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extend get_connected_neurons_by_type to be able to group by class #252

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extend get_connected_neurons_by_type to be able to group by class #252

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c6343cd
extend get_connected_neurons_by_type to be able to group by class
Clare72 Sep 5, 2025
09b6596
optimisation
Clare72 Sep 16, 2025
4075037
add a test
Clare72 Sep 16, 2025
a8ed9da
add Neuron labels
Clare72 Sep 16, 2025
23d092b
minor improvements to query
Clare72 Sep 19, 2025
700691b
exclude particular databases
Clare72 Sep 22, 2025
1092b42
fix tests
Clare72 Sep 22, 2025
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88 changes: 57 additions & 31 deletions src/vfb_connect/cross_server_tools.py
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Original file line number Diff line number Diff line change
Expand Up @@ -521,15 +521,17 @@ def get_neurons_upstream_of(self, neuron, weight, classification=None, query_by_
classification=classification, query_by_label=query_by_label,
return_dataframe=return_dataframe, verbose=verbose)

def get_connected_neurons_by_type(self, weight, upstream_type=None, downstream_type=None, query_by_label=True,
return_dataframe=True, verbose=False):
def get_connected_neurons_by_type(self, weight, upstream_type=None, downstream_type=None, group_by_class=False,
query_by_label=True, exclude_dbs=['hb', 'fafb'], return_dataframe=True, verbose=False):

"""Get all synaptic connections between individual neurons of `upstream_type` and `downstream_type` where
synapse count >= `weight`. At least one of 'upstream_type' or downstream_type must be specified.

:param upstream_type: The upstream neuron type (e.g., 'GABAergic neuron').
:param downstream_type: The downstream neuron type (e.g., 'Descending neuron').
:param group_by_class: If `True`, return connectivity results aggregated by class rather than per neuron. Default `False`.
:param query_by_label: Optional. Specify neuron type by label if `True` (default) or by short_form ID if `False`.
:param exclude_dbs: Optional. List of databases (short_forms or symbols) to exclude from results. Hemibrain and catmaid FAFB excluded by default.
:param return_dataframe: Optional. Returns pandas DataFrame if `True`, otherwise returns list of dicts. Default `True`.
:return: A DataFrame or list of synaptic connections between specified neuron types.
:rtype: pandas.DataFrame or list of dicts
Expand All @@ -546,36 +548,60 @@ def get_connected_neurons_by_type(self, weight, upstream_type=None, downstream_t
if upstream_type: upstream_type = self.lookup_id(dequote(upstream_type))
if downstream_type: downstream_type = self.lookup_id(dequote(downstream_type))
cypher_ql = []
if upstream_type:
cypher_ql.append(
"MATCH (up:Class)<-[:SUBCLASSOF*0..]-(c1:Class)<-[:INSTANCEOF]-(n1:has_neuron_connectivity)"
" WHERE up.short_form = '%s' " % upstream_type)
if downstream_type:
cypher_ql.append(
"MATCH (down:Class)<-[:SUBCLASSOF*0..]-(c2:Class)<-[:INSTANCEOF]-(n2:has_neuron_connectivity)"
"WHERE down.short_form = '%s' " % downstream_type)
if not upstream_type:
cypher_ql.append(
"MATCH (c1:Class)<-[:INSTANCEOF]-(n1)-[r:synapsed_to]->(n2) WHERE r.weight[0] >= %d " % weight)
elif not downstream_type:
cypher_ql.append(
"MATCH (n1)-[r:synapsed_to]->(n2)-[:INSTANCEOF]->(c2:Class) WHERE r.weight[0] >= %d " % weight)

cypher_ql.append(
"MATCH %s(c1:Class:Neuron) "
% ('(:Class:Neuron {short_form:"' + upstream_type + '"})<-[:SUBCLASSOF*0..]-' if upstream_type else ""))
cypher_ql.append(
"MATCH %s(c2:Class:Neuron) "
% ('(:Class:Neuron {short_form:"' + downstream_type + '"})<-[:SUBCLASSOF*0..]-' if downstream_type else ""))

cypher_ql.append("MATCH (c1)<-[:INSTANCEOF]-(n1:Individual:Neuron:has_neuron_connectivity)-"
"[r:synapsed_to]->(n2:Individual:Neuron:has_neuron_connectivity)-[:INSTANCEOF]->(c2) "
"WHERE r.weight[0] >= %s " % weight)

if exclude_dbs:
cypher_ql.append("MATCH (n1)-[:database_cross_reference]->(s:Individual:Site {is_data_source:[True]}) \n"
"WHERE NOT (s.short_form IN %s) \n"
"AND NOT (s.symbol[0] IN %s) "
% (exclude_dbs, exclude_dbs))

