In [1]:

    

!python --version


    

    




Python 3.5.2 :: Anaconda custom (x86_64)

In [51]:

    

# Load data sets
import pandas as pd

treeSourceUrl = './data/preds_yeastnet_no_gi_0.04_0.5.txt.propagate.small_parent_tree'
geneCountFile = './data/preds_yeastnet_no_gi_0.04_0.5.txt.propagate.term_sizes'
alignmentFile = './data/alignments_FDR_0.1_t_0.1'
geneAssignment = './data/preds_yeastnet_no_gi_0.04_0.5.txt.propagate.mapping'

# Load the tree data
treeColNames = ['parent', 'child', 'type', 'in_tree']
tree = pd.read_csv(treeSourceUrl, delimiter='\t', names=treeColNames)
tree.tail()


    

    
Out[51]:






  

    

      

      
parent
      
child
      
type
      
in_tree
    
  
  

    

      
136996
      
10051
      
YHR083W
      
gene
      
NOT_TREE
    
    

      
136997
      
10704
      
YHR083W
      
gene
      
NOT_TREE
    
    

      
136998
      
10699
      
YHR083W
      
gene
      
NOT_TREE
    
    

      
136999
      
10705
      
YHR083W
      
gene
      
NOT_TREE
    
    

      
137000
      
9816
      
YHR083W
      
gene
      
NOT_TREE
    
  

In [55]:

    

assignment = pd.read_csv(geneAssignment, sep='\t', names=['gene', 'clixo'])
print(assignment['clixo'].unique().shape)
assignment.head()


    

    




(4805,)






    
Out[55]:






  

    

      

      
gene
      
clixo
    
  
  

    

      
0
      
YGR220C
      
10000
    
    

      
1
      
YPR100W
      
10000
    
    

      
2
      
YNR022C
      
10000
    
    

      
3
      
YNL252C
      
10000
    
    

      
4
      
YCR046C
      
10000
    
  

In [56]:

    

al = pd.read_csv(alignmentFile, sep='\t', names=['clixo', 'go', 'similarity', 'fdr', 'genes'])
al.head()


    

    
Out[56]:






  

    

      

      
clixo
      
go
      
similarity
      
fdr
      
genes
    
  
  

    

      
0
      
8607
      
GO:0031417
      
0.919767
      
0.0
      
3
    
    

      
1
      
7720
      
GO:0004354
      
0.911533
      
0.0
      
2
    
    

      
2
      
8636
      
GO:0036437
      
0.911062
      
0.0
      
3
    
    

      
3
      
9228
      
GO:0004574
      
0.909649
      
0.0
      
5
    
    

      
4
      
9773
      
GO:0019773
      
0.908339
      
0.0
      
7
    
  

In [57]:

    

mapping = {}
for row in al.itertuples():
    entry = {
        'go': row[2],
        'score': row[3],
        'dfr': row[4]
    }
    mapping[str(row[1])] = entry


    

In [58]:

    

geneCounts = pd.read_csv(geneCountFile, names=['clixo', 'count'], sep='\t')

term2count = {}
for row in geneCounts.itertuples():
    term2count[str(row[1])] = row[2].item()


    

In [59]:

    

# Get unique terms

clixo_terms = set()

for row in tree.itertuples():
    etype = row[3]

    if not etype.startswith('gene'):
        clixo_terms.add(str(row[1]))
        clixo_terms.add(str(row[2]))

print(len(clixo_terms))


    

    




4805

In [60]:

    

import json

clixoTree = {
    'data': {
        'name': 'CLIXO Tree'
    },
    'elements': {
        'nodes': [],
        'edges': []
    }
}

print(json.dumps(clixoTree, indent=4))


    

    




{
    "data": {
        "name": "CLIXO Tree"
    },
    "elements": {
        "edges": [],
        "nodes": []
    }
}

In [63]:

    

def get_node(id, count):
    node = {
        'data': {
            'id': id,
            'geneCount': count
        }
    }
        
    return node

def get_edge(source, target):
    edge = {
        'data': {
            'source': target,
            'target': source
        }
    }
    
    return edge


    

In [65]:

    

edges = []
PREFIX = 'CLIXO:'

for row in tree.itertuples():
    etype = row[3]
    in_tree = row[4]
    if etype.startswith('gene') or in_tree == 'NOT_TREE':
        continue
    
    source = PREFIX + str(row[1])
    child = PREFIX + str(row[2])
    edges.append(get_edge(source, child))
    
print(len(edges))


    

    




4804

In [66]:

    

nodes = []

for id in clixo_terms:
    node = get_node(PREFIX + id, term2count[id])
    nodes.append(node)

print(len(nodes))


    

    




4805

In [67]:

    

clixoTree['elements']['nodes'] = nodes
clixoTree['elements']['edges'] = edges

with open('./data/clixo-tree.cyjs', 'w') as outfile:
    json.dump(clixoTree, outfile)


    

In [29]:

    

import networkx as nx

DG=nx.DiGraph()

for node in nodes:
    DG.add_node(node['data']['id'])

for edge in edges:
    DG.add_edge(edge['data']['source'], edge['data']['target'])


    

In [30]:

    

import matplotlib.pyplot as plt


    

In [31]:

    

nx.draw_circular(DG)


    

In [33]:

    

# pos = nx.nx_pydot.pydot_layout(DG)