def expression_cluster_json(cluster_id, family_method_id=None):
"""
Generates JSON output compatible with cytoscape.js (see planet/static/planet_graph.js for details how to render)
:param cluster_id: id of the cluster to plot
:param family_method_id: gene family method used for color coding the graph
"""
network = CoexpressionCluster.get_cluster(cluster_id)
if family_method_id is None:
family_method = GeneFamilyMethod.query.first()
if family_method is not None:
family_method_id = family_method.id
else:
family_method_id = None
network_cytoscape = CytoscapeHelper.parse_network(network)
network_cytoscape = CytoscapeHelper.add_family_data_nodes(
network_cytoscape, family_method_id)
network_cytoscape = CytoscapeHelper.add_lc_data_nodes(network_cytoscape)
network_cytoscape = CytoscapeHelper.add_connection_data_nodes(
network_cytoscape)
network_cytoscape = CytoscapeHelper.add_descriptions_nodes(
network_cytoscape)
return Response(json.dumps(network_cytoscape), mimetype='application/json')
def expression_network_json(node_id, family_method_id=None):
"""
Generates JSON output compatible with cytoscape.js (see planet/static/planet_graph.js for details how to render)
:param node_id: id of the network's probe (the query) to visualize
:param family_method_id: Which gene families to use
"""
node = ExpressionNetwork.query.get(node_id)
enable_second_level = node.method.enable_second_level
depth = 1 if enable_second_level else 0
network = ExpressionNetwork.get_neighborhood(node_id, depth=depth)
if family_method_id is None:
family_method = GeneFamilyMethod.query.first()
if family_method is not None:
family_method_id = family_method.id
else:
family_method_id = None
network_cytoscape = CytoscapeHelper.parse_network(network)
network_cytoscape = CytoscapeHelper.add_family_data_nodes(
network_cytoscape, family_method_id)
network_cytoscape = CytoscapeHelper.add_lc_data_nodes(network_cytoscape)
network_cytoscape = CytoscapeHelper.add_descriptions_nodes(
network_cytoscape)
return Response(json.dumps(network_cytoscape), mimetype='application/json')
def graph_comparison_cluster_json(one, two, family_method_id=None):
"""
Controller that fetches network data from two clusters from the database, adds all essential information and merges
the two networks. The function returns a JSON object compatible with cytoscape.js
:param one: internal id of the first cluster
:param two: internal id of the second cluster
:param family_method_id: internal id of the gene family method (used down stream for coloring and connecting)
:return: json object compatible with cytoscape.js and our UI elements
"""
if family_method_id is None:
family_method = GeneFamilyMethod.query.first()
family_method_id = family_method.id
network_one = CytoscapeHelper.parse_network(
CoexpressionCluster.get_cluster(one))
network_one = CytoscapeHelper.add_family_data_nodes(
network_one, family_method_id)
network_one = CytoscapeHelper.add_connection_data_nodes(network_one)
network_two = CytoscapeHelper.parse_network(
CoexpressionCluster.get_cluster(two))
network_two = CytoscapeHelper.add_family_data_nodes(
network_two, family_method_id)
network_two = CytoscapeHelper.add_connection_data_nodes(network_two)
output = CytoscapeHelper.merge_networks(network_one, network_two)
output = CytoscapeHelper.add_lc_data_nodes(output)
output = CytoscapeHelper.add_descriptions_nodes(output)
return Response(json.dumps(output), mimetype='application/json')
def ecc_graph_json(sequence, network, family):
"""
Returns a JSON object compatible with cytoscape.js that contains the ECC graph for a specific sequence
:param sequence: Internal ID of a sequence
:param network: Internal ID of the network method
:param family: Internal ID of the family method
:return: JSON object compatible with cytoscape.js
"""
network = SequenceSequenceECCAssociation.get_ecc_network(
sequence, network, family)
network_cytoscape = CytoscapeHelper.parse_network(network)
network_cytoscape = CytoscapeHelper.add_descriptions_nodes(
network_cytoscape)
network_cytoscape = CytoscapeHelper.add_family_data_nodes(
network_cytoscape, family)
network_cytoscape = CytoscapeHelper.add_lc_data_nodes(network_cytoscape)
network_cytoscape = CytoscapeHelper.add_species_data_nodes(
network_cytoscape)
return json.dumps(network_cytoscape)