if not group_by_class:
cypher_ql.append("OPTIONAL MATCH (n1)-[r1:database_cross_reference]->(s1:Individual:Site {is_data_source:[True]}) \n"
"OPTIONAL MATCH (n2)-[r2:database_cross_reference]->(s2:Individual:Site {is_data_source:[True]}) \n"
"RETURN apoc.text.join(collect(distinct c1.label),'|') AS upstream_class, "
"apoc.text.join(collect(distinct c1.short_form),'|') AS upstream_class_id, "
"n1.short_form as upstream_neuron_id, n1.label as upstream_neuron_name, "
"r.weight[0] as weight, n2.short_form as downstream_neuron_id, "
"n2.label as downstream_neuron_name, "
"apoc.text.join(collect(distinct c2.label),'|') as downstream_class, "
"apoc.text.join(collect(distinct c2.short_form),'|') as downstream_class_id, "
"s1.short_form AS up_data_source, r1.accession[0] as up_accession, "
"s2.short_form AS down_data_source, r2.accession[0] AS down_accession ")

else:
cypher_ql.append("MATCH (n1)-[r:synapsed_to]->(n2) WHERE r.weight[0] >= %d " % weight)
cypher_ql.append("OPTIONAL MATCH (n1)-[r1:database_cross_reference]->(s1:Site) "
"WHERE exists(s1.is_data_source) AND s1.is_data_source = [True] ")
cypher_ql.append("OPTIONAL MATCH (n2)-[r2:database_cross_reference]->(s2:Site) "
"WHERE exists(s2.is_data_source) AND s2.is_data_source = [True] " )
cypher_ql.append("RETURN apoc.text.join(collect(distinct c1.label),'|') AS upstream_class, "
"apoc.text.join(collect(distinct c1.short_form),'|') AS upstream_class_id, "
"n1.short_form as upstream_neuron_id, n1.label as upstream_neuron_name,"
"r.weight[0] as weight, n2.short_form as downstream_neuron_id, "
"n2.label as downstream_neuron_name, "
"apoc.text.join(collect(distinct c2.label),'|') as downstream_class, "
"apoc.text.join(collect(distinct c2.short_form),'|') as downstream_class_id, "
"s1.short_form AS up_data_source, r1.accession[0] as up_accession, "
"s2.short_form AS down_source, r2.accession[0] AS down_accession")
cypher_q = ' \n'.join(cypher_ql)
cypher_ql.append("WITH c1, c2, count(*) as pairwise_connections, sum(r.weight[0]) as total_weight, "
"count(distinct n1) as connected_upstream_count \n\n"
"MATCH (c1)<-[:INSTANCEOF]-(all_n1:Individual:has_neuron_connectivity)%s \n\n"
"WITH c1, c2, pairwise_connections, total_weight, connected_upstream_count, "
"count(distinct all_n1) as total_upstream_count \n\n"
"RETURN c1.label AS upstream_class, "
"c1.short_form AS upstream_class_id, "
"c2.label AS downstream_class, "
"c2.short_form AS downstream_class_id, "
"total_upstream_count, "
"connected_upstream_count, "
"round((toFloat(connected_upstream_count)/toFloat(total_upstream_count))*100) as percent_connected, "
"pairwise_connections, "
"total_weight, "
"total_weight/pairwise_connections as average_weight "
"ORDER BY pairwise_connections DESC, average_weight DESC"
% ("-[:database_cross_reference]->(s:Individual:Site {is_data_source:[True]}) \n"
"WHERE NOT (s.short_form IN %s) \n"
"AND NOT (s.symbol[0] IN %s) "
% (exclude_dbs, exclude_dbs) if exclude_dbs else ""))

cypher_q = ' \n\n'.join(cypher_ql)
print(cypher_q) if verbose else None
r = self.nc.commit_list([cypher_q])
if not r:
Expand Down
8 changes: 5 additions & 3 deletions src/vfb_connect/test/cross_server_tools_test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,11 +72,13 @@ def test_get_upstream_neurons(self):

def test_get_connected_neurons_by_type(self):
print()
fu = self.vc.get_connected_neurons_by_type(upstream_type='Kenyon cell', downstream_type='mushroom body output neuron', weight=20)
fu = self.vc.get_connected_neurons_by_type(upstream_type='Kenyon cell', exclude_dbs=[], downstream_type='mushroom body output neuron', weight=20)
self.assertTrue(len(fu) > 0)
fu = self.vc.get_connected_neurons_by_type(upstream_type='FBbt_00051488', weight=5)
fu = self.vc.get_connected_neurons_by_type(upstream_type='FBbt_00051488', weight=5, exclude_dbs=[])
self.assertTrue(len(fu) > 0)
fu = self.vc.get_connected_neurons_by_type(downstream_type='FBbt_00051488', weight=5)
fu = self.vc.get_connected_neurons_by_type(downstream_type='FBbt_00053287', weight=5)
self.assertTrue(len(fu) > 0)
fu = self.vc.get_connected_neurons_by_type(weight=10, upstream_type='C2', downstream_type='visual projection neuron', group_by_class=True)
self.assertTrue(len(fu) > 0)


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