queries.txt

#Create the graph with all the nodes of gene families and edges 

CALL gds.graph.project.cypher(
  "Family",
  "MATCH (n:Family) RETURN id(n) AS id",
  "MATCH (n:Family)-[r:NEIGHBOR|IS_SIMILAR]-(m:Family) WITH n, m, r RETURN id(n) AS source, id(m) AS target"
) YIELD
  graphName,
  nodeQuery,
  nodeCount,
  relationshipQuery,
  relationshipCount

#Cluster with labelPropagation algorithm and visualize with Gephi
  
CALL gds.labelPropagation.stream('Family')
YIELD nodeId, communityId
with collect(nodeId) as nodeIds, communityId
match (n:Family)
where id(n) in nodeIds
with collect(n) as ns, communityId
match path=(f1:Family)-[:IS_SIMILAR|NEIGHBOR]-(f2:Family)
where f1 in ns and f2 in ns
call apoc.gephi.add(null,'workspace1', path, '',['annotation','pgname','pname', 'mname', 'communityId'])
yield nodes, relationships, time
return nodes, relationships, time

#Cluster with louvian algorithm and visualize with Gephi
  
CALL gds.louvian.stream('Family')
YIELD nodeId, communityId
with collect(nodeId) as nodeIds, communityId
match (n:Family)
where id(n) in nodeIds
with collect(n) as ns, communityId
match path=(f1:Family)-[:IS_SIMILAR|NEIGHBOR]-(f2:Family)
where f1 in ns and f2 in ns
call apoc.gephi.add(null,'workspace1', path, '',['annotation','pgname','pname', 'mname', 'communityId'])
yield nodes, relationships, time
return nodes, relationships, time