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-rw-r--r--Code/draw_subnetwork.py161
1 files changed, 120 insertions, 41 deletions
diff --git a/Code/draw_subnetwork.py b/Code/draw_subnetwork.py
index 79ab5cd..d05f2d4 100644
--- a/Code/draw_subnetwork.py
+++ b/Code/draw_subnetwork.py
@@ -1,7 +1,10 @@
# Usage: python draw_subnetwork.py edges.txt
-# Purpose: draw a sub-network given a list of genes.
+# Purpose: draw a sub-network given a list of genes from thermomorphogenesis paper.
+# The paper Molecular and genetic control of plant thermomorphogenesis. https://doi.org/10.1038/nplants.2015.190
+#
# Created on 5 December 2019 by Hui Lan (lanhui@zjnu.edu.cn)
+
import os, sys
import networkx as nx
import pylab as plt
@@ -9,6 +12,7 @@ import glob
import math
from networkx.algorithms.distance_measures import diameter, eccentricity
+
def build_network_from_file(edge_fname, gene_lst, gene_dict):
G = nx.DiGraph()
@@ -46,6 +50,33 @@ def build_network_from_file(edge_fname, gene_lst, gene_dict):
return G
+
+def build_thermomorphogenesis_network(gene_lst, gene_dict):
+ ''' Edges from thermo.png in my asus laptop. '''
+ G = nx.DiGraph()
+
+ for g in gene_lst:
+ G.add_node(gene_dict[g])
+
+ pairs = [('PIF4', 'PAR1'), ('PIF4', 'PRE1'), ('PIF4', 'YUC8'), ('PIF4', 'TAA1'), ('PIF4', 'IAA4'), ('PIF4', 'SAUR21'),
+ ('HY5', 'PAR1'), ('HY5', 'PRE1'), ('HY5', 'YUC8'), ('HY5', 'TAA1'), ('HY5', 'IAA4'), ('HY5', 'SAUR21'),
+ ('FCA', 'PAR1'), ('FCA', 'PRE1'), ('FCA', 'YUC8'), ('FCA', 'TAA1'), ('FCA', 'IAA4'), ('FCA', 'SAUR21'),
+ ('BZR1', 'PAR1'), ('BZR1', 'PRE1'), ('BZR1', 'YUC8'), ('BZR1', 'TAA1'), ('BZR1', 'IAA4'), ('BZR1', 'SAUR21'),
+ ('ARF6', 'PAR1'), ('ARF6', 'PRE1'), ('ARF6', 'YUC8'), ('ARF6', 'TAA1'), ('ARF6', 'IAA4'), ('ARF6', 'SAUR21'),
+ ('PAR1', 'IBH1'), ('PRE1', 'IBH1'),
+ ('PAR1', 'PIF4'), ('PRE1', 'PIF4'),
+ ('IBH1', 'HBI1'),
+ ('IAA4', 'ARF6'),
+ ('ARF6', 'SAUR21')
+ ] # see paper Molecular and genetic control of plant thermomorphogenesis. https://doi.org/10.1038/nplants.2015.190
+
+ for (g2, g1) in pairs: # g2 is source, g1 is target
+ G.add_edge(g2, g1, weight=2) # g2 is source, and g1 is target
+
+
+ return G
+
+
def compute_total_edge_weight(edges, G):
total = 0
for e in edges:
@@ -71,18 +102,22 @@ def draw_graph(G, fname):
nx.draw_networkx_edges(G,pos,edgelist=esmall,width=1,alpha=0.1,edge_color='k',style='dashed')
nx.draw_networkx_labels(G,pos,font_size=8,font_color='k',font_family='sans-serif')
plt.axis('off')
- plt.savefig(fname) # save as png
+ plt.savefig(fname)
+ plt.close()
#plt.show() # display
def better_date(s):
+ ''' Add a dash between year and month, and a dash between month and day.'''
