From 4f36a48ddcab9599660d9ff0c24436df13a11fb8 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 09:35:49 +0100 Subject: [PATCH 01/20] Add libraries for OMOP plugin --- requirements.txt | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/requirements.txt b/requirements.txt index a4a8447..d6e755e 100644 --- a/requirements.txt +++ b/requirements.txt @@ -26,4 +26,6 @@ paramiko==2.7.2 six==1.16.0 progressbar==2.5 tqdm==4.62.3 -obonet==0.3.1 \ No newline at end of file +obonet==0.3.1 +psycopg2==2.9.5 +aiosql==8.0 \ No newline at end of file From f4f5890d64810b538952b4a2dfc45cf421997216 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 09:36:24 +0100 Subject: [PATCH 02/20] Add port to gather URL from OMOP database --- docker-compose.yml | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docker-compose.yml b/docker-compose.yml index cb9270a..98ecf29 100644 --- a/docker-compose.yml +++ b/docker-compose.yml @@ -16,6 +16,8 @@ services: - ./beacon/logs/logs.log:/beacon/logs/logs.log - ./beacon/conf/conf.py:/beacon/conf/conf.py - ./beacon/permissions:/beacon/permissions + extra_hosts: + - "host.docker.internal:host-gateway" networks: - pub From dc75491ed160338bd198b4d47f3c1edc8f10dcc9 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 09:37:25 +0100 Subject: [PATCH 03/20] Add omop plugin extension --- beacon/connections/omopcdm/Makefile | 19 + beacon/connections/omopcdm/__init__.py | 26 + beacon/connections/omopcdm/analyses.py | 99 + beacon/connections/omopcdm/biosamples.py | 126 + beacon/connections/omopcdm/cohorts.py | 169 + beacon/connections/omopcdm/conf.py | 5 + beacon/connections/omopcdm/data/analyses.json | 30050 +++ .../connections/omopcdm/data/biosamples.json | 90146 +++++++ .../omopcdm/data/caseLevelData.json | 1 + beacon/connections/omopcdm/data/cohorts.json | 116 + beacon/connections/omopcdm/data/datasets.json | 1 + .../omopcdm/data/filtering_terms.json | 23 + .../omopcdm/data/genomicVariations.json | 1 + .../connections/omopcdm/data/individuals.json | 183766 +++++++++++++++ beacon/connections/omopcdm/data/runs.json | 47578 ++++ beacon/connections/omopcdm/data/targets.json | 1 + beacon/connections/omopcdm/datasets.py | 193 + beacon/connections/omopcdm/executor.py | 105 + .../omopcdm/extract_filtering_terms.py | 493 + beacon/connections/omopcdm/filtering_terms.py | 27 + beacon/connections/omopcdm/filters.py | 247 + beacon/connections/omopcdm/g_variants.py | 278 + beacon/connections/omopcdm/get_descendants.py | 178 + beacon/connections/omopcdm/individuals.py | 286 + beacon/connections/omopcdm/mappings.py | 76 + beacon/connections/omopcdm/mongo-init/init.js | 27 + .../omopcdm/ontologies/example.txt | 0 beacon/connections/omopcdm/ping.py | 33 + beacon/connections/omopcdm/reindex.py | 79 + beacon/connections/omopcdm/runs.py | 111 + .../connections/omopcdm/sql/basic_queries.sql | 19 + .../connections/omopcdm/sql/individuals.sql | 151 + beacon/connections/omopcdm/utils.py | 207 + 33 files changed, 354637 insertions(+) create mode 100644 beacon/connections/omopcdm/Makefile create mode 100644 beacon/connections/omopcdm/__init__.py create mode 100644 beacon/connections/omopcdm/analyses.py create mode 100644 beacon/connections/omopcdm/biosamples.py create mode 100644 beacon/connections/omopcdm/cohorts.py create mode 100644 beacon/connections/omopcdm/conf.py create mode 100644 beacon/connections/omopcdm/data/analyses.json create mode 100644 beacon/connections/omopcdm/data/biosamples.json create mode 100644 beacon/connections/omopcdm/data/caseLevelData.json create mode 100644 beacon/connections/omopcdm/data/cohorts.json create mode 100644 beacon/connections/omopcdm/data/datasets.json create mode 100644 beacon/connections/omopcdm/data/filtering_terms.json create mode 100644 beacon/connections/omopcdm/data/genomicVariations.json create mode 100644 beacon/connections/omopcdm/data/individuals.json create mode 100644 beacon/connections/omopcdm/data/runs.json create mode 100644 beacon/connections/omopcdm/data/targets.json create mode 100644 beacon/connections/omopcdm/datasets.py create mode 100644 beacon/connections/omopcdm/executor.py create mode 100644 beacon/connections/omopcdm/extract_filtering_terms.py create mode 100644 beacon/connections/omopcdm/filtering_terms.py create mode 100644 beacon/connections/omopcdm/filters.py create mode 100644 beacon/connections/omopcdm/g_variants.py create mode 100644 beacon/connections/omopcdm/get_descendants.py create mode 100644 beacon/connections/omopcdm/individuals.py create mode 100644 beacon/connections/omopcdm/mappings.py create mode 100644 beacon/connections/omopcdm/mongo-init/init.js create mode 100644 beacon/connections/omopcdm/ontologies/example.txt create mode 100644 beacon/connections/omopcdm/ping.py create mode 100644 beacon/connections/omopcdm/reindex.py create mode 100644 beacon/connections/omopcdm/runs.py create mode 100644 beacon/connections/omopcdm/sql/basic_queries.sql create mode 100644 beacon/connections/omopcdm/sql/individuals.sql create mode 100644 beacon/connections/omopcdm/utils.py diff --git a/beacon/connections/omopcdm/Makefile b/beacon/connections/omopcdm/Makefile new file mode 100644 index 0000000..53d796a --- /dev/null +++ b/beacon/connections/omopcdm/Makefile @@ -0,0 +1,19 @@ +build: + docker cp data/analyses.json mongoprod:tmp/analyses.json + docker cp data/biosamples.json mongoprod:tmp/biosamples.json + docker cp data/cohorts.json mongoprod:tmp/cohorts.json + docker cp data/datasets.json mongoprod:tmp/datasets.json + docker cp data/genomicVariations.json mongoprod:tmp/genomicVariations.json + docker cp data/individuals.json mongoprod:tmp/individuals.json + docker cp data/runs.json mongoprod:tmp/runs.json + docker cp data/targets.json mongoprod:tmp/targets.json + docker cp data/caseLevelData.json mongoprod:tmp/caseLevelData.json + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/datasets.json --collection datasets + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/individuals.json --collection individuals + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/cohorts.json --collection cohorts + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/analyses.json --collection analyses + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/biosamples.json --collection biosamples + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/genomicVariations.json --collection genomicVariations + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/runs.json --collection runs + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/targets.json --collection targets + docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/caseLevelData.json --collection caseLevelData \ No newline at end of file diff --git a/beacon/connections/omopcdm/__init__.py b/beacon/connections/omopcdm/__init__.py new file mode 100644 index 0000000..535def0 --- /dev/null +++ b/beacon/connections/omopcdm/__init__.py @@ -0,0 +1,26 @@ +from beacon.connections.omopcdm import conf +import psycopg2 +import os +from beacon.logs.logs import log_with_args, LOG + + +# db_url = os.getenv('POSTGRES_URL', default="postgresql://pgadmin:admin@localhost:5432/omopdb") +uri = "postgresql://{}:{}@{}:{}/{}".format( + conf.database_user, + conf.database_password, + conf.database_host, # Ex: localhost + conf.database_port, # Ex: 5432 + conf.database_name, +) +# LOG.debug(f"URI {uri}") + +client = psycopg2.connect(uri) + +# CDM_SCHEMA='cdm' +# VOCABULARIES_SCHEMA='vocabularies' +# query = "select * from cdm.person limit 10" +# cur = client.cursor() +# cur.execute(query) +# records = cur.fetchall() +# listOfList = [str(record[0]) for record in records] +# LOG.debug(f"list of lissssssttttttt {listOfList}") diff --git a/beacon/connections/omopcdm/analyses.py b/beacon/connections/omopcdm/analyses.py new file mode 100644 index 0000000..2389640 --- /dev/null +++ b/beacon/connections/omopcdm/analyses.py @@ -0,0 +1,99 @@ + +from beacon.request.parameters import RequestParams +from beacon.response.schemas import DefaultSchemas +import yaml +from beacon.connections.mongo.__init__ import client +from beacon.connections.mongo.utils import get_docs_by_response_type, query_id +from beacon.logs.logs import log_with_args +from beacon.conf.conf import level +from beacon.connections.mongo.filters import apply_filters +from beacon.connections.mongo.request_parameters import apply_request_parameters +from typing import Optional + +@log_with_args(level) +def get_analyses(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'analyses' + mongo_collection = client.beacon.analyses + parameters_as_filters=False + query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) + if parameters_as_filters == True and query_parameters != {'$and': []}:# pragma: no cover + query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) + query_parameters={} + elif query_parameters != {'$and': []}: + query=query_parameters + elif query_parameters == {'$and': []}:# pragma: no cover + query_parameters = {} + query={} + query = apply_filters(self, query, qparams.query.filters, collection, query_parameters, dataset) + schema = DefaultSchemas.ANALYSES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100 + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_analysis_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'analyses' + idq="biosampleId" + mongo_collection = client.beacon.analyses + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + schema = DefaultSchemas.ANALYSES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_variants_of_analysis(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'analyses' + mongo_collection = client.beacon.genomicVariations + query = {"$and": [{"id": entry_id}]} + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + analysis_ids = client.beacon.analyses \ + .find_one(query, {"biosampleId": 1, "_id": 0}) + targets = client.beacon.targets \ + .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) + position=0 + bioids=targets[0]["biosampleIds"] + for bioid in bioids: + if bioid == analysis_ids["biosampleId"]: + break + position+=1 + position=str(position) + position1="^"+position+"," + position2=","+position+"," + position3=","+position+"$" + query_cl={ "$or": [ + {"biosampleIds": {"$regex": position1}}, + {"biosampleIds": {"$regex": position2}}, + {"biosampleIds": {"$regex": position3}} + ]} + string_of_ids = client.beacon.caseLevelData \ + .find(query_cl, {"id": 1, "_id": 0}) + HGVSIds=list(string_of_ids) + query={} + queryHGVS={} + listHGVS=[] + for HGVSId in HGVSIds: + justid=HGVSId["id"] + listHGVS.append(justid) + queryHGVS["$in"]=listHGVS + query["identifiers.genomicHGVSId"]=queryHGVS + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.GENOMICVARIATIONS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="caseLevelData.biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/biosamples.py b/beacon/connections/omopcdm/biosamples.py new file mode 100644 index 0000000..d6530a7 --- /dev/null +++ b/beacon/connections/omopcdm/biosamples.py @@ -0,0 +1,126 @@ +from beacon.request.parameters import RequestParams +from beacon.response.schemas import DefaultSchemas +import yaml +from beacon.connections.mongo.__init__ import client +from beacon.connections.mongo.utils import get_docs_by_response_type, query_id +from beacon.logs.logs import log_with_args +from beacon.conf.conf import level +from beacon.connections.mongo.filters import apply_filters +from beacon.connections.mongo.request_parameters import apply_request_parameters +from typing import Optional + +@log_with_args(level) +def get_biosamples(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'biosamples' + mongo_collection = client.beacon.biosamples + parameters_as_filters=False + query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) + if parameters_as_filters == True and query_parameters != {'$and': []}:# pragma: no cover + query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) + query_parameters={} + elif query_parameters != {'$and': []}: + query=query_parameters + elif query_parameters == {'$and': []}:# pragma: no cover + query_parameters = {} + query={} + query = apply_filters(self, query, qparams.query.filters, collection, query_parameters, dataset) + schema = DefaultSchemas.BIOSAMPLES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100 + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_biosample_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'biosamples' + mongo_collection = client.beacon.biosamples + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + schema = DefaultSchemas.BIOSAMPLES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_variants_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'g_variants' + mongo_collection = client.beacon.genomicVariations + targets = client.beacon.targets \ + .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) + position=0 + bioids=targets[0]["biosampleIds"] + for bioid in bioids: + if bioid == entry_id: + break + position+=1 + position=str(position) + position1="^"+position+"," + position2=","+position+"," + position3=","+position+"$" + query_cl={ "$or": [ + {"biosampleIds": {"$regex": position1}}, + {"biosampleIds": {"$regex": position2}}, + {"biosampleIds": {"$regex": position3}} + ]} + string_of_ids = client.beacon.caseLevelData \ + .find(query_cl, {"id": 1, "_id": 0}) + HGVSIds=list(string_of_ids) + query={} + queryHGVS={} + listHGVS=[] + for HGVSId in HGVSIds: + justid=HGVSId["id"] + listHGVS.append(justid) + queryHGVS["$in"]=listHGVS + query["identifiers.genomicHGVSId"]=queryHGVS + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.GENOMICVARIATIONS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="caseLevelData.biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_analyses_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'biosamples' + mongo_collection = client.beacon.analyses + query = {"biosampleId": entry_id} + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.ANALYSES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_runs_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'biosamples' + mongo_collection = client.beacon.runs + query = {"individualId": entry_id} + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.RUNS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/cohorts.py b/beacon/connections/omopcdm/cohorts.py new file mode 100644 index 0000000..c75cedd --- /dev/null +++ b/beacon/connections/omopcdm/cohorts.py @@ -0,0 +1,169 @@ +from beacon.request.parameters import RequestParams +from beacon.response.schemas import DefaultSchemas +from beacon.connections.mongo.__init__ import client +from beacon.logs.logs import log_with_args_mongo +from beacon.conf.conf import level +from beacon.connections.mongo.filters import apply_filters +from typing import Optional +from beacon.connections.mongo.utils import get_count, get_documents, get_documents_for_cohorts +from beacon.connections.mongo.utils import get_docs_by_response_type, query_id, get_cross_query +import yaml + +@log_with_args_mongo(level) +def get_cohorts(self, entry_id: Optional[str], qparams: RequestParams): + collection = 'cohorts' + limit = qparams.query.pagination.limit + query = apply_filters(self, {}, qparams.query.filters, collection, {}, "a") + schema = DefaultSchemas.COHORTS + count = get_count(self, client.beacon.cohorts, query) + docs = get_documents(self, + client.beacon.cohorts, + query, + qparams.query.pagination.skip, + qparams.query.pagination.skip*limit + ) + response_converted = ( + [r for r in docs] if docs else [] + ) + return response_converted, count, schema + +@log_with_args_mongo(level) +def get_cohort_with_id(self, entry_id: Optional[str], qparams: RequestParams): + collection = 'cohorts' + limit = qparams.query.pagination.limit + query = apply_filters(self, {}, qparams.query.filters, collection, {}, "a") + query = query_id(self, query, entry_id) + schema = DefaultSchemas.COHORTS + count = get_count(self, client.beacon.cohorts, query) + docs = get_documents(self, + client.beacon.cohorts, + query, + qparams.query.pagination.skip, + qparams.query.pagination.skip*limit + ) + response_converted = ( + [r for r in docs] if docs else [] + ) + return response_converted, count, schema + +@log_with_args_mongo(level) +def get_individuals_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'cohorts' + mongo_collection = client.beacon.individuals + dataset_count=0 + limit = qparams.query.pagination.limit + include = qparams.query.include_resultset_responses + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.cohorts, query) + dict_in={} + dict_in['datasetId']=dataset + query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + + schema = DefaultSchemas.INDIVIDUALS + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args_mongo(level) +def get_analyses_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'cohorts' + mongo_collection = client.beacon.analyses + dataset_count=0 + limit = qparams.query.pagination.limit + include = qparams.query.include_resultset_responses + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.cohorts, query) + dict_in={} + dict_in['datasetId']=dataset + query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.ANALYSES + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args_mongo(level) +def get_variants_of_cohort(self,entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'cohorts' + mongo_collection = client.beacon.genomicVariations + dataset_count=0 + limit = qparams.query.pagination.limit + include = qparams.query.include_resultset_responses + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.cohorts, query) + query_count={} + query_count["$or"]=[] + docs = get_documents_for_cohorts(self, + client.beacon.cohorts, + query, + qparams.query.pagination.skip, + qparams.query.pagination.skip*limit + ) + for doc in docs: + if doc["datasetId"] == dataset: + entry_id = dataset + if dataset == entry_id: + queryid={} + queryid["datasetId"]=dataset + query_count["$or"].append(queryid) + else: + schema = DefaultSchemas.GENOMICVARIATIONS# pragma: no cover + return schema, 0, 0, None, dataset# pragma: no cover + query = apply_filters(self, query_count, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.GENOMICVARIATIONS + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="caseLevelData.biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args_mongo(level) +def get_runs_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'cohorts' + mongo_collection = client.beacon.runs + dataset_count=0 + limit = qparams.query.pagination.limit + include = qparams.query.include_resultset_responses + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.cohorts, query) + dict_in={} + dict_in['datasetId']=dataset + query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.RUNS + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args_mongo(level) +def get_biosamples_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'cohorts' + mongo_collection = client.beacon.biosamples + dataset_count=0 + limit = qparams.query.pagination.limit + include = qparams.query.include_resultset_responses + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.cohorts, query) + dict_in={} + dict_in['datasetId']=dataset + query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.BIOSAMPLES + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/conf.py b/beacon/connections/omopcdm/conf.py new file mode 100644 index 0000000..003f4cb --- /dev/null +++ b/beacon/connections/omopcdm/conf.py @@ -0,0 +1,5 @@ +database_user = 'pgadmin' +database_password = 'admin' +database_host = 'host.docker.internal' #'host.docker.internal' or localhost +database_port = 5432 +database_name = 'synthetic_data_w_measurements' \ No newline at end of file diff --git a/beacon/connections/omopcdm/data/analyses.json b/beacon/connections/omopcdm/data/analyses.json new file mode 100644 index 0000000..2b5eac8 --- /dev/null +++ b/beacon/connections/omopcdm/data/analyses.json @@ -0,0 +1,30050 @@ +[ + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00096", + "id": "UK1_analysisId_1", + "individualId": "HG00096", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000001", + "variantCaller": "GATK4.0" + }, + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00097", + "id": "UK1_analysisId_2", + "individualId": "HG00097", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000002", + "variantCaller": "GATK4.0" + }, + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00099", + "id": "UK1_analysisId_3", + "individualId": "HG00099", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000003", + "variantCaller": "GATK4.0" + }, + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00100", + "id": "UK1_analysisId_4", + "individualId": "HG00100", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000004", + "variantCaller": "GATK4.0" + }, + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00101", + "id": "UK1_analysisId_5", + "individualId": "HG00101", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000005", + "variantCaller": "GATK4.0" + }, + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00102", + "id": "UK1_analysisId_6", + "individualId": "HG00102", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000006", + "variantCaller": "GATK4.0" + }, + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00103", + "id": "UK1_analysisId_7", + "individualId": "HG00103", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000007", + "variantCaller": "GATK4.0" + }, + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00105", + "id": "UK1_analysisId_8", + "individualId": "HG00105", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000008", + "variantCaller": "GATK4.0" + }, + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "aligner": "bwa-0.5.9", + "analysisDate": "2015-09-30", + "biosampleId": "HG00106", + "id": "UK1_analysisId_9", + "individualId": "HG00106", + "pipelineName": "1000G-low-coverage-WGS", + "pipelineRef": "https://www.nature.com/articles/nature15393", + "runId": "SRR00000009", + "variantCaller": "GATK4.0" + }, + { + "datasetId": 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diff --git a/beacon/connections/omopcdm/data/cohorts.json b/beacon/connections/omopcdm/data/cohorts.json new file mode 100644 index 0000000..89ec5f2 --- /dev/null +++ b/beacon/connections/omopcdm/data/cohorts.json @@ -0,0 +1,116 @@ +[ + { + "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", + "cohortType": "study-defined", + "collectionEvents": [ + { + "eventDiseases": { + "availability": true, + "availabilityCount": 1705, + "distribution": { + "diseases": { + "acutebronchitis": 121, + "agranulocytosis": 111, + "asthma": 134, + "bipolaraffectivedisorder": 134, + "cardiomyopathy": 133, + "dentalcaries": 139, + "eatingdisorders": 134, + "fibrosisandcirrhosisofliver": 132, + "gastro-oesophagealrefluxdisease": 140, + "haemorrhoids": 127, + "influenzaduetocertainidentifiedinfluenzavirus": 135, + "insulin-dependentdiabetesmellitus": 165, + "irondeficiencyanaemia": 142, + "multiplesclerosis": 125, + "obesity": 136, + "sarcoidosis": 136, + "schizophrenia": 138, + "thyroiditis": 141, + "varicoseveinsoflowerextremities": 139 + } + } + }, + "eventEthnicities": { + "availability": true, + "availabilityCount": 2287, + "distribution": { + "ethnicities": { + "African": 119, + "AnyotherAsianbackground": 120, + "AnyotherBlackbackground": 104, + "Anyothermixedbackground": 92, + "Anyotherwhitebackground": 114, + "AsianorAsianBritish": 125, + "Bangladeshi": 96, + "BlackorBlackBritish": 131, + "British": 114, + "Caribbean": 127, + "Chinese": 100, + "Indian": 110, + "Irish": 111, + "Mixed": 127, + "Otherethnicgroup": 116, + "Pakistani": 115, + "White": 105, + "WhiteandAsian": 114, + "WhiteandBlackAfrican": 115, + "WhiteandBlackCaribbean": 132 + } + } + }, + "eventGenders": { + "availability": true, + "availabilityCount": 1597, + "distribution": { + "genders": { + "female": 1271, + "male": 1233 + } + } + }, + "eventLocations": { + "availability": true, + "availabilityCount": 1597, + "distribution": { + "locations": { + "England": 322, + "NorthernIreland": 317, + "RepublicofIreland": 311, + "Scotland": 308, + "Wales": 339 + } + } + } + } + ], + "id": "CINECA_synthetic_cohort_UK1", + "inclusionCriteria": { + "ageRange": { + "end": { + "iso8601duration": "P65Y" + }, + "start": { + "iso8601duration": "P18Y" + } + }, + "genders": [ + { + "id": "NCIT:C16576", + "label": "female" + }, + { + "id": "NCIT:C20197", + "label": "male" + } + ], + "locations": [ + { + "id": "GAZ:00150372", + "label": "UK" + } + ] + }, + "name": "CINECA synthetic cohort UK1" + } +] \ No newline at end of file diff --git a/beacon/connections/omopcdm/data/datasets.json b/beacon/connections/omopcdm/data/datasets.json new file mode 100644 index 0000000..41d537c --- /dev/null +++ b/beacon/connections/omopcdm/data/datasets.json @@ -0,0 +1 @@ +[{"createDateTime": "2021-12-29T20:33:40Z", "dataUseConditions": {"duoDataUse": [{"id": "DUO:0000019,DUO:00000020", "label": "publication required,publication required", "version": "7-1-19,7-1-19"}]}, "description": "Please note: This synthetic data set (with cohort participants / subjects marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.\",\"externalUrl\":\u00a0\"https://ega-archive.org/datasets/EGAD00001006673/", "externalUrl": "https://ega-archive.org/datasets/EGAD00001006673/", "id": "CINECA_synthetic_cohort_EUROPE_UK1", "info": {"beacon": {"contact": "manuel.rueda@crg.eu", "mapping": "ManuelRueda", "version": "v2.0"}, "dataset": {"derived": [{"EGA": {"contact": "helpdesk@ega-archive.org", "externalUrl": "https://ega-archive.org/datasets/EGAD00001006673", "license": {"$ref": "#/dataUseConditions/duoDataUse"}}}, {"BioSamples": {"contact": "biosamples@ebi.ac.uk", "externalUrl": "https://www.ebi.ac.uk/biosamples", "license": "CreativeCommonsLicence(CC-BY)"}}], "origin": [{"CINECAprojectEU": {"contact": "cthomas@ebi.ac.uk", "externalUrl": "https://www.cineca-project.eu/cineca-synthetic-dataset", "license": "CreativeCommonsLicence(CC-BY)", "managers": "ColineThomas,IsuruLiyanageandDylanSpalding"}}, {"1000Genomes": {"externalUrl": "https://www.internationalgenome.org/category/phase-3", "license": "CCBY-NC-SA3.0", "version": "v5aphase3VCF"}}]}}, "name": "CINECA_synthetic_cohort_EUROPE_UK1", "updateDateTime": "2021-12-29T20:33:40Z", "version": "v1.0"}] \ No newline at end of file diff --git a/beacon/connections/omopcdm/data/filtering_terms.json b/beacon/connections/omopcdm/data/filtering_terms.json new file mode 100644 index 0000000..23a750a --- /dev/null +++ b/beacon/connections/omopcdm/data/filtering_terms.json @@ -0,0 +1,23 @@ +[ + { + "type": "alphanumeric", + "id": "libraryStrategy", + "scopes": [ + "run" + ] + }, + { + "type": "alphanumeric", + "id": "molecularAttributes.geneIds", + "scopes": [ + "genomicVariation" + ] + }, + { + "type": "alphanumeric", + "id": "diseases.ageOfOnset.iso8601duration", + "scopes": [ + "individual" + ] + } +] \ No newline at end of file diff --git a/beacon/connections/omopcdm/data/genomicVariations.json b/beacon/connections/omopcdm/data/genomicVariations.json new file mode 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diff --git a/beacon/connections/omopcdm/datasets.py b/beacon/connections/omopcdm/datasets.py new file mode 100644 index 0000000..19d8640 --- /dev/null +++ b/beacon/connections/omopcdm/datasets.py @@ -0,0 +1,193 @@ +from beacon.connections.mongo.__init__ import client +from beacon.logs.logs import log_with_args_mongo +from beacon.conf.conf import level +from beacon.exceptions.exceptions import raise_exception +from beacon.connections.mongo.utils import get_count, get_documents +from typing import Optional +from beacon.response.schemas import DefaultSchemas +from beacon.request.parameters import RequestParams +from beacon.connections.mongo.filters import apply_filters +from beacon.connections.mongo.utils import get_docs_by_response_type, query_id, get_cross_query +from beacon.connections.mongo.request_parameters import apply_request_parameters + +@log_with_args_mongo(level) +def get_datasets(self): + try: + collection = client.beacon.datasets + query = {} + query = collection.find(query) + return query + except Exception as e:# pragma: no cover + err = str(e) + errcode=500 + raise_exception(err, errcode) + +@log_with_args_mongo(level) +def get_full_datasets(self, entry_id: Optional[str], qparams: RequestParams): + try: + collection = client.beacon.datasets + if entry_id == None: + query = {} + else:# pragma: no cover + query = {'id': entry_id} + count = get_count(self, client.beacon.datasets, query) + query = collection.find(query) + entity_schema = DefaultSchemas.DATASETS + response_converted = ( + [r for r in query] if query else [] + ) + return response_converted, count, entity_schema + except Exception as e:# pragma: no cover + err = str(e) + errcode=500 + raise_exception(err, errcode) + +@log_with_args_mongo(level) +def get_list_of_datasets(self): + try: + datasets = get_datasets(self) + beacon_datasets = [ r for r in datasets ] + return beacon_datasets + except Exception as e:# pragma: no cover + err = str(e) + errcode=500 + raise_exception(err, errcode) + +@log_with_args_mongo(level) +def get_dataset_with_id(self, entry_id: Optional[str], qparams: RequestParams): + limit = qparams.query.pagination.limit + query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, entry_id) + if parameters_as_filters == True: + query, parameters_as_filters = apply_request_parameters(self, {}, qparams, entry_id)# pragma: no cover + else: + query={} + query = query_id(self, query, entry_id) + schema = DefaultSchemas.DATASETS + count = get_count(self, client.beacon.datasets, query) + docs = get_documents(self, + client.beacon.datasets, + query, + qparams.query.pagination.skip, + qparams.query.pagination.skip*limit + ) + response_converted = ( + [r for r in docs] if docs else [] + ) + return response_converted, count, schema + +@log_with_args_mongo(level) +def get_variants_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'datasets' + mongo_collection = client.beacon.genomicVariations + dataset_count=0 + limit = qparams.query.pagination.limit + query_count={} + idq="caseLevelData.biosampleId" + query_count["$or"]=[] + if dataset == entry_id: + queryid={} + queryid["datasetId"]=dataset + query_count["$or"].append(queryid) + else: + schema = DefaultSchemas.GENOMICVARIATIONS# pragma: no cover + return schema, 0, 0, None, dataset# pragma: no cover + query = apply_filters(self, query_count, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.GENOMICVARIATIONS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args_mongo(level) +def get_biosamples_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'datasets' + mongo_collection = client.beacon.biosamples + dataset_count=0 + limit = qparams.query.pagination.limit + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.datasets, query) + dict_in={} + dict_in['datasetId']=dataset + query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.BIOSAMPLES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args_mongo(level) +def get_individuals_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'datasets' + mongo_collection = client.beacon.individuals + dataset_count=0 + limit = qparams.query.pagination.limit + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.datasets, query) + dict_in={} + dict_in['datasetId']=dataset + query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.INDIVIDUALS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args_mongo(level) +def get_runs_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'datasets' + mongo_collection = client.beacon.runs + dataset_count=0 + limit = qparams.query.pagination.limit + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.datasets, query) + dict_in={} + dict_in['datasetId']=dataset + query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.RUNS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + list_of_records = ( + [r for r in docs] if docs else [] + ) + return schema, count, dataset_count, list_of_records, dataset + +@log_with_args_mongo(level) +def get_analyses_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'datasets' + idq="biosampleId" + mongo_collection = client.beacon.analyses + dataset_count=0 + limit = qparams.query.pagination.limit + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + count = get_count(self, client.beacon.datasets, query) + dict_in={} + dict_in['datasetId']=dataset + query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.ANALYSES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/executor.py b/beacon/connections/omopcdm/executor.py