def add_node_if_not_drawn(element_set, element, flux):
if element.id not in element_set:
n = element.name[4:]
name = met_name_by_kegg_id[n] if n in met_name_by_kegg_id else None
Kegg._add_node(data,
element,
int(flux),
name=name,
show_compound_img=None)
element_set.add(element.id)
def add_node(elements):
for e in elements:
e_name = e.name
if e_name in UNDESIRABLES:
continue
e_id = e.id
if e_name not in added_node:
added_node.add(e_name)
id_by_name[e_name] = e_id
Kegg._add_node(data,
e_id,
'metabolites',
e.name, None,
'#000000')
def get_kgml():
pathway_id = request.args.get("pathway_id")
if pathway_id is None:
return []
cytoscape_formatted = Kegg.get_kgml_network(pathway_id)
j = json.dumps(cytoscape_formatted)
return j
def test_unique_kegg_names():
kegg_list = Kegg.get_org_list()
from collections import Counter
l = []
d = csv.DictReader(kegg_list.split('\n'), delimiter='\t', fieldnames=('code', 'org', 'tax'))
for row in d:
code, org, tax = row['code'], row['org'], row['tax']
l.append(tax)
c = Counter(l)
max_val = max(c.values())
print "Max val:", max_val
while max_val > 1:
print "#", max_val, " count:", len([v for v in c.values() if v == max_val])
max_val -= 1
def get_kgml(username):
"""
main function to visualize network
return json encoded graph
"""
pathway_id = request.args.get('pathway_id')
if pathway_id is None:
return json.dumps([])
analysis_id = request.args.get('analysis_id')
analysis = Analysis.query.filter(Analysis.id == analysis_id).first_or_404()
# retrieve file data from s3
filename = '{}/{}/{}'.format(username, analysis.project_id, analysis_id)
try:
resp = requests.get(S3_URL + filename)
except ConnectionError:
return render_template('errors/server_error.html', form=LoginForm())
# return error code if request failed
if resp.status_code != 200:
return render_template('errors/server_error.html', form=LoginForm())
# load fba analysis results
results = json.loads(resp.text)
# get the sbml model
model = analysis.model.get_cobra_model()
if model is None:
return render_template('errors/server_error.html')
if pathway_id == 'whole':
# whole drawing requested
cytoscape_formatted = _build_genome_scale_network(model, results)
else:
kegg_model = Kegg.get_kgml_obj(pathway_id)
if model is None or kegg_model is None:
return render_template('errors/page_not_found.html', form=LoginForm())
kegg_model_name = request.args.get('pathway_name')
cytoscape_formatted = build_kegg_network_mixed(kegg_model,
kegg_model_name,
model,
results)
return json.dumps(cytoscape_formatted)
def initdb():
"""Creates the database."""
db.create_all()
logging.info('Getting kegg organism list...')
kegg_list = Kegg.get_org_list()
# use only get memory error otherwise
# print BiomodelMongo.objects.only('organism', 'name').all()
mongo_list = dict(
(b.organism, b.name)
for b in BiomodelMongo.objects.only('organism', 'name').all()
)
mongo_orgs = set(mongo_list.keys())
# to prevent insertion porting the same name
kegg_names = set()
logging.info('Insertion begins...')
d = csv.DictReader(kegg_list.split('\n'), delimiter='\t', fieldnames=('code', 'org', 'tax'))
for row in d:
code, org, tax = row['code'], row['org'], row['tax']
if org in mongo_orgs:
if tax not in kegg_names:
o = Organism(row['code'], row['org'], row['tax'])
o.save()
b = Biomodel(name=tax, kegg_org=org)
b.save()
# finally tax to the set
kegg_names.add(tax)
# insert user
u = User(username='******', email='*****@*****.**', password='******')
u.save()
logging.info('Done !')
def visualize_fba_analysis(username, analysis_id):
"""
main endpoint to visualize flux balance analysis
"""
analysis = Analysis.query.filter(Analysis.id == analysis_id).first_or_404()
# retrieve file data from s3
filename = '{}/{}/{}'.format(username, analysis.project_id, analysis_id)
resp = requests.get(S3_URL + filename)
# return error code if request failed
if resp.status_code != 200:
return render_template('errors/server_error.html'), 500
orgs = Organism.query.order_by(Organism.tax).all()
model = analysis.model
model_name = model.name
pathways = Kegg.get_pathways_list(org=model.kegg_org)
return render_template('user/fba_analysis.html',
analysis=analysis, organisms=orgs,
model_name=model_name, pathways=pathways,
display_sidebar=False)
def get_pathways():
org = request.args.get("org", "hsa") # the default will be the human.
pathways = Kegg.get_pathways_list(org)
data = json.dumps(pathways)
return data
def get_kegg_pathways(username):
org = request.args.get('org', 'hsa') # the default will be the human.
pathways = Kegg.get_pathways_list(org)
data = json.dumps(pathways)
return data