if len(s) == 8:
return '-'.join([s[:4], s[4:6], s[6:]])
else:
return s
+
def draw_graph2(G, fname, date):
- pos=nx.circular_layout(G)
+
+ pos = nx.circular_layout(G)
all_edges = []
all_widths = []
@@ -91,11 +126,29 @@ def draw_graph2(G, fname, date):
all_widths.append(math.sqrt(d['weight']))
nx.draw_networkx_nodes(G,pos,alpha=0.05)
- nx.draw_networkx_edges(G,pos,edgelist=all_edges,width=all_widths,alpha=0.05,edge_color='k',style='dashed')
+ nx.draw_networkx_edges(G,pos,edgelist=all_edges,width=all_widths,alpha=0.2,edge_color='k',style='dashed')
nx.draw_networkx_labels(G,pos,font_size=11,font_color='b',font_family='sans-serif')
plt.axis('off')
plt.title(better_date(date))
- plt.savefig(fname) # save as png
+ plt.savefig(fname)
+ plt.close()
+ #plt.show() # display
+
+
+def draw_graph3(G, fname):
+
+ pos = nx.circular_layout(G)
+ all_edges = []
+
+ for (u, v, d) in G.edges(data=True):
+ all_edges.append((u, v))
+
+ nx.draw_networkx_nodes(G,pos,alpha=0.05)
+ nx.draw_networkx_edges(G,pos,edgelist=all_edges,alpha=0.2,edge_color='k',style='dashed')
+ nx.draw_networkx_labels(G,pos,font_size=11,font_color='b',font_family='sans-serif')
+ plt.axis('off')
+ plt.savefig(fname)
+ plt.close() # it is important to close the plot before creating another one. Otherwise, plots will overlap.
#plt.show() # display
@@ -165,6 +218,7 @@ thermomorphogenesis_genes_small = [
'AT5G11260', #HY5
'AT2G42870', #PAR1
'AT5G39860', #PRE1
+ 'AT5G43700', #IAA4
'AT4G16280', #FCA
'AT2G43060', #IBH1
'AT2G18300', #HBI1
@@ -172,18 +226,19 @@ thermomorphogenesis_genes_small = [
'AT1G70560', #TAA1
'AT1G30330', #ARF6
'AT1G19850', #ARF5
- 'AT1G75080', #BZR1
- 'AT2G25930', #ELF3
- 'AT2G40080', #ELF4
- 'AT3G46640', #LUX
+ 'AT5G01830', #SAUR21
+ 'AT1G75080' #BZR1
+# 'AT2G25930', #ELF3
+# 'AT2G40080', #ELF4
+# 'AT3G46640', #LUX
]
-
gene_dict = {
'AT2G43010':'PIF4',
'AT5G11260':'HY5',
'AT2G42870':'PAR1',
'AT5G39860':'PRE1',
+ 'AT5G43700':'IAA4',
'AT4G16280':'FCA',
'AT2G43060':'IBH1',
'AT2G18300':'HBI1',
@@ -191,13 +246,18 @@ gene_dict = {
'AT1G70560':'TAA1',
'AT1G30330':'ARF6',
'AT1G19850':'ARF5',
+ 'AT5G01830':'SAUR21',
'AT1G75080':'BZR1',
'AT2G25930':'ELF3',
'AT2G40080':'ELF4',
'AT3G46640':'LUX'
}
-print('Make sub graph...')
+print('Make sub graphs ...')
+
+G0 = build_thermomorphogenesis_network(thermomorphogenesis_genes_small, gene_dict)
+print('Number of edges in the paper thermomorphogenesis is %d' % (len(G0.edges())))
+draw_graph2(G0, '../Data/temp/graph-%s.pdf' % ('20160101'), '')
graph_lst = []
graph_names = []
@@ -206,43 +266,62 @@ for fname in sorted(glob.glob('../Analysis/edges.txt.2019*')):
continue
print(fname)
graph_names.append(fname)
- graph_lst.append(build_network_from_file(fname, thermomorphogenesis_genes_small, gene_dict))
+ G = build_network_from_file(fname, thermomorphogenesis_genes_small, gene_dict)
+ graph_lst.append(G)
-#G1205 = build_network_from_file('../Analysis/edges.txt.20191205', thermomorphogenesis_genes)
-#G1203 = build_network_from_file('../Analysis/edges.txt.20191203', thermomorphogenesis_genes)
-#G1126 = build_network_from_file('../Analysis/edges.txt.20191126', thermomorphogenesis_genes)
-#G1108 = build_network_from_file('../Analysis/edges.txt.20191108', thermomorphogenesis_genes)
+for i in range(len(graph_lst)):
+ G = graph_lst[i]
+ print('Graph from %s' % (graph_names[i]))
+ e = G.edges(data=True)
+ n = len(e)
+ print('Number of edges is %d' % (n))
+ print('------------------------------------------------------------------------')
+ draw_graph2(G, '../Data/temp/graph-%s.pdf' % (graph_names[i].split('.')[-1]), graph_names[i].split('.')[-1])
-for i in range(len(graph_lst)-1):
- G1 = graph_lst[i]
- G2 = graph_lst[i+1]
+print('Compute network differences ...')
