From ff8f093b2021ac8e1dd90449d61196ae4ed76e61 Mon Sep 17 00:00:00 2001
From: AndiMajore <andi.majore@googlemail.com>
Date: Tue, 19 Jul 2022 17:49:07 +0200
Subject: [PATCH] handling protein nodes now with multiple ids outside of main
id space
Former-commit-id: 6244c171b0ec97affbc2992e4e568b6d9d6c22d6 [formerly 8eb44b9fb87e1ca95eb0c09c98e7253b1f0ce702]
Former-commit-id: 6e33edc763b4f47b04180e818f68097887204133
---
docker-django.env.dev | 2 +-
drugstone/management/commands/make_graphs.py | 18 ++++++++----
drugstone/util/query_db.py | 30 ++++++++++++++++----
drugstone/views.py | 29 ++++++++++++++-----
tasks/betweenness_centrality.py | 6 +++-
tasks/closeness_centrality.py | 5 +++-
tasks/degree_centrality.py | 5 +++-
tasks/multi_steiner.py | 6 +++-
tasks/network_proximity.py | 5 +++-
tasks/trust_rank.py | 5 +++-
tasks/util/read_graph_tool_graph.py | 2 +-
11 files changed, 88 insertions(+), 25 deletions(-)
diff --git a/docker-django.env.dev b/docker-django.env.dev
index 66f78b1..1f3d65d 100644
--- a/docker-django.env.dev
+++ b/docker-django.env.dev
@@ -14,4 +14,4 @@ DJANGO_SETTINGS_MODULE=drugstone.settings
CELERY_BROKER_URL=redis://redis:6379/0
FLOWER_PORT=8888
FLOWER_BASIC_AUTH=drugstone:test
-GT_THREADS=8
\ No newline at end of file
+GT_THREADS=2
\ No newline at end of file
diff --git a/drugstone/management/commands/make_graphs.py b/drugstone/management/commands/make_graphs.py
index 98c7ce1..0ff9bb3 100755
--- a/drugstone/management/commands/make_graphs.py
+++ b/drugstone/management/commands/make_graphs.py
@@ -95,7 +95,9 @@ def create_gt(params: Tuple) -> None:
v_type = g.new_vertex_property("string")
v_name = g.new_vertex_property("string")
v_drugstone_id = g.new_vertex_property("string")
- v_entrez = g.new_vertex_property("string")
+ v_has_symbol = g.new_vertex_property("bool")
+ v_has_entrez = g.new_vertex_property("bool")
+ v_has_ensembl = g.new_vertex_property("bool")
v_expression = g.new_vertex_property("string")
# for drugs
@@ -108,7 +110,9 @@ def create_gt(params: Tuple) -> None:
g.vertex_properties["type"] = v_type
g.vertex_properties["name"] = v_name
g.vertex_properties["drugstone_id"] = v_drugstone_id
- g.vertex_properties["entrez"] = v_entrez
+ g.vertex_properties["has_symbol"] = v_has_symbol
+ g.vertex_properties["has_entrez"] = v_has_entrez
+ g.vertex_properties["has_ensembl"] = v_has_ensembl
g.vertex_properties["status"] = v_status
g.vertex_properties["drug_id"] = v_drug_id
g.vertex_properties["expression"] = v_expression
@@ -122,11 +126,16 @@ def create_gt(params: Tuple) -> None:
print(f'loading nodes')