new file mode 100644 index 0000000..21b15ec --- /dev/null +++ b/beacon/connections/omopcdm/executor.py @@ -0,0 +1,105 @@ +from beacon.connections.omopcdm.individuals import get_individuals, get_individual_with_id, get_biosamples_of_individual +from beacon.connections.omopcdm.biosamples import get_biosamples, get_biosample_with_id +import asyncio +from concurrent.futures import ThreadPoolExecutor +from beacon.logs.logs import log_with_args, level, LOG +from typing import Optional +from beacon.request.parameters import RequestParams +from beacon.connections.omopcdm.datasets import get_biosamples_of_dataset, get_individuals_of_dataset +from beacon.connections.omopcdm.cohorts import get_biosamples_of_cohort, get_individuals_of_cohort +from beacon.connections.omopcdm.datasets import get_full_datasets, get_dataset_with_id +from beacon.connections.omopcdm.cohorts import get_cohorts, get_cohort_with_id + +@log_with_args(level) +async def execute_function(self, entry_type: str, datasets: list, qparams: RequestParams, entry_id: Optional[str]): + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + datasets_docs={} + datasets_count={} + new_count=0 + LOG.debug(f"entry_type {entry_type}") + LOG.debug(f"datasets {datasets}") + LOG.debug(f"qparams {qparams}") + + if entry_id == None: + if entry_type == 'individuals': + function=get_individuals + elif entry_type == 'biosamples': + function=get_biosamples + else: + if entry_type == 'individuals': + function=get_individual_with_id + elif entry_type == 'biosamples': + function=get_biosample_with_id + elif entry_type == 'individuals_biosamples': + function = get_biosamples_of_individual + elif entry_type == 'datasets_biosamples': + function=get_biosamples_of_dataset + elif entry_type == 'datasets_individuals': + function=get_individuals_of_dataset + elif entry_type == 'cohorts_biosamples': + function=get_biosamples_of_cohort + elif entry_type == 'cohorts_individuals': + function=get_individuals_of_cohort + + loop = asyncio.get_running_loop() + + if datasets != [] and include != 'NONE': + with ThreadPoolExecutor() as pool: + done, pending = await asyncio.wait(fs=[loop.run_in_executor(pool, function, self, entry_id, qparams, dataset) for dataset in datasets], + return_when=asyncio.ALL_COMPLETED + ) + for task in done: + entity_schema, count, dataset_count, records, dataset = task.result() + if include == 'ALL': + if dataset_count != -1: + new_count+=dataset_count + datasets_docs[dataset]=records + datasets_count[dataset]=dataset_count + else: + datasets.remove(dataset) + elif include == 'HIT': + if dataset_count != -1 and dataset_count != 0: + new_count+=dataset_count + datasets_docs[dataset]=records + datasets_count[dataset]=dataset_count + else: + datasets.remove(dataset) + else: + if dataset_count == 0: + new_count+=dataset_count + datasets_docs[dataset]=records + datasets_count[dataset]=dataset_count + else: + datasets.remove(dataset) + count=new_count + + else: + with ThreadPoolExecutor() as pool: + done, pending = await asyncio.wait(fs=[loop.run_in_executor(pool, function, self, entry_id, qparams, dataset) for dataset in datasets], + return_when=asyncio.ALL_COMPLETED + ) + for task in done: + entity_schema, count, dataset_count, records, dataset = task.result() + datasets_docs["NONE"]=records + if limit == 0 or new_count < limit: + pass + else: + count = limit# pragma: no cover + datasets_count["NONE"]=count + return datasets_docs, datasets_count, count, entity_schema, include, datasets + +@log_with_args(level) +async def execute_collection_function(self, entry_type: str, qparams: RequestParams, entry_id: Optional[str]): + if entry_id == None: + if entry_type == 'datasets': + function=get_full_datasets + elif entry_type == 'cohorts': + function=get_cohorts + else: + if entry_type == 'datasets': + function=get_dataset_with_id + elif entry_type == 'cohorts': + function=get_cohort_with_id + response_converted, count, entity_schema = function(self, entry_id, qparams) + return response_converted, count, entity_schema \ No newline at end of file diff --git a/beacon/connections/omopcdm/extract_filtering_terms.py b/beacon/connections/omopcdm/extract_filtering_terms.py new file mode 100644 index 0000000..0bed779 --- /dev/null +++ b/beacon/connections/omopcdm/extract_filtering_terms.py @@ -0,0 +1,493 @@ +import os.path +from typing import List, Dict, Optional +import re +from pymongo.mongo_client import MongoClient +import progressbar +from bson.objectid import ObjectId +from tqdm import tqdm +from bson.json_util import dumps +import json + +import sys +import os + + +current = os.path.dirname(os.path.realpath(__file__)) + + +parent = os.path.dirname(current) + + +sys.path.append(parent) + + +import conf + + +ONTOLOGY_REGEX = re.compile(r"([_A-Za-z0-9]+):([_A-Za-z0-9^\-]+)") +ICD_REGEX = re.compile(r"(ICD[_A-Za-z0-9]+):([_A-Za-z0-9^\./-]+)") + + +if conf.database_cluster: + uri = "mongodb+srv://{}:{}@{}/?tls=true&authMechanism=SCRAM-SHA-256&retrywrites=false&maxIdleTimeMS=120000".format( + conf.database_user, + conf.database_password, + conf.database_host + ) +else: + uri = "mongodb://{}:{}@{}:{}/{}?authSource={}".format( + conf.database_user, + conf.database_password, + conf.database_host, + conf.database_port, + conf.database_name, + conf.database_auth_source + ) + +if os.path.isfile(conf.database_certificate): + uri += '&tls=true&tlsCertificateKeyFile={}'.format(conf.database_certificate) + if os.path.isfile(conf.database_cafile): + uri += '&tlsCAFile={}'.format(conf.database_cafile) + +client = MongoClient(uri) +''' + +client = MongoClient( +client = MongoClient( + #"mongodb://127.0.0.1:27017/" + "mongodb://root:example@mongo:27017/beacon?authSource=admin" + +) +''' + +class MyProgressBar: + def __init__(self): + self.pbar = None + + def __call__(self, block_num: int, block_size: int, total_size: int): + if not self.pbar: + self.pbar = progressbar.ProgressBar(maxval=total_size) + self.pbar.start() + + downloaded = block_num * block_size + if downloaded < total_size: + self.pbar.update(downloaded) + else: + self.pbar.finish() + + +def get_ontology_field_name(ontology_id:str, term_id:str, collection:str): + biosamples=['biosampleStatus.id','diagnosticMarkers.id','histologicalDiagnosis.id','measurements.assayCode.id','measurements.measurementValue.id','measurements.measurementValue.referenceRange.unit.id','measurements.measurementValue.typedQuantities.quantity.unit.id','measurements.measurementValue.unit.id','measurements.observationMoment.id','measurements.procedure.bodySite.id','measurements.procedure.procedureCode.id','pathologicalStage.id','pathologicalTnmFinding.id','phenotypicFeatures.evidence.evidenceCode.id','phenotypicFeatures.evidence.reference.id','phenotypicFeatures.featureType.id','phenotypicFeatures.modifiers.id','phenotypicFeatures.onset.id','phenotypicFeatures.resolution.id','phenotypicFeatures.severity.id','sampleOriginDetail.id','sampleOriginType.id','sampleProcessing.id','sampleStorage.id','tumorGrade.id','tumorProgression.id'] + cohorts=['cohortDataTypes.id','cohortDesign.id','exclusionCriteria.diseaseConditions.diseaseCode.id','exclusionCriteria.diseaseConditions.severity.id','exclusionCriteria.diseaseConditions.stage.id','exclusionCriteria.ethnicities.id','exclusionCriteria.genders.id','exclusionCriteria.locations.id','exclusionCriteria.phenotypicConditions.featureType.id','exclusionCriteria.phenotypicConditions.severity.id','inclusionCriteria.diseaseConditions.diseaseCode.id','inclusionCriteria.diseaseConditions.severity.id','inclusionCriteria.diseaseConditions.stage.id','inclusionCriteria.ethnicities.id','inclusionCriteria.genders.id','inclusionCriteria.locations.id','inclusionCriteria.phenotypicConditions.featureType.id','inclusionCriteria.phenotypicConditions.severity.id'] + datasets=['dataUseConditions.duoDataUse.id'] + genomicVariations=['caseLevelData.alleleOrigin.id','caseLevelData.clinicalInterpretations.category.id','caseLevelData.clinicalInterpretations.effect.id','caseLevelData.clinicalInterpretations.evidenceType.id','caseLevelData.id','caseLevelData.phenotypicEffects.category.id','caseLevelData.phenotypicEffects.effect.id','caseLevelData.phenotypicEffects.evidenceType.id','caseLevelData.zygosity.id','identifiers.variantAlternativeIds.id','molecularAttributes.molecularEffects.id','variantLevelData.clinicalInterpretations.category.id','variantLevelData.clinicalInterpretations.effect.id','variantLevelData.clinicalInterpretations.evidenceType.id','variantLevelData.phenotypicEffects.category.id','variantLevelData.phenotypicEffects.effect.id','variantLevelData.phenotypicEffects.evidenceType.id'] + individuals=['diseases.ageOfOnset.id','diseases.diseaseCode.id','diseases.severity.id','diseases.stage.id','ethnicity.id','exposures.exposureCode.id','exposures.unit.id','geographicOrigin.id','interventionsOrProcedures.ageAtProcedure.id','interventionsOrProcedures.bodySite.id','interventionsOrProcedures.procedureCode.id','measures.assayCode.id','measures.measurementValue.id','measures.measurementValue.typedQuantities.quantity.unit.id','measures.measurementValue.unit.id','measures.observationMoment.id','measures.procedure.bodySite.id','measures.procedure.procedureCode.id','pedigrees.disease.diseaseCode.id','pedigrees.disease.severity.id','pedigrees.disease.stage.id','pedigrees.id','pedigrees.members.role.id','phenotypicFeatures.evidence.evidenceCode.id','phenotypicFeatures.evidence.reference.id','phenotypicFeatures.featureType.id','phenotypicFeatures.modifiers.id','phenotypicFeatures.onset.id','phenotypicFeatures.resolution.id','phenotypicFeatures.severity.id','sex.id','treatments.cumulativeDose.referenceRange.id','treatments.doseIntervals.id','treatments.routeOfAdministration.id','treatments.treatmentCode.id'] + runs=['librarySource.id','platformModel.id'] + array=[] + if collection == 'biosamples': + array=biosamples + elif collection == 'cohorts': + array=cohorts + elif collection == 'datasets': + array=datasets + elif collection == 'genomicVariations': + array=genomicVariations + elif collection == 'individuals': + array=individuals + elif collection == 'runs': + array=runs + query={} + query['$or']=[] + for field in array: + fieldquery={} + fieldquery[field]=ontology_id + ":" + term_id + query['$or'].append(fieldquery) + results = client.beacon.get_collection(collection).find(query).limit(1) + results = list(results) + results = dumps(results) + results = json.loads(results) + field = '' + for result in results: + for k, v in result.items(): + if isinstance(v, str): + if v == ontology_id + ':' + term_id: + field = k + for key, value in result.items(): + if key == 'label': + label = value + break + break + elif isinstance(v, dict): + for k2, v2 in v.items(): + if isinstance(v2, list): + for item_list in v2: + if isinstance(item_list, str): + if item_list == ontology_id + ':' + term_id: + field = k + '.' + k2 + for key, value in v.items(): + if key == 'label': + label = value + break + break + elif isinstance(item_list, dict): + for k21, v21 in item_list.items(): + if isinstance(v21, str): + if v21 == ontology_id + ':' + term_id: + field = k + '.' + k2 + '.' + k21 + for key, value in item_list.items(): + if key == 'label': + label = value + break + break + elif isinstance(v21,dict): + for k22, v22 in v21.items(): + if v22 == v21 == ontology_id + ':' + term_id: + field = k + '.' + k2 + '.' + k22 + for key, value in v21.items(): + if key == 'label': + label = value + break + break + elif v2 == ontology_id + ':' + term_id: + field = k + '.' + k2 + for key, value in v.items(): + if key == 'label': + label = value + break + break + elif isinstance(v, list): + for item in v: + if isinstance(item, str): + if item == ontology_id + ':' + term_id: + field = k + for key, value in result.items(): + if key == 'label': + label = value + break + break + elif isinstance(item, dict): + for k2, v2 in item.items(): + if isinstance(v2, str): + if v2 == ontology_id + ':' + term_id: + field = k + '.' + k2 + for key, value in item.items(): + if k == 'label': + label = v + break + break + elif isinstance(v2, dict): + for k3, v3 in v2.items(): + if isinstance(v3, str): + if v3 == ontology_id + ':' + term_id: + field = k + '.' + k2 + '.' + k3 + for key, value in v2.items(): + if key == 'label': + label = value + break + break + elif isinstance(v3, dict): + for k4, v4 in v3.items(): + if isinstance(v4, str): + if v4 == ontology_id + ':' + term_id: + field = k + '.' + k2 + '.' + k3 + '.' + k4 + for key, value in v3.items(): + if key == 'label': + label = value + break + break + elif isinstance(v4, dict): + for k5, v5 in v4.items(): + if v5 == ontology_id + ':' + term_id: + field = k + '.' + k2 + '.' + k3 + '.' + k4 + '.' + k5 + for key, value in v4.items(): + if key == 'label': + label = value + break + break + + + if '.' in field: + try: + final_field = '' + field_split = field.split('.') + del field_split[-1] + for item in field_split: + if final_field == '': + final_field = item + else: + final_field = final_field + '.' + item + final_dict={} + final_dict['field']=final_field + final_dict['label']=label + return final_dict + except Exception: + pass + else: + pass + + +def insert_all_ontology_terms_used(): + collections = client.beacon.list_collection_names() + if 'filtering_terms' in collections: + collections.remove('filtering_terms') + print("Collections:", collections) + for c_name in collections: + if c_name not in ['counts', 'similarities', 'synonyms', 'caseLevelData', 'targets']: + terms_ids = find_ontology_terms_used(c_name) + terms = get_filtering_object(terms_ids, c_name) + if len(terms) > 0: + client.beacon.filtering_terms.insert_many(terms) + +def find_ontology_terms_used(collection_name: str) -> List[Dict]: + print(collection_name) + terms_ids = [] + count = client.beacon.get_collection(collection_name).estimated_document_count() + if count < 10000: + num_total=count + else: + num_total=10000 + i=0 + if count > 10000: + while i < count: + xs = client.beacon.get_collection(collection_name).find().skip(i).limit(10000) + for r in tqdm(xs, total=num_total): + matches = ONTOLOGY_REGEX.findall(str(r)) + icd_matches = ICD_REGEX.findall(str(r)) + for ontology_id, term_id in matches: + term = ':'.join([ontology_id, term_id]) + if term not in terms_ids: + terms_ids.append(term) + for ontology_id, term_id in icd_matches: + term = ':'.join([ontology_id, term_id]) + if term not in terms_ids: + terms_ids.append(term) + i += 10000 + if i > 30000: + break + print(i) + else: + xs = client.beacon.get_collection(collection_name).find().skip(0).limit(10000) + for r in tqdm(xs, total=num_total): + matches = ONTOLOGY_REGEX.findall(str(r)) + icd_matches = ICD_REGEX.findall(str(r)) + for ontology_id, term_id in matches: + term = ':'.join([ontology_id, term_id]) + if term not in terms_ids: + terms_ids.append(term) + for ontology_id, term_id in icd_matches: + term = ':'.join([ontology_id, term_id]) + if term not in terms_ids: + terms_ids.append(term) + + return terms_ids + + + +def get_filtering_object(terms_ids: list, collection_name: str): + terms = [] + list_of_ontologies=[] + #ontologies = dict() + for onto in terms_ids: + ontology = onto.split(':') + ontology_id = ontology[0] + term_id = ontology[1] + #if ontology_id not in ontologies: + #ontologies[ontology_id] = load_ontology(ontology_id) + if ontology_id.isupper(): + field_dict = get_ontology_field_name(ontology_id, term_id, collection_name) + else: + continue + try: + field = field_dict['field'] + label = field_dict['label'] + value_id=None + if 'measurements.assayCode' in field: + value_id = label + else: + ontology_label = label + if field is not None: + if onto not in list_of_ontologies: + list_of_ontologies.append(onto) + if label: + terms.append({ + 'type': 'ontology', + 'id': onto, + 'label': ontology_label, + # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms + #'count': get_ontology_term_count(collection_name, onto), + 'scopes': [collection_name[0:-1]] + }) + + terms.append({ + 'type': 'alphanumeric', + 'id': field, + # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms + #'count': get_ontology_term_count(collection_name, onto), + 'scopes': [collection_name[0:-1]] + }) + terms.append({ + 'type': 'custom', + 'id': '{}:{}'.format(field,label), + # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms + #'count': get_ontology_term_count(collection_name, onto), + 'scopes': [collection_name[0:-1]] + }) + if value_id is not None: + terms.append({ + 'type': 'alphanumeric', + 'id': value_id, + # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms + #'count': get_ontology_term_count(collection_name, onto), + 'scopes': [collection_name[0:-1]] + }) + + print(terms) + except Exception: + pass + + return terms + + +def get_alphanumeric_term_count(collection_name: str, key: str) -> int: + return len(client.beacon\ + .get_collection(collection_name)\ + .distinct(key)) + +def get_properties_of_document(document, prefix="") -> List[str]: + properties = [] + if document is None or isinstance(document, str) or isinstance(document, int): + return [] + elif isinstance(document, list): + for elem in document: + properties += get_properties_of_document(elem, prefix) + elif isinstance(document, dict): + for key, value in document.items(): + if isinstance(value, ObjectId): + continue + elif value is None: + properties.append(prefix + '.' + key if prefix else key) + elif isinstance(value, int): + properties.append(prefix + '.' + key if prefix else key) + elif isinstance(value, str): + properties.append(prefix + '.' + key if prefix else key) + elif isinstance(value, list): + properties += get_properties_of_document(value, prefix + '.' + key if prefix else key) + elif isinstance(value, dict): + properties += get_properties_of_document(value, prefix + '.' + key if prefix else key) + else: + print('Unknown type:', value, ' (', type(value), ')') + exit(0) + else: + print('Unknown type2:', document, ' (', type(document), ')') + exit(0) + return properties + +def merge_ontology_terms(): + filtering_terms = client.beacon.filtering_terms.find({"type": "ontology"}) + array_of_ids=[] + repeated_ids=[] + new_terms=[] + for filtering_term in filtering_terms: + new_id=filtering_term["id"] + if new_id not in array_of_ids: + array_of_ids.append(new_id) + else: + repeated_ids.append(new_id) + #print("repeated_ids are {}".format(repeated_ids)) + for repeated_id in repeated_ids: + repeated_terms = client.beacon.filtering_terms.find({"id": repeated_id, "type": "ontology"}) + array_of_scopes=[] + for repeated_term in repeated_terms: + #print(repeated_term) + id=repeated_term["id"] + label=repeated_term["label"] + if repeated_term['scopes'] != []: + if repeated_term['scopes'][0] not in array_of_scopes: + array_of_scopes.append(repeated_term['scopes'][0]) + if array_of_scopes != []: + new_terms.append({ + 'type': 'ontology', + 'id': id, + 'label': label, + # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms + #'count': get_ontology_term_count(collection_name, onto), + 'scopes': array_of_scopes + }) + client.beacon.filtering_terms.delete_many({"id": repeated_id}) + if new_terms != []: + client.beacon.filtering_terms.insert_many(new_terms) + + +def merge_alphanumeric_terms(): + filtering_terms = client.beacon.filtering_terms.find({"type": "alphanumeric"}) + array_of_ids=[] + repeated_ids=[] + new_terms=[] + for filtering_term in filtering_terms: + new_id=filtering_term["id"] + if new_id not in array_of_ids: + array_of_ids.append(new_id) + else: + repeated_ids.append(new_id) + #print("repeated_ids are {}".format(repeated_ids)) + for repeated_id in repeated_ids: + repeated_terms = client.beacon.filtering_terms.find({"id": repeated_id, "type": "alphanumeric"}) + array_of_scopes=[] + for repeated_term in repeated_terms: + #print(repeated_term) + id=repeated_term["id"] + if repeated_term['scopes'] != []: + if repeated_term['scopes'][0] not in array_of_scopes: + array_of_scopes.append(repeated_term['scopes'][0]) + if array_of_scopes != []: + new_terms.append({ + 'type': 'alphanumeric', + 'id': id, + # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms + #'count': get_ontology_term_count(collection_name, onto), + 'scopes': array_of_scopes + }) + client.beacon.filtering_terms.delete_many({"id": repeated_id}) + if new_terms != []: + client.beacon.filtering_terms.insert_many(new_terms) + +def merge_custom_terms(): + filtering_terms = client.beacon.filtering_terms.find({"type": "custom"}) + array_of_ids=[] + repeated_ids=[] + new_terms=[] + for filtering_term in filtering_terms: + new_id=filtering_term["id"] + if new_id not in array_of_ids: + array_of_ids.append(new_id) + else: + repeated_ids.append(new_id) + #print("repeated_ids are {}".format(repeated_ids)) + for repeated_id in repeated_ids: + repeated_terms = client.beacon.filtering_terms.find({"id": repeated_id, "type": "custom"}) + array_of_scopes=[] + for repeated_term in repeated_terms: + #print(repeated_term) + id=repeated_term["id"] + if repeated_term['scopes'] != []: + if repeated_term['scopes'][0] not in array_of_scopes: + array_of_scopes.append(repeated_term['scopes'][0]) + if array_of_scopes != []: + new_terms.append({ + 'type': 'custom', + 'id': id, + # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms + #'count': get_ontology_term_count(collection_name, onto), + 'scopes': array_of_scopes + }) + client.beacon.filtering_terms.delete_many({"id": repeated_id}) + if new_terms != []: + client.beacon.filtering_terms.insert_many(new_terms) + + + + +insert_all_ontology_terms_used() +merge_ontology_terms() +merge_alphanumeric_terms() +merge_custom_terms() \ No newline at end of file diff --git a/beacon/connections/omopcdm/filtering_terms.py b/beacon/connections/omopcdm/filtering_terms.py new file mode 100644 index 0000000..67d7a22 --- /dev/null +++ b/beacon/connections/omopcdm/filtering_terms.py @@ -0,0 +1,27 @@ +from beacon.connections.mongo.__init__ import client +from beacon.connections.mongo.utils import get_count +from typing import Optional +from beacon.response.schemas import DefaultSchemas +from beacon.request.parameters import RequestParams +from beacon.connections.mongo.utils import get_filtering_documents +from beacon.exceptions.exceptions import raise_exception + +def get_filtering_terms(self, qparams: RequestParams): + try: + query = {} + schema = DefaultSchemas.FILTERINGTERMS + count = get_count(self, client.beacon.filtering_terms, query) + remove_id={'_id':0} + docs = get_filtering_documents( + self, + client.beacon.filtering_terms, + query, + remove_id, + qparams.query.pagination.skip, + qparams.query.pagination.limit + ) + return schema, count, docs + except Exception as e:# pragma: no cover + err = str(e) + errcode=500 + raise_exception(err, errcode) \ No newline at end of file diff --git a/beacon/connections/omopcdm/filters.py b/beacon/connections/omopcdm/filters.py new file mode 100644 index 0000000..e6ae138 --- /dev/null +++ b/beacon/connections/omopcdm/filters.py @@ -0,0 +1,247 @@ +from typing import List, Union +import re +from beacon.request.parameters import AlphanumericFilter, OntologyFilter +from beacon.connections.omopcdm.utils import peek +from beacon.connections.omopcdm.__init__ import client +from beacon.logs.logs import log_with_args, LOG +from beacon.conf.conf import level + +import aiosql +from pathlib import Path + +CURIE_REGEX = r'^([a-zA-Z0-9]*):\/?[a-zA-Z0-9./]*$' + +queries_file = Path(__file__).parent / "sql" / "basic_queries.sql" +filter_queries = aiosql.from_path(queries_file, "psycopg2") + +@log_with_args(level) +def apply_filters(self, filtersGet: dict, filtersPost: List[dict], scope: str, granularity : str, limit : int = 10, skip : int = 0) -> dict: + # Get and Post Filters as dict + filters = [] + if filtersGet: + LOG.debug("Get Query") + listFilters= filtersGet["filters"].split(",") + for filter in listFilters: + # All Get Queries have include descendant terms as default + filterDict = {"id":filter, "scope": scope, "includeDescendantTerms": "true"} + filters.append(filterDict) + elif filtersPost: + LOG.debug("Post Query") + filters = filtersPost + else: + return {} + + # Create query + query = '' + for filter in filters: + # Alphanumeric filter + if "value" in filter: + filter = AlphanumericFilter(**filter) + partial_query = apply_alphanumeric_filter(self, filter) # Only individuals + # Ontology filters + elif re.match(CURIE_REGEX, filter["id"]): + ontFilter = OntologyFilter(**filter) + if 'includeDescendantTerms' not in filter: + ontFilter.include_descendant_terms = True + elif filter['includeDescendantTerms'] == 'true': + ontFilter.include_descendant_terms = True + partial_query = apply_ontology_filter(self, ontFilter, scope) # Individuals or biosamples + else: + return query + query += partial_query + + # Create final SQL queries per scope + if scope == "biosamples": + column = "specimen_id" + table = "specimen" + + else: # Individuals + column = "person_id" + table = "person" + + # Query different on granularity + if granularity == "boolean": + finalQuery = f""" + SELECT EXISTS ( + SELECT 1 + FROM cdm.{table} p + WHERE true {query} + ); + """ + elif granularity == "count": + finalQuery = f""" + SELECT COUNT(*) + FROM cdm.{table} p + WHERE true {query} + """ + else: # Record response + finalQuery = f""" + SELECT {column}, + ( SELECT COUNT(*) + FROM cdm.{table} p + WHERE true {query}) AS totalCount + FROM cdm.{table} p + WHERE true {query} + limit {limit} + offset {skip}; + """ + return finalQuery + +def search_descendants(concept_id: str) -> list: + records = filter_queries.sql_get_descendants(client, concept_id=concept_id) + l_descendants = set() + for descendant in records: + l_descendants.add(descendant[0]) + return l_descendants + + +def map_domains(domain_id: str) -> dict: + # Domain_id : Table in OMOP + # Maybe there is more than one mapping in the condition domain + dictMapping = { + # Individuals + 'Gender':['person','gender_concept_id'], + 'Race':['person','race_concept_id'], + 'Condition':['condition_occurrence','condition_concept_id'], + 'Measurement':['measurement','measurement_concept_id'], + 'Procedure':['procedure_occurrence','procedure_concept_id'], + 'Observation':['observation','observation_concept_id'], + 'Drug':['drug_exposure','drug_concept_id'], + + # Biosamples + 'Spec Disease Status':['specimen', 'disease_status_concept_id'], + 'Spec Anatomic Site':['specimen', 'anatomic_site_concept_id'] + } + return dictMapping[domain_id] + +@log_with_args(level) +def filter_to_OMOP_vocabulary(self, filter: Union[OntologyFilter, AlphanumericFilter]): + listConcept_id = set() # Set to store Concept id + Possible descendant terms + vocabulary_id, concept_code = filter.id.split(':') + records = filter_queries.sql_get_concept_domain(client, + vocabulary_id=vocabulary_id, + concept_code=concept_code) + # Check if records is empty + res = peek(records) + if res is None: + return [], 0 + _, records = res + for record in records: + original_concept_id = record[0] + domain_id = record[1] + listConcept_id.add(original_concept_id) + # Look in which domains the concept_id belongs + tableMap=map_domains(domain_id) + if type(filter) == OntologyFilter: + if filter.include_descendant_terms: + # Import descendants of the concept_id + concept_ids= search_descendants(original_concept_id) + # Concept_id and descendants in same set() + listConcept_id = listConcept_id.union(concept_ids) + return listConcept_id, tableMap + +@log_with_args(level) +def format_value(self, value: Union[str, List[int]]) -> Union[List[int], str, int, float]: + if isinstance(value, list): + return value# pragma: no cover + elif isinstance(value, int): + return value# pragma: no cover + + elif value.isnumeric(): + if float(value).is_integer(): + return int(value) + else: + return float(value)# pragma: no cover + + else: + return value + + +@log_with_args(level) +def apply_alphanumeric_filter(self, filter: AlphanumericFilter) -> str: + scope = filter.scope + + formatted_value = format_value(self, filter.value) + + # # If value is string + # if isinstance(formatted_value,str): + # if filter.id in conf.alphanumeric_terms: + # filter.id = filter.id# pragma: no cover + # else: + # filter.id = filter.id + '.' + 'label' + # else: + # # Age Alphanumeric filters + if (filter.id == 'ageOfOnset' or + filter.id == 'ageAtProcedure' or + filter.id == 'observationMoment' or + filter.id == 'ageAtExposure'): + listConcept_id = ['None'] + if filter.id == 'ageOfOnset': + try: + scope = filter['scope'] + except: + print("You need an scope if you are using 'ageOfOnset', try 'disease' or 'treatments'") + if "disease" in scope: + filter.id = 'ageAtDisease' + elif "treatments" in scope: + filter.id = 'ageAtTreatment' + mappingDict = { + 'ageAtDisease': ['condition_occurrence', 'condition_start_date'], + 'ageAtProcedure': ['procedure_occurrence', 'procedure_date'], + 'observationMoment': ['measurement', 'measurement_date'], + 'ageAtExposure': ['observation', 'observation_date'], + 'ageAtTreatment': ['drug_exposure', 'drug_exposure_start_date'] + } + LOG.debug(f"scope {scope}") + LOG.debug(f"mappingDict[filter.id][0] {mappingDict[filter.id][0]}") + + # Create filter + query = f""" + and exists ( + select 1 + from cdm.{mappingDict[filter.id][0]} tab + where p.person_id = tab.person_id + and ( + CASE + WHEN birth_datetime IS NOT NULL THEN extract(Year from age({mappingDict[filter.id][1]}, birth_datetime)) {filter.operator} {filter.value} + ELSE (extract(Year from {mappingDict[filter.id][1]}) - year_of_birth) {filter.operator} {filter.value} + END ) + ) + """ + # Other alphanumeric filters with integers + else: + conceptId, tableMap = filter_to_OMOP_vocabulary(self, filter) + LOG.debug(tableMap) + query = f""" + and exists ( + select 1 + from cdm.{tableMap[0]} tab + where p.person_id = tab.person_id + and ( + {tableMap[1]} = {''.join(map(str, conceptId))} and value_as_number {filter.operator} {filter.value}) + ) + """ + return query + + +@log_with_args(level) +def apply_ontology_filter(self, filter: OntologyFilter, scope: str) -> str: + setConceptId, tableMap = filter_to_OMOP_vocabulary(self, filter) + LOG.debug(tableMap) + listConceptId = [] + for conceptId in setConceptId: + listConceptId.append(tableMap[1] + ' = ' + str(conceptId)) + partialQuery = ' or '.join(listConceptId) + if scope == "biosamples": + partialQuery = f"and ({partialQuery})" + return partialQuery + elif scope == "individuals": + query = f""" + and exists ( + select 1 + from cdm.{tableMap[0]} tab + where p.person_id = tab.person_id + and ({partialQuery}) + ) + """ + return query \ No newline at end of file diff --git a/beacon/connections/omopcdm/g_variants.py b/beacon/connections/omopcdm/g_variants.py new file mode 100644 index 0000000..19ca95d --- /dev/null +++ b/beacon/connections/omopcdm/g_variants.py @@ -0,0 +1,278 @@ +from beacon.request.parameters import RequestParams +from beacon.response.schemas import DefaultSchemas +from beacon.connections.mongo.__init__ import client +from beacon.connections.mongo.utils import get_docs_by_response_type +from beacon.logs.logs import log_with_args, LOG +from beacon.conf.conf import level +from beacon.connections.mongo.filters import apply_filters +from beacon.connections.mongo.request_parameters import apply_request_parameters +from typing import Optional +from bson import json_util + +@log_with_args(level) +def get_variants(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'g_variants' + mongo_collection = client.beacon.genomicVariations + parameters_as_filters=False + query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) + if parameters_as_filters == True and query_parameters != {'$and': []}: + query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset)# pragma: no cover + query_parameters={}# pragma: no cover + elif query_parameters != {'$and': []}: + query=query_parameters + elif query_parameters == {'$and': []}: + query_parameters = {} + query={} + query = apply_filters(self, query, qparams.query.filters, collection,query_parameters, dataset) + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100 + schema = DefaultSchemas.GENOMICVARIATIONS + idq="caseLevelData.biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + #∫docs = json_util.dumps(docs) + + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_variant_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'g_variants' + mongo_collection = client.beacon.genomicVariations + query = {"$and": [{"variantInternalId": entry_id}]} + query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) + if parameters_as_filters == True: + query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset)# pragma: no cover + query_parameters={}# pragma: no cover + else: + query=query_parameters + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.GENOMICVARIATIONS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="caseLevelData.biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_biosamples_of_variant(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'g_variants' + mongo_collection = client.beacon.biosamples + query = {"$and": [{"variantInternalId": entry_id}]} + query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) + if parameters_as_filters == True: + query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset)# pragma: no cover + query_parameters={}# pragma: no cover + else: + query=query_parameters + collection='biosamples' + HGVSIds = client.beacon.genomicVariations \ + .find(query, {"identifiers.genomicHGVSId": 1, "datasetId": 1, "_id": 0}) + HGVSDataset=HGVSIds[0]["datasetId"] + if dataset != HGVSDataset: + schema = DefaultSchemas.BIOSAMPLES + return schema, 0, 0, [], dataset + HGVSIds=list(HGVSIds) + HGVSId=HGVSIds[0]["identifiers"]["genomicHGVSId"] + queryHGVSId={"datasetId": dataset, "id": HGVSId} + string_of_ids = client.beacon.caseLevelData \ + .find(queryHGVSId, {"biosampleIds": 1, "_id": 0}) + targets = client.beacon.targets \ + .