547a8dd0a9391c9e382246d045be0b7b
# Parent  c8a8a1e90a9d3f5ef1bca4a6c78a5209b4a1631e
Uploaded

diff -r c8a8a1e90a9d -r e4a55256547a Calculate_attributes.R
--- /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)