+Gdiff1 = nx.difference(G0, G)
+draw_graph3(Gdiff1, '../Data/temp/graph-in-G0-not-in-G.pdf')
- print(nx.is_isomorphic(G1, G2))
- print('Graph 1 from %s' % (graph_names[i]))
- e1 = G1.edges(data=True)
- n1 = len(e1)
- tw1 = compute_total_edge_weight(e1, G1)
- print('Number of edges is %d' % (n1))
- if n1 > 0:
- print('Total edge association strength is %4.2f (avg=%4.2f).' % (tw1, tw1/n1))
- #print(e1)
+Gdiff2 = nx.difference(G, G0)
+draw_graph3(Gdiff2, '../Data/temp/graph-in-G-not-in-G0.pdf')
- print('Graph 2 from %s' % (graph_names[i+1]))
- e2 = G2.edges(data=True)
- n2 = len(e2)
- tw2 = compute_total_edge_weight(e2, G2)
- print('Number of edges is %d' % (n2))
- if n2 > 0:
- print('Total edge association strength is %4.2f (avg=%4.2f).' % (tw2, tw2/n2))
- #print(e2)
+print('Compute network intersection ...')
+Gdiff1 = nx.intersection(G0, G)
+draw_graph3(Gdiff1, '../Data/temp/graph-in-G0-and-in-G.pdf')
- ged = nx.algorithms.similarity.graph_edit_distance(G1, G2)
- print(ged)
+print('Compute edit distance ...')
+ged = nx.algorithms.similarity.graph_edit_distance(G0, G) # sometimes take very long time to finish
+print('Edit distance is %4.0f' % (ged))
- print('------------------------------------------------------------------------')
+# for i in range(len(graph_lst)-1):
+# G1 = graph_lst[i]
+# G2 = graph_lst[i+1]
- draw_graph2(G1, '../Data/temp/graph-%s.png' % (graph_names[i].split('.')[-1]), graph_names[i].split('.')[-1])
-
+# print(nx.is_isomorphic(G1, G2))
+# print('Graph 1 from %s' % (graph_names[i]))
+# e1 = G1.edges(data=True)
+# n1 = len(e1)
+# tw1 = compute_total_edge_weight(e1, G1)
+# print('Number of edges is %d' % (n1))
+# if n1 > 0:
+# print('Total edge association strength is %4.2f (avg=%4.2f).' % (tw1, tw1/n1))
+# #print(e1)
+
+# print('Graph 2 from %s' % (graph_names[i+1]))
+# e2 = G2.edges(data=True)
+# n2 = len(e2)
+# tw2 = compute_total_edge_weight(e2, G2)
+# print('Number of edges is %d' % (n2))
+# if n2 > 0:
+# print('Total edge association strength is %4.2f (avg=%4.2f).' % (tw2, tw2/n2))
+# #print(e2)
+
+# ged = nx.algorithms.similarity.graph_edit_distance(G1, G2)
+# print(ged)
+
+# print('------------------------------------------------------------------------')
+
+# draw_graph2(G1, '../Data/temp/graph-%s.png' % (graph_names[i].split('.')[-1]), graph_names[i].split('.')[-1])
generated by cgit v1.2.1 (git 2.18.0) at 2025-03-15 12:15:57 +0000