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) + targets=list(targets) + list_of_targets=targets[0]["biosampleIds"] + list_of_positions_strings= string_of_ids[0]['biosampleIds'].split(',') + biosampleIds=[] + for position in list_of_positions_strings: + if position != '': + biosampleIds.append(list_of_targets[int(position)]) + finalids=biosampleIds + try: + finalids=[] + for bioid in biosampleIds: + finalids.append({"id": bioid}) + except Exception:# pragma: no cover + finalids=[] + query = {"$and": [{"$or": finalids}]} + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.BIOSAMPLES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_runs_of_variant(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'g_variants' + mongo_collection = client.beacon.runs + query = {"$and": [{"variantInternalId": entry_id}]} + query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) + if parameters_as_filters == True: + query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset)# pragma: no cover + query_parameters={}# pragma: no cover + else: + query=query_parameters + collection='runs' + HGVSIds = client.beacon.genomicVariations \ + .find(query, {"identifiers.genomicHGVSId": 1, "datasetId": 1, "_id": 0}) + HGVSDataset=HGVSIds[0]["datasetId"] + if dataset != HGVSDataset: + schema = DefaultSchemas.INDIVIDUALS + return schema, 0, 0, [], dataset + HGVSIds=list(HGVSIds) + HGVSId=HGVSIds[0]["identifiers"]["genomicHGVSId"] + queryHGVSId={"datasetId": dataset, "id": HGVSId} + string_of_ids = client.beacon.caseLevelData \ + .find(queryHGVSId, {"biosampleIds": 1, "_id": 0}) + targets = client.beacon.targets \ + .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) + targets=list(targets) + list_of_targets=targets[0]["biosampleIds"] + list_of_positions_strings= string_of_ids[0]['biosampleIds'].split(',') + biosampleIds=[] + for position in list_of_positions_strings: + if position != '': + biosampleIds.append(list_of_targets[int(position)]) + try: + finalids=[] + for bioid in biosampleIds: + finalids.append({"biosampleId": bioid}) + except Exception:# pragma: no cover + finalids=[] + query = {"$and": [{"$or": finalids}]} + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.RUNS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_analyses_of_variant(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'g_variants' + mongo_collection = client.beacon.analyses + query = {"$and": [{"variantInternalId": entry_id}]} + query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) + if parameters_as_filters == True: + query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset)# pragma: no cover + query_parameters={}# pragma: no cover + else: + query=query_parameters + collection='analyses' + HGVSIds = client.beacon.genomicVariations \ + .find(query, {"identifiers.genomicHGVSId": 1, "datasetId": 1, "_id": 0}) + HGVSDataset=HGVSIds[0]["datasetId"] + if dataset != HGVSDataset: + schema = DefaultSchemas.INDIVIDUALS + return schema, 0, 0, [], dataset + HGVSIds=list(HGVSIds) + HGVSId=HGVSIds[0]["identifiers"]["genomicHGVSId"] + queryHGVSId={"datasetId": dataset, "id": HGVSId} + string_of_ids = client.beacon.caseLevelData \ + .find(queryHGVSId, {"biosampleIds": 1, "_id": 0}) + targets = client.beacon.targets \ + .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) + targets=list(targets) + list_of_targets=targets[0]["biosampleIds"] + list_of_positions_strings= string_of_ids[0]['biosampleIds'].split(',') + biosampleIds=[] + for position in list_of_positions_strings: + if position != '': + biosampleIds.append(list_of_targets[int(position)]) + try: + finalids=[] + for bioid in biosampleIds: + finalids.append({"biosampleId": bioid}) + except Exception:# pragma: no cover + finalids=[] + query = {"$and": [{"$or": finalids}]} + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.ANALYSES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_individuals_of_variant(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'g_variants' + mongo_collection = client.beacon.individuals + query = {"$and": [{"variantInternalId": entry_id}]} + query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) + if parameters_as_filters == True: + query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset)# pragma: no cover + query_parameters={}# pragma: no cover + else: + query=query_parameters + collection='individuals' + HGVSIds = client.beacon.genomicVariations \ + .find(query, {"identifiers.genomicHGVSId": 1, "datasetId": 1, "_id": 0}) + HGVSIds=list(HGVSIds) + HGVSDataset=HGVSIds[0]["datasetId"] + if dataset != HGVSDataset: + schema = DefaultSchemas.INDIVIDUALS + return schema, 0, 0, [], dataset + HGVSId=HGVSIds[0]["identifiers"]["genomicHGVSId"] + queryHGVSId={"datasetId": HGVSDataset, "id": HGVSId} + string_of_ids = client.beacon.caseLevelData \ + .find(queryHGVSId, {"biosampleIds": 1, "_id": 0}) + targets = client.beacon.targets \ + .find({"datasetId": HGVSDataset}, {"biosampleIds": 1, "_id": 0}) + targets=list(targets) + list_of_targets=targets[0]["biosampleIds"] + list_of_positions_strings= string_of_ids[0]['biosampleIds'].split(',') + biosampleIds=[] + for position in list_of_positions_strings: + if position != '': + biosampleIds.append(list_of_targets[int(position)]) + try: + finalquery={} + finalquery["$or"]=[] + for finalid in biosampleIds: + query = {"id": finalid} + finalquery["$or"].append(query) + individual_id = client.beacon.biosamples \ + .find(finalquery, {"individualId": 1, "_id": 0}) + try: + finalids=[] + for indid in individual_id: + finalids.append(indid["individualId"]) + except Exception:# pragma: no cover + finalids=[] + if finalids==[]: + finalids=biosampleIds + except Exception: + finalids=biosampleIds + finalquery={} + finalquery["$or"]=[] + for finalid in finalids: + query = {"id": finalid} + finalquery["$or"].append(query) + superfinalquery={} + superfinalquery["$and"]=[finalquery] + query = apply_filters(self, superfinalquery, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.INDIVIDUALS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/get_descendants.py b/beacon/connections/omopcdm/get_descendants.py new file mode 100644 index 0000000..0385673 --- /dev/null +++ b/beacon/connections/omopcdm/get_descendants.py @@ -0,0 +1,178 @@ +import obonet +import networkx +import os +from typing import List, Dict, Optional +import urllib.request +from urllib.error import HTTPError +import progressbar +from pymongo.mongo_client import MongoClient +import os + + + +import conf + + +if conf.database_cluster: + uri = "mongodb+srv://{}:{}@{}/?tls=true&authMechanism=SCRAM-SHA-256&retrywrites=false&maxIdleTimeMS=120000".format( + conf.database_user, + conf.database_password, + conf.database_host + ) +else: + uri = "mongodb://{}:{}@{}:{}/{}?authSource={}".format( + conf.database_user, + conf.database_password, + conf.database_host, + conf.database_port, + conf.database_name, + conf.database_auth_source + ) + +if os.path.isfile(conf.database_certificate): + uri += '&tls=true&tlsCertificateKeyFile={}'.format(conf.database_certificate) + if os.path.isfile(conf.database_cafile): + uri += '&tlsCAFile={}'.format(conf.database_cafile) + +client = MongoClient(uri) + +class MyProgressBar: + def __init__(self): + self.pbar = None + + def __call__(self, block_num: int, block_size: int, total_size: int): + if not self.pbar: + self.pbar = progressbar.ProgressBar(maxval=total_size) + self.pbar.start() + + downloaded = block_num * block_size + if downloaded < total_size: + self.pbar.update(downloaded) + else: + self.pbar.finish() + +def load_ontology(ontology_id: str): + if ontology_id.isalpha(): + print(ontology_id) + url_alt = "https://www.ebi.ac.uk/efo/EFO.obo" + url = "http://purl.obolibrary.org/obo/{}.obo".format(ontology_id.lower()) + path = "/beacon/connections/mongo/ontologies/{}.obo".format(ontology_id) + try: + if not os.path.exists(path): + full_path = os.path.realpath(__file__) + print(full_path) + urllib.request.urlretrieve(url, path, MyProgressBar()) + except HTTPError: + # TODO: Handle error + #print("ERROR", HTTPError) + pass + except ValueError: + #print("ERROR", ValueError) + pass + except Exception: + pass + try: + #print (os.stat(path).st_size) + if os.stat(path).st_size == 0: + try: + urllib.request.urlretrieve(url_alt, path, MyProgressBar()) + except HTTPError: + # TODO: Handle error + #print("ERROR", HTTPError) + pass + except ValueError: + #print("ERROR", ValueError) + pass + except Exception: + pass + return '{}'.format(ontology_id) + + +def get_descendants_and_similarities(): + try: + client.beacon.drop_collection("similarities") + except Exception: + client.beacon.create_collection(name="similarities") + try: + client.beacon.validate_collection("similarities") + except Exception: + db=client.beacon.create_collection(name="similarities") + filtering_docs=client.beacon.filtering_terms.find({"type": "ontology"}) + array_of_ontologies=[] + for ft_doc in filtering_docs: + if ft_doc["id"] not in array_of_ontologies: + array_of_ontologies.append(ft_doc["id"]) + for ontology in array_of_ontologies: + ontology_list = ontology.split(':') + load_ontology(ontology_list[0]) + url = "/beacon/connections/mongo/ontologies/{}.obo".format(ontology_list[0].lower()) + list_of_cousins = [] + list_of_brothers = [] + list_of_uncles = [] + list_of_grandpas = [] + url_alt = "https://www.ebi.ac.uk/efo/EFO.obo" + try: + graph = obonet.read_obo(url) + except Exception: + graph = obonet.read_obo(url_alt) + try: + descendants = networkx.ancestors(graph, ontology) + except Exception: + descendants = '' + descendants=list(descendants) + + print(descendants) + + + try: + tree = [n for n in graph.successors(ontology)] + for onto in tree: + predecessors = [n for n in graph.successors(onto)] + successors = [n for n in graph.predecessors(onto)] + list_of_brothers.append(successors) + list_of_grandpas.append(predecessors) + similarity_high=[] + similarity_medium=[] + similarity_low=[] + for llista in list_of_grandpas: + for item in llista: + uncles = [n for n in graph.predecessors(item)] + list_of_uncles.append(uncles) + for uncle in uncles: + cousins = [n for n in graph.predecessors(uncle)] + if ontology not in cousins: + list_of_cousins.append(cousins) + + for llista in list_of_brothers: + for item in llista: + similarity_high.append(item) + similarity_medium.append(item) + similarity_low.append(item) + + for llista in list_of_cousins: + for item in llista: + similarity_medium.append(item) + similarity_low.append(item) + + for llista in list_of_uncles: + for item in llista: + similarity_low.append(item) + + except Exception: + similarity_high=[] + similarity_medium=[] + similarity_low=[] + + dict={} + dict['id']=ontology + dict['descendants']=descendants + dict['similarity_high']=similarity_high + dict['similarity_medium']=similarity_medium + dict['similarity_low']=similarity_low + + client.beacon.similarities.insert_one(dict) + print("succesfully retrieved descendants from {}".format(ontology)) + + +get_descendants_and_similarities() + diff --git a/beacon/connections/omopcdm/individuals.py b/beacon/connections/omopcdm/individuals.py new file mode 100644 index 0000000..cbeb923 --- /dev/null +++ b/beacon/connections/omopcdm/individuals.py @@ -0,0 +1,286 @@ +from beacon.request.parameters import RequestParams +from beacon.response.schemas import DefaultSchemas +from beacon.connections.omopcdm.__init__ import client +from beacon.connections.omopcdm.utils import queryExecutor, search_ontologies, get_docs_by_response_type, query_id +from beacon.logs.logs import log_with_args, LOG +from beacon.conf.conf import level +from beacon.connections.omopcdm.filters import apply_filters +from typing import Optional + +import beacon.connections.omopcdm.mappings as mappings + +import aiosql +from pathlib import Path +queries_file = Path(__file__).parent / "sql" / "individuals.sql" +individual_queries = aiosql.from_path(queries_file, "psycopg2") + + +def get_individual_id(offset=0, limit=10, person_id=None): + if person_id == None: + records = individual_queries.sql_get_individuals(client, offset=offset, limit=limit) + listId = [str(record[0]) for record in records] + else: + records = individual_queries.sql_get_individual_id(client, person_id=person_id) + listId = [str(records[0])] + return listId + +def get_individuals_person(listIds): + dict_person = {} + for person_id in listIds: + records = individual_queries.sql_get_person(client, person_id=person_id) + listValues = [] + for record in records: + listValues.append({"gender_concept_id" : record[0], + "race_concept_id" : record[1]}) + dict_person[person_id] = listValues + return dict_person + + +def get_individuals_condition(listIds): + dict_condition = {} + for person_id in listIds: + records = individual_queries.sql_get_condition(client, person_id=person_id) + listValues = [] + for record in records: + if record[1] == None: + ageOfOnset = "Not Available" + else: + ageOfOnset = f"P{record[1]}Y" + listValues.append({"condition_concept_id" : record[0], + "condition_ageOfOnset" : ageOfOnset}) + dict_condition[person_id] = listValues + + return dict_condition + +def get_individuals_procedure(listIds): + dict_procedure = {} + for person_id in listIds: + records = individual_queries.sql_get_procedure(client, person_id=person_id) + listValues = [] + for record in records: + if record[1] == "None": + ageOfOnset = "Not Available" + else: + ageOfOnset = f"P{record[1]}Y" + listValues.append({"procedure_concept_id" : record[0], + "procedure_ageOfOnset" : ageOfOnset, + "procedure_date" : record[2]}) + dict_procedure[person_id] = listValues + return dict_procedure + + +def get_individuals_measures(listIds): + dict_measures = {} + for person_id in listIds: + records = individual_queries.sql_get_measure(client, person_id=person_id) + listValues = [] + for record in records: + if record[1] == "None": + ageOfOnset = "Not Available" + else: + ageOfOnset = f"P{record[1]}Y" + listValues.append({"measurement_concept_id" : record[0], + "measurement_ageOfOnset" : ageOfOnset, + "measurement_date" : record[2], + "unit_concept_id" : record[3], + "value_source_value" : record[4]}) + dict_measures[person_id] = listValues + return dict_measures + + +def get_individuals_exposures(listIds): + dict_exposures = {} + for person_id in listIds: + records = individual_queries.sql_get_exposure(client, person_id=person_id) + records_duration = individual_queries.sql_get_exposure_period(client, person_id=person_id) + listValues = [] + for record in records: + if record[1] == "None": + ageOfOnset = "Not Available" + else: + ageOfOnset = f"P{record[1]}Y" + if records_duration: + records_duration = str(records_duration[0]) + else: + records_duration = "Not Available" + listValues.append({"observation_concept_id" : record[0], + "observation_ageOfOnset" : ageOfOnset, + "observation_date" : record[2], + "unit_concept_id" : record[3], + "duration": records_duration}) + dict_exposures[person_id] = listValues + return dict_exposures + +def get_individuals_treatments(listIds): + dict_treatments = {} + for person_id in listIds: + records = individual_queries.sql_get_treatment(client, person_id=person_id) + listValues = [] + for record in records: + if record[1] == "None": + ageOfOnset = "Not Available" + else: + ageOfOnset = f"P{record[1]}Y" + listValues.append({"drugExposure_concept_id" : record[0], + "drugExposure_ageOfOnset" : ageOfOnset}) + dict_treatments[person_id] = listValues + return dict_treatments + + +def format_query(listIds, dictPerson, dictCondition, dictProcedures, dictMeasures, dictExposures, dictTreatments): + list_format = [] + for person_id in listIds: + dictId = {"id":person_id} + if any("gender_concept_id" in d for d in dictPerson[person_id]): + dictId["sex"] = dictPerson[person_id][0]["gender_concept_id"] + if any("race_concept_id" in d for d in dictPerson[person_id]): + dictId["ethnicity"] = dictPerson[person_id][0]["race_concept_id"] + if any("condition_concept_id" in d for d in dictCondition[person_id]): + dictId["diseases"] = list(map(mappings.diseases_table_map, dictCondition[person_id])) + if any("procedure_concept_id" in d for d in dictProcedures[person_id]): + dictId["interventionsOrProcedures"] = list(map(mappings.procedures_table_map, dictProcedures[person_id])) + if any("measurement_concept_id" in d for d in dictMeasures[person_id]): + dictId["measures"] = list(map(mappings.measures_table_map, dictMeasures[person_id])) + if any("observation_concept_id" in d for d in dictExposures[person_id]): + dictId["exposures"] = list(map(mappings.exposures_table_map, dictExposures[person_id])) + if any("drugExposure_concept_id" in d for d in dictTreatments[person_id]): + dictId["treatments"] = list(map(mappings.treatments_table_map, dictTreatments[person_id])) + list_format.append(dictId) + return list_format + +@log_with_args(level) +def get_individuals(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + + include = qparams.query.include_resultset_responses # Always HIT responses + scope = "individuals" + schema = DefaultSchemas.INDIVIDUALS + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 50 or limit == 0: + limit = 50 + granularity = qparams.query.requested_granularity # record, count, boolean + + # If filters + if qparams.query.filters or "filters" in qparams.query.request_parameters: + query = apply_filters(self, + qparams.query.request_parameters, + qparams.query.filters, + scope, + granularity, + limit, + skip) + LOG.debug(f"Final query {query}") + # Run query + resultQuery = queryExecutor(query) + else: # Get All individuals + resultQuery = get_individual_with_id(entry_id, qparams, dataset) # List with all Ids + + # Different response depending the granularity + if granularity == "boolean": + if resultQuery: + return schema, 1, 1, {}, dataset + else: + return schema, 0, 0, {}, dataset + elif granularity == "count": + return schema, resultQuery[0][0], resultQuery[0][0], {}, dataset + # Record response + count = resultQuery[0][1] + listIds = [str(record[0]) for record in resultQuery] + LOG.debug(f"count {count}") + LOG.debug(f"listIds {listIds}") + + dictPerson = get_individuals_person(listIds) # List with Id, sex, ethnicity + dictCondition = get_individuals_condition(listIds) # List with al the diseases per Id + dictProcedures = get_individuals_procedure(listIds) + dictMeasures = get_individuals_measures(listIds) + dictExposures = get_individuals_exposures(listIds) + dictTreatments = get_individuals_treatments(listIds) + + dictPerson = search_ontologies(dictPerson) + dictCondition = search_ontologies(dictCondition) + dictProcedures = search_ontologies(dictProcedures) + dictMeasures = search_ontologies(dictMeasures) + dictExposures = search_ontologies(dictExposures) + dictTreatments = search_ontologies(dictTreatments) + + docs = format_query(listIds, dictPerson, dictCondition, dictProcedures, dictMeasures, dictExposures, dictTreatments) + + return schema, count, count, docs, dataset + +@log_with_args(level) +def get_individual_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'individuals' + idq="id" + mongo_collection = client.beacon.individuals + query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + schema = DefaultSchemas.INDIVIDUALS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_variants_of_individual(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'g_variants' + targets = client.beacon.targets \ + .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) + position=0 + bioids=targets[0]["biosampleIds"] + for bioid in bioids: + if bioid == entry_id: + break + position+=1 + position=str(position) + position1="^"+position+"," + position2=","+position+"," + position3=","+position+"$" + query_cl={ "$or": [ + {"biosampleIds": {"$regex": position1}}, + {"biosampleIds": {"$regex": position2}}, + {"biosampleIds": {"$regex": position3}} + ]} + string_of_ids = client.beacon.caseLevelData \ + .find(query_cl, {"id": 1, "_id": 0}) + HGVSIds=list(string_of_ids) + query={} + queryHGVS={} + listHGVS=[] + for HGVSId in HGVSIds: + justid=HGVSId["id"] + listHGVS.append(justid) + queryHGVS["$in"]=listHGVS + query["identifiers.genomicHGVSId"]=queryHGVS + mongo_collection = client.beacon.genomicVariations + query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.GENOMICVARIATIONS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="caseLevelData.biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_biosamples_of_individual(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'biosamples' + mongo_collection = client.beacon.biosamples + query = {"individualId": entry_id} + query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.BIOSAMPLES + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="id" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/mappings.py b/beacon/connections/omopcdm/mappings.py new file mode 100644 index 0000000..6bae5ec --- /dev/null +++ b/beacon/connections/omopcdm/mappings.py @@ -0,0 +1,76 @@ + +# File for all the mappings from the Beacon v2 specification and the results of the SQL Queries + +############################### Individual model #################################### + +def diseases_table_map(dictValues): + return { + 'diseaseCode': dictValues["condition_concept_id"], + 'ageOfOnset': {'iso8601duration': dictValues["condition_ageOfOnset"]}, + } + +def procedures_table_map(dictValues): + return { + 'procedureCode': dictValues["procedure_concept_id"], + 'ageAtProcedure': {'iso8601duration': dictValues["procedure_ageOfOnset"]}, + 'dateOfProcedure': dictValues["procedure_date"], + } + +def isfloat(num): + try: + float(num) + return True + except ValueError: + return False + +def convertToNum(num): + try: + float(num) + return float(num) + except ValueError: + pass + + + + +def measures_table_map(dictValues): + # TO DO + # Make the return complex so depend on the type of data. It can be a unit/value, an ontology, referenceRange, complexValue, etc. + + measures_dict ={ + 'assayCode': dictValues["measurement_concept_id"], + 'date' : dictValues["measurement_date"], + 'observationMoment': {'iso8601duration':dictValues["measurement_ageOfOnset"]} + } + if dictValues["value_source_value"] is None: # Return null Ontology term + measure_value_dict = {'measurementValue': dictValues["unit_concept_id"]} + else: + if isfloat(str(dictValues["value_source_value"])): # If numeric value + measure_value_dict = { + 'measurementValue': { + 'unit': dictValues["unit_concept_id"], + 'value': convertToNum(dictValues["value_source_value"]) + } + } + else: + measure_value_dict = {'measurementValue': { + 'id': 'None:None', + 'label': dictValues["value_source_value"] + }} + + return {**measures_dict, **measure_value_dict} + +def exposures_table_map(dictValues): + return { + 'exposureCode': dictValues["observation_concept_id"], + 'ageAtExposure': {'iso8601duration': dictValues["observation_ageOfOnset"]}, + 'date': dictValues["observation_date"], + 'unit': dictValues["unit_concept_id"], + 'duration':dictValues["duration"] + } + +def treatments_table_map(dictValues): + return { + 'treatmentCode': dictValues["drugExposure_concept_id"], + 'ageOfOnset': {'iso8601duration': dictValues["drugExposure_ageOfOnset"]}, + } \ No newline at end of file diff --git a/beacon/connections/omopcdm/mongo-init/init.js b/beacon/connections/omopcdm/mongo-init/init.js new file mode 100644 index 0000000..a4112e9 --- /dev/null +++ b/beacon/connections/omopcdm/mongo-init/init.js @@ -0,0 +1,27 @@ +conn = new Mongo({ useUnifiedTopology: true }); +db = conn.getDB("beacon"); + + +// db.beacon.createIndex({ "address.zip": 1 }, { unique: false }); +// db.beacon.insert({ "address": { "city": "Paris", "zip": "123" }, "name": "Mike", "phone": "1234" }); +// db.beacon.insert({ "address": { "city": "Marsel", "zip": "321" }, "name": "Helga", "phone": "4321" }); + +// Create collections + +db.createCollection("analyses"); +db.createCollection("biosamples"); +db.createCollection("cohorts"); +db.createCollection("datasets"); +db.createCollection("genomicVariations"); +db.createCollection("individuals"); +db.createCollection("runs"); + +// Create indexes for all the entities in the database + +db.analyses.createIndex([('$**', 'text')]); +db.biosamples.createIndex([('$**', 'text')]); +db.cohorts.createIndex([('$**', 'text')]); +db.datasets.createIndex([('$**', 'text')]); +db.genomicVariations.createIndex([('$**', 'text')]); +db.individuals.createIndex([('$**', 'text')]); +db.runs.createIndex([('$**', 'text')]); diff --git a/beacon/connections/omopcdm/ontologies/example.txt b/beacon/connections/omopcdm/ontologies/example.txt new file mode 100644 index 0000000..e69de29 diff --git a/beacon/connections/omopcdm/ping.py b/beacon/connections/omopcdm/ping.py new file mode 100644 index 0000000..2a4ee63 --- /dev/null +++ b/beacon/connections/omopcdm/ping.py @@ -0,0 +1,33 @@ +from pymongo.mongo_client import MongoClient +from pymongo.errors import ConnectionFailure +import conf +import os +from beacon.logs.logs import LOG + + +if conf.database_cluster: + uri = "mongodb+srv://{}:{}@{}/?tls=true&authMechanism=SCRAM-SHA-256&retrywrites=false&maxIdleTimeMS=120000".format( + conf.database_user, + conf.database_password, + conf.database_host + ) +else: + uri = "mongodb://{}:{}@{}:{}/{}?authSource={}".format( + conf.database_user, + conf.database_password, + conf.database_host, + conf.database_port, + conf.database_name, + conf.database_auth_source + ) + +if os.path.isfile(conf.database_certificate): + uri += '&tls=true&tlsCertificateKeyFile={}'.format(conf.database_certificate) + if os.path.isfile(conf.database_cafile): + uri += '&tlsCAFile={}'.format(conf.database_cafile) + +client = MongoClient(uri, serverSelectionTimeoutMS=30000) +try: + client.admin.command('ping') +except ConnectionFailure as err: + LOG.debug(f"Database error encountered: {err}") \ No newline at end of file diff --git a/beacon/connections/omopcdm/reindex.py b/beacon/connections/omopcdm/reindex.py new file mode 100644 index 0000000..4100094 --- /dev/null +++ b/beacon/connections/omopcdm/reindex.py @@ -0,0 +1,79 @@ +from pymongo.mongo_client import MongoClient +import conf +import os + + +if conf.database_cluster: + uri = "mongodb+srv://{}:{}@{}/?tls=true&authMechanism=SCRAM-SHA-256&retrywrites=false&maxIdleTimeMS=120000".format( + conf.database_user, + conf.database_password, + conf.database_host + ) +else: + uri = "mongodb://{}:{}@{}:{}/{}?authSource={}".format( + conf.database_user, + conf.database_password, + conf.database_host, + conf.database_port, + conf.database_name, + conf.database_auth_source + ) + +if os.path.isfile(conf.database_certificate): + uri += '&tls=true&tlsCertificateKeyFile={}'.format(conf.database_certificate) + if os.path.isfile(conf.database_cafile): + uri += '&tlsCAFile={}'.format(conf.database_cafile) + +client = MongoClient(uri) +try: + client.beacon.drop_collection("synonyms") +except Exception: + client.beacon.create_collection(name="synonyms") +try: + client.beacon.validate_collection("synonyms") +except Exception: + db=client.beacon.create_collection(name="synonyms") +try: + client.beacon.validate_collection("targets") +except Exception: + db=client.beacon.create_collection(name="targets") +try: + client.beacon.validate_collection("caseLevelData") +except Exception: + db=client.beacon.create_collection(name="caseLevelData") +try: + client.beacon.drop_collection("counts") +except Exception: + client.beacon.create_collection(name="counts") +try: + client.beacon.validate_collection("counts") +except Exception: + db=client.beacon.create_collection(name="counts") +try: + client.beacon.drop_collection("similarities") +except Exception: + client.beacon.create_collection(name="similarities") +try: + client.beacon.validate_collection("similarities") +except Exception: + db=client.beacon.create_collection(name="similarities") +#client.beacon.analyses.create_index([("$**", "text")]) +#client.beacon.biosamples.create_index([("$**", "text")]) +#client.beacon.cohorts.create_index([("$**", "text")]) +#client.beacon.datasets.create_index([("$**", "text")]) +#client.beacon.genomicVariations.create_index([("$**", "text")]) +#client.beacon.genomicVariations.create_index([("caseLevelData.biosampleId", 1)]) +#client.beacon.genomicVariations.create_index([("variation.location.interval.end.value", -1), ("variation.location.interval.start.value", 1)]) +client.beacon.genomicVariations.create_index([("datasetId", 1)]) +client.beacon.genomicVariations.create_index([("variantInternalId", 1)]) +client.beacon.genomicVariations.create_index([("variation.location.interval.start.value", 1)]) +#client.beacon.genomicVariations.create_index([("variation.location.interval.start.value", 1), ("variation.location.interval.end.value", -1)]) +client.beacon.genomicVariations.create_index([("identifiers.genomicHGVSId", 1)]) +#client.beacon.genomicVariations.create_index([("datasetId", 1), ("variation.location.interval.start.value", 1), ("variation.referenceBases", 1), ("variation.alternateBases", 1)]) +client.beacon.genomicVariations.create_index([("molecularAttributes.geneIds", 1), ("variation.variantType", 1)]) +client.beacon.caseLevelData.create_index([("id", 1), ("datasetId", 1)]) +#client.beacon.individuals.create_index([("$**", "text")]) +#client.beacon.runs.create_index([("$**", "text")]) +#collection_name = client.beacon.analyses +#print(collection_name.index_information()) + diff --git a/beacon/connections/omopcdm/runs.py b/beacon/connections/omopcdm/runs.py new file mode 100644 index 0000000..14151b9 --- /dev/null +++ b/beacon/connections/omopcdm/runs.py @@ -0,0 +1,111 @@ +from beacon.request.parameters import RequestParams +from beacon.response.schemas import DefaultSchemas +import yaml +from beacon.connections.mongo.__init__ import client +from beacon.connections.mongo.utils import get_docs_by_response_type, query_id +from beacon.logs.logs import log_with_args, LOG +from beacon.conf.conf import level +from beacon.connections.mongo.filters import apply_filters +from beacon.connections.mongo.request_parameters import apply_request_parameters +from typing import Optional + +@log_with_args(level) +def get_runs(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'runs' + mongo_collection = client.beacon.runs + parameters_as_filters=False + query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) + if parameters_as_filters == True: + query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset)# pragma: no cover + query_parameters={}# pragma: no cover + else: + query={} + query = apply_filters(self, query, qparams.query.filters, collection, query_parameters, dataset) + schema = DefaultSchemas.RUNS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100 + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_run_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'runs' + mongo_collection = client.beacon.runs + query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) + query = query_id(self, query, entry_id) + schema = DefaultSchemas.RUNS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_variants_of_run(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'runs' + mongo_collection = client.beacon.genomicVariations + query = {"$and": [{"id": entry_id}]} + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + run_ids = client.beacon.runs \ + .find_one(query, {"biosampleId": 1, "_id": 0}) + targets = client.beacon.targets \ + .