In [1]:

    

import requests # Best REST client for Python!
import json # Standard toolkit to do something with JSON in Python
import networkx as nx # Popular python library for network analysis
from IPython.display import Image # Library to display images in IPython Notebook
import pandas as pd # Pandas - de-facto standard tool for data analysis in Python 
from py2cytoscape import util # Small utility to convert Python objects to Cytoscape-friendly ones.

# Default Port Number for cyREST
PORT_NUMBER = 1234

# Header for posting data to the server as JSON
HEADERS = {'Content-Type': 'application/json'}

# The base URL to talking to local instance of Cytoscape
BASE_URL = 'http://localhost:' + str(PORT_NUMBER) + '/v1/'
styles_url = BASE_URL + 'styles'

print('\n\nCytoscape service is located at: ' + BASE_URL + '\n\n')
print('Available Styles are: ' + styles_url + '\n\n\n')

# Give a fresh start...  Delete all networks
requests.delete(BASE_URL + 'session')


    

    





Cytoscape service is located at: http://localhost:1234/v1/


Available Styles are: http://localhost:1234/v1/styles









    
Out[1]:





<Response [200]>

In [2]:

    

def create_scale_free_graph(size, index):
    scale_free_graph = nx.scale_free_graph(size)
    scale_free_graph.graph['name'] = 'Scale-Free Graph ' + str(index)
    return scale_free_graph

# Create 10 scale-free networks on-the-fly
networks = []

suids = []

for i in range(5):
    network = create_scale_free_graph(100, i)
    networks.append(network)
    
    # Send generated network to Cytoscape
    res1 = requests.post(BASE_URL + 'networks', data=json.dumps(util.from_networkx(network)), headers=HEADERS)
    res1_dict = json.loads(res1.content)
    new_suid = res1_dict['networkSUID']
    suids.append(new_suid)
    
    # Apply layout!
    requests.get(BASE_URL + 'apply/layouts/force-directed/' + str(new_suid))
    requests.get(BASE_URL + 'apply/styles/Directed/' + str(new_suid))


    

In [3]:

    

network_image_url = BASE_URL+ 'networks/' + str(suids[0]) + '/views/first.png'

print('\n\nThe network Image is available here: ' + network_image_url + '\n\n\n')
Image(network_image_url)


    

    





The network Image is available here: http://localhost:1234/v1/networks/89996/views/first.png









    
Out[3]:

In [4]:

    

import io

# KEGG API
KEGG_API_URL = 'http://rest.kegg.jp/'

# Find information about 'cancer' from KEGG disease database.
query = 'cancer'

res = requests.get(KEGG_API_URL + '/find/disease/' + query)
pathway_list = res.content.decode('utf8')

disease_df = pd.read_csv(io.StringIO(pathway_list), delimiter='\t',  header=None, names=['id', 'name'])
disease_df.head(10)


    

    
Out[4]:






  

    

      

      
id
      
name
    
  
  

    

      
0
      
ds:H00013
      
Small cell lung cancer
    
    

      
1
      
ds:H00014
      
Non-small cell lung cancer
    
    

      
2
      
ds:H00016
      
Oral cancer
    
    

      
3
      
ds:H00017
      
Esophageal cancer
    
    

      
4
      
ds:H00018
      
Gastric cancer
    
    

      
5
      
ds:H00019
      
Pancreatic cancer
    
    

      
6
      
ds:H00020
      
Colorectal cancer
    
    

      
7
      
ds:H00022
      
Bladder cancer
    
    

      
8
      
ds:H00023
      
Testicular cancer
    
    

      
9
      
ds:H00024
      
Prostate cancer
    
  

In [5]:

    

disease_ids = disease_df['id']
disease_urls = disease_ids.apply(lambda x: KEGG_API_URL + 'get/' + x)

def disease_parser(entry):
    lines = entry.split('\n')
    data = {}
    
    last_key = None
    for line in lines:
        if '///' in line:
            return data
        
        parts = line.split(' ')
        if parts[0] is not None and len(parts[0]) != 0:
            last_key = parts[0]
            data[parts[0]] = line.replace(parts[0], '').strip()
        else:
            last_val = data[last_key]
            data[last_key] = last_val + '|' + line.strip()
    return data   

result = []
for url in disease_urls:
        res = requests.get(url)
        rows = disease_parser(res.content)
        result.append(rows)
disease_df = pd.DataFrame(result)
pathways = disease_df['PATHWAY'].dropna().unique()

p_urls = []
for pathway in pathways:
    entries = pathway.split('|')
    for en in entries:
        url = KEGG_API_URL + 'get/' + en.split(' ')[0].split('(')[0] + '/kgml'
        p_urls.append(url)


    

In [6]:

    

disease_df = pd.DataFrame(result)
pathways = disease_df['PATHWAY'].dropna().unique()

p_urls = []
for pathway in pathways:
    entries = pathway.split('|')
    for en in entries:
        url = KEGG_API_URL + 'get/' + en.split(' ')[0].split('(')[0] + '/kgml'
        p_urls.append(url)


    

In [7]:

    

def create_from_list(network_list):
    server_res = requests.post(BASE_URL + 'networks?source=url&collection=' + query, data=json.dumps(network_list), headers=HEADERS)
    return json.loads(server_res.content)

requests.delete(BASE_URL + 'networks')

url_list = list(set(p_urls))
pathway_suids = create_from_list(url_list)


    

In [8]:

    

# Package to render networks in Cytoscape.js
from py2cytoscape import cytoscapejs as cyjs

res1 = requests.get(BASE_URL + 'styles/KEGG Style.json')
kegg_style = res1.json()

# Load local network files
kegg_url = BASE_URL + 'networks/' + str(pathway_suids[3]['networkSUID'][0])
net1 =  requests.get(kegg_url + '/views/first')

# Render it!
cyjs.render(net1.json(), style=kegg_style[0]['style'], background='white')