# extend node data by cancer nodes, we create a normal node for each cancer node.
# on reading the data, we decide which one to keep based on the user selected cancer types
+
+ has_ensembl_set = {node.protein_id for node in models.EnsemblGene.objects.all()}
+
for node in models.Protein.objects.all():
v = g.add_vertex()
v_type[v] = 'protein'
v_drugstone_id[v] = f"p{node.id}"
-
+ v_has_symbol[v] = len(node.gene) != 0
+ v_has_entrez[v] = len(node.entrez) != 0
+ v_has_ensembl[v] = node.id in has_ensembl_set
vertices[node.id] = v
print("done with nodes")
@@ -148,7 +157,6 @@ def create_gt(params: Tuple) -> None:
e_type[e] = 'protein-protein'
print("done with edges")
-
print(f'loading drug_edges/{pdi_dataset}')
for edge_raw in _internal_pdis(pdi_dataset):
e = g.add_edge(drug_vertices[edge_raw.drug_id], vertices[edge_raw.protein_id])
@@ -161,7 +169,7 @@ def create_gt(params: Tuple) -> None:
if vertex.out_degree() == 0:
delete_vertices.add(vertex)
- #remove unconnected drugs
+ # remove unconnected drugs
for vertex in drug_vertices.values():
if vertex.out_degree() == 0:
delete_vertices.add(vertex)
diff --git a/drugstone/util/query_db.py b/drugstone/util/query_db.py
index 62e2e83..89fd8be 100644
--- a/drugstone/util/query_db.py
+++ b/drugstone/util/query_db.py
@@ -1,4 +1,5 @@
-from typing import List, Tuple, Set
+from collections import defaultdict
+from typing import List, Tuple, Set, OrderedDict
from functools import reduce
from django.db.models import Q
from drugstone.models import Protein, EnsemblGene
@@ -31,7 +32,8 @@ def query_proteins_by_identifier(node_ids: Set[str], identifier: str) -> Tuple[L
q_list = map(lambda n: Q(uniprot_code__iexact=n), node_ids)
elif identifier == 'ensg':
protein_attribute = 'ensg'
- node_ids = map(lambda n: n.protein_id, EnsemblGene.objects.filter(reduce(lambda a,b: a|b, map(lambda n:Q(name__iexact=n),list(node_ids)))))
+ node_ids = map(lambda n: n.protein_id, EnsemblGene.objects.filter(
+ reduce(lambda a, b: a | b, map(lambda n: Q(name__iexact=n), list(node_ids)))))
q_list = map(lambda n: Q(id=n), node_ids)
elif identifier == 'entrez':
protein_attribute = 'entrez'
@@ -40,9 +42,27 @@ def query_proteins_by_identifier(node_ids: Set[str], identifier: str) -> Tuple[L
# node_ids is an empty list
return [], protein_attribute
q_list = reduce(lambda a, b: a | b, q_list)
-
node_objects = Protein.objects.filter(q_list)
- # serialize
- nodes = ProteinSerializer(many=True).to_representation(node_objects)
+
+ nodes = list()
+
+ node_map = defaultdict(list)
+
+ for node in ProteinSerializer(many=True).to_representation(node_objects):
+ node_map[node.get(protein_attribute)].append(node)
+ for node_id, entries in node_map.items():
+ nodes.append(aggregate_nodes(entries))
return nodes, protein_attribute
+
+
+def aggregate_nodes(nodes: List[OrderedDict]):
+ node = defaultdict(set)
+ for n in nodes:
+ for key, value in n.items():
+ if isinstance(value,list):
+ for e in value:
+ node[key].add(e)
+ else:
+ node[key].add(value)
+ return {k: list(v) for k, v in node.items()}
diff --git a/drugstone/views.py b/drugstone/views.py
index 19cde80..038fa88 100755
--- a/drugstone/views.py
+++ b/drugstone/views.py
@@ -58,7 +58,7 @@ def get_pdis_ds(source, licenced):
def get_drdis_ds(source, licenced):
try:
- ds = models.PDisDataset.objects.filter(name__iexact=source, licenced=licenced).last()
+ ds = models.PDisDataset.objects.filter(name__iexact=source, licenced=licenced).last()
ds.id
return ds
except:
@@ -128,7 +128,14 @@ def fetch_edges(request) -> Response:
Response: List of edges which are objects with 'from' and to ' attribtues'
"""
dataset = request.data.get('dataset', DEFAULTS['ppi'])
- drugstone_ids = [node['drugstone_id'][1:] for node in request.data.get('nodes', '[]') if 'drugstone_id' in node]
+ drugstone_ids = set()
+ for node in request.data.get('nodes', '[]'):
+ if 'drugstone_id' in node:
+ if isinstance(node['drugstone_id'], list):
+ for id in node['drugstone_id']:
+ drugstone_ids.add(id[1:])
+ else:
+ drugstone_ids.add(node['drugstone_id'])
licenced = request.data.get('licenced', False)
dataset_object = get_ppi_ds(dataset, licenced)
interaction_objects = models.ProteinProteinInteraction.objects.filter(
@@ -168,16 +175,19 @@ def map_nodes(request) -> Response:
nodes_mapped, id_key = query_proteins_by_identifier(node_ids, identifier)
# change data structure to dict in order to be quicker when merging
- if identifier == 'ensg':
- # a protein might have multiple ensg-numbers, unpack these into single nodes
- nodes_mapped_dict = {node_id: node for node in nodes_mapped for node_id in node[id_key]}
- else:
- nodes_mapped_dict = {node[id_key]: node for node in nodes_mapped}