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) + position=0 + bioids=targets[0]["biosampleIds"] + for bioid in bioids: + if bioid == run_ids["biosampleId"]: + break + position+=1 + position=str(position) + position1="^"+position+"," + position2=","+position+"," + position3=","+position+"$" + query_cl={ "$or": [ + {"biosampleIds": {"$regex": position1}}, + {"biosampleIds": {"$regex": position2}}, + {"biosampleIds": {"$regex": position3}} + ]} + string_of_ids = client.beacon.caseLevelData \ + .find(query_cl, {"id": 1, "_id": 0}) + HGVSIds=list(string_of_ids) + query={} + queryHGVS={} + listHGVS=[] + for HGVSId in HGVSIds: + justid=HGVSId["id"] + listHGVS.append(justid) + queryHGVS["$in"]=listHGVS + query["identifiers.genomicHGVSId"]=queryHGVS + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.GENOMICVARIATIONS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="caseLevelData.biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset + +@log_with_args(level) +def get_analyses_of_run(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): + collection = 'runs' + mongo_collection = client.beacon.analyses + query = {"runId": entry_id} + query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.RUNS + include = qparams.query.include_resultset_responses + limit = qparams.query.pagination.limit + skip = qparams.query.pagination.skip + if limit > 100 or limit == 0: + limit = 100# pragma: no cover + idq="biosampleId" + count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) + return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/sql/basic_queries.sql b/beacon/connections/omopcdm/sql/basic_queries.sql new file mode 100644 index 0000000..3cc3910 --- /dev/null +++ b/beacon/connections/omopcdm/sql/basic_queries.sql @@ -0,0 +1,19 @@ + +-- name: sql_get_descendants +-- Get descendants from concept_id +SELECT descendant_concept_id +FROM vocabularies.concept_ancestor +WHERE ancestor_concept_id = :concept_id + +-- name: sql_get_concept_domain +-- Get OMOP concept_id and domain of the concept +SELECT concept_id, domain_id +FROM vocabularies.concept +WHERE vocabulary_id = :vocabulary_id and concept_code = :concept_code + +-- name: sql_get_ontology^ +-- Get ontology +SELECT concept_name as label, + vocabulary_id || ':' || concept_code as id +FROM vocabularies.concept +WHERE concept_id = :concept_id \ No newline at end of file diff --git a/beacon/connections/omopcdm/sql/individuals.sql b/beacon/connections/omopcdm/sql/individuals.sql new file mode 100644 index 0000000..9b0a45f --- /dev/null +++ b/beacon/connections/omopcdm/sql/individuals.sql @@ -0,0 +1,151 @@ + +-- name: sql_get_individuals +-- Get individuals +SELECT person_id +FROM cdm.person +LIMIT :limit +OFFSET :offset + +-- name: cohort_individuals +-- Get individuals +SELECT subject_id as person_id +FROM cdm.cohort +where cohort_definition_id = :cohort_id +LIMIT :limit +OFFSET :offset + +-- name: count_cohort_individuals$ +-- Get individuals count +SELECT count(*) +FROM cdm.cohort +where cohort_definition_id = :cohort_id + +-- name: count_individuals$ +-- Get individuals count +SELECT count(*) +FROM cdm.person + +-- name: sql_get_individual_id^ +-- Get individual by id +SELECT DISTINCT person_id +FROM cdm.person +WHERE person_id = :person_id + +-- name: sql_get_person +-- Get gender and race by id +SELECT gender_concept_id, race_concept_id +FROM cdm.person +WHERE person_id = :person_id + +-- name: sql_get_condition +-- Get condition properties by id +SELECT condition_concept_id, + CASE + WHEN birth_datetime IS NOT NULL THEN extract(Year from age(condition_start_date, birth_datetime)) + ELSE extract(Year from condition_start_date) - year_of_birth + END AS condition_ageOfOnset +FROM cdm.person as p, + cdm.condition_occurrence as c +WHERE p.person_id = :person_id and p.person_id = c.person_id; + +-- name: sql_get_procedure +-- Get procedure properties by id +SELECT procedure_concept_id, + CASE + WHEN birth_datetime IS NOT NULL THEN extract(Year from age(procedure_date, birth_datetime)) + ELSE extract(Year from procedure_date) - year_of_birth + END AS procedure_ageOfOnset, + to_char(procedure_date, 'YYYY-MM-DD') +FROM cdm.person as p, + cdm.procedure_occurrence as c +WHERE p.person_id = :person_id and p.person_id=c.person_id + +-- name: sql_get_measure +-- Get measure properties by id +Select measurement_concept_id, + CASE + WHEN birth_datetime IS NOT NULL THEN extract(Year from age(measurement_date, birth_datetime)) + ELSE extract(Year from measurement_date) - year_of_birth + END AS measurement_ageOfOnset, + to_char(measurement_date, 'YYYY-MM-DD'), + unit_concept_id, + value_source_value +FROM cdm.person as p, + cdm.measurement c +WHERE p.person_id = :person_id and p.person_id=c.person_id + +-- name: sql_get_exposure +-- Get exposure properties by id +Select observation_concept_id, + CASE + WHEN birth_datetime IS NOT NULL THEN extract(Year from age(observation_date, birth_datetime)) + ELSE extract(Year from observation_date) - year_of_birth + END AS observation_ageOfOnset, + to_char(observation_date, 'YYYY-MM-DD'), + unit_concept_id +FROM cdm.person as p, + cdm.observation c +WHERE p.person_id = :person_id and p.person_id=c.person_id + +-- name: sql_get_exposure_period^ +-- Get exposure duration by id +SELECT + concat( + 'P', + extract(years from age(observation_period_end_date, observation_period_start_date)), + 'Y', + extract(months from age(observation_period_end_date, observation_period_start_date)), + 'M', + extract(days from age(observation_period_end_date, observation_period_start_date)), + 'D' + ) as duration +FROM cdm.observation_period c +WHERE c.person_id = :person_id + +-- name: sql_get_treatment +-- Get treatment properties by id +SELECT drug_concept_id, + CASE + WHEN birth_datetime IS NOT NULL THEN extract(Year from age(drug_exposure_start_date, birth_datetime)) + ELSE extract(Year from drug_exposure_start_date) - year_of_birth + END AS drug_exposure_ageOfOnset +FROM cdm.person as p, + cdm.drug_exposure as c +WHERE p.person_id = :person_id and p.person_id = c.person_id; + +-- name: sql_filtering_terms_race_gender +-- Get all the race and gender filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.person as p on p.race_concept_id=c.concept_id or p.gender_concept_id=c.concept_id + +-- name: sql_filtering_terms_condition +-- Get all the condition_occurrence filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.condition_occurrence as con on con.condition_concept_id=c.concept_id + +-- name: sql_filtering_terms_measurement +-- Get all the measurement filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.measurement as con on con.measurement_concept_id=c.concept_id + +-- name: sql_filtering_terms_procedure +-- Get all the procedure_occurrence filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.procedure_occurrence as con on con.procedure_concept_id=c.concept_id + +-- name: sql_filtering_terms_observation +-- Get all the observation filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.observation as con on con.observation_concept_id=c.concept_id + +-- name: sql_filtering_terms_drug_exposure +-- Get all the drug exposure filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.drug_exposure as con on con.drug_concept_id=c.concept_id + diff --git a/beacon/connections/omopcdm/utils.py b/beacon/connections/omopcdm/utils.py new file mode 100644 index 0000000..fed3ccb --- /dev/null +++ b/beacon/connections/omopcdm/utils.py @@ -0,0 +1,207 @@ +from pymongo.cursor import Cursor +from beacon.connections.omopcdm.__init__ import client +from pymongo.collection import Collection +from beacon.logs.logs import log_with_args_mongo, LOG +from beacon.conf.conf import level +from bson import json_util + +import itertools + +import aiosql +from pathlib import Path +queries_file = Path(__file__).parent / "sql" / "basic_queries.sql" +basic_queries = aiosql.from_path(queries_file, "psycopg2") + +# Function to know if generator is empty +def peek(iterable): + try: + first = next(iterable) + except StopIteration: + return None + return first, itertools.chain([first], iterable) + +# Query executor +def queryExecutor(query): + cur = client.cursor() + cur.execute(query) + records = cur.fetchall() + return records + +def search_ontology(concept_id): + records = basic_queries.sql_get_ontology(client, concept_id=concept_id) + return records + + +def search_ontologies(dictValues): + for person_id, listVariableValues in dictValues.items(): # For each id + for dictVariableValue in listVariableValues: # For each object of the list + for variable, value in dictVariableValue.items(): + # If id in variable, extract the label and OntologyId + if "concept_id" in variable: + if value == 0: + dictVariableValue[variable] = {'id':"None:No matching concept", 'label':"No matching concept"} + continue + records = search_ontology(value) + if records: + label = records[0] + id = records[1] + else: + label = "No matching concept" + id = "None:No matching concept" + dictVariableValue[variable] = {'id':id, 'label':label} + return dictValues + +@log_with_args_mongo(level) +def get_cross_query(self, ids: dict, cross_type: str, collection_id: str): + id_list=[] + dict_in={} + id_dict={} + if cross_type == 'biosampleId' or cross_type=='id':# pragma: no cover + list_item=ids + id_list.append(str(list_item)) + dict_in["$in"]=id_list + id_dict[collection_id]=dict_in + query = id_dict + elif cross_type == 'individualIds' or cross_type=='biosampleIds': + list_individualIds=ids + dict_in["$in"]=list_individualIds + id_dict[collection_id]=dict_in + query = id_dict + else:# pragma: no cover + for k, v in ids.items(): + for item in v: + id_list.append(item[cross_type]) + dict_in["$in"]=id_list + id_dict[collection_id]=dict_in + query = id_dict + + return query + +@log_with_args_mongo(level) +def query_id(self, query: dict, document_id) -> dict: + query["id"] = document_id + return query + +@log_with_args_mongo(level) +def join_query(self, collection: Collection,query: dict, original_id): + #LOG.debug(query) + excluding_fields={"_id": 0, original_id: 1} + return collection.find(query, excluding_fields).max_time_ms(100 * 1000) + +@log_with_args_mongo(level) +def get_documents(self, collection: Collection, query: dict, skip: int, limit: int) -> Cursor: + return collection.find(query,{"_id": 0, "datasetId": 0}).skip(skip).limit(limit).max_time_ms(100 * 1000) + +@log_with_args_mongo(level) +def get_documents_for_cohorts(self, collection: Collection, query: dict, skip: int, limit: int) -> Cursor: + return collection.find(query,{"_id": 0}).skip(skip).limit(limit).max_time_ms(100 * 1000) + +@log_with_args_mongo(level) +def get_count(self, collection: Collection, query: dict) -> int: + if not query: + return collection.estimated_document_count() + else: + counts=client.beacon.counts.find({"id": str(query), "collection": str(collection)}) + try: + counts=list(counts) + if counts == []: + total_counts=collection.count_documents(query) + insert_dict={} + insert_dict['id']=str(query) + insert_dict['num_results']=total_counts# pragma: no cover + insert_dict['collection']=str(collection)# pragma: no cover + insert_total=client.beacon.counts.insert_one(insert_dict)# pragma: no cover + else: + total_counts=counts[0]["num_results"] + except Exception as e:# pragma: no cover + LOG.debug(e) + insert_dict={} + insert_dict['id']=str(query) + total_counts=0 + insert_dict['num_results']=total_counts# pragma: no cover + insert_dict['collection']=str(collection)# pragma: no cover + insert_total=client.beacon.counts.insert_one(insert_dict) + return total_counts + +@log_with_args_mongo(level) +def get_docs_by_response_type(self, include: str, query: dict, dataset: str, limit: int, skip: int, mongo_collection, idq: str): + if include == 'NONE': + count = get_count(self, mongo_collection, query) + dataset_count=0 + docs = get_documents( + self, + mongo_collection, + query, + skip*limit, + limit + ) + elif include == 'ALL': + count=0 + query_count=query + i=1 + query_count["$or"]=[] + queryid={} + queryid['datasetId']=dataset + query_count["$or"].append(queryid) + if query_count["$or"]!=[]: + dataset_count = get_count(self, mongo_collection, query_count) + docs = get_documents( + self, + mongo_collection, + query_count, + skip*limit, + limit + ) + docs=list(docs) + elif include == 'HIT': + count=0 + query_count=query + query_count["$or"]=[] + queryid={} + queryid['datasetId']=dataset + query_count["$or"].append(queryid) + if query_count["$or"]!=[]: + dataset_count = get_count(self, mongo_collection, query_count) + if dataset_count == 0: + docs = [] + else: + docs = get_documents( + self, + mongo_collection, + query_count, + skip*limit, + limit + ) + docs=list(docs) + else: + dataset_count=0# pragma: no cover + if dataset_count==0: + return count, -1, None + elif include == 'MISS': + count=0 + query_count=query + i=1 + query_count["$or"]=[] + queryid={} + queryid['datasetId']=dataset + query_count["$or"].append(queryid) + if query_count["$or"]!=[]: + dataset_count = get_count(self, mongo_collection, query_count) + docs = get_documents( + self, + mongo_collection, + query_count, + skip*limit, + limit + ) + docs=list(docs) + else: + dataset_count=0# pragma: no cover + if dataset_count !=0: + return count, -1, None + return count, dataset_count, docs + +@log_with_args_mongo(level) +def get_filtering_documents(self, collection: Collection, query: dict, remove_id: dict,skip: int, limit: int) -> Cursor: + ##LOG.debug("FINAL QUERY: {}".format(query)) + return collection.find(query,remove_id).skip(skip).limit(limit).max_time_ms(100 * 1000) \ No newline at end of file From a7e46fafb655e0c1937347cb9f46c15d762c8523 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 11:18:10 +0100 Subject: [PATCH 04/20] Fix typo --- beacon/connections/omopcdm/mappings.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/beacon/connections/omopcdm/mappings.py b/beacon/connections/omopcdm/mappings.py index 6bae5ec..57a44fd 100644 --- a/beacon/connections/omopcdm/mappings.py +++ b/beacon/connections/omopcdm/mappings.py @@ -1,7 +1,7 @@ # File for all the mappings from the Beacon v2 specification and the results of the SQL Queries -############################### Individual model #################################### +## Individual model ## def diseases_table_map(dictValues): return { From 8ed686f3ef2a7cc1265911e309300760603f0e6a Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 11:20:15 +0100 Subject: [PATCH 05/20] Add if statement to unfound ontologies --- beacon/connections/omopcdm/filters.py | 13 ++++++------- 1 file changed, 6 insertions(+), 7 deletions(-) diff --git a/beacon/connections/omopcdm/filters.py b/beacon/connections/omopcdm/filters.py index e6ae138..b913436 100644 --- a/beacon/connections/omopcdm/filters.py +++ b/beacon/connections/omopcdm/filters.py @@ -76,10 +76,10 @@ def apply_filters(self, filtersGet: dict, filtersPost: List[dict], scope: str, g """ else: # Record response finalQuery = f""" - SELECT {column}, - ( SELECT COUNT(*) + SELECT ( SELECT COUNT(*) FROM cdm.{table} p - WHERE true {query}) AS totalCount + WHERE true {query}) AS totalCount, + {column} FROM cdm.{table} p WHERE true {query} limit {limit} @@ -192,8 +192,6 @@ def apply_alphanumeric_filter(self, filter: AlphanumericFilter) -> str: 'ageAtExposure': ['observation', 'observation_date'], 'ageAtTreatment': ['drug_exposure', 'drug_exposure_start_date'] } - LOG.debug(f"scope {scope}") - LOG.debug(f"mappingDict[filter.id][0] {mappingDict[filter.id][0]}") # Create filter query = f""" @@ -211,7 +209,6 @@ def apply_alphanumeric_filter(self, filter: AlphanumericFilter) -> str: # Other alphanumeric filters with integers else: conceptId, tableMap = filter_to_OMOP_vocabulary(self, filter) - LOG.debug(tableMap) query = f""" and exists ( select 1 @@ -227,7 +224,9 @@ def apply_alphanumeric_filter(self, filter: AlphanumericFilter) -> str: @log_with_args(level) def apply_ontology_filter(self, filter: OntologyFilter, scope: str) -> str: setConceptId, tableMap = filter_to_OMOP_vocabulary(self, filter) - LOG.debug(tableMap) + + if tableMap == 0: + return "and False" listConceptId = [] for conceptId in setConceptId: listConceptId.append(tableMap[1] + ' = ' + str(conceptId)) From 047db176977cba499b205b832327183ab547fb44 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 11:20:56 +0100 Subject: [PATCH 06/20] Remove commentaries --- beacon/connections/omopcdm/__init__.py | 13 +------------ 1 file changed, 1 insertion(+), 12 deletions(-) diff --git a/beacon/connections/omopcdm/__init__.py b/beacon/connections/omopcdm/__init__.py index 535def0..f22caed 100644 --- a/beacon/connections/omopcdm/__init__.py +++ b/beacon/connections/omopcdm/__init__.py @@ -4,7 +4,6 @@ from beacon.logs.logs import log_with_args, LOG -# db_url = os.getenv('POSTGRES_URL', default="postgresql://pgadmin:admin@localhost:5432/omopdb") uri = "postgresql://{}:{}@{}:{}/{}".format( conf.database_user, conf.database_password, @@ -12,15 +11,5 @@ conf.database_port, # Ex: 5432 conf.database_name, ) -# LOG.debug(f"URI {uri}") -client = psycopg2.connect(uri) - -# CDM_SCHEMA='cdm' -# VOCABULARIES_SCHEMA='vocabularies' -# query = "select * from cdm.person limit 10" -# cur = client.cursor() -# cur.execute(query) -# records = cur.fetchall() -# listOfList = [str(record[0]) for record in records] -# LOG.debug(f"list of lissssssttttttt {listOfList}") +client = psycopg2.connect(uri) \ No newline at end of file From 4bf510b643092df82f60134482fa3bfa896c1eab Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 11:21:48 +0100 Subject: [PATCH 07/20] Formatting and adding individual by id --- beacon/connections/omopcdm/individuals.py | 160 +++++++++------------- 1 file changed, 61 insertions(+), 99 deletions(-) diff --git a/beacon/connections/omopcdm/individuals.py b/beacon/connections/omopcdm/individuals.py index cbeb923..b8755d1 100644 --- a/beacon/connections/omopcdm/individuals.py +++ b/beacon/connections/omopcdm/individuals.py @@ -15,16 +15,20 @@ individual_queries = aiosql.from_path(queries_file, "psycopg2") -def get_individual_id(offset=0, limit=10, person_id=None): +def get_individual_info(offset: int=0, limit: int=10, person_id: str=None) -> list: if person_id == None: records = individual_queries.sql_get_individuals(client, offset=offset, limit=limit) + if not records: + return [] listId = [str(record[0]) for record in records] else: records = individual_queries.sql_get_individual_id(client, person_id=person_id) + if not records: + return [] listId = [str(records[0])] return listId -def get_individuals_person(listIds): +def get_individuals_person(listIds: list) -> dict: dict_person = {} for person_id in listIds: records = individual_queries.sql_get_person(client, person_id=person_id) @@ -36,7 +40,7 @@ def get_individuals_person(listIds): return dict_person -def get_individuals_condition(listIds): +def get_individuals_condition(listIds: list) -> dict: dict_condition = {} for person_id in listIds: records = individual_queries.sql_get_condition(client, person_id=person_id) @@ -52,7 +56,7 @@ def get_individuals_condition(listIds): return dict_condition -def get_individuals_procedure(listIds): +def get_individuals_procedure(listIds: list) -> dict: dict_procedure = {} for person_id in listIds: records = individual_queries.sql_get_procedure(client, person_id=person_id) @@ -69,7 +73,7 @@ def get_individuals_procedure(listIds): return dict_procedure -def get_individuals_measures(listIds): +def get_individuals_measures(listIds: list) -> dict: dict_measures = {} for person_id in listIds: records = individual_queries.sql_get_measure(client, person_id=person_id) @@ -88,7 +92,7 @@ def get_individuals_measures(listIds): return dict_measures -def get_individuals_exposures(listIds): +def get_individuals_exposures(listIds: list) -> dict: dict_exposures = {} for person_id in listIds: records = individual_queries.sql_get_exposure(client, person_id=person_id) @@ -111,7 +115,7 @@ def get_individuals_exposures(listIds): dict_exposures[person_id] = listValues return dict_exposures -def get_individuals_treatments(listIds): +def get_individuals_treatments(listIds: list) -> dict: dict_treatments = {} for person_id in listIds: records = individual_queries.sql_get_treatment(client, person_id=person_id) @@ -127,7 +131,7 @@ def get_individuals_treatments(listIds): return dict_treatments -def format_query(listIds, dictPerson, dictCondition, dictProcedures, dictMeasures, dictExposures, dictTreatments): +def format_query(listIds: list, dictPerson: dict, dictCondition: dict, dictProcedures: dict, dictMeasures: dict, dictExposures: dict, dictTreatments: dict)-> list: list_format = [] for person_id in listIds: dictId = {"id":person_id} @@ -148,6 +152,25 @@ def format_query(listIds, dictPerson, dictCondition, dictProcedures, dictMeasure list_format.append(dictId) return list_format +def retrieveRecords(listIds: list) -> list: + dictPerson = get_individuals_person(listIds) # List with Id, sex, ethnicity + dictCondition = get_individuals_condition(listIds) # List with al the diseases per Id + dictProcedures = get_individuals_procedure(listIds) + dictMeasures = get_individuals_measures(listIds) + dictExposures = get_individuals_exposures(listIds) + dictTreatments = get_individuals_treatments(listIds) + + dictPerson = search_ontologies(dictPerson) + dictCondition = search_ontologies(dictCondition) + dictProcedures = search_ontologies(dictProcedures) + dictMeasures = search_ontologies(dictMeasures) + dictExposures = search_ontologies(dictExposures) + dictTreatments = search_ontologies(dictTreatments) + + docs = format_query(listIds, dictPerson, dictCondition, dictProcedures, dictMeasures, dictExposures, dictTreatments) + + return docs + @log_with_args(level) def get_individuals(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): @@ -169,118 +192,57 @@ def get_individuals(self, entry_id: Optional[str], qparams: RequestParams, datas granularity, limit, skip) - LOG.debug(f"Final query {query}") # Run query resultQuery = queryExecutor(query) else: # Get All individuals - resultQuery = get_individual_with_id(entry_id, qparams, dataset) # List with all Ids + listIds = get_individual_info(skip, limit, entry_id) # List with all Ids + countIds = individual_queries.count_individuals(client) # Count individuals + if countIds ==0: + resultQuery = [] + else: + resultQuery = [(countIds, listId) for listId in listIds ] + LOG.debug(f"Final query {resultQuery}") + if not resultQuery: + return schema, 0, 0, {}, dataset # Different response depending the granularity if granularity == "boolean": - if resultQuery: - return schema, 1, 1, {}, dataset - else: - return schema, 0, 0, {}, dataset + return schema, 1, 1, {}, dataset elif granularity == "count": return schema, resultQuery[0][0], resultQuery[0][0], {}, dataset # Record response - count = resultQuery[0][1] - listIds = [str(record[0]) for record in resultQuery] - LOG.debug(f"count {count}") - LOG.debug(f"listIds {listIds}") - - dictPerson = get_individuals_person(listIds) # List with Id, sex, ethnicity - dictCondition = get_individuals_condition(listIds) # List with al the diseases per Id - dictProcedures = get_individuals_procedure(listIds) - dictMeasures = get_individuals_measures(listIds) - dictExposures = get_individuals_exposures(listIds) - dictTreatments = get_individuals_treatments(listIds) - - dictPerson = search_ontologies(dictPerson) - dictCondition = search_ontologies(dictCondition) - dictProcedures = search_ontologies(dictProcedures) - dictMeasures = search_ontologies(dictMeasures) - dictExposures = search_ontologies(dictExposures) - dictTreatments = search_ontologies(dictTreatments) - - docs = format_query(listIds, dictPerson, dictCondition, dictProcedures, dictMeasures, dictExposures, dictTreatments) + count = resultQuery[0][0] + listIds = [str(record[1]) for record in resultQuery] + docs = retrieveRecords(listIds) return schema, count, count, docs, dataset @log_with_args(level) def get_individual_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'individuals' - idq="id" - mongo_collection = client.beacon.individuals - query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) schema = DefaultSchemas.INDIVIDUALS include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + + # Search Id + listIds = get_individual_info(person_id=entry_id) + if not listIds: + return schema, 0, 0, {}, dataset + + docs = retrieveRecords(listIds) + + return schema, 1, 1, docs, dataset +# OMOP CDM do not work with variants @log_with_args(level) def get_variants_of_individual(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'g_variants' - targets = client.beacon.targets \ - .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) - position=0 - bioids=targets[0]["biosampleIds"] - for bioid in bioids: - if bioid == entry_id: - break - position+=1 - position=str(position) - position1="^"+position+"," - position2=","+position+"," - position3=","+position+"$" - query_cl={ "$or": [ - {"biosampleIds": {"$regex": position1}}, - {"biosampleIds": {"$regex": position2}}, - {"biosampleIds": {"$regex": position3}} - ]} - string_of_ids = client.beacon.caseLevelData \ - .find(query_cl, {"id": 1, "_id": 0}) - HGVSIds=list(string_of_ids) - query={} - queryHGVS={} - listHGVS=[] - for HGVSId in HGVSIds: - justid=HGVSId["id"] - listHGVS.append(justid) - queryHGVS["$in"]=listHGVS - query["identifiers.genomicHGVSId"]=queryHGVS - mongo_collection = client.beacon.genomicVariations - query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) schema = DefaultSchemas.GENOMICVARIATIONS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="caseLevelData.biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + + return schema, 0, 0, {}, dataset @log_with_args(level) def get_biosamples_of_individual(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'biosamples' - mongo_collection = client.beacon.biosamples - query = {"individualId": entry_id} - query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.BIOSAMPLES - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset \ No newline at end of file + + # schema, count, docs = get_biosamples_with_person_id(entry_id, qparams) + + # return schema, count, dataset_count, docs, dataset \ No newline at end of file From d2527b9068ab3ab91d43d781b9a5932e8d440250 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 15:46:55 +0100 Subject: [PATCH 08/20] add initial file for search by biosample --- beacon/connections/omopcdm/biosamples.py | 234 ++++++++++-------- beacon/connections/omopcdm/sql/biosamples.sql | 31 +++ 2 files changed, 165 insertions(+), 100 deletions(-) create mode 100644 beacon/connections/omopcdm/sql/biosamples.sql diff --git a/beacon/connections/omopcdm/biosamples.py b/beacon/connections/omopcdm/biosamples.py index d6530a7..4f42878 100644 --- a/beacon/connections/omopcdm/biosamples.py +++ b/beacon/connections/omopcdm/biosamples.py @@ -1,126 +1,160 @@ from beacon.request.parameters import RequestParams from beacon.response.schemas import DefaultSchemas -import yaml -from beacon.connections.mongo.__init__ import client -from beacon.connections.mongo.utils import get_docs_by_response_type, query_id -from beacon.logs.logs import log_with_args +from beacon.connections.omopcdm.__init__ import client +from beacon.connections.omopcdm.utils import queryExecutor, search_ontologies +from beacon.logs.logs import log_with_args, LOG from beacon.conf.conf import level -from beacon.connections.mongo.filters import apply_filters -from beacon.connections.mongo.request_parameters import apply_request_parameters +from beacon.connections.omopcdm.filters import apply_filters from typing import Optional +import aiosql +from pathlib import Path +queries_file = Path(__file__).parent / "sql" / "biosamples.sql" +biosamples_queries = aiosql.from_path(queries_file, "psycopg2") + +def get_biosample_info(offset=0, limit=10, biosample_id=None): + if biosample_id == None: + records = biosamples_queries.sql_get_biosamples(client, offset=offset, limit=limit) + if not records: + return [] + listId = [str(record[0]) for record in records] + else: + records = biosamples_queries.sql_get_biosample_id(client, specimen_id=biosample_id) + if not records: + return [] + listId = [str(records[0])] + return listId + +def get_specimens(listIds): + dict_specimens = {} + for biosample_id in listIds: + records = biosamples_queries.sql_get_specimen(client, specimen_id = biosample_id) + listValues = [] + for record in records: + listValues.append({'person_id': record[0], + 'disease_status_concept_id': record[1], + 'anatomic_site_concept_id': record[2], + 'specimen_date': record[3], + 'specimen_moment': record[4]}) + dict_specimens[biosample_id] = listValues + return dict_specimens + +def format_query(listIds, specimens): + + list_format = [] + for biosample_id in listIds: + dict_biosample_id = { + "id": str(biosample_id), + "individualId": str(specimens[biosample_id][0]["person_id"]), + "biosampleStatus": { + "id": specimens[biosample_id][0]["disease_status_concept_id"]["id"], + "label": specimens[biosample_id][0]["disease_status_concept_id"]["label"] + }, + "sampleOriginType": { + "id" : specimens[biosample_id][0]["anatomic_site_concept_id"]["id"], + "label" : specimens[biosample_id][0]["anatomic_site_concept_id"]["label"] + }, + "collectionMoment": specimens[biosample_id][0]["specimen_date"], + "collectionDate": specimens[biosample_id][0]["specimen_moment"], + "info": {} + } + list_format.append(dict_biosample_id) + return list_format + + +def retrieveRecords(listIds: list) -> list: + specimens = get_specimens(listIds) + + specimens = search_ontologies(specimens) + + docs = format_query(listIds, specimens) + + return docs + @log_with_args(level) def get_biosamples(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'biosamples' - mongo_collection = client.beacon.biosamples - parameters_as_filters=False - query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) - if parameters_as_filters == True and query_parameters != {'$and': []}:# pragma: no cover - query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) - query_parameters={} - elif query_parameters != {'$and': []}: - query=query_parameters - elif query_parameters == {'$and': []}:# pragma: no cover - query_parameters = {} - query={} - query = apply_filters(self, query, qparams.query.filters, collection, query_parameters, dataset) + scope = 'biosamples' + include = qparams.query.include_resultset_responses # Always HIT responses schema = DefaultSchemas.BIOSAMPLES - include = qparams.query.include_resultset_responses limit = qparams.query.pagination.limit skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100 - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + if limit > 50 or limit == 0: + limit = 50 + granularity = qparams.query.requested_granularity # record, count, boolean + + # If filters + if qparams.query.filters or "filters" in qparams.query.request_parameters: + query = apply_filters(self, + qparams.query.request_parameters, + qparams.query.filters, + scope, + granularity, + limit, + skip) + # Run query + resultQuery = queryExecutor(query) + else: # Get All individuals + listIds = get_biosample_info(skip, limit, entry_id) # List with all Ids + countIds = biosamples_queries.get_count_specimen(client) # Count individuals + if countIds ==0: + resultQuery = [] + else: + resultQuery = [(countIds, listId) for listId in listIds ] + + LOG.debug(f"Final query {resultQuery}") + if not resultQuery: + return schema, 0, 0, {}, dataset + # Different response depending the granularity + if granularity == "boolean": + return schema, 1, 1, {}, dataset + elif granularity == "count": + return schema, resultQuery[0][0], resultQuery[0][0], {}, dataset + # Record response + count = resultQuery[0][0] + listIds = [str(record[1]) for record in resultQuery] + docs = retrieveRecords(listIds) + + return schema, count, count, docs, dataset @log_with_args(level) def get_biosample_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'biosamples' - mongo_collection = client.beacon.biosamples - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - schema = DefaultSchemas.BIOSAMPLES include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + schema = DefaultSchemas.BIOSAMPLES + + # Search Id + listIds = get_biosample_info(person_id=entry_id) + if not listIds: + return schema, 0, 0, {}, dataset + + docs = retrieveRecords(listIds) + + return schema, 1, 1, docs, dataset + +# Function to get all the biosamples from an individual id +def get_biosamples_with_person_id(person_id: Optional[str], qparams: RequestParams): + + schema = DefaultSchemas.BIOSAMPLES + specimens = biosamples_queries.get_specimen_by_person_id(client, person_id=person_id) + listSpecimenIds = [specimen[0] for specimen in specimens ] + if not listSpecimenIds: + return 0, {} + docs = retrieveRecords(listSpecimenIds) + return len(listSpecimenIds), docs @log_with_args(level) def get_variants_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'g_variants' - mongo_collection = client.beacon.genomicVariations - targets = client.beacon.targets \ - .