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# Usage: python degree_of_deparation.py edges.txt
# Purpose: get the maximum degree of separation
import os, sys
import networkx as nx
#import util_networkx
from networkx.algorithms.distance_measures import diameter
def build_network_from_file(edge_fname):
G = nx.DiGraph()
source_nodes = []
f = open(edge_fname)
for line in f:
line = line.strip()
lst = line.split('\t')
if line != '':
strength = float(lst[8])
method_or_tissue = lst[9]
g1 = lst[0].split()[0] # target gene ID
g1_label = lst[0].split()[1].split(';')[0] if lst[0].split()[1] != '.' else g1
g1_name = lst[0].split()[1] if lst[0].split()[1] != '.' else ''
g2 = lst[1].split()[0] # source gene ID
g2_label = lst[1].split()[1].split(';')[0] if lst[1].split()[1] != '.' else g2
g2_name = lst[1].split()[1] if lst[1].split()[1] != '.' else ''
G.add_node(g1, full_name=g1_name, label=g1_label) # if g1 is also a TF, then istf='0' will overwrite it in the following for loop
G.add_node(g2, full_name=g2_name, label=g2_label) # tf_category contains default TF category code. It can be modified later given user's input
G.add_edge(g2, g1, weight=float(lst[2]), strength=strength, method=method_or_tissue) # g2 is source, and g1 is target
source_nodes.append(g2)
f.close()
source_nodes = list(set(source_nodes))
return G, source_nodes
## main
print('Load graph...')
G, source_nodes = build_network_from_file(sys.argv[1])
print('Convert to undirected...')
G2 = G.to_undirected()
print('Compute diameter...')
d1 = diameter(G2)
print('Graph diameter: %d' % (d1))
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