def ecc_graph_pair_json(ecc_id):
"""
Returns a JSON object compatible with cytoscape.js that contains the ECC graph for a specific pair of sequences
:param ecc_id: internal ID of the sequence to sequence ECC relationship
:return: JSON object compatible with cytoscape.js
"""
network, family = SequenceSequenceECCAssociation.get_ecc_pair_network(
ecc_id)
network_cytoscape = CytoscapeHelper.parse_network(network)
network_cytoscape = CytoscapeHelper.add_descriptions_nodes(
network_cytoscape)
network_cytoscape = CytoscapeHelper.add_family_data_nodes(
network_cytoscape, family)
network_cytoscape = CytoscapeHelper.add_lc_data_nodes(network_cytoscape)
network_cytoscape = CytoscapeHelper.add_species_data_nodes(
network_cytoscape)
network_cytoscape = CytoscapeHelper.connect_homologs(network_cytoscape)
network_cytoscape = CytoscapeHelper.tag_ecc_singles(network_cytoscape)
return json.dumps(network_cytoscape)
def custom_network_json():
"""
Profile comparison tool, accepts a species and a list of probes and plots the profiles for the selected
"""
terms = request.form.get('probes').split()
method_id = request.form.get('method_id')
family_method_id = request.form.get('family_method')
cluster_method_id = request.form.get('cluster_method')
specificity_method_id = request.form.get('specificity_method')
probes = terms
# also do search by gene ID
sequences = Sequence.query.filter(Sequence.name.in_(terms)).all()
for s in sequences:
for ep in s.expression_profiles:
probes.append(ep.probe)
# make probe list unique
probes = list(set(probes))
network = ExpressionNetwork.get_custom_network(method_id, probes)
network_cytoscape = CytoscapeHelper.parse_network(network)
network_cytoscape = CytoscapeHelper.add_family_data_nodes(
network_cytoscape, family_method_id)
network_cytoscape = CytoscapeHelper.add_lc_data_nodes(network_cytoscape)
network_cytoscape = CytoscapeHelper.add_descriptions_nodes(
network_cytoscape)
network_cytoscape = CytoscapeHelper.add_cluster_data_nodes(
network_cytoscape, cluster_method_id)
network_cytoscape = CytoscapeHelper.add_specificity_data_nodes(
network_cytoscape, specificity_method_id)
return Response(json.dumps(network_cytoscape), mimetype='application/json')
def custom_network_main():
"""
Profile comparison tool, accepts a species and a list of probes and plots the profiles for the selected
"""
form = CustomNetworkForm(request.form)
form.populate_method()
if request.method == 'POST':
terms = request.form.get('probes').split()
method_id = request.form.get('method_id')
family_method_id = request.form.get('family_method')
cluster_method_id = request.form.get('cluster_method')
specificity_method_id = request.form.get('specificity_method')
probes = terms
# also do search by gene ID
sequences = Sequence.query.filter(Sequence.name.in_(terms)).all()
for s in sequences:
for ep in s.expression_profiles:
probes.append(ep.probe)
# make probe list unique
probes = list(set(probes))
network_method = ExpressionNetworkMethod.query.get_or_404(method_id)
network = ExpressionNetwork.get_custom_network(method_id, probes)
network_cytoscape = CytoscapeHelper.parse_network(network)
network_cytoscape = CytoscapeHelper.add_family_data_nodes(
network_cytoscape, family_method_id)
network_cytoscape = CytoscapeHelper.add_lc_data_nodes(
network_cytoscape)
network_cytoscape = CytoscapeHelper.add_descriptions_nodes(
network_cytoscape)
network_cytoscape = CytoscapeHelper.add_cluster_data_nodes(
network_cytoscape, cluster_method_id)
network_cytoscape = CytoscapeHelper.add_specificity_data_nodes(
network_cytoscape, specificity_method_id)
return render_template("expression_graph.html",
graph_data=Markup(
json.dumps(network_cytoscape)),
cutoff=network_method.hrr_cutoff)
else:
example = {'method_id': None, 'probes': None}
data = ExpressionNetwork.query.order_by(
ExpressionNetwork.method_id).limit(20).all()
probes = []
for d in data:
example['method_id'] = d.method_id
if d.probe not in probes:
probes.append(d.probe)
network = json.loads(d.network)
for n in network:
if "gene_name" in n and "gene_name" not in probes and len(
probes) < 35:
probes.append(n["gene_name"])
if len(probes) >= 35:
break
example['probes'] = ' '.join(probes)
return render_template("custom_network.html",
form=form,
example=example)