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) - position=0 - bioids=targets[0]["biosampleIds"] - for bioid in bioids: - if bioid == entry_id: - break - position+=1 - position=str(position) - position1="^"+position+"," - position2=","+position+"," - position3=","+position+"$" - query_cl={ "$or": [ - {"biosampleIds": {"$regex": position1}}, - {"biosampleIds": {"$regex": position2}}, - {"biosampleIds": {"$regex": position3}} - ]} - string_of_ids = client.beacon.caseLevelData \ - .find(query_cl, {"id": 1, "_id": 0}) - HGVSIds=list(string_of_ids) - query={} - queryHGVS={} - listHGVS=[] - for HGVSId in HGVSIds: - justid=HGVSId["id"] - listHGVS.append(justid) - queryHGVS["$in"]=listHGVS - query["identifiers.genomicHGVSId"]=queryHGVS - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) schema = DefaultSchemas.GENOMICVARIATIONS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="caseLevelData.biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + + return schema, 0, 0, {}, dataset @log_with_args(level) def get_analyses_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'biosamples' - mongo_collection = client.beacon.analyses - query = {"biosampleId": entry_id} - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) schema = DefaultSchemas.ANALYSES - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + + return schema, 0, 0, {}, dataset @log_with_args(level) def get_runs_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'biosamples' - mongo_collection = client.beacon.runs - query = {"individualId": entry_id} - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) schema = DefaultSchemas.RUNS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset \ No newline at end of file + + return schema, 0, 0, {}, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/sql/biosamples.sql b/beacon/connections/omopcdm/sql/biosamples.sql new file mode 100644 index 0000000..7a72238 --- /dev/null +++ b/beacon/connections/omopcdm/sql/biosamples.sql @@ -0,0 +1,31 @@ + +-- name: sql_get_biosamples +-- Get biosamples +SELECT specimen_id +FROM cdm.specimen +LIMIT :limit +OFFSET :offset + +-- name: sql_get_biosample_id^ +-- Get biosample by id +SELECT DISTINCT specimen_id +FROM cdm.specimen +WHERE specimen_id = :specimen_id + +-- name: get_count_specimen$ +-- Get specimen count +SELECT count(*) +FROM cdm.specimen + +-- name: sql_get_specimen +-- Get gender and race by id +SELECT person_id, disease_status_concept_id, anatomic_site_concept_id, + specimen_date::text, specimen_datetime::text +FROM cdm.specimen +WHERE specimen_id = :specimen_id + +-- name: get_specimen_by_person_id +-- Get specimen id by person id +SELECT distinct specimen_id +FROM cdm.specimen +WHERE person_id = :person_id \ No newline at end of file From 7737de8d29bf4c0c0d8cc44aae85f406593522e5 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 15:47:37 +0100 Subject: [PATCH 09/20] add biosample from individual id --- beacon/connections/omopcdm/individuals.py | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/beacon/connections/omopcdm/individuals.py b/beacon/connections/omopcdm/individuals.py index b8755d1..a79bb48 100644 --- a/beacon/connections/omopcdm/individuals.py +++ b/beacon/connections/omopcdm/individuals.py @@ -1,13 +1,14 @@ from beacon.request.parameters import RequestParams from beacon.response.schemas import DefaultSchemas from beacon.connections.omopcdm.__init__ import client -from beacon.connections.omopcdm.utils import queryExecutor, search_ontologies, get_docs_by_response_type, query_id +from beacon.connections.omopcdm.utils import queryExecutor, search_ontologies from beacon.logs.logs import log_with_args, LOG from beacon.conf.conf import level from beacon.connections.omopcdm.filters import apply_filters from typing import Optional import beacon.connections.omopcdm.mappings as mappings +from beacon.connections.omopcdm.biosamples import get_biosamples_with_person_id import aiosql from pathlib import Path @@ -243,6 +244,6 @@ def get_biosamples_of_individual(self, entry_id: Optional[str], qparams: Request schema = DefaultSchemas.BIOSAMPLES - # schema, count, docs = get_biosamples_with_person_id(entry_id, qparams) + count, docs = get_biosamples_with_person_id(entry_id, qparams) - # return schema, count, dataset_count, docs, dataset \ No newline at end of file + return schema, count, count, docs, dataset \ No newline at end of file From 8b24b464fd2db087aa8c1e82de5c396a4281d25b Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 15:48:55 +0100 Subject: [PATCH 10/20] Add filtering terms initial file --- beacon/connections/omopcdm/filtering_terms.py | 64 ++++++++++++------- .../omopcdm/sql/filteringTerms.sql | 47 ++++++++++++++ .../connections/omopcdm/sql/individuals.sql | 39 +---------- 3 files changed, 90 insertions(+), 60 deletions(-) create mode 100644 beacon/connections/omopcdm/sql/filteringTerms.sql diff --git a/beacon/connections/omopcdm/filtering_terms.py b/beacon/connections/omopcdm/filtering_terms.py index 67d7a22..2b415a2 100644 --- a/beacon/connections/omopcdm/filtering_terms.py +++ b/beacon/connections/omopcdm/filtering_terms.py @@ -1,27 +1,47 @@ -from beacon.connections.mongo.__init__ import client -from beacon.connections.mongo.utils import get_count +from beacon.connections.omopcdm.__init__ import client from typing import Optional from beacon.response.schemas import DefaultSchemas from beacon.request.parameters import RequestParams -from beacon.connections.mongo.utils import get_filtering_documents -from beacon.exceptions.exceptions import raise_exception + +import aiosql +from pathlib import Path +queries_file = Path(__file__).parent / "sql" / "filteringTerms.sql" +filteringTerms_queries = aiosql.from_path(queries_file, "psycopg2") + +def get_filtering_terms_of_individual(entry_id: Optional[str], qparams: RequestParams): + schema = DefaultSchemas.FILTERINGTERMS + + indFilters = [filteringTerms_queries.sql_filtering_terms_race_gender(client), + filteringTerms_queries.sql_filtering_terms_condition(client), + filteringTerms_queries.sql_filtering_terms_measurement(client), + filteringTerms_queries.sql_filtering_terms_procedure(client), + filteringTerms_queries.sql_filtering_terms_observation(client), + filteringTerms_queries.sql_filtering_terms_drug_exposure(client)] + finalIndFilters = [] + for ind_filters in indFilters: + for filters in ind_filters: + if filters[0].endswith("OMOP generated"): + continue + dict_filter = {"id":filters[0],"label":filters[1],"scopes":["individual"],"type":"ontology"} + finalIndFilters.append(dict_filter) + return len(finalIndFilters), finalIndFilters + + + +def get_filtering_terms_of_biosample(entry_id: Optional[str], qparams: RequestParams): + schema = DefaultSchemas.FILTERINGTERMS + bio_filters = filteringTerms_queries.sql_filtering_terms_biosample(client) + l_bioFilters = [] + for filters in bio_filters: + dict_filter = {"id":filters[0],"label":filters[1],"scopes":["biosample"],"type":"ontology"} + l_bioFilters.append(dict_filter) + return len(l_bioFilters), l_bioFilters + def get_filtering_terms(self, qparams: RequestParams): - try: - query = {} - schema = DefaultSchemas.FILTERINGTERMS - count = get_count(self, client.beacon.filtering_terms, query) - remove_id={'_id':0} - docs = get_filtering_documents( - self, - client.beacon.filtering_terms, - query, - remove_id, - qparams.query.pagination.skip, - qparams.query.pagination.limit - ) - return schema, count, docs - except Exception as e:# pragma: no cover - err = str(e) - errcode=500 - raise_exception(err, errcode) \ No newline at end of file + + schema = DefaultSchemas.FILTERINGTERMS + indCount, indDocs = get_filtering_terms_of_individual(None, None) + bioCount, bioDocs = get_filtering_terms_of_biosample(None, None) + + return schema, indCount + bioCount, indDocs + bioDocs \ No newline at end of file diff --git a/beacon/connections/omopcdm/sql/filteringTerms.sql b/beacon/connections/omopcdm/sql/filteringTerms.sql new file mode 100644 index 0000000..379b4f0 --- /dev/null +++ b/beacon/connections/omopcdm/sql/filteringTerms.sql @@ -0,0 +1,47 @@ + +--Individuals-- + +-- name: sql_filtering_terms_race_gender +-- Get all the race and gender filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.person as p on p.race_concept_id=c.concept_id or p.gender_concept_id=c.concept_id + +-- name: sql_filtering_terms_condition +-- Get all the condition_occurrence filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.condition_occurrence as con on con.condition_concept_id=c.concept_id + +-- name: sql_filtering_terms_measurement +-- Get all the measurement filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.measurement as con on con.measurement_concept_id=c.concept_id + +-- name: sql_filtering_terms_procedure +-- Get all the procedure_occurrence filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.procedure_occurrence as con on con.procedure_concept_id=c.concept_id + +-- name: sql_filtering_terms_observation +-- Get all the observation filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.observation as con on con.observation_concept_id=c.concept_id + +-- name: sql_filtering_terms_drug_exposure +-- Get all the drug exposure filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.drug_exposure as con on con.drug_concept_id=c.concept_id + +--Biosamples-- + +-- name: sql_filtering_terms_biosample +-- Get all the observation filtering terms for individual +select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name +from vocabularies.concept as c +join cdm.specimen as con + on con.disease_status_concept_id=c.concept_id or con.anatomic_site_concept_id=c.concept_id \ No newline at end of file diff --git a/beacon/connections/omopcdm/sql/individuals.sql b/beacon/connections/omopcdm/sql/individuals.sql index 9b0a45f..e64f66c 100644 --- a/beacon/connections/omopcdm/sql/individuals.sql +++ b/beacon/connections/omopcdm/sql/individuals.sql @@ -111,41 +111,4 @@ SELECT drug_concept_id, END AS drug_exposure_ageOfOnset FROM cdm.person as p, cdm.drug_exposure as c -WHERE p.person_id = :person_id and p.person_id = c.person_id; - --- name: sql_filtering_terms_race_gender --- Get all the race and gender filtering terms for individual -select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name -from vocabularies.concept as c -join cdm.person as p on p.race_concept_id=c.concept_id or p.gender_concept_id=c.concept_id - --- name: sql_filtering_terms_condition --- Get all the condition_occurrence filtering terms for individual -select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name -from vocabularies.concept as c -join cdm.condition_occurrence as con on con.condition_concept_id=c.concept_id - --- name: sql_filtering_terms_measurement --- Get all the measurement filtering terms for individual -select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name -from vocabularies.concept as c -join cdm.measurement as con on con.measurement_concept_id=c.concept_id - --- name: sql_filtering_terms_procedure --- Get all the procedure_occurrence filtering terms for individual -select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name -from vocabularies.concept as c -join cdm.procedure_occurrence as con on con.procedure_concept_id=c.concept_id - --- name: sql_filtering_terms_observation --- Get all the observation filtering terms for individual -select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name -from vocabularies.concept as c -join cdm.observation as con on con.observation_concept_id=c.concept_id - --- name: sql_filtering_terms_drug_exposure --- Get all the drug exposure filtering terms for individual -select distinct CONCAT(vocabulary_id,':',concept_code) as uri, c.concept_name -from vocabularies.concept as c -join cdm.drug_exposure as con on con.drug_concept_id=c.concept_id - +WHERE p.person_id = :person_id and p.person_id = c.person_id; \ No newline at end of file From 94ddf97cb737874ab70498eddabec97bea33144c Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Mon, 30 Dec 2024 16:56:17 +0100 Subject: [PATCH 11/20] Add cohorts --- beacon/connections/omopcdm/cohorts.py | 347 +++++++++++------- beacon/connections/omopcdm/sql/cohorts.sql | 164 +++++++++ .../connections/omopcdm/sql/individuals.sql | 14 - 3 files changed, 382 insertions(+), 143 deletions(-) create mode 100644 beacon/connections/omopcdm/sql/cohorts.sql diff --git a/beacon/connections/omopcdm/cohorts.py b/beacon/connections/omopcdm/cohorts.py index c75cedd..a5fff1a 100644 --- a/beacon/connections/omopcdm/cohorts.py +++ b/beacon/connections/omopcdm/cohorts.py @@ -1,169 +1,258 @@ from beacon.request.parameters import RequestParams from beacon.response.schemas import DefaultSchemas -from beacon.connections.mongo.__init__ import client +from beacon.connections.omopcdm.__init__ import client from beacon.logs.logs import log_with_args_mongo from beacon.conf.conf import level -from beacon.connections.mongo.filters import apply_filters from typing import Optional -from beacon.connections.mongo.utils import get_count, get_documents, get_documents_for_cohorts -from beacon.connections.mongo.utils import get_docs_by_response_type, query_id, get_cross_query -import yaml +from beacon.connections.omopcdm.individuals import get_individuals + +import aiosql +from pathlib import Path +queries_file = Path(__file__).parent / "sql" / "cohorts.sql" +cohortQueries = aiosql.from_path(queries_file, "psycopg2") + +def disease_criteria(cohortBasicInfo): + if cohortBasicInfo['individuals']: + diseases = cohortQueries.get_condition_per_person(client, person_ids = cohortBasicInfo['individuals']) + else: + diseases = cohortQueries.get_condition(client) + + list_diseases = [] + for disease in diseases: + dict_disease = {"diseaseCode": {"label": disease[0], + "id": disease[1]}} + list_diseases.append(dict_disease) + + return list_diseases + +def location_criteria(cohortBasicInfo): + if cohortBasicInfo['individuals']: + locations = cohortQueries.get_location_per_person(client, person_ids = cohortBasicInfo['individuals']) + else: + locations = cohortQueries.get_location(client) + + list_locations = [] + for location in locations: + dict_location = {"label": location[0], + "id": location[1]} + list_locations.append(dict_location) + + return list_locations + +def gender_criteria(cohortBasicInfo): + if cohortBasicInfo['individuals']: + genders = cohortQueries.get_gender_per_person(client, person_ids = cohortBasicInfo['individuals']) + else: + genders = cohortQueries.get_gender(client) + list_genders = [] + + for gender in genders: + dict_gender = {"label": gender[0], + "id": gender[1]} + list_genders.append(dict_gender) + + return list_genders + +def cohort_data_types(): + return [{ + "id": "OGMS:0000015", + "label": "clinical history" + }] + +def dataAvailabilityAndDistributionFunction(eventData): + + dict_distribution = {} + count_ind = 0 + for event in eventData: + count_ind += int(event[1]) + dict_distribution[str(event[0])] = event[1] + + if not dict_distribution: + return {"availability": False} + + return { + "availability": True, + "availabilityCount":count_ind, + "distribution":dict_distribution + } + +def createEvent(cohortBasicInfo): + if cohortBasicInfo['individuals']: + year_per_person = cohortQueries.get_year_of_birth_count_per_person(client, person_ids = cohortBasicInfo['individuals']) + sex_per_person = cohortQueries.get_gender_count_per_person(client, person_ids = cohortBasicInfo['individuals']) + disease_per_person = cohortQueries.get_condition_count_person(client, person_ids = cohortBasicInfo['individuals']) + eventSize = len(cohortBasicInfo['individuals']) + + else: # For all individuals + year_per_person = cohortQueries.get_year_of_birth_count(client) + sex_per_person = cohortQueries.get_gender_count(client) + disease_per_person = cohortQueries.get_condition_count(client) + eventSize = cohortQueries.get_cohort_count(client) + + distributionAge = dataAvailabilityAndDistributionFunction(year_per_person) + distributionSex = dataAvailabilityAndDistributionFunction(sex_per_person) + distributionDiseases = dataAvailabilityAndDistributionFunction(disease_per_person) + + + return { + "eventAgeRange": { + "availability": distributionAge['availability'], + "availabilityCount": distributionAge['availabilityCount'], + "distribution": { + "year": distributionAge['distribution'] + } + }, + "eventNum": 1, + "eventDate": cohortBasicInfo['cohort']['date'], + "eventGenders": { + "availability": distributionSex['availability'], + "availabilityCount": distributionSex['availabilityCount'], + "distribution": { + "genders": distributionSex['distribution'] + } + }, + "eventDiseases": { + "availability": distributionDiseases['availability'], + "availabilityCount": distributionDiseases['availabilityCount'], + "distribution": { + "diseases": distributionDiseases['distribution'] + } + }, + + "eventSize": eventSize + } + + +def create_cohort_model(cohortBasicInfo): + + if not cohortBasicInfo['individuals']: # All database + cohortSize = cohortQueries.get_cohort_count(client) + min_age, max_age = cohortQueries.get_age_range(client) + + else: + cohortSize = len(cohortBasicInfo['individuals']) + min_age, max_age = cohortQueries.get_age_range_person(client, person_ids=cohortBasicInfo['individuals']) + + + cohort = { + 'id': str(cohortBasicInfo['cohort']['id']), + 'name': cohortBasicInfo['cohort']['name'], + 'cohortDataTypes': cohort_data_types(), + 'cohortSize': cohortSize, + # 'cohortType': cohort_type, + 'collectionEvents': [createEvent(cohortBasicInfo)], + "inclusionCriteria": { + 'ageRange' : { + "end": { + "iso8601duration": f"P{max_age}Y" + }, + "start": { + "iso8601duration": f"P{min_age}Y" + } + }, + 'genders': gender_criteria(cohortBasicInfo), + 'locations': location_criteria(cohortBasicInfo), + 'diseaseConditions':disease_criteria(cohortBasicInfo) + } + } + return cohort + +def search_cohorts(isAll): + list_cohorts = [] + if isAll: + dict_cohort = {'id': '0', 'date': '', 'name':"All patients"} + list_cohorts.append({'cohort':dict_cohort,'individuals': []}) + + cohorts=cohortQueries.get_all_cohorts(client) + for cohort in cohorts: + dict_cohort = {'id': cohort[0], 'date': cohort[1], + 'name':cohort[2]} + individuals=[ind[0] for ind in cohortQueries.get_cohort_individuals(client, cohort_id=cohort[0])] + + list_cohorts.append({'cohort':dict_cohort, 'individuals': individuals}) + return list_cohorts @log_with_args_mongo(level) def get_cohorts(self, entry_id: Optional[str], qparams: RequestParams): - collection = 'cohorts' - limit = qparams.query.pagination.limit - query = apply_filters(self, {}, qparams.query.filters, collection, {}, "a") + schema = DefaultSchemas.COHORTS - count = get_count(self, client.beacon.cohorts, query) - docs = get_documents(self, - client.beacon.cohorts, - query, - qparams.query.pagination.skip, - qparams.query.pagination.skip*limit - ) + + list_cohorts = search_cohorts(isAll=True) + count = len(list_cohorts) + docs = [] + for cohort in list_cohorts: + docs.append(create_cohort_model(cohort)) + + response_converted = ( [r for r in docs] if docs else [] ) return response_converted, count, schema +def search_single_cohort(cohort_id): + if int(cohort_id)==0: + dict_cohort = {'id': '0', 'date': '', + 'name':"All patients"} + individuals=[] + return {'cohort':dict_cohort, 'individuals': individuals} + + cohorts=cohortQueries.get_single_cohort(client, cohort_id=cohort_id) + for cohort in cohorts: + dict_cohort = {'id': str(cohort[0]), 'date': cohort[1], + 'name':cohort[2]} + individuals=[ind[0] for ind in cohortQueries.get_cohort_individuals(client, cohort_id=cohort[0])] + + return {'cohort':dict_cohort, 'individuals': individuals} + + @log_with_args_mongo(level) def get_cohort_with_id(self, entry_id: Optional[str], qparams: RequestParams): - collection = 'cohorts' - limit = qparams.query.pagination.limit - query = apply_filters(self, {}, qparams.query.filters, collection, {}, "a") - query = query_id(self, query, entry_id) schema = DefaultSchemas.COHORTS - count = get_count(self, client.beacon.cohorts, query) - docs = get_documents(self, - client.beacon.cohorts, - query, - qparams.query.pagination.skip, - qparams.query.pagination.skip*limit - ) + cohortBasicInfo = search_single_cohort(entry_id) + print(cohortBasicInfo) + docs = [create_cohort_model(cohortBasicInfo)] + response_converted = ( [r for r in docs] if docs else [] ) - return response_converted, count, schema + return response_converted, 1, schema @log_with_args_mongo(level) def get_individuals_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'cohorts' - mongo_collection = client.beacon.individuals - dataset_count=0 + schema = DefaultSchemas.INDIVIDUALS limit = qparams.query.pagination.limit - include = qparams.query.include_resultset_responses - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.cohorts, query) - dict_in={} - dict_in['datasetId']=dataset - query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + if entry_id == '1': + return get_individuals(self, entry_id, qparams, dataset) + else: + listIds = cohortQueries.get_cohort_individuals_limited(client, + limit=limit, + cohort_id=entry_id) # List with all Ids + count_ids = cohortQueries.count_cohort_individuals(client, cohort_id=entry_id) # Count individuals + + return get_individuals(self, [listIds], qparams, dataset) - schema = DefaultSchemas.INDIVIDUALS - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + + return schema, 0, 0, {}, dataset @log_with_args_mongo(level) def get_analyses_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'cohorts' - mongo_collection = client.beacon.analyses - dataset_count=0 - limit = qparams.query.pagination.limit - include = qparams.query.include_resultset_responses - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.cohorts, query) - dict_in={} - dict_in['datasetId']=dataset - query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.ANALYSES - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + return schema, 0, 0, {}, dataset @log_with_args_mongo(level) def get_variants_of_cohort(self,entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'cohorts' - mongo_collection = client.beacon.genomicVariations - dataset_count=0 - limit = qparams.query.pagination.limit - include = qparams.query.include_resultset_responses - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.cohorts, query) - query_count={} - query_count["$or"]=[] - docs = get_documents_for_cohorts(self, - client.beacon.cohorts, - query, - qparams.query.pagination.skip, - qparams.query.pagination.skip*limit - ) - for doc in docs: - if doc["datasetId"] == dataset: - entry_id = dataset - if dataset == entry_id: - queryid={} - queryid["datasetId"]=dataset - query_count["$or"].append(queryid) - else: - schema = DefaultSchemas.GENOMICVARIATIONS# pragma: no cover - return schema, 0, 0, None, dataset# pragma: no cover - query = apply_filters(self, query_count, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.GENOMICVARIATIONS - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="caseLevelData.biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + + schema = DefaultSchemas.GENOMICVARIATIONS# pragma: no cover + return schema, 0, 0, {}, dataset @log_with_args_mongo(level) def get_runs_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'cohorts' - mongo_collection = client.beacon.runs - dataset_count=0 - limit = qparams.query.pagination.limit - include = qparams.query.include_resultset_responses - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.cohorts, query) - dict_in={} - dict_in['datasetId']=dataset - query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) schema = DefaultSchemas.RUNS - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + return schema, 0, 0, {}, dataset @log_with_args_mongo(level) def get_biosamples_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'cohorts' - mongo_collection = client.beacon.biosamples - dataset_count=0 - limit = qparams.query.pagination.limit - include = qparams.query.include_resultset_responses - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.cohorts, query) - dict_in={} - dict_in['datasetId']=dataset - query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) + schema = DefaultSchemas.BIOSAMPLES - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset \ No newline at end of file + return schema, 0, 0, {}, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/sql/cohorts.sql b/beacon/connections/omopcdm/sql/cohorts.sql new file mode 100644 index 0000000..07fe876 --- /dev/null +++ b/beacon/connections/omopcdm/sql/cohorts.sql @@ -0,0 +1,164 @@ +-- name: get_all_cohorts +-- Get all cohorts in database +SELECT cohort_definition_id, to_char(cohort_initiation_date, 'YYYY-MM-DD'), + cohort_definition_name +FROM cdm.cohort_definition +ORDER BY cohort_definition_id + +-- name: get_single_cohort +-- Get a cohort in database +SELECT cohort_definition_id, to_char(cohort_initiation_date, 'YYYY-MM-DD'), + cohort_definition_name +FROM cdm.cohort_definition +where cohort_definition_id=:cohort_id + +-- name: get_cohort_individuals +-- Get individuals from a cohort +SELECT subject_id +FROM cdm.cohort +where cohort_definition_id=:cohort_id +ORDER BY cohort_definition_id + +-- name: get_cohort_individuals_limited +-- Get individuals from a cohort +SELECT subject_id +FROM cdm.cohort +where cohort_definition_id=:cohort_id +limit :limit + +-- name: count_cohort_individuals$ +-- Get individuals count +SELECT count(*) +FROM cdm.cohort +where cohort_definition_id = :cohort_id + +-- name: get_cohort_count$ +-- Get gender count +select count(*) +from cdm.person p + +-- name: get_age_range^ +-- Get age min-max +select min(date_part('year', age( now(), p.birth_datetime)))::int min_age, max(date_part('year', age( now(), p.birth_datetime)))::int max_age +from cdm.person p + +-- name: get_age_range_person^ +-- Get age min-max per person +select min(date_part('year', age( now(), p.birth_datetime)))::int min_age, max(date_part('year', age( now(), p.birth_datetime)))::int max_age +from cdm.person p +where p.person_id = ANY(:person_ids) + +-- name: get_gender +-- Get gender +SELECT c.concept_name as label, + c.vocabulary_id || ':' || c.concept_code as id +from cdm.person p +inner join vocabularies.concept c on c.concept_id = p.gender_concept_id +group by c.concept_name, c.vocabulary_id, c.concept_code + +-- name: get_gender_per_person +-- Get gender per person +SELECT c.concept_name as label, + c.vocabulary_id || ':' || c.concept_code as id +from cdm.person p +inner join vocabularies.concept c on c.concept_id = p.gender_concept_id +where p.person_id = ANY(:person_ids) +group by c.concept_name, c.vocabulary_id, c.concept_code + +-- name: get_gender_count +-- Get gender count +select c.concept_name, count(*) +from cdm.person p +inner join vocabularies.concept c on c.concept_id = p.gender_concept_id +group by concept_name + +-- name: get_gender_count_per_person +-- Get gender count +select c.concept_name, count(*) +from cdm.person p +inner join vocabularies.concept c on c.concept_id = p.gender_concept_id +where p.person_id = ANY(:person_ids) +group by concept_name + +-- name: get_location +-- Get location +SELECT distinct c.concept_name as label, + c.vocabulary_id || ':' || c.concept_code as id +from cdm.location p +inner join vocabularies.concept c on c.concept_id = p.country_concept_id +group by c.concept_name, c.vocabulary_id, c.concept_code + +-- name: get_location_per_person +-- Get location +SELECT distinct c.concept_name as label, + c.vocabulary_id || ':' || c.concept_code as id +from cdm.location l +inner join vocabularies.concept c on c.concept_id = l.country_concept_id +inner join cdm.person p on l.location_id = l.location_id +where p.person_id = ANY(:person_ids) +group by c.concept_name, c.vocabulary_id, c.concept_code + +-- name: get_year_of_birth_count +-- Get year_of_birth count +select p.year_of_birth, count(*) +from cdm.person p +group by p.year_of_birth +order by year_of_birth + +-- name: get_year_of_birth_count_per_person +-- Get year_of_birth count per person +select p.year_of_birth, count(*) +from cdm.person p +where p.person_id = ANY(:person_ids) +group by p.year_of_birth +order by year_of_birth + +-- name: get_condition_count +-- Get condtion concept count +select concept_name, count(distinct person_id) count_value +from cdm.condition_occurrence co +inner join vocabularies.concept c on c.concept_id = co.condition_concept_id +group by c.concept_code, c.vocabulary_id, concept_name +order by count_value desc + +-- name: get_condition_count_person +-- Get condtion concept count per person +select concept_name, count(distinct person_id) count_value +from cdm.condition_occurrence co +inner join vocabularies.concept c on c.concept_id = co.condition_concept_id +where person_id = ANY(:person_ids) +group by c.concept_code, c.vocabulary_id, concept_name +order by count_value desc + +-- name: get_condition +-- Get condition +SELECT distinct c.concept_name as label, + c.vocabulary_id || ':' || c.concept_code as id +from cdm.condition_occurrence p +inner join vocabularies.concept c on c.concept_id = p.condition_concept_id +group by c.concept_name, c.vocabulary_id, c.concept_code + +-- name: get_condition_per_person +-- Get condition per person +SELECT distinct c.concept_name as label, + c.vocabulary_id || ':' || c.concept_code as id +from cdm.condition_occurrence con +inner join vocabularies.concept c on c.concept_id = con.condition_concept_id +where person_id = ANY(:person_ids) +group by c.concept_name, c.vocabulary_id, c.concept_code + +-- name: get_procedure_count +-- Get procedure concept count +select c.concept_code, c.vocabulary_id, concept_name, count(distinct person_id) count_value +from cdm.procedure_occurrence po +inner join vocabularies.concept c on c.concept_id = po.procedure_concept_id +group by c.concept_code, c.vocabulary_id, concept_name +order by count_value desc + +-- name: get_drug_count +-- Get drug concept count +select c.concept_code, c.vocabulary_id, concept_name, count(distinct person_id) count_value +from cdm.drug_exposure de +inner join vocabularies.concept c on c.concept_id = de.drug_concept_id +group by c.concept_code, c.vocabulary_id, concept_name +order by count_value desc \ No newline at end of file diff --git a/beacon/connections/omopcdm/sql/individuals.sql b/beacon/connections/omopcdm/sql/individuals.sql index e64f66c..7b28d43 100644 --- a/beacon/connections/omopcdm/sql/individuals.sql +++ b/beacon/connections/omopcdm/sql/individuals.sql @@ -6,20 +6,6 @@ FROM cdm.person LIMIT :limit OFFSET :offset --- name: cohort_individuals --- Get individuals -SELECT subject_id as person_id -FROM cdm.cohort -where cohort_definition_id = :cohort_id -LIMIT :limit -OFFSET :offset - --- name: count_cohort_individuals$ --- Get individuals count -SELECT count(*) -FROM cdm.cohort -where cohort_definition_id = :cohort_id - -- name: count_individuals$ -- Get individuals count SELECT count(*) From 38ac7e6862a55b7a32a58941c1c1d3c2bd24f025 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Thu, 2 Jan 2025 10:14:41 +0100 Subject: [PATCH 12/20] Remove files that are not used --- beacon/connections/omopcdm/Makefile | 19 - beacon/connections/omopcdm/analyses.py | 99 - beacon/connections/omopcdm/data/analyses.json | 30050 --- .../connections/omopcdm/data/biosamples.json | 90146 ------- .../omopcdm/data/caseLevelData.json | 1 - beacon/connections/omopcdm/data/cohorts.json | 116 - beacon/connections/omopcdm/data/datasets.json | 1 - .../omopcdm/data/filtering_terms.json | 23 - .../omopcdm/data/genomicVariations.json | 1 - .../connections/omopcdm/data/individuals.json | 183766 --------------- beacon/connections/omopcdm/data/runs.json | 47578 ---- beacon/connections/omopcdm/data/targets.json | 1 - .../omopcdm/extract_filtering_terms.py | 493 - beacon/connections/omopcdm/g_variants.py | 278 - beacon/connections/omopcdm/get_descendants.py | 178 - beacon/connections/omopcdm/mongo-init/init.js | 27 - .../omopcdm/ontologies/example.txt | 0 beacon/connections/omopcdm/ping.py | 33 - beacon/connections/omopcdm/reindex.py | 79 - beacon/connections/omopcdm/runs.py | 111 - 20 files changed, 353000 deletions(-) delete mode 100644 beacon/connections/omopcdm/Makefile delete mode 100644 beacon/connections/omopcdm/analyses.py delete mode 100644 beacon/connections/omopcdm/data/analyses.json delete mode 100644 beacon/connections/omopcdm/data/biosamples.json delete mode 100644 beacon/connections/omopcdm/data/caseLevelData.json delete mode 100644 beacon/connections/omopcdm/data/cohorts.json delete mode 100644 beacon/connections/omopcdm/data/datasets.json delete mode 100644 beacon/connections/omopcdm/data/filtering_terms.json delete mode 100644 beacon/connections/omopcdm/data/genomicVariations.json delete mode 100644 beacon/connections/omopcdm/data/individuals.json delete mode 100644 beacon/connections/omopcdm/data/runs.json delete mode 100644 beacon/connections/omopcdm/data/targets.json delete mode 100644 beacon/connections/omopcdm/extract_filtering_terms.py delete mode 100644 beacon/connections/omopcdm/g_variants.py delete mode 100644 beacon/connections/omopcdm/get_descendants.py delete mode 100644 beacon/connections/omopcdm/mongo-init/init.js delete mode 100644 beacon/connections/omopcdm/ontologies/example.txt delete mode 100644 beacon/connections/omopcdm/ping.py delete mode 100644 beacon/connections/omopcdm/reindex.py delete mode 100644 beacon/connections/omopcdm/runs.py diff --git a/beacon/connections/omopcdm/Makefile b/beacon/connections/omopcdm/Makefile deleted file mode 100644 index 53d796a..0000000 --- a/beacon/connections/omopcdm/Makefile +++ /dev/null @@ -1,19 +0,0 @@ -build: - docker cp data/analyses.json mongoprod:tmp/analyses.json - docker cp data/biosamples.json mongoprod:tmp/biosamples.json - docker cp data/cohorts.json mongoprod:tmp/cohorts.json - docker cp data/datasets.json mongoprod:tmp/datasets.json - docker cp data/genomicVariations.json mongoprod:tmp/genomicVariations.json - docker cp data/individuals.json mongoprod:tmp/individuals.json - docker cp data/runs.json mongoprod:tmp/runs.json - docker cp data/targets.json mongoprod:tmp/targets.json - docker cp data/caseLevelData.json mongoprod:tmp/caseLevelData.json - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/datasets.json --collection datasets - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/individuals.json --collection individuals - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/cohorts.json --collection cohorts - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/analyses.json --collection analyses - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/biosamples.json --collection biosamples - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/genomicVariations.json --collection genomicVariations - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/runs.json --collection runs - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/targets.json --collection targets - docker exec mongoprod mongoimport --jsonArray --uri "mongodb://root:example@127.0.0.1:27017/beacon?authSource=admin" --file /tmp/caseLevelData.json --collection caseLevelData \ No newline at end of file diff --git a/beacon/connections/omopcdm/analyses.py b/beacon/connections/omopcdm/analyses.py deleted file mode 100644 index 2389640..0000000 --- a/beacon/connections/omopcdm/analyses.py +++ /dev/null @@ -1,99 +0,0 @@ - -from beacon.request.parameters import RequestParams -from beacon.response.schemas import DefaultSchemas -import yaml -from beacon.connections.mongo.