+ # if identifier == 'ensg':
+ # # a protein might have multiple ensg-numbers, unpack these into single nodes
+ # nodes_mapped_dict = {node_id: node for node in nodes_mapped for node_id in node[id_key]}
+ # else:
+ nodes_mapped_dict = {node[id_key][0]: node for node in nodes_mapped}
# merge fetched data with given data to avoid data loss
for node in nodes:
+ node['drugstoneType'] = 'other'
if node['id'] in nodes_mapped_dict:
node.update(nodes_mapped_dict[node['id']])
+ node['drugstoneType'] = 'protein'
node['id'] = id_map[node['id']]
+
# set label to node identifier if label is unset, otherwise
# return list of nodes updated nodes
return Response(nodes)
@@ -489,6 +499,8 @@ def adjacent_disorders(request) -> Response:
# serialize
edges = DrugDisorderIndicationSerializer(many=True).to_representation(drdi_objects)
disorders = DisorderSerializer(many=True).to_representation(disorders)
+ for d in disorders:
+ d['drugstone_type'] = 'disorder'
return Response({
'edges': edges,
'disorders': disorders,
@@ -514,6 +526,9 @@ def adjacent_drugs(request) -> Response:
# serialize
pdis = ProteinDrugInteractionSerializer(many=True).to_representation(pdi_objects)
drugs = DrugSerializer(many=True).to_representation(drugs)
+ for drug in drugs:
+ drug['drugstone_type'] = 'drug'
+
return Response({
'pdis': pdis,
'drugs': drugs,
diff --git a/tasks/betweenness_centrality.py b/tasks/betweenness_centrality.py
index d839c5e..f763b1e 100755
--- a/tasks/betweenness_centrality.py
+++ b/tasks/betweenness_centrality.py
@@ -170,13 +170,17 @@ def betweenness_centrality(task_hook: TaskHook):
filterPaths = task_hook.parameters.get("filter_paths", True)
+ id_space = task_hook.parameters["config"].get("identifier","symbol")
+
+ print(id_space)
+
# Parsing input file.
task_hook.set_progress(0 / 3.0, "Parsing input.")
filename = f"internal_{ppi_dataset['name']}_{pdi_dataset['name']}"
if ppi_dataset['licenced'] or pdi_dataset['licenced']:
filename += "_licenced"
filename = os.path.join(task_hook.data_directory, filename+".gt")
- g, seed_ids, drug_ids = read_graph_tool_graph(
+ g, seed_ids, id_space, drug_ids = read_graph_tool_graph(
filename,
seeds,
max_deg,
diff --git a/tasks/closeness_centrality.py b/tasks/closeness_centrality.py
index a90014f..78222aa 100755
--- a/tasks/closeness_centrality.py
+++ b/tasks/closeness_centrality.py
@@ -173,9 +173,12 @@ def closeness_centrality(task_hook: TaskHook):
filename = f"internal_{ppi_dataset['name']}_{pdi_dataset['name']}"
if ppi_dataset['licenced'] or pdi_dataset['licenced']:
filename += "_licenced"
+
+ id_space = task_hook.parameters["config"].get("identifier", "symbol")
+
filename = os.path.join(task_hook.data_directory, filename+".gt")
# g, seed_ids, viral_protein_ids, drug_ids = read_graph_tool_graph(file_path, seeds, datasets, ignored_edge_types, max_deg, ignore_non_seed_baits, include_indirect_drugs, include_non_approved_drugs)
- g, seed_ids, drug_ids = read_graph_tool_graph(filename, seeds, max_deg, include_indirect_drugs, include_non_approved_drugs, search_target)
+ g, seed_ids, drug_ids = read_graph_tool_graph(filename, seeds, id_space, max_deg, include_indirect_drugs, include_non_approved_drugs, search_target)
task_hook.set_progress(1 / 4.0, "Computing edge weights.")
weights = edge_weights(g, hub_penalty)
diff --git a/tasks/degree_centrality.py b/tasks/degree_centrality.py
index bceffec..1a709a0 100755
--- a/tasks/degree_centrality.py
+++ b/tasks/degree_centrality.py
@@ -153,9 +153,12 @@ def degree_centrality(task_hook: TaskHook):
filename = f"internal_{ppi_dataset['name']}_{pdi_dataset['name']}"
if ppi_dataset['licenced'] or pdi_dataset['licenced']:
filename += "_licenced"
+
+ id_space = task_hook.parameters["config"].get("identifier", "symbol")
+
filename = os.path.join(task_hook.data_directory, filename+".gt")
# g, seed_ids, viral_protein_ids, drug_ids = read_graph_tool_graph(file_path, seeds, datasets, ignored_edge_types, max_deg, ignore_non_seed_baits, False, include_non_approved_drugs)
- g, seed_ids, drug_ids = read_graph_tool_graph(filename, seeds, max_deg, False, include_non_approved_drugs, search_target)
+ g, seed_ids, drug_ids = read_graph_tool_graph(filename, seeds, id_space, max_deg, False, include_non_approved_drugs, search_target)
# Set number of threads if OpenMP support is enabled.
if gt.openmp_enabled():
diff --git a/tasks/multi_steiner.py b/tasks/multi_steiner.py
index f8e9a80..6e81bca 100755
--- a/tasks/multi_steiner.py
+++ b/tasks/multi_steiner.py
@@ -105,11 +105,15 @@ def multi_steiner(task_hook: TaskHook):
# Parsing input file.
task_hook.set_progress(0 / (float(num_trees + 3)), "Parsing input.")