__init__ import client -from beacon.connections.mongo.utils import get_docs_by_response_type, query_id -from beacon.logs.logs import log_with_args -from beacon.conf.conf import level -from beacon.connections.mongo.filters import apply_filters -from beacon.connections.mongo.request_parameters import apply_request_parameters -from typing import Optional - -@log_with_args(level) -def get_analyses(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'analyses' - mongo_collection = client.beacon.analyses - parameters_as_filters=False - query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) - if parameters_as_filters == True and query_parameters != {'$and': []}:# pragma: no cover - query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) - query_parameters={} - elif query_parameters != {'$and': []}: - query=query_parameters - elif query_parameters == {'$and': []}:# pragma: no cover - query_parameters = {} - query={} - query = apply_filters(self, query, qparams.query.filters, collection, query_parameters, dataset) - schema = DefaultSchemas.ANALYSES - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100 - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_analysis_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'analyses' - idq="biosampleId" - mongo_collection = client.beacon.analyses - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - schema = DefaultSchemas.ANALYSES - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_variants_of_analysis(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'analyses' - mongo_collection = client.beacon.genomicVariations - query = {"$and": [{"id": entry_id}]} - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - analysis_ids = client.beacon.analyses \ - .find_one(query, {"biosampleId": 1, "_id": 0}) - targets = client.beacon.targets \ - .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) - position=0 - bioids=targets[0]["biosampleIds"] - for bioid in bioids: - if bioid == analysis_ids["biosampleId"]: - break - position+=1 - position=str(position) - position1="^"+position+"," - position2=","+position+"," - position3=","+position+"$" - query_cl={ "$or": [ - {"biosampleIds": {"$regex": position1}}, - {"biosampleIds": {"$regex": position2}}, - {"biosampleIds": {"$regex": position3}} - ]} - string_of_ids = client.beacon.caseLevelData \ - .find(query_cl, {"id": 1, "_id": 0}) - HGVSIds=list(string_of_ids) - query={} - queryHGVS={} - listHGVS=[] - for HGVSId in HGVSIds: - justid=HGVSId["id"] - listHGVS.append(justid) - queryHGVS["$in"]=listHGVS - query["identifiers.genomicHGVSId"]=queryHGVS - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.GENOMICVARIATIONS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="caseLevelData.biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/data/analyses.json b/beacon/connections/omopcdm/data/analyses.json deleted file mode 100644 index 2b5eac8..0000000 --- a/beacon/connections/omopcdm/data/analyses.json +++ /dev/null @@ -1,30050 +0,0 @@ -[ - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00096", - "id": "UK1_analysisId_1", - "individualId": "HG00096", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000001", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00097", - "id": "UK1_analysisId_2", - "individualId": "HG00097", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000002", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00099", - "id": "UK1_analysisId_3", - "individualId": "HG00099", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000003", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00100", - "id": "UK1_analysisId_4", - "individualId": "HG00100", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000004", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00101", - "id": "UK1_analysisId_5", - "individualId": "HG00101", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000005", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00102", - "id": "UK1_analysisId_6", - "individualId": "HG00102", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000006", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00103", - "id": "UK1_analysisId_7", - "individualId": "HG00103", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000007", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00105", - "id": "UK1_analysisId_8", - "individualId": "HG00105", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000008", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00106", - "id": "UK1_analysisId_9", - "individualId": "HG00106", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000009", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00107", - "id": "UK1_analysisId_10", - "individualId": "HG00107", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000010", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00108", - "id": "UK1_analysisId_11", - "individualId": "HG00108", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000011", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00109", - "id": "UK1_analysisId_12", - "individualId": "HG00109", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000012", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00110", - "id": "UK1_analysisId_13", - "individualId": "HG00110", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000013", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00111", - "id": "UK1_analysisId_14", - "individualId": "HG00111", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000014", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00112", - "id": "UK1_analysisId_15", - "individualId": "HG00112", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000015", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00113", - "id": "UK1_analysisId_16", - "individualId": "HG00113", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000016", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00114", - "id": "UK1_analysisId_17", - "individualId": "HG00114", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000017", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00115", - "id": "UK1_analysisId_18", - "individualId": "HG00115", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000018", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00116", - "id": "UK1_analysisId_19", - "individualId": "HG00116", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000019", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00117", - "id": "UK1_analysisId_20", - "individualId": "HG00117", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000020", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00118", - "id": "UK1_analysisId_21", - "individualId": "HG00118", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000021", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00119", - "id": "UK1_analysisId_22", - "individualId": "HG00119", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000022", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00120", - "id": "UK1_analysisId_23", - "individualId": "HG00120", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000023", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00121", - "id": "UK1_analysisId_24", - "individualId": "HG00121", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000024", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00122", - "id": "UK1_analysisId_25", - "individualId": "HG00122", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000025", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00123", - "id": "UK1_analysisId_26", - "individualId": "HG00123", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000026", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00125", - "id": "UK1_analysisId_27", - "individualId": "HG00125", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000027", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00126", - "id": "UK1_analysisId_28", - "individualId": "HG00126", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000028", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00127", - "id": "UK1_analysisId_29", - "individualId": "HG00127", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000029", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00128", - "id": "UK1_analysisId_30", - "individualId": "HG00128", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000030", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00129", - "id": "UK1_analysisId_31", - "individualId": "HG00129", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000031", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00130", - "id": "UK1_analysisId_32", - "individualId": "HG00130", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000032", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00131", - "id": "UK1_analysisId_33", - "individualId": "HG00131", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000033", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00132", - "id": "UK1_analysisId_34", - "individualId": "HG00132", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000034", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00133", - "id": "UK1_analysisId_35", - "individualId": "HG00133", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000035", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00136", - "id": "UK1_analysisId_36", - "individualId": "HG00136", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000036", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00137", - "id": "UK1_analysisId_37", - "individualId": "HG00137", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000037", - "variantCaller": "GATK4.0" - }, - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "aligner": "bwa-0.5.9", - "analysisDate": "2015-09-30", - "biosampleId": "HG00138", - "id": "UK1_analysisId_38", - "individualId": "HG00138", - "pipelineName": "1000G-low-coverage-WGS", - "pipelineRef": "https://www.nature.com/articles/nature15393", - "runId": "SRR00000038", - "variantCaller": "GATK4.0" - }, - { - "datasetId": 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diff --git a/beacon/connections/omopcdm/data/cohorts.json b/beacon/connections/omopcdm/data/cohorts.json deleted file mode 100644 index 89ec5f2..0000000 --- a/beacon/connections/omopcdm/data/cohorts.json +++ /dev/null @@ -1,116 +0,0 @@ -[ - { - "datasetId": "CINECA_synthetic_cohort_EUROPE_UK1", - "cohortType": "study-defined", - "collectionEvents": [ - { - "eventDiseases": { - "availability": true, - "availabilityCount": 1705, - "distribution": { - "diseases": { - "acutebronchitis": 121, - "agranulocytosis": 111, - "asthma": 134, - "bipolaraffectivedisorder": 134, - "cardiomyopathy": 133, - "dentalcaries": 139, - "eatingdisorders": 134, - "fibrosisandcirrhosisofliver": 132, - "gastro-oesophagealrefluxdisease": 140, - "haemorrhoids": 127, - "influenzaduetocertainidentifiedinfluenzavirus": 135, - "insulin-dependentdiabetesmellitus": 165, - "irondeficiencyanaemia": 142, - "multiplesclerosis": 125, - "obesity": 136, - "sarcoidosis": 136, - "schizophrenia": 138, - "thyroiditis": 141, - "varicoseveinsoflowerextremities": 139 - } - } - }, - "eventEthnicities": { - "availability": true, - "availabilityCount": 2287, - "distribution": { - "ethnicities": { - "African": 119, - "AnyotherAsianbackground": 120, - "AnyotherBlackbackground": 104, - "Anyothermixedbackground": 92, - "Anyotherwhitebackground": 114, - "AsianorAsianBritish": 125, - "Bangladeshi": 96, - "BlackorBlackBritish": 131, - "British": 114, - "Caribbean": 127, - "Chinese": 100, - "Indian": 110, - "Irish": 111, - "Mixed": 127, - "Otherethnicgroup": 116, - "Pakistani": 115, - "White": 105, - "WhiteandAsian": 114, - "WhiteandBlackAfrican": 115, - "WhiteandBlackCaribbean": 132 - } - } - }, - "eventGenders": { - "availability": true, - "availabilityCount": 1597, - "distribution": { - "genders": { - "female": 1271, - "male": 1233 - } - } - }, - "eventLocations": { - "availability": true, - "availabilityCount": 1597, - "distribution": { - "locations": { - "England": 322, - "NorthernIreland": 317, - "RepublicofIreland": 311, - "Scotland": 308, - "Wales": 339 - } - } - } - } - ], - "id": "CINECA_synthetic_cohort_UK1", - "inclusionCriteria": { - "ageRange": { - "end": { - "iso8601duration": "P65Y" - }, - "start": { - "iso8601duration": "P18Y" - } - }, - "genders": [ - { - "id": "NCIT:C16576", - "label": "female" - }, - { - "id": "NCIT:C20197", - "label": "male" - } - ], - "locations": [ - { - "id": "GAZ:00150372", - "label": "UK" - } - ] - }, - "name": "CINECA synthetic cohort UK1" - } -] \ No newline at end of file diff --git a/beacon/connections/omopcdm/data/datasets.json b/beacon/connections/omopcdm/data/datasets.json deleted file mode 100644 index 41d537c..0000000 --- a/beacon/connections/omopcdm/data/datasets.json +++ /dev/null @@ -1 +0,0 @@ -[{"createDateTime": "2021-12-29T20:33:40Z", "dataUseConditions": {"duoDataUse": [{"id": "DUO:0000019,DUO:00000020", "label": "publication required,publication required", "version": "7-1-19,7-1-19"}]}, "description": "Please note: This synthetic data set (with cohort participants / subjects marked with FAKE) has no identifiable data and cannot be used to make any inference about cohort data or results. The purpose of this dataset is to aid development of technical implementations for cohort data discovery, harmonization, access, and federated analysis. In support of FAIRness in data sharing, this dataset is made freely available under the Creative Commons Licence (CC-BY). Please ensure this preamble is included with this dataset and that the CINECA project (funding: EC H2020 grant 825775) is acknowledged. For any questions please contact isuru@ebi.ac.uk or cthomas@ebi.ac.uk This dataset (CINECA_synthetic_cohort_EUROPE_UK1) consists of 2521 samples which have genetic data based on 1000 Genomes data (https://www.nature.com/articles/nature15393), and synthetic subject attributes and phenotypic data derived from UKBiobank (https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1001779). These data were initially derived using the TOFU tool (https://github.com/spiros/tofu), which generates randomly generated values based on the UKBiobank data dictionary. Categorical values were randomly generated based on the data dictionary, continuous variables generated based on the distribution of values reported by the UK Biobank showcase, and date / time values were random. Additionally we split the phenotypes and attributes into 4 main classes - general, cancer, diabetes mellitus, and cardiac. We assigned the general attributes to all the samples, and the cardiac / diabetes mellitus / cancer attributes to a proportion of the total samples. Once the initial set of phenotypes and attributes were generated, the data data was checked for consistency and where possible dependent attributes were calculated from the independent variables generated by TOFU. For example, BMI was calculated from height and weight data, and age at death generated by date of death and date of birth. These data were then loaded to the development instance of Biosamples (https://www.ebi.ac.uk/biosamples/) which accessioned each of the samples. The genetic data are derived from the 1000 Genomes Phase 3 release (https://www.internationalgenome.org/category/phase-3/). The genotype data consists of a single joint call vcf files with call genotypes for all 2504 samples, plus bed, bim, fam, and nosex files generated via plink for these samples and genotypes. The genotype data has had a variety of errors introduced to mimic real data and as a test for quality control pipelines. These include gender mismatches, ethnic background mislabelling and low call rates for a randomly chosen subset of sample data as well as deviations from Hardy Weinberg equilibrium and low call rates for a random selection of variants. Additionally 40 samples have raw genetic data available in the form of both bam and cram files, including unmapped data. The gender of the samples in the 1000 genomes data has been matched to the synthetic phenotypic data generated for these samples. The genetic data was then linked to the synthetic data in BioSamples, and submitted to EGA.\",\"externalUrl\":\u00a0\"https://ega-archive.org/datasets/EGAD00001006673/", "externalUrl": "https://ega-archive.org/datasets/EGAD00001006673/", "id": "CINECA_synthetic_cohort_EUROPE_UK1", "info": {"beacon": {"contact": "manuel.rueda@crg.eu", "mapping": "ManuelRueda", "version": "v2.0"}, "dataset": {"derived": [{"EGA": {"contact": "helpdesk@ega-archive.org", "externalUrl": "https://ega-archive.org/datasets/EGAD00001006673", "license": {"$ref": "#/dataUseConditions/duoDataUse"}}}, {"BioSamples": {"contact": "biosamples@ebi.ac.uk", "externalUrl": "https://www.ebi.ac.uk/biosamples", "license": "CreativeCommonsLicence(CC-BY)"}}], "origin": [{"CINECAprojectEU": {"contact": "cthomas@ebi.ac.uk", "externalUrl": "https://www.cineca-project.eu/cineca-synthetic-dataset", "license": "CreativeCommonsLicence(CC-BY)", "managers": "ColineThomas,IsuruLiyanageandDylanSpalding"}}, {"1000Genomes": {"externalUrl": "https://www.internationalgenome.org/category/phase-3", "license": "CCBY-NC-SA3.0", "version": "v5aphase3VCF"}}]}}, "name": "CINECA_synthetic_cohort_EUROPE_UK1", "updateDateTime": "2021-12-29T20:33:40Z", "version": "v1.0"}] \ No newline at end of file diff --git a/beacon/connections/omopcdm/data/filtering_terms.json b/beacon/connections/omopcdm/data/filtering_terms.json deleted file mode 100644 index 23a750a..0000000 --- a/beacon/connections/omopcdm/data/filtering_terms.json +++ /dev/null @@ -1,23 +0,0 @@ -[ - { - "type": "alphanumeric", - "id": "libraryStrategy", - "scopes": [ - "run" - ] - }, - { - "type": "alphanumeric", - "id": "molecularAttributes.geneIds", - "scopes": [ - "genomicVariation" - ] - }, - { - "type": "alphanumeric", - "id": "diseases.ageOfOnset.iso8601duration", - "scopes": [ - "individual" - ] - } -] \ No newline at end of file diff --git a/beacon/connections/omopcdm/data/genomicVariations.json b/beacon/connections/omopcdm/data/genomicVariations.json deleted file 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diff --git a/beacon/connections/omopcdm/extract_filtering_terms.py b/beacon/connections/omopcdm/extract_filtering_terms.py deleted file mode 100644 index 0bed779..0000000 --- a/beacon/connections/omopcdm/extract_filtering_terms.py +++ /dev/null @@ -1,493 +0,0 @@ -import os.path -from typing import List, Dict, Optional -import re -from pymongo.mongo_client import MongoClient -import progressbar -from bson.objectid import ObjectId -from tqdm import tqdm -from bson.json_util import dumps -import json - -import sys -import os - - -current = os.path.dirname(os.path.realpath(__file__)) - - -parent = os.path.dirname(current) - - -sys.path.append(parent) - - -import conf - - -ONTOLOGY_REGEX = re.compile(r"([_A-Za-z0-9]+):([_A-Za-z0-9^\-]+)") -ICD_REGEX = re.compile(r"(ICD[_A-Za-z0-9]+):([_A-Za-z0-9^\./-]+)") - - -if conf.database_cluster: - uri = "mongodb+srv://{}:{}@{}/?tls=true&authMechanism=SCRAM-SHA-256&retrywrites=false&maxIdleTimeMS=120000".format( - conf.database_user, - conf.database_password, - conf.database_host - ) -else: - uri = "mongodb://{}:{}@{}:{}/{}?authSource={}".format( - conf.database_user, - conf.database_password, - conf.database_host, - conf.database_port, - conf.database_name, - conf.database_auth_source - ) - -if os.path.isfile(conf.database_certificate): - uri += '&tls=true&tlsCertificateKeyFile={}'.format(conf.database_certificate) - if os.path.isfile(conf.database_cafile): - uri += '&tlsCAFile={}'.format(conf.database_cafile) - -client = MongoClient(uri) -''' - -client = MongoClient( -client = MongoClient( - #"mongodb://127.0.0.1:27017/" - "mongodb://root:example@mongo:27017/beacon?authSource=admin" - -) -''' - -class MyProgressBar: - def __init__(self): - self.pbar = None - - def __call__(self, block_num: int, block_size: int, total_size: int): - if not self.pbar: - self.pbar = progressbar.ProgressBar(maxval=total_size) - self.pbar.start() - - downloaded = block_num * block_size - if downloaded < total_size: - self.pbar.update(downloaded) - else: - self.pbar.finish() - - -def get_ontology_field_name(ontology_id:str, term_id:str, collection:str): - biosamples=['biosampleStatus.id','diagnosticMarkers.id','histologicalDiagnosis.id','measurements.assayCode.id','measurements.measurementValue.id','measurements.measurementValue.referenceRange.unit.id','measurements.measurementValue.typedQuantities.quantity.unit.id','measurements.measurementValue.unit.id','measurements.observationMoment.id','measurements.procedure.bodySite.id','measurements.procedure.procedureCode.id','pathologicalStage.id','pathologicalTnmFinding.id','phenotypicFeatures.evidence.evidenceCode.id','phenotypicFeatures.evidence.reference.id','phenotypicFeatures.featureType.id','phenotypicFeatures.modifiers.id','phenotypicFeatures.onset.id','phenotypicFeatures.resolution.id','phenotypicFeatures.severity.id','sampleOriginDetail.id','sampleOriginType.id','sampleProcessing.id','sampleStorage.id','tumorGrade.id','tumorProgression.id'] - cohorts=['cohortDataTypes.id','cohortDesign.id','exclusionCriteria.diseaseConditions.diseaseCode.id','exclusionCriteria.diseaseConditions.severity.id','exclusionCriteria.diseaseConditions.stage.id','exclusionCriteria.ethnicities.id','exclusionCriteria.genders.id','exclusionCriteria.locations.id','exclusionCriteria.phenotypicConditions.featureType.id','exclusionCriteria.phenotypicConditions.severity.id','inclusionCriteria.diseaseConditions.diseaseCode.id','inclusionCriteria.diseaseConditions.severity.id','inclusionCriteria.diseaseConditions.stage.id','inclusionCriteria.ethnicities.id','inclusionCriteria.genders.id','inclusionCriteria.locations.id','inclusionCriteria.phenotypicConditions.featureType.id','inclusionCriteria.phenotypicConditions.severity.id'] - datasets=['dataUseConditions.duoDataUse.id'] - genomicVariations=['caseLevelData.alleleOrigin.id','caseLevelData.clinicalInterpretations.category.id','caseLevelData.clinicalInterpretations.effect.id','caseLevelData.clinicalInterpretations.evidenceType.id','caseLevelData.id','caseLevelData.phenotypicEffects.category.id','caseLevelData.phenotypicEffects.effect.id','caseLevelData.phenotypicEffects.evidenceType.id','caseLevelData.zygosity.id','identifiers.variantAlternativeIds.id','molecularAttributes.molecularEffects.id','variantLevelData.clinicalInterpretations.category.id','variantLevelData.clinicalInterpretations.effect.id','variantLevelData.clinicalInterpretations.evidenceType.id','variantLevelData.phenotypicEffects.category.id','variantLevelData.phenotypicEffects.effect.id','variantLevelData.phenotypicEffects.evidenceType.id'] - individuals=['diseases.ageOfOnset.id','diseases.diseaseCode.id','diseases.severity.id','diseases.stage.id','ethnicity.id','exposures.exposureCode.id','exposures.unit.id','geographicOrigin.id','interventionsOrProcedures.ageAtProcedure.id','interventionsOrProcedures.bodySite.id','interventionsOrProcedures.procedureCode.id','measures.assayCode.id','measures.measurementValue.id','measures.measurementValue.typedQuantities.quantity.unit.id','measures.measurementValue.unit.id','measures.observationMoment.id','measures.procedure.bodySite.id','measures.procedure.procedureCode.id','pedigrees.disease.diseaseCode.id','pedigrees.disease.severity.id','pedigrees.disease.stage.id','pedigrees.id','pedigrees.members.role.id','phenotypicFeatures.evidence.evidenceCode.id','phenotypicFeatures.evidence.reference.id','phenotypicFeatures.featureType.id','phenotypicFeatures.modifiers.id','phenotypicFeatures.onset.id','phenotypicFeatures.resolution.id','phenotypicFeatures.severity.id','sex.id','treatments.cumulativeDose.referenceRange.id','treatments.doseIntervals.id','treatments.routeOfAdministration.id','treatments.treatmentCode.id'] - runs=['librarySource.id','platformModel.id'] - array=[] - if collection == 'biosamples': - array=biosamples - elif collection == 'cohorts': - array=cohorts - elif collection == 'datasets': - array=datasets - elif collection == 'genomicVariations': - array=genomicVariations - elif collection == 'individuals': - array=individuals - elif collection == 'runs': - array=runs - query={} - query['$or']=[] - for field in array: - fieldquery={} - fieldquery[field]=ontology_id + ":" + term_id - query['$or'].append(fieldquery) - results = client.beacon.get_collection(collection).find(query).limit(1) - results = list(results) - results = dumps(results) - results = json.loads(results) - field = '' - for result in results: - for k, v in result.items(): - if isinstance(v, str): - if v == ontology_id + ':' + term_id: - field = k - for key, value in result.items(): - if key == 'label': - label = value - break - break - elif isinstance(v, dict): - for k2, v2 in v.items(): - if isinstance(v2, list): - for item_list in v2: - if isinstance(item_list, str): - if item_list == ontology_id + ':' + term_id: - field = k + '.' + k2 - for key, value in v.items(): - if key == 'label': - label = value - break - break - elif isinstance(item_list, dict): - for k21, v21 in item_list.items(): - if isinstance(v21, str): - if v21 == ontology_id + ':' + term_id: - field = k + '.' + k2 + '.' + k21 - for key, value in item_list.items(): - if key == 'label': - label = value - break - break - elif isinstance(v21,dict): - for k22, v22 in v21.items(): - if v22 == v21 == ontology_id + ':' + term_id: - field = k + '.' + k2 + '.' + k22 - for key, value in v21.items(): - if key == 'label': - label = value - break - break - elif v2 == ontology_id + ':' + term_id: - field = k + '.' + k2 - for key, value in v.items(): - if key == 'label': - label = value - break - break - elif isinstance(v, list): - for item in v: - if isinstance(item, str): - if item == ontology_id + ':' + term_id: - field = k - for key, value in result.items(): - if key == 'label': - label = value - break - break - elif isinstance(item, dict): - for k2, v2 in item.items(): - if isinstance(v2, str): - if v2 == ontology_id + ':' + term_id: - field = k + '.' + k2 - for key, value in item.items(): - if k == 'label': - label = v - break - break - elif isinstance(v2, dict): - for k3, v3 in v2.items(): - if isinstance(v3, str): - if v3 == ontology_id + ':' + term_id: - field = k + '.' + k2 + '.' + k3 - for key, value in v2.items(): - if key == 'label': - label = value - break - break - elif isinstance(v3, dict): - for k4, v4 in v3.items(): - if isinstance(v4, str): - if v4 == ontology_id + ':' + term_id: - field = k + '.' + k2 + '.' + k3 + '.' + k4 - for key, value in v3.items(): - if key == 'label': - label = value - break - break - elif isinstance(v4, dict): - for k5, v5 in v4.items(): - if v5 == ontology_id + ':' + term_id: - field = k + '.' + k2 + '.' + k3 + '.' + k4 + '.' + k5 - for key, value in v4.items(): - if key == 'label': - label = value - break - break - - - if '.' in field: - try: - final_field = '' - field_split = field.split('.') - del field_split[-1] - for item in field_split: - if final_field == '': - final_field = item - else: - final_field = final_field + '.' + item - final_dict={} - final_dict['field']=final_field - final_dict['label']=label - return final_dict - except Exception: - pass - else: - pass - - -def insert_all_ontology_terms_used(): - collections = client.beacon.list_collection_names() - if 'filtering_terms' in collections: - collections.remove('filtering_terms') - print("Collections:", collections) - for c_name in collections: - if c_name not in ['counts', 'similarities', 'synonyms', 'caseLevelData', 'targets']: - terms_ids = find_ontology_terms_used(c_name) - terms = get_filtering_object(terms_ids, c_name) - if len(terms) > 0: - client.beacon.filtering_terms.insert_many(terms) - -def find_ontology_terms_used(collection_name: str) -> List[Dict]: - print(collection_name) - terms_ids = [] - count = client.beacon.get_collection(collection_name).estimated_document_count() - if count < 10000: - num_total=count - else: - num_total=10000 - i=0 - if count > 10000: - while i < count: - xs = client.beacon.get_collection(collection_name).find().skip(i).limit(10000) - for r in tqdm(xs, total=num_total): - matches = ONTOLOGY_REGEX.findall(str(r)) - icd_matches = ICD_REGEX.findall(str(r)) - for ontology_id, term_id in matches: - term = ':'.join([ontology_id, term_id]) - if term not in terms_ids: - terms_ids.append(term) - for ontology_id, term_id in icd_matches: - term = ':'.join([ontology_id, term_id]) - if term not in terms_ids: - terms_ids.append(term) - i += 10000 - if i > 30000: - break - print(i) - else: - xs = client.beacon.get_collection(collection_name).find().skip(0).limit(10000) - for r in tqdm(xs, total=num_total): - matches = ONTOLOGY_REGEX.findall(str(r)) - icd_matches = ICD_REGEX.findall(str(r)) - for ontology_id, term_id in matches: - term = ':'.join([ontology_id, term_id]) - if term not in terms_ids: - terms_ids.append(term) - for ontology_id, term_id in icd_matches: - term = ':'.join([ontology_id, term_id]) - if term not in terms_ids: - terms_ids.append(term) - - return terms_ids - - - -def get_filtering_object(terms_ids: list, collection_name: str): - terms = [] - list_of_ontologies=[] - #ontologies = dict() - for onto in terms_ids: - ontology = onto.split(':') - ontology_id = ontology[0] - term_id = ontology[1] - #if ontology_id not in ontologies: - #ontologies[ontology_id] = load_ontology(ontology_id) - if ontology_id.isupper(): - field_dict = get_ontology_field_name(ontology_id, term_id, collection_name) - else: - continue - try: - field = field_dict['field'] - label = field_dict['label'] - value_id=None - if 'measurements.assayCode' in field: - value_id = label - else: - ontology_label = label - if field is not None: - if onto not in list_of_ontologies: - list_of_ontologies.append(onto) - if label: - terms.append({ - 'type': 'ontology', - 'id': onto, - 'label': ontology_label, - # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms - #'count': get_ontology_term_count(collection_name, onto), - 'scopes': [collection_name[0:-1]] - }) - - terms.append({ - 'type': 'alphanumeric', - 'id': field, - # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms - #'count': get_ontology_term_count(collection_name, onto), - 'scopes': [collection_name[0:-1]] - }) - terms.append({ - 'type': 'custom', - 'id': '{}:{}'.format(field,label), - # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms - #'count': get_ontology_term_count(collection_name, onto), - 'scopes': [collection_name[0:-1]] - }) - if value_id is not None: - terms.append({ - 'type': 'alphanumeric', - 'id': value_id, - # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms - #'count': get_ontology_term_count(collection_name, onto), - 'scopes': [collection_name[0:-1]] - }) - - print(terms) - except Exception: - pass - - return terms - - -def get_alphanumeric_term_count(collection_name: str, key: str) -> int: - return len(client.beacon\ - .get_collection(collection_name)\ - .distinct(key)) - -def get_properties_of_document(document, prefix="") -> List[str]: - properties = [] - if document is None or isinstance(document, str) or isinstance(document, int): - return [] - elif isinstance(document, list): - for elem in document: - properties += get_properties_of_document(elem, prefix) - elif isinstance(document, dict): - for key, value in document.items(): - if isinstance(value, ObjectId): - continue - elif value is None: - properties.append(prefix + '.' + key if prefix else key) - elif isinstance(value, int): - properties.append(prefix + '.' + key if prefix else key) - elif isinstance(value, str): - properties.append(prefix + '.' + key if prefix else key) - elif isinstance(value, list): - properties += get_properties_of_document(value, prefix + '.' + key if prefix else key) - elif isinstance(value, dict): - properties += get_properties_of_document(value, prefix + '.' + key if prefix else key) - else: - print('Unknown type:', value, ' (', type(value), ')') - exit(0) - else: - print('Unknown type2:', document, ' (', type(document), ')') - exit(0) - return properties - -def merge_ontology_terms(): - filtering_terms = client.beacon.filtering_terms.find({"type": "ontology"}) - array_of_ids=[] - repeated_ids=[] - new_terms=[] - for filtering_term in filtering_terms: - new_id=filtering_term["id"] - if new_id not in array_of_ids: - array_of_ids.append(new_id) - else: - repeated_ids.append(new_id) - #print("repeated_ids are {}".format(repeated_ids)) - for repeated_id in repeated_ids: - repeated_terms = client.beacon.filtering_terms.find({"id": repeated_id, "type": "ontology"}) - array_of_scopes=[] - for repeated_term in repeated_terms: - #print(repeated_term) - id=repeated_term["id"] - label=repeated_term["label"] - if repeated_term['scopes'] != []: - if repeated_term['scopes'][0] not in array_of_scopes: - array_of_scopes.append(repeated_term['scopes'][0]) - if array_of_scopes != []: - new_terms.append({ - 'type': 'ontology', - 'id': id, - 'label': label, - # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms - #'count': get_ontology_term_count(collection_name, onto), - 'scopes': array_of_scopes - }) - client.beacon.filtering_terms.delete_many({"id": repeated_id}) - if new_terms != []: - client.beacon.filtering_terms.insert_many(new_terms) - - -def merge_alphanumeric_terms(): - filtering_terms = client.beacon.filtering_terms.find({"type": "alphanumeric"}) - array_of_ids=[] - repeated_ids=[] - new_terms=[] - for filtering_term in filtering_terms: - new_id=filtering_term["id"] - if new_id not in array_of_ids: - array_of_ids.append(new_id) - else: - repeated_ids.append(new_id) - #print("repeated_ids are {}".format(repeated_ids)) - for repeated_id in repeated_ids: - repeated_terms = client.beacon.filtering_terms.find({"id": repeated_id, "type": "alphanumeric"}) - array_of_scopes=[] - for repeated_term in repeated_terms: - #print(repeated_term) - id=repeated_term["id"] - if repeated_term['scopes'] != []: - if repeated_term['scopes'][0] not in array_of_scopes: - array_of_scopes.append(repeated_term['scopes'][0]) - if array_of_scopes != []: - new_terms.append({ - 'type': 'alphanumeric', - 'id': id, - # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms - #'count': get_ontology_term_count(collection_name, onto), - 'scopes': array_of_scopes - }) - client.beacon.filtering_terms.delete_many({"id": repeated_id}) - if new_terms != []: - client.beacon.filtering_terms.insert_many(new_terms) - -def merge_custom_terms(): - filtering_terms = client.beacon.filtering_terms.find({"type": "custom"}) - array_of_ids=[] - repeated_ids=[] - new_terms=[] - for filtering_term in filtering_terms: - new_id=filtering_term["id"] - if new_id not in array_of_ids: - array_of_ids.append(new_id) - else: - repeated_ids.append(new_id) - #print("repeated_ids are {}".format(repeated_ids)) - for repeated_id in repeated_ids: - repeated_terms = client.beacon.filtering_terms.find({"id": repeated_id, "type": "custom"}) - array_of_scopes=[] - for repeated_term in repeated_terms: - #print(repeated_term) - id=repeated_term["id"] - if repeated_term['scopes'] != []: - if repeated_term['scopes'][0] not in array_of_scopes: - array_of_scopes.append(repeated_term['scopes'][0]) - if array_of_scopes != []: - new_terms.append({ - 'type': 'custom', - 'id': id, - # TODO: Use conf.py -> beaconGranularity to not disclouse counts in the filtering terms - #'count': get_ontology_term_count(collection_name, onto), - 'scopes': array_of_scopes - }) - client.beacon.filtering_terms.delete_many({"id": repeated_id}) - if new_terms != []: - client.beacon.filtering_terms.insert_many(new_terms) - - - - -insert_all_ontology_terms_used() -merge_ontology_terms() -merge_alphanumeric_terms() -merge_custom_terms() \ No newline at end of file diff --git a/beacon/connections/omopcdm/g_variants.py b/beacon/connections/omopcdm/g_variants.py deleted file mode 100644 index 19ca95d..0000000 --- a/beacon/connections/omopcdm/g_variants.py +++ /dev/null @@ -1,278 +0,0 @@ -from beacon.request.parameters import RequestParams -from beacon.response.schemas import DefaultSchemas -from beacon.connections.mongo.__init__ import client -from beacon.connections.mongo.utils import get_docs_by_response_type -from beacon.logs.logs import log_with_args, LOG -from beacon.conf.conf import level -from beacon.connections.mongo.filters import apply_filters -from beacon.connections.mongo.request_parameters import apply_request_parameters -from typing import Optional -from bson import json_util - -@log_with_args(level) -def get_variants(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'g_variants' - mongo_collection = client.beacon.genomicVariations - parameters_as_filters=False - query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) - if parameters_as_filters == True and query_parameters != {'$and': []}: - query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset)# pragma: no cover - query_parameters={}# pragma: no cover - elif query_parameters != {'$and': []}: - query=query_parameters - elif query_parameters == {'$and': []}: - query_parameters = {} - query={} - query = apply_filters(self, query, qparams.query.filters, collection,query_parameters, dataset) - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100 - schema = DefaultSchemas.GENOMICVARIATIONS - idq="caseLevelData.biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - #∫docs = json_util.dumps(docs) - - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_variant_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'g_variants' - mongo_collection = client.beacon.genomicVariations - query = {"$and": [{"variantInternalId": entry_id}]} - query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) - if parameters_as_filters == True: - query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset)# pragma: no cover - query_parameters={}# pragma: no cover - else: - query=query_parameters - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.GENOMICVARIATIONS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="caseLevelData.biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_biosamples_of_variant(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'g_variants' - mongo_collection = client.beacon.biosamples - query = {"$and": [{"variantInternalId": entry_id}]} - query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) - if parameters_as_filters == True: - query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset)# pragma: no cover - query_parameters={}# pragma: no cover - else: - query=query_parameters - collection='biosamples' - HGVSIds = client.beacon.genomicVariations \ - .find(query, {"identifiers.genomicHGVSId": 1, "datasetId": 1, "_id": 0}) - HGVSDataset=HGVSIds[0]["datasetId"] - if dataset != HGVSDataset: - schema = DefaultSchemas.BIOSAMPLES - return schema, 0, 0, [], dataset - HGVSIds=list(HGVSIds) - HGVSId=HGVSIds[0]["identifiers"]["genomicHGVSId"] - queryHGVSId={"datasetId": dataset, "id": HGVSId} - string_of_ids = client.beacon.caseLevelData \ - .find(queryHGVSId, {"biosampleIds": 1, "_id": 0}) - targets = client.beacon.targets \ - .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) - targets=list(targets) - list_of_targets=targets[0]["biosampleIds"] - list_of_positions_strings= string_of_ids[0]['biosampleIds'].split(',') - biosampleIds=[] - for position in list_of_positions_strings: - if position != '': - biosampleIds.append(list_of_targets[int(position)]) - finalids=biosampleIds - try: - finalids=[] - for bioid in biosampleIds: - finalids.append({"id": bioid}) - except Exception:# pragma: no cover - finalids=[] - query = {"$and": [{"$or": finalids}]} - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.BIOSAMPLES - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_runs_of_variant(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'g_variants' - mongo_collection = client.beacon.runs - query = {"$and": [{"variantInternalId": entry_id}]} - query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) - if parameters_as_filters == True: - query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset)# pragma: no cover - query_parameters={}# pragma: no cover - else: - query=query_parameters - collection='runs' - HGVSIds = client.beacon.genomicVariations \ - .find(query, {"identifiers.genomicHGVSId": 1, "datasetId": 1, "_id": 0}) - HGVSDataset=HGVSIds[0]["datasetId"] - if dataset != HGVSDataset: - schema = DefaultSchemas.INDIVIDUALS - return schema, 0, 0, [], dataset - HGVSIds=list(HGVSIds) - HGVSId=HGVSIds[0]["identifiers"]["genomicHGVSId"] - queryHGVSId={"datasetId": dataset, "id": HGVSId} - string_of_ids = client.beacon.caseLevelData \ - .find(queryHGVSId, {"biosampleIds": 1, "_id": 0}) - targets = client.beacon.targets \ - .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) - targets=list(targets) - list_of_targets=targets[0]["biosampleIds"] - list_of_positions_strings= string_of_ids[0]['biosampleIds'].split(',') - biosampleIds=[] - for position in list_of_positions_strings: - if position != '': - biosampleIds.append(list_of_targets[int(position)]) - try: - finalids=[] - for bioid in biosampleIds: - finalids.append({"biosampleId": bioid}) - except Exception:# pragma: no cover - finalids=[] - query = {"$and": [{"$or": finalids}]} - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.RUNS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_analyses_of_variant(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'g_variants' - mongo_collection = client.beacon.analyses - query = {"$and": [{"variantInternalId": entry_id}]} - query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) - if parameters_as_filters == True: - query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset)# pragma: no cover - query_parameters={}# pragma: no cover - else: - query=query_parameters - collection='analyses' - HGVSIds = client.beacon.genomicVariations \ - .find(query, {"identifiers.genomicHGVSId": 1, "datasetId": 1, "_id": 0}) - HGVSDataset=HGVSIds[0]["datasetId"] - if dataset != HGVSDataset: - schema = DefaultSchemas.INDIVIDUALS - return schema, 0, 0, [], dataset - HGVSIds=list(HGVSIds) - HGVSId=HGVSIds[0]["identifiers"]["genomicHGVSId"] - queryHGVSId={"datasetId": dataset, "id": HGVSId} - string_of_ids = client.beacon.caseLevelData \ - .find(queryHGVSId, {"biosampleIds": 1, "_id": 0}) - targets = client.beacon.targets \ - .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) - targets=list(targets) - list_of_targets=targets[0]["biosampleIds"] - list_of_positions_strings= string_of_ids[0]['biosampleIds'].split(',') - biosampleIds=[] - for position in list_of_positions_strings: - if position != '': - biosampleIds.append(list_of_targets[int(position)]) - try: - finalids=[] - for bioid in biosampleIds: - finalids.append({"biosampleId": bioid}) - except Exception:# pragma: no cover - finalids=[] - query = {"$and": [{"$or": finalids}]} - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.ANALYSES - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_individuals_of_variant(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'g_variants' - mongo_collection = client.beacon.individuals - query = {"$and": [{"variantInternalId": entry_id}]} - query_parameters, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset) - if parameters_as_filters == True: - query, parameters_as_filters = apply_request_parameters(self, query, qparams, dataset)# pragma: no cover - query_parameters={}# pragma: no cover - else: - query=query_parameters - collection='individuals' - HGVSIds = client.beacon.genomicVariations \ - .find(query, {"identifiers.genomicHGVSId": 1, "datasetId": 1, "_id": 0}) - HGVSIds=list(HGVSIds) - HGVSDataset=HGVSIds[0]["datasetId"] - if dataset != HGVSDataset: - schema = DefaultSchemas.INDIVIDUALS - return schema, 0, 0, [], dataset - HGVSId=HGVSIds[0]["identifiers"]["genomicHGVSId"] - queryHGVSId={"datasetId": HGVSDataset, "id": HGVSId} - string_of_ids = client.beacon.caseLevelData \ - .find(queryHGVSId, {"biosampleIds": 1, "_id": 0}) - targets = client.beacon.targets \ - .find({"datasetId": HGVSDataset}, {"biosampleIds": 1, "_id": 0}) - targets=list(targets) - list_of_targets=targets[0]["biosampleIds"] - list_of_positions_strings= string_of_ids[0]['biosampleIds'].split(',') - biosampleIds=[] - for position in list_of_positions_strings: - if position != '': - biosampleIds.append(list_of_targets[int(position)]) - try: - finalquery={} - finalquery["$or"]=[] - for finalid in biosampleIds: - query = {"id": finalid} - finalquery["$or"].append(query) - individual_id = client.beacon.biosamples \ - .find(finalquery, {"individualId": 1, "_id": 0}) - try: - finalids=[] - for indid in individual_id: - finalids.append(indid["individualId"]) - except Exception:# pragma: no cover - finalids=[] - if finalids==[]: - finalids=biosampleIds - except Exception: - finalids=biosampleIds - finalquery={} - finalquery["$or"]=[] - for finalid in finalids: - query = {"id": finalid} - finalquery["$or"].append(query) - superfinalquery={} - superfinalquery["$and"]=[finalquery] - query = apply_filters(self, superfinalquery, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.INDIVIDUALS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/get_descendants.py b/beacon/connections/omopcdm/get_descendants.py deleted file mode 100644 index 0385673..0000000 --- a/beacon/connections/omopcdm/get_descendants.py +++ /dev/null @@ -1,178 +0,0 @@ -import obonet -import networkx -import os -from typing import List, Dict, Optional -import urllib.request -from urllib.error import HTTPError -import progressbar -from pymongo.mongo_client import MongoClient -import os - - - -import conf - - -if conf.database_cluster: - uri = "mongodb+srv://{}:{}@{}/?tls=true&authMechanism=SCRAM-SHA-256&retrywrites=false&maxIdleTimeMS=120000".format( - conf.database_user, - conf.database_password, - conf.database_host - ) -else: - uri = "mongodb://{}:{}@{}:{}/{}?authSource={}".format( - conf.database_user, - conf.database_password, - conf.database_host, - conf.database_port, - conf.database_name, - conf.database_auth_source - ) - -if os.path.isfile(conf.database_certificate): - uri += '&tls=true&tlsCertificateKeyFile={}'.format(conf.database_certificate) - if os.path.isfile(conf.database_cafile): - uri += '&tlsCAFile={}'.format(conf.database_cafile) - -client = MongoClient(uri) - -class MyProgressBar: - def __init__(self): - self.pbar = None - - def __call__(self, block_num: int, block_size: int, total_size: int): - if not self.pbar: - self.pbar = progressbar.ProgressBar(maxval=total_size) - self.pbar.start() - - downloaded = block_num * block_size - if downloaded < total_size: - self.pbar.update(downloaded) - else: - self.pbar.finish() - -def load_ontology(ontology_id: str): - if ontology_id.isalpha(): - print(ontology_id) - url_alt = "https://www.ebi.ac.uk/efo/EFO.obo" - url = "http://purl.obolibrary.org/obo/{}.obo".format(ontology_id.lower()) - path = "/beacon/connections/mongo/ontologies/{}.obo".format(ontology_id) - try: - if not os.path.exists(path): - full_path = os.path.realpath(__file__) - print(full_path) - urllib.request.urlretrieve(url, path, MyProgressBar()) - except HTTPError: - # TODO: Handle error - #print("ERROR", HTTPError) - pass - except ValueError: - #print("ERROR", ValueError) - pass - except Exception: - pass - try: - #print (os.stat(path).st_size) - if os.stat(path).st_size == 0: - try: - urllib.request.urlretrieve(url_alt, path, MyProgressBar()) - except HTTPError: - # TODO: Handle error - #print("ERROR", HTTPError) - pass - except ValueError: - #print("ERROR", ValueError) - pass - except Exception: - pass - return '{}'.format(ontology_id) - - -def get_descendants_and_similarities(): - try: - client.beacon.drop_collection("similarities") - except Exception: - client.beacon.create_collection(name="similarities") - try: - client.beacon.validate_collection("similarities") - except Exception: - db=client.beacon.create_collection(name="similarities") - filtering_docs=client.beacon.filtering_terms.find({"type": "ontology"}) - array_of_ontologies=[] - for ft_doc in filtering_docs: - if ft_doc["id"] not in array_of_ontologies: - array_of_ontologies.append(ft_doc["id"]) - for ontology in array_of_ontologies: - ontology_list = ontology.split(':') - load_ontology(ontology_list[0]) - url = "/beacon/connections/mongo/ontologies/{}.obo".format(ontology_list[0].lower()) - list_of_cousins = [] - list_of_brothers = [] - list_of_uncles = [] - list_of_grandpas = [] - url_alt = "https://www.ebi.ac.uk/efo/EFO.obo" - try: - graph = obonet.read_obo(url) - except Exception: - graph = obonet.read_obo(url_alt) - try: - descendants = networkx.ancestors(graph, ontology) - except Exception: - descendants = '' - descendants=list(descendants) - - print(descendants) - - - try: - tree = [n for n in graph.successors(ontology)] - for onto in tree: - predecessors = [n for n in graph.successors(onto)] - successors = [n for n in graph.predecessors(onto)] - list_of_brothers.append(successors) - list_of_grandpas.append(predecessors) - similarity_high=[] - similarity_medium=[] - similarity_low=[] - for llista in list_of_grandpas: - for item in llista: - uncles = [n for n in graph.predecessors(item)] - list_of_uncles.append(uncles) - for uncle in uncles: - cousins = [n for n in graph.predecessors(uncle)] - if ontology not in cousins: - list_of_cousins.append(cousins) - - for llista in list_of_brothers: - for item in llista: - similarity_high.append(item) - similarity_medium.append(item) - similarity_low.append(item) - - for llista in list_of_cousins: - for item in llista: - similarity_medium.append(item) - similarity_low.append(item) - - for llista in list_of_uncles: - for item in llista: - similarity_low.append(item) - - except Exception: - similarity_high=[] - similarity_medium=[] - similarity_low=[] - - dict={} - dict['id']=ontology - dict['descendants']=descendants - dict['similarity_high']=similarity_high - dict['similarity_medium']=similarity_medium - dict['similarity_low']=similarity_low - - client.beacon.similarities.insert_one(dict) - print("succesfully retrieved descendants from {}".format(ontology)) - - -get_descendants_and_similarities() - diff --git a/beacon/connections/omopcdm/mongo-init/init.js b/beacon/connections/omopcdm/mongo-init/init.js deleted file mode 100644 index a4112e9..0000000 --- a/beacon/connections/omopcdm/mongo-init/init.js +++ /dev/null @@ -1,27 +0,0 @@ -conn = new Mongo({ useUnifiedTopology: true }); -db = conn.getDB("beacon"); - - -// db.beacon.createIndex({ "address.zip": 1 }, { unique: false }); -// db.beacon.insert({ "address": { "city": "Paris", "zip": "123" }, "name": "Mike", "phone": "1234" }); -// db.beacon.insert({ "address": { "city": "Marsel", "zip": "321" }, "name": "Helga", "phone": "4321" }); - -// Create collections - -db.createCollection("analyses"); -db.createCollection("biosamples"); -db.createCollection("cohorts"); -db.createCollection("datasets"); -db.createCollection("genomicVariations"); -db.createCollection("individuals"); -db.createCollection("runs"); - -// Create indexes for all the entities in the database - -db.analyses.createIndex([('$**', 'text')]); -db.biosamples.createIndex([('$**', 'text')]); -db.cohorts.createIndex([('$**', 'text')]); -db.datasets.createIndex([('$**', 'text')]); -db.genomicVariations.createIndex([('$**', 'text')]); -db.individuals.createIndex([('$**', 'text')]); -db.runs.createIndex([('$**', 'text')]); diff --git a/beacon/connections/omopcdm/ontologies/example.txt b/beacon/connections/omopcdm/ontologies/example.txt deleted file mode 100644 index e69de29..0000000 diff --git a/beacon/connections/omopcdm/ping.py b/beacon/connections/omopcdm/ping.py deleted file mode 100644 index 2a4ee63..0000000 --- a/beacon/connections/omopcdm/ping.py +++ /dev/null @@ -1,33 +0,0 @@ -from pymongo.mongo_client import MongoClient -from pymongo.errors import ConnectionFailure -import conf -import os -from beacon.logs.logs import LOG - - -if conf.database_cluster: - uri = "mongodb+srv://{}:{}@{}/?tls=true&authMechanism=SCRAM-SHA-256&retrywrites=false&maxIdleTimeMS=120000".format( - conf.database_user, - conf.database_password, - conf.database_host - ) -else: - uri = "mongodb://{}:{}@{}:{}/{}?authSource={}".format( - conf.database_user, - conf.database_password, - conf.database_host, - conf.database_port, - conf.database_name, - conf.database_auth_source - ) - -if os.path.isfile(conf.database_certificate): - uri += '&tls=true&tlsCertificateKeyFile={}'.format(conf.database_certificate) - if os.path.isfile(conf.database_cafile): - uri += '&tlsCAFile={}'.format(conf.database_cafile) - -client = MongoClient(uri, serverSelectionTimeoutMS=30000) -try: - client.admin.command('ping') -except ConnectionFailure as err: - LOG.debug(f"Database error encountered: {err}") \ No newline at end of file diff --git a/beacon/connections/omopcdm/reindex.py b/beacon/connections/omopcdm/reindex.py deleted file mode 100644 index 4100094..0000000 --- a/beacon/connections/omopcdm/reindex.py +++ /dev/null @@ -1,79 +0,0 @@ -from pymongo.mongo_client import MongoClient -import conf -import os - - -if conf.database_cluster: - uri = "mongodb+srv://{}:{}@{}/?tls=true&authMechanism=SCRAM-SHA-256&retrywrites=false&maxIdleTimeMS=120000".format( - conf.database_user, - conf.database_password, - conf.database_host - ) -else: - uri = "mongodb://{}:{}@{}:{}/{}?authSource={}".format( - conf.database_user, - conf.database_password, - conf.database_host, - conf.database_port, - conf.database_name, - conf.database_auth_source - ) - -if os.path.isfile(conf.database_certificate): - uri += '&tls=true&tlsCertificateKeyFile={}'.format(conf.database_certificate) - if os.path.isfile(conf.database_cafile): - uri += '&tlsCAFile={}'.format(conf.database_cafile) - -client = MongoClient(uri) -try: - client.beacon.drop_collection("synonyms") -except Exception: - client.beacon.create_collection(name="synonyms") -try: - client.beacon.validate_collection("synonyms") -except Exception: - db=client.beacon.create_collection(name="synonyms") -try: - client.beacon.validate_collection("targets") -except Exception: - db=client.beacon.create_collection(name="targets") -try: - client.beacon.validate_collection("caseLevelData") -except Exception: - db=client.beacon.create_collection(name="caseLevelData") -try: - client.beacon.drop_collection("counts") -except Exception: - client.beacon.create_collection(name="counts") -try: - client.beacon.validate_collection("counts") -except Exception: - db=client.beacon.create_collection(name="counts") -try: - client.beacon.drop_collection("similarities") -except Exception: - client.beacon.create_collection(name="similarities") -try: - client.beacon.validate_collection("similarities") -except Exception: - db=client.beacon.create_collection(name="similarities") -#client.beacon.analyses.create_index([("$**", "text")]) -#client.beacon.biosamples.create_index([("$**", "text")]) -#client.beacon.cohorts.create_index([("$**", "text")]) -#client.beacon.datasets.create_index([("$**", "text")]) -#client.beacon.genomicVariations.create_index([("$**", "text")]) -#client.beacon.genomicVariations.create_index([("caseLevelData.biosampleId", 1)]) -#client.beacon.genomicVariations.create_index([("variation.location.interval.end.value", -1), ("variation.location.interval.start.value", 1)]) -client.beacon.genomicVariations.create_index([("datasetId", 1)]) -client.beacon.genomicVariations.create_index([("variantInternalId", 1)]) -client.beacon.genomicVariations.create_index([("variation.location.interval.start.value", 1)]) -#client.beacon.genomicVariations.create_index([("variation.location.interval.start.value", 1), ("variation.location.interval.end.value", -1)]) -client.beacon.genomicVariations.create_index([("identifiers.genomicHGVSId", 1)]) -#client.beacon.genomicVariations.create_index([("datasetId", 1), ("variation.location.interval.start.value", 1), ("variation.referenceBases", 1), ("variation.alternateBases", 1)]) -client.beacon.genomicVariations.create_index([("molecularAttributes.geneIds", 1), ("variation.variantType", 1)]) -client.beacon.caseLevelData.create_index([("id", 1), ("datasetId", 1)]) -#client.beacon.individuals.create_index([("$**", "text")]) -#client.beacon.runs.create_index([("$**", "text")]) -#collection_name = client.beacon.analyses -#print(collection_name.index_information()) - diff --git a/beacon/connections/omopcdm/runs.py b/beacon/connections/omopcdm/runs.py deleted file mode 100644 index 14151b9..0000000 --- a/beacon/connections/omopcdm/runs.py +++ /dev/null @@ -1,111 +0,0 @@ -from beacon.request.parameters import RequestParams -from beacon.response.schemas import DefaultSchemas -import yaml -from beacon.connections.mongo.__init__ import client -from beacon.connections.mongo.utils import get_docs_by_response_type, query_id -from beacon.logs.logs import log_with_args, LOG -from beacon.conf.conf import level -from beacon.connections.mongo.filters import apply_filters -from beacon.connections.mongo.request_parameters import apply_request_parameters -from typing import Optional - -@log_with_args(level) -def get_runs(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'runs' - mongo_collection = client.beacon.runs - parameters_as_filters=False - query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset) - if parameters_as_filters == True: - query, parameters_as_filters = apply_request_parameters(self, {}, qparams, dataset)# pragma: no cover - query_parameters={}# pragma: no cover - else: - query={} - query = apply_filters(self, query, qparams.query.filters, collection, query_parameters, dataset) - schema = DefaultSchemas.RUNS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100 - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_run_with_id(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'runs' - mongo_collection = client.beacon.runs - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - schema = DefaultSchemas.RUNS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_variants_of_run(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'runs' - mongo_collection = client.beacon.genomicVariations - query = {"$and": [{"id": entry_id}]} - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - run_ids = client.beacon.runs \ - .find_one(query, {"biosampleId": 1, "_id": 0}) - targets = client.beacon.targets \ - .find({"datasetId": dataset}, {"biosampleIds": 1, "_id": 0}) - position=0 - bioids=targets[0]["biosampleIds"] - for bioid in bioids: - if bioid == run_ids["biosampleId"]: - break - position+=1 - position=str(position) - position1="^"+position+"," - position2=","+position+"," - position3=","+position+"$" - query_cl={ "$or": [ - {"biosampleIds": {"$regex": position1}}, - {"biosampleIds": {"$regex": position2}}, - {"biosampleIds": {"$regex": position3}} - ]} - string_of_ids = client.beacon.caseLevelData \ - .find(query_cl, {"id": 1, "_id": 0}) - HGVSIds=list(string_of_ids) - query={} - queryHGVS={} - listHGVS=[] - for HGVSId in HGVSIds: - justid=HGVSId["id"] - listHGVS.append(justid) - queryHGVS["$in"]=listHGVS - query["identifiers.genomicHGVSId"]=queryHGVS - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.GENOMICVARIATIONS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="caseLevelData.biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args(level) -def get_analyses_of_run(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'runs' - mongo_collection = client.beacon.analyses - query = {"runId": entry_id} - query = apply_filters(self, query, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.RUNS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset \ No newline at end of file From e5df112db07e773f2dc0a216fb2a156a0e7477b8 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Thu, 2 Jan 2025 10:20:23 +0100 Subject: [PATCH 13/20] Remove unused functions and remove blank lines --- beacon/connections/omopcdm/__init__.py | 3 - beacon/connections/omopcdm/biosamples.py | 20 +-- beacon/connections/omopcdm/cohorts.py | 21 +-- beacon/connections/omopcdm/datasets.py | 87 +-------- beacon/connections/omopcdm/executor.py | 3 - beacon/connections/omopcdm/filtering_terms.py | 2 +- beacon/connections/omopcdm/filters.py | 8 - beacon/connections/omopcdm/individuals.py | 10 +- beacon/connections/omopcdm/mappings.py | 29 ++- beacon/connections/omopcdm/utils.py | 165 +----------------- 10 files changed, 26 insertions(+), 322 deletions(-) diff --git a/beacon/connections/omopcdm/__init__.py b/beacon/connections/omopcdm/__init__.py index f22caed..87cc929 100644 --- a/beacon/connections/omopcdm/__init__.py +++ b/beacon/connections/omopcdm/__init__.py @@ -1,8 +1,5 @@ from beacon.connections.omopcdm import conf import psycopg2 -import os -from beacon.logs.logs import log_with_args, LOG - uri = "postgresql://{}:{}@{}:{}/{}".format( conf.database_user, diff --git a/beacon/connections/omopcdm/biosamples.py b/beacon/connections/omopcdm/biosamples.py index 4f42878..50e5fb1 100644 --- a/beacon/connections/omopcdm/biosamples.py +++ b/beacon/connections/omopcdm/biosamples.py @@ -139,22 +139,4 @@ def get_biosamples_with_person_id(person_id: Optional[str], qparams: RequestPara if not listSpecimenIds: return 0, {} docs = retrieveRecords(listSpecimenIds) - return len(listSpecimenIds), docs - -@log_with_args(level) -def get_variants_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - schema = DefaultSchemas.GENOMICVARIATIONS - - return schema, 0, 0, {}, dataset - -@log_with_args(level) -def get_analyses_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - schema = DefaultSchemas.ANALYSES - - return schema, 0, 0, {}, dataset - -@log_with_args(level) -def get_runs_of_biosample(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - schema = DefaultSchemas.RUNS - - return schema, 0, 0, {}, dataset \ No newline at end of file + return len(listSpecimenIds), docs \ No newline at end of file diff --git a/beacon/connections/omopcdm/cohorts.py b/beacon/connections/omopcdm/cohorts.py index a5fff1a..34041f5 100644 --- a/beacon/connections/omopcdm/cohorts.py +++ b/beacon/connections/omopcdm/cohorts.py @@ -231,26 +231,7 @@ def get_individuals_of_cohort(self, entry_id: Optional[str], qparams: RequestPar return get_individuals(self, [listIds], qparams, dataset) - - return schema, 0, 0, {}, dataset - -@log_with_args_mongo(level) -def get_analyses_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - - schema = DefaultSchemas.ANALYSES - return schema, 0, 0, {}, dataset - -@log_with_args_mongo(level) -def get_variants_of_cohort(self,entry_id: Optional[str], qparams: RequestParams, dataset: str): - - schema = DefaultSchemas.GENOMICVARIATIONS# pragma: no cover - return schema, 0, 0, {}, dataset - -@log_with_args_mongo(level) -def get_runs_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - schema = DefaultSchemas.RUNS - return schema, 0, 0, {}, dataset - +# To Do @log_with_args_mongo(level) def get_biosamples_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): diff --git a/beacon/connections/omopcdm/datasets.py b/beacon/connections/omopcdm/datasets.py index 19d8640..b7633c7 100644 --- a/beacon/connections/omopcdm/datasets.py +++ b/beacon/connections/omopcdm/datasets.py @@ -1,5 +1,5 @@ from beacon.connections.mongo.