+
+ id_space = task_hook.parameters["config"].get("identifier", "symbol")
+
filename = f"internal_{ppi_dataset['name']}_{pdi_dataset['name']}"
if ppi_dataset['licenced'] or pdi_dataset['licenced']:
filename += "_licenced"
+
filename = os.path.join(task_hook.data_directory, filename+".gt")
- g, seed_ids, _ = read_graph_tool_graph(filename, seeds, max_deg, target=search_target)
+ g, seed_ids, _ = read_graph_tool_graph(filename, seeds, id_space, max_deg, target=search_target)
# seed_map = {g.vertex_properties["name"][node]: node for node in seed_ids}
seed_map = {g.vertex_properties[node_name_attribute][node]: node for node in seed_ids}
task_hook.set_progress(1 / (float(num_trees + 3)), "Computing edge weights.")
diff --git a/tasks/network_proximity.py b/tasks/network_proximity.py
index 90b7708..6755d8e 100755
--- a/tasks/network_proximity.py
+++ b/tasks/network_proximity.py
@@ -86,12 +86,15 @@ def network_proximity(task_hook: TaskHook):
# Parsing input file.
task_hook.set_progress(0.0 / 8, "Parsing input.")
+
+ id_space = task_hook.parameters["config"].get("identifier", "symbol")
+
filename = f"internal_{ppi_dataset['name']}_{pdi_dataset['name']}"
if ppi_dataset['licenced'] or pdi_dataset['licenced']:
filename += "_licenced"
filename = os.path.join(task_hook.data_directory, filename+".gt")
# g, seed_ids, _, drug_ids = read_graph_tool_graph(file_path, seeds, "", "", max_deg, False, True, include_non_approved_drugs)
- g, seed_ids, drug_ids = read_graph_tool_graph(filename, seeds, max_deg, True, include_non_approved_drugs, target=search_target)
+ g, seed_ids, drug_ids = read_graph_tool_graph(filename, seeds, id_space, max_deg, True, include_non_approved_drugs, target=search_target)
# Computing edge weights.
task_hook.set_progress(1.0 / 8, "Computing edge weights.")
weights = edge_weights(g, hub_penalty)
diff --git a/tasks/trust_rank.py b/tasks/trust_rank.py
index ceda67c..4737bbe 100755
--- a/tasks/trust_rank.py
+++ b/tasks/trust_rank.py
@@ -198,11 +198,14 @@ def trust_rank(task_hook: TaskHook):
# Parsing input file.
task_hook.set_progress(0 / 4.0, "Parsing input.")
+
+ id_space = task_hook.parameters["config"].get("identifier", "symbol")
+
filename = f"internal_{ppi_dataset['name']}_{pdi_dataset['name']}"
if ppi_dataset['licenced'] or pdi_dataset['licenced']:
filename += "_licenced"
filename = os.path.join(task_hook.data_directory, filename+".gt")
- g, seed_ids, drug_ids = read_graph_tool_graph(filename, seeds, max_deg, include_indirect_drugs, include_non_approved_drugs, search_target)
+ g, seed_ids, drug_ids = read_graph_tool_graph(filename, seeds, id_space, max_deg, include_indirect_drugs, include_non_approved_drugs, search_target)
task_hook.set_progress(1 / 4.0, "Computing edge weights.")
weights = edge_weights(g, hub_penalty, inverse=True)
diff --git a/tasks/util/read_graph_tool_graph.py b/tasks/util/read_graph_tool_graph.py
index 4e7c9fe..d496f3b 100755
--- a/tasks/util/read_graph_tool_graph.py
+++ b/tasks/util/read_graph_tool_graph.py
@@ -3,7 +3,7 @@ import graph_tool.topology as gtt
# def read_graph_tool_graph(file_path, seeds, datasets, ignored_edge_types, max_deg, ignore_non_seed_baits=False, include_indirect_drugs=False, include_non_approved_drugs=False):
-def read_graph_tool_graph(file_path, seeds, max_deg, include_indirect_drugs=False, include_non_approved_drugs=False,
+def read_graph_tool_graph(file_path, seeds,id_space, max_deg, include_indirect_drugs=False, include_non_approved_drugs=False,
target='drug'):
r"""Reads a graph-tool graph from file.
--
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