__init__ import client -from beacon.logs.logs import log_with_args_mongo +from beacon.logs.logs import log_with_args from beacon.conf.conf import level from beacon.exceptions.exceptions import raise_exception from beacon.connections.mongo.utils import get_count, get_documents @@ -10,7 +10,7 @@ from beacon.connections.mongo.utils import get_docs_by_response_type, query_id, get_cross_query from beacon.connections.mongo.request_parameters import apply_request_parameters -@log_with_args_mongo(level) +@log_with_args(level) def get_datasets(self): try: collection = client.beacon.datasets @@ -22,7 +22,7 @@ def get_datasets(self): errcode=500 raise_exception(err, errcode) -@log_with_args_mongo(level) +@log_with_args(level) def get_full_datasets(self, entry_id: Optional[str], qparams: RequestParams): try: collection = client.beacon.datasets @@ -42,7 +42,7 @@ def get_full_datasets(self, entry_id: Optional[str], qparams: RequestParams): errcode=500 raise_exception(err, errcode) -@log_with_args_mongo(level) +@log_with_args(level) def get_list_of_datasets(self): try: datasets = get_datasets(self) @@ -53,7 +53,7 @@ def get_list_of_datasets(self): errcode=500 raise_exception(err, errcode) -@log_with_args_mongo(level) +@log_with_args(level) def get_dataset_with_id(self, entry_id: Optional[str], qparams: RequestParams): limit = qparams.query.pagination.limit query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, entry_id) @@ -75,33 +75,7 @@ def get_dataset_with_id(self, entry_id: Optional[str], qparams: RequestParams): ) return response_converted, count, schema -@log_with_args_mongo(level) -def get_variants_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'datasets' - mongo_collection = client.beacon.genomicVariations - dataset_count=0 - limit = qparams.query.pagination.limit - query_count={} - idq="caseLevelData.biosampleId" - query_count["$or"]=[] - if dataset == entry_id: - queryid={} - queryid["datasetId"]=dataset - query_count["$or"].append(queryid) - else: - schema = DefaultSchemas.GENOMICVARIATIONS# pragma: no cover - return schema, 0, 0, None, dataset# pragma: no cover - query = apply_filters(self, query_count, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.GENOMICVARIATIONS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args_mongo(level) +@log_with_args(level) def get_biosamples_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): collection = 'datasets' mongo_collection = client.beacon.biosamples @@ -123,7 +97,7 @@ def get_biosamples_of_dataset(self, entry_id: Optional[str], qparams: RequestPar count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) return schema, count, dataset_count, docs, dataset -@log_with_args_mongo(level) +@log_with_args(level) def get_individuals_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): collection = 'datasets' mongo_collection = client.beacon.individuals @@ -143,51 +117,4 @@ def get_individuals_of_dataset(self, entry_id: Optional[str], qparams: RequestPa limit = 100# pragma: no cover idq="id" count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset - -@log_with_args_mongo(level) -def get_runs_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'datasets' - mongo_collection = client.beacon.runs - dataset_count=0 - limit = qparams.query.pagination.limit - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.datasets, query) - dict_in={} - dict_in['datasetId']=dataset - query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.RUNS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="biosampleId" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - list_of_records = ( - [r for r in docs] if docs else [] - ) - return schema, count, dataset_count, list_of_records, dataset - -@log_with_args_mongo(level) -def get_analyses_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'datasets' - idq="biosampleId" - mongo_collection = client.beacon.analyses - dataset_count=0 - limit = qparams.query.pagination.limit - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.datasets, query) - dict_in={} - dict_in['datasetId']=dataset - query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) - schema = DefaultSchemas.ANALYSES - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) return schema, count, dataset_count, docs, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/executor.py b/beacon/connections/omopcdm/executor.py index 21b15ec..84eceb9 100644 --- a/beacon/connections/omopcdm/executor.py +++ b/beacon/connections/omopcdm/executor.py @@ -17,9 +17,6 @@ async def execute_function(self, entry_type: str, datasets: list, qparams: Reque datasets_docs={} datasets_count={} new_count=0 - LOG.debug(f"entry_type {entry_type}") - LOG.debug(f"datasets {datasets}") - LOG.debug(f"qparams {qparams}") if entry_id == None: if entry_type == 'individuals': diff --git a/beacon/connections/omopcdm/filtering_terms.py b/beacon/connections/omopcdm/filtering_terms.py index 2b415a2..c726982 100644 --- a/beacon/connections/omopcdm/filtering_terms.py +++ b/beacon/connections/omopcdm/filtering_terms.py @@ -2,9 +2,9 @@ from typing import Optional from beacon.response.schemas import DefaultSchemas from beacon.request.parameters import RequestParams - import aiosql from pathlib import Path + queries_file = Path(__file__).parent / "sql" / "filteringTerms.sql" filteringTerms_queries = aiosql.from_path(queries_file, "psycopg2") diff --git a/beacon/connections/omopcdm/filters.py b/beacon/connections/omopcdm/filters.py index b913436..e04cfc0 100644 --- a/beacon/connections/omopcdm/filters.py +++ b/beacon/connections/omopcdm/filters.py @@ -5,7 +5,6 @@ from beacon.connections.omopcdm.__init__ import client from beacon.logs.logs import log_with_args, LOG from beacon.conf.conf import level - import aiosql from pathlib import Path @@ -163,13 +162,6 @@ def apply_alphanumeric_filter(self, filter: AlphanumericFilter) -> str: formatted_value = format_value(self, filter.value) - # # If value is string - # if isinstance(formatted_value,str): - # if filter.id in conf.alphanumeric_terms: - # filter.id = filter.id# pragma: no cover - # else: - # filter.id = filter.id + '.' + 'label' - # else: # # Age Alphanumeric filters if (filter.id == 'ageOfOnset' or filter.id == 'ageAtProcedure' or diff --git a/beacon/connections/omopcdm/individuals.py b/beacon/connections/omopcdm/individuals.py index a79bb48..0421264 100644 --- a/beacon/connections/omopcdm/individuals.py +++ b/beacon/connections/omopcdm/individuals.py @@ -6,12 +6,11 @@ from beacon.conf.conf import level from beacon.connections.omopcdm.filters import apply_filters from typing import Optional - import beacon.connections.omopcdm.mappings as mappings from beacon.connections.omopcdm.biosamples import get_biosamples_with_person_id - import aiosql from pathlib import Path + queries_file = Path(__file__).parent / "sql" / "individuals.sql" individual_queries = aiosql.from_path(queries_file, "psycopg2") @@ -232,13 +231,6 @@ def get_individual_with_id(self, entry_id: Optional[str], qparams: RequestParams return schema, 1, 1, docs, dataset -# OMOP CDM do not work with variants -@log_with_args(level) -def get_variants_of_individual(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - schema = DefaultSchemas.GENOMICVARIATIONS - - return schema, 0, 0, {}, dataset - @log_with_args(level) def get_biosamples_of_individual(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): diff --git a/beacon/connections/omopcdm/mappings.py b/beacon/connections/omopcdm/mappings.py index 57a44fd..e5c6b76 100644 --- a/beacon/connections/omopcdm/mappings.py +++ b/beacon/connections/omopcdm/mappings.py @@ -1,21 +1,6 @@ # File for all the mappings from the Beacon v2 specification and the results of the SQL Queries -## Individual model ## - -def diseases_table_map(dictValues): - return { - 'diseaseCode': dictValues["condition_concept_id"], - 'ageOfOnset': {'iso8601duration': dictValues["condition_ageOfOnset"]}, - } - -def procedures_table_map(dictValues): - return { - 'procedureCode': dictValues["procedure_concept_id"], - 'ageAtProcedure': {'iso8601duration': dictValues["procedure_ageOfOnset"]}, - 'dateOfProcedure': dictValues["procedure_date"], - } - def isfloat(num): try: float(num) @@ -30,8 +15,20 @@ def convertToNum(num): except ValueError: pass - +## Individual model ## + +def diseases_table_map(dictValues): + return { + 'diseaseCode': dictValues["condition_concept_id"], + 'ageOfOnset': {'iso8601duration': dictValues["condition_ageOfOnset"]}, + } +def procedures_table_map(dictValues): + return { + 'procedureCode': dictValues["procedure_concept_id"], + 'ageAtProcedure': {'iso8601duration': dictValues["procedure_ageOfOnset"]}, + 'dateOfProcedure': dictValues["procedure_date"], + } def measures_table_map(dictValues): # TO DO diff --git a/beacon/connections/omopcdm/utils.py b/beacon/connections/omopcdm/utils.py index fed3ccb..87353d0 100644 --- a/beacon/connections/omopcdm/utils.py +++ b/beacon/connections/omopcdm/utils.py @@ -1,14 +1,8 @@ -from pymongo.cursor import Cursor from beacon.connections.omopcdm.__init__ import client -from pymongo.collection import Collection -from beacon.logs.logs import log_with_args_mongo, LOG -from beacon.conf.conf import level -from bson import json_util - import itertools - import aiosql from pathlib import Path + queries_file = Path(__file__).parent / "sql" / "basic_queries.sql" basic_queries = aiosql.from_path(queries_file, "psycopg2") @@ -49,159 +43,4 @@ def search_ontologies(dictValues): label = "No matching concept" id = "None:No matching concept" dictVariableValue[variable] = {'id':id, 'label':label} - return dictValues - -@log_with_args_mongo(level) -def get_cross_query(self, ids: dict, cross_type: str, collection_id: str): - id_list=[] - dict_in={} - id_dict={} - if cross_type == 'biosampleId' or cross_type=='id':# pragma: no cover - list_item=ids - id_list.append(str(list_item)) - dict_in["$in"]=id_list - id_dict[collection_id]=dict_in - query = id_dict - elif cross_type == 'individualIds' or cross_type=='biosampleIds': - list_individualIds=ids - dict_in["$in"]=list_individualIds - id_dict[collection_id]=dict_in - query = id_dict - else:# pragma: no cover - for k, v in ids.items(): - for item in v: - id_list.append(item[cross_type]) - dict_in["$in"]=id_list - id_dict[collection_id]=dict_in - query = id_dict - - return query - -@log_with_args_mongo(level) -def query_id(self, query: dict, document_id) -> dict: - query["id"] = document_id - return query - -@log_with_args_mongo(level) -def join_query(self, collection: Collection,query: dict, original_id): - #LOG.debug(query) - excluding_fields={"_id": 0, original_id: 1} - return collection.find(query, excluding_fields).max_time_ms(100 * 1000) - -@log_with_args_mongo(level) -def get_documents(self, collection: Collection, query: dict, skip: int, limit: int) -> Cursor: - return collection.find(query,{"_id": 0, "datasetId": 0}).skip(skip).limit(limit).max_time_ms(100 * 1000) - -@log_with_args_mongo(level) -def get_documents_for_cohorts(self, collection: Collection, query: dict, skip: int, limit: int) -> Cursor: - return collection.find(query,{"_id": 0}).skip(skip).limit(limit).max_time_ms(100 * 1000) - -@log_with_args_mongo(level) -def get_count(self, collection: Collection, query: dict) -> int: - if not query: - return collection.estimated_document_count() - else: - counts=client.beacon.counts.find({"id": str(query), "collection": str(collection)}) - try: - counts=list(counts) - if counts == []: - total_counts=collection.count_documents(query) - insert_dict={} - insert_dict['id']=str(query) - insert_dict['num_results']=total_counts# pragma: no cover - insert_dict['collection']=str(collection)# pragma: no cover - insert_total=client.beacon.counts.insert_one(insert_dict)# pragma: no cover - else: - total_counts=counts[0]["num_results"] - except Exception as e:# pragma: no cover - LOG.debug(e) - insert_dict={} - insert_dict['id']=str(query) - total_counts=0 - insert_dict['num_results']=total_counts# pragma: no cover - insert_dict['collection']=str(collection)# pragma: no cover - insert_total=client.beacon.counts.insert_one(insert_dict) - return total_counts - -@log_with_args_mongo(level) -def get_docs_by_response_type(self, include: str, query: dict, dataset: str, limit: int, skip: int, mongo_collection, idq: str): - if include == 'NONE': - count = get_count(self, mongo_collection, query) - dataset_count=0 - docs = get_documents( - self, - mongo_collection, - query, - skip*limit, - limit - ) - elif include == 'ALL': - count=0 - query_count=query - i=1 - query_count["$or"]=[] - queryid={} - queryid['datasetId']=dataset - query_count["$or"].append(queryid) - if query_count["$or"]!=[]: - dataset_count = get_count(self, mongo_collection, query_count) - docs = get_documents( - self, - mongo_collection, - query_count, - skip*limit, - limit - ) - docs=list(docs) - elif include == 'HIT': - count=0 - query_count=query - query_count["$or"]=[] - queryid={} - queryid['datasetId']=dataset - query_count["$or"].append(queryid) - if query_count["$or"]!=[]: - dataset_count = get_count(self, mongo_collection, query_count) - if dataset_count == 0: - docs = [] - else: - docs = get_documents( - self, - mongo_collection, - query_count, - skip*limit, - limit - ) - docs=list(docs) - else: - dataset_count=0# pragma: no cover - if dataset_count==0: - return count, -1, None - elif include == 'MISS': - count=0 - query_count=query - i=1 - query_count["$or"]=[] - queryid={} - queryid['datasetId']=dataset - query_count["$or"].append(queryid) - if query_count["$or"]!=[]: - dataset_count = get_count(self, mongo_collection, query_count) - docs = get_documents( - self, - mongo_collection, - query_count, - skip*limit, - limit - ) - docs=list(docs) - else: - dataset_count=0# pragma: no cover - if dataset_count !=0: - return count, -1, None - return count, dataset_count, docs - -@log_with_args_mongo(level) -def get_filtering_documents(self, collection: Collection, query: dict, remove_id: dict,skip: int, limit: int) -> Cursor: - ##LOG.debug("FINAL QUERY: {}".format(query)) - return collection.find(query,remove_id).skip(skip).limit(limit).max_time_ms(100 * 1000) \ No newline at end of file + return dictValues \ No newline at end of file From 1156404352675448eb5bed3396633841fa5fe790 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Thu, 2 Jan 2025 14:57:05 +0100 Subject: [PATCH 14/20] Add cohorts links to other schemas --- beacon/connections/omopcdm/biosamples.py | 3 +- beacon/connections/omopcdm/cohorts.py | 41 +++++++++++-------- beacon/connections/omopcdm/individuals.py | 6 +-- beacon/connections/omopcdm/sql/biosamples.sql | 2 +- .../connections/omopcdm/sql/individuals.sql | 12 ++++-- 5 files changed, 39 insertions(+), 25 deletions(-) diff --git a/beacon/connections/omopcdm/biosamples.py b/beacon/connections/omopcdm/biosamples.py index 50e5fb1..824cf59 100644 --- a/beacon/connections/omopcdm/biosamples.py +++ b/beacon/connections/omopcdm/biosamples.py @@ -133,8 +133,7 @@ def get_biosample_with_id(self, entry_id: Optional[str], qparams: RequestParams, # Function to get all the biosamples from an individual id def get_biosamples_with_person_id(person_id: Optional[str], qparams: RequestParams): - schema = DefaultSchemas.BIOSAMPLES - specimens = biosamples_queries.get_specimen_by_person_id(client, person_id=person_id) + specimens = biosamples_queries.get_specimen_by_person_id(client, person_id=tuple(person_id)) listSpecimenIds = [specimen[0] for specimen in specimens ] if not listSpecimenIds: return 0, {} diff --git a/beacon/connections/omopcdm/cohorts.py b/beacon/connections/omopcdm/cohorts.py index 34041f5..c49fe39 100644 --- a/beacon/connections/omopcdm/cohorts.py +++ b/beacon/connections/omopcdm/cohorts.py @@ -1,10 +1,12 @@ from beacon.request.parameters import RequestParams from beacon.response.schemas import DefaultSchemas from beacon.connections.omopcdm.__init__ import client -from beacon.logs.logs import log_with_args_mongo +from beacon.logs.logs import log_with_args from beacon.conf.conf import level from typing import Optional from beacon.connections.omopcdm.individuals import get_individuals +from beacon.connections.omopcdm.biosamples import get_biosamples, get_biosamples_with_person_id + import aiosql from pathlib import Path @@ -172,7 +174,7 @@ def search_cohorts(isAll): list_cohorts.append({'cohort':dict_cohort, 'individuals': individuals}) return list_cohorts -@log_with_args_mongo(level) +@log_with_args(level) def get_cohorts(self, entry_id: Optional[str], qparams: RequestParams): schema = DefaultSchemas.COHORTS @@ -205,7 +207,7 @@ def search_single_cohort(cohort_id): return {'cohort':dict_cohort, 'individuals': individuals} -@log_with_args_mongo(level) +@log_with_args(level) def get_cohort_with_id(self, entry_id: Optional[str], qparams: RequestParams): schema = DefaultSchemas.COHORTS cohortBasicInfo = search_single_cohort(entry_id) @@ -217,23 +219,30 @@ def get_cohort_with_id(self, entry_id: Optional[str], qparams: RequestParams): ) return response_converted, 1, schema -@log_with_args_mongo(level) +@log_with_args(level) def get_individuals_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): schema = DefaultSchemas.INDIVIDUALS limit = qparams.query.pagination.limit - if entry_id == '1': - return get_individuals(self, entry_id, qparams, dataset) - else: - listIds = cohortQueries.get_cohort_individuals_limited(client, - limit=limit, - cohort_id=entry_id) # List with all Ids - count_ids = cohortQueries.count_cohort_individuals(client, cohort_id=entry_id) # Count individuals + if entry_id == '0': + return get_individuals(self, None, qparams, dataset) + + records = cohortQueries.get_cohort_individuals_limited(client, + limit=limit, + cohort_id=entry_id) # List with all Ids + listIds = [record[0] for record in records] - return get_individuals(self, [listIds], qparams, dataset) + return get_individuals(self, listIds, qparams, dataset) -# To Do -@log_with_args_mongo(level) +@log_with_args(level) def get_biosamples_of_cohort(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - schema = DefaultSchemas.BIOSAMPLES - return schema, 0, 0, {}, dataset \ No newline at end of file + + limit = qparams.query.pagination.limit + if entry_id == '0': + return get_biosamples(self, None, qparams, dataset) + + listIndividualIds = cohortQueries.get_cohort_individuals_limited(client, + limit=limit, + cohort_id=entry_id) # List with all Ids + count, records= get_biosamples_with_person_id(listIndividualIds, qparams) + return schema, count, count, records, dataset \ No newline at end of file diff --git a/beacon/connections/omopcdm/individuals.py b/beacon/connections/omopcdm/individuals.py index 0421264..9329087 100644 --- a/beacon/connections/omopcdm/individuals.py +++ b/beacon/connections/omopcdm/individuals.py @@ -15,17 +15,17 @@ individual_queries = aiosql.from_path(queries_file, "psycopg2") -def get_individual_info(offset: int=0, limit: int=10, person_id: str=None) -> list: +def get_individual_info(offset: int=0, limit: int=10, person_id = None) -> list: if person_id == None: records = individual_queries.sql_get_individuals(client, offset=offset, limit=limit) if not records: return [] listId = [str(record[0]) for record in records] else: - records = individual_queries.sql_get_individual_id(client, person_id=person_id) + records = individual_queries.sql_get_individual_id(client, person_id=tuple(person_id)) if not records: return [] - listId = [str(records[0])] + listId = [str(record[0]) for record in records] return listId def get_individuals_person(listIds: list) -> dict: diff --git a/beacon/connections/omopcdm/sql/biosamples.sql b/beacon/connections/omopcdm/sql/biosamples.sql index 7a72238..5aa26e9 100644 --- a/beacon/connections/omopcdm/sql/biosamples.sql +++ b/beacon/connections/omopcdm/sql/biosamples.sql @@ -28,4 +28,4 @@ WHERE specimen_id = :specimen_id -- Get specimen id by person id SELECT distinct specimen_id FROM cdm.specimen -WHERE person_id = :person_id \ No newline at end of file +WHERE person_id in :person_id \ No newline at end of file diff --git a/beacon/connections/omopcdm/sql/individuals.sql b/beacon/connections/omopcdm/sql/individuals.sql index 7b28d43..0b38c64 100644 --- a/beacon/connections/omopcdm/sql/individuals.sql +++ b/beacon/connections/omopcdm/sql/individuals.sql @@ -6,16 +6,22 @@ FROM cdm.person LIMIT :limit OFFSET :offset +-- name: sql_get_individual_listIds +-- Check individuals list +SELECT person_id +FROM cdm.person +where person_id in :person_id + -- name: count_individuals$ -- Get individuals count SELECT count(*) FROM cdm.person --- name: sql_get_individual_id^ --- Get individual by id +-- name: sql_get_individual_id +-- Check individual by id SELECT DISTINCT person_id FROM cdm.person -WHERE person_id = :person_id +WHERE person_id in :person_id -- name: sql_get_person -- Get gender and race by id From e54a514e7fbec0b2c1a414a3a55eb724d3ab9567 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Thu, 2 Jan 2025 14:57:46 +0100 Subject: [PATCH 15/20] add dataset basic info --- beacon/connections/omopcdm/datasets.py | 117 +++++-------------------- 1 file changed, 21 insertions(+), 96 deletions(-) diff --git a/beacon/connections/omopcdm/datasets.py b/beacon/connections/omopcdm/datasets.py index b7633c7..09bfe31 100644 --- a/beacon/connections/omopcdm/datasets.py +++ b/beacon/connections/omopcdm/datasets.py @@ -1,120 +1,45 @@ -from beacon.connections.mongo.__init__ import client from beacon.logs.logs import log_with_args from beacon.conf.conf import level -from beacon.exceptions.exceptions import raise_exception -from beacon.connections.mongo.utils import get_count, get_documents from typing import Optional from beacon.response.schemas import DefaultSchemas from beacon.request.parameters import RequestParams -from beacon.connections.mongo.filters import apply_filters -from beacon.connections.mongo.utils import get_docs_by_response_type, query_id, get_cross_query -from beacon.connections.mongo.request_parameters import apply_request_parameters +from beacon.connections.omopcdm.biosamples import get_biosamples +from beacon.connections.omopcdm.individuals import get_individuals -@log_with_args(level) -def get_datasets(self): - try: - collection = client.beacon.datasets - query = {} - query = collection.find(query) - return query - except Exception as e:# pragma: no cover - err = str(e) - errcode=500 - raise_exception(err, errcode) +# There are no different datasets in OMOPCDM @log_with_args(level) def get_full_datasets(self, entry_id: Optional[str], qparams: RequestParams): - try: - collection = client.beacon.datasets - if entry_id == None: - query = {} - else:# pragma: no cover - query = {'id': entry_id} - count = get_count(self, client.beacon.datasets, query) - query = collection.find(query) - entity_schema = DefaultSchemas.DATASETS - response_converted = ( - [r for r in query] if query else [] - ) - return response_converted, count, entity_schema - except Exception as e:# pragma: no cover - err = str(e) - errcode=500 - raise_exception(err, errcode) + schema = DefaultSchemas.DATASETS + response = [{'id':'cdm', 'name':'OMOP CDM dataset'}] + count = 1 + return response, count, schema @log_with_args(level) def get_list_of_datasets(self): - try: - datasets = get_datasets(self) - beacon_datasets = [ r for r in datasets ] - return beacon_datasets - except Exception as e:# pragma: no cover - err = str(e) - errcode=500 - raise_exception(err, errcode) + datasets = get_full_datasets( None, None) + beacon_datasets = [ r for r in datasets ] + return beacon_datasets @log_with_args(level) def get_dataset_with_id(self, entry_id: Optional[str], qparams: RequestParams): - limit = qparams.query.pagination.limit - query_parameters, parameters_as_filters = apply_request_parameters(self, {}, qparams, entry_id) - if parameters_as_filters == True: - query, parameters_as_filters = apply_request_parameters(self, {}, qparams, entry_id)# pragma: no cover - else: - query={} - query = query_id(self, query, entry_id) schema = DefaultSchemas.DATASETS - count = get_count(self, client.beacon.datasets, query) - docs = get_documents(self, - client.beacon.datasets, - query, - qparams.query.pagination.skip, - qparams.query.pagination.skip*limit - ) - response_converted = ( - [r for r in docs] if docs else [] - ) - return response_converted, count, schema + if entry_id=='cdm': + response = [{'id':'cdm', 'name':'OMOP CDM dataset'}] + count = 1 + return response, count, schema + return {}, 0, schema @log_with_args(level) def get_biosamples_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'datasets' - mongo_collection = client.beacon.biosamples - dataset_count=0 - limit = qparams.query.pagination.limit - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.datasets, query) - dict_in={} - dict_in['datasetId']=dataset - query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) schema = DefaultSchemas.BIOSAMPLES - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset + if entry_id=='cdm': + return get_biosamples(self, None, qparams, dataset) + return schema, 0, 0, {}, dataset @log_with_args(level) def get_individuals_of_dataset(self, entry_id: Optional[str], qparams: RequestParams, dataset: str): - collection = 'datasets' - mongo_collection = client.beacon.individuals - dataset_count=0 - limit = qparams.query.pagination.limit - query = apply_filters(self, {}, qparams.query.filters, collection, {}, dataset) - query = query_id(self, query, entry_id) - count = get_count(self, client.beacon.datasets, query) - dict_in={} - dict_in['datasetId']=dataset - query = apply_filters(self, dict_in, qparams.query.filters, collection, {}, dataset) schema = DefaultSchemas.INDIVIDUALS - include = qparams.query.include_resultset_responses - limit = qparams.query.pagination.limit - skip = qparams.query.pagination.skip - if limit > 100 or limit == 0: - limit = 100# pragma: no cover - idq="id" - count, dataset_count, docs = get_docs_by_response_type(self, include, query, dataset, limit, skip, mongo_collection, idq) - return schema, count, dataset_count, docs, dataset \ No newline at end of file + if entry_id=='cdm': + return get_individuals(self, None, qparams, dataset) + return schema, 0, 0, {}, dataset \ No newline at end of file From 2c5c54ab16b2b858fcb66d5f04023b6c09da90f9 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Wed, 8 Jan 2025 13:58:52 +0100 Subject: [PATCH 16/20] remove logs --- beacon/connections/omopcdm/filters.py | 2 -- 1 file changed, 2 deletions(-) diff --git a/beacon/connections/omopcdm/filters.py b/beacon/connections/omopcdm/filters.py index e04cfc0..2b0c578 100644 --- a/beacon/connections/omopcdm/filters.py +++ b/beacon/connections/omopcdm/filters.py @@ -18,14 +18,12 @@ def apply_filters(self, filtersGet: dict, filtersPost: List[dict], scope: str, g # Get and Post Filters as dict filters = [] if filtersGet: - LOG.debug("Get Query") listFilters= filtersGet["filters"].split(",") for filter in listFilters: # All Get Queries have include descendant terms as default filterDict = {"id":filter, "scope": scope, "includeDescendantTerms": "true"} filters.append(filterDict) elif filtersPost: - LOG.debug("Post Query") filters = filtersPost else: return {} From 70987949e27d592fb90bbe3d8c0974c470365a88 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Wed, 8 Jan 2025 14:00:24 +0100 Subject: [PATCH 17/20] Add possibility to create a materialised view --- beacon/connections/omopcdm/individuals.py | 63 +++++++++------- beacon/connections/omopcdm/reindex.py | 75 +++++++++++++++++++ .../connections/omopcdm/sql/basic_queries.sql | 11 ++- beacon/connections/omopcdm/utils.py | 26 +++++-- 4 files changed, 140 insertions(+), 35 deletions(-) create mode 100644 beacon/connections/omopcdm/reindex.py diff --git a/beacon/connections/omopcdm/individuals.py b/beacon/connections/omopcdm/individuals.py index 9329087..c05a865 100644 --- a/beacon/connections/omopcdm/individuals.py +++ b/beacon/connections/omopcdm/individuals.py @@ -1,7 +1,7 @@ from beacon.request.parameters import RequestParams from beacon.response.schemas import DefaultSchemas from beacon.connections.omopcdm.__init__ import client -from beacon.connections.omopcdm.utils import queryExecutor, search_ontologies +from beacon.connections.omopcdm.utils import queryExecutor, search_ontologies, materialised_view_exists from beacon.logs.logs import log_with_args, LOG from beacon.conf.conf import level from beacon.connections.omopcdm.filters import apply_filters @@ -28,7 +28,8 @@ def get_individual_info(offset: int=0, limit: int=10, person_id = None) -> list: listId = [str(record[0]) for record in records] return listId -def get_individuals_person(listIds: list) -> dict: +@log_with_args(level) +def get_individuals_person(self, listIds: list) -> dict: dict_person = {} for person_id in listIds: records = individual_queries.sql_get_person(client, person_id=person_id) @@ -39,8 +40,8 @@ def get_individuals_person(listIds: list) -> dict: dict_person[person_id] = listValues return dict_person - -def get_individuals_condition(listIds: list) -> dict: +@log_with_args(level) +def get_individuals_condition(self, listIds: list) -> dict: dict_condition = {} for person_id in listIds: records = individual_queries.sql_get_condition(client, person_id=person_id) @@ -56,7 +57,8 @@ def get_individuals_condition(listIds: list) -> dict: return dict_condition -def get_individuals_procedure(listIds: list) -> dict: +@log_with_args(level) +def get_individuals_procedure(self, listIds: list) -> dict: dict_procedure = {} for person_id in listIds: records = individual_queries.sql_get_procedure(client, person_id=person_id) @@ -73,7 +75,8 @@ def get_individuals_procedure(listIds: list) -> dict: return dict_procedure -def get_individuals_measures(listIds: list) -> dict: +@log_with_args(level) +def get_individuals_measures(self, listIds: list) -> dict: dict_measures = {} for person_id in listIds: records = individual_queries.sql_get_measure(client, person_id=person_id) @@ -91,8 +94,8 @@ def get_individuals_measures(listIds: list) -> dict: dict_measures[person_id] = listValues return dict_measures - -def get_individuals_exposures(listIds: list) -> dict: +@log_with_args(level) +def get_individuals_exposures(self, listIds: list) -> dict: dict_exposures = {} for person_id in listIds: records = individual_queries.sql_get_exposure(client, person_id=person_id) @@ -115,7 +118,8 @@ def get_individuals_exposures(listIds: list) -> dict: dict_exposures[person_id] = listValues return dict_exposures -def get_individuals_treatments(listIds: list) -> dict: +@log_with_args(level) +def get_individuals_treatments(self, listIds: list) -> dict: dict_treatments = {} for person_id in listIds: records = individual_queries.sql_get_treatment(client, person_id=person_id) @@ -130,8 +134,8 @@ def get_individuals_treatments(listIds: list) -> dict: dict_treatments[person_id] = listValues return dict_treatments - -def format_query(listIds: list, dictPerson: dict, dictCondition: dict, dictProcedures: dict, dictMeasures: dict, dictExposures: dict, dictTreatments: dict)-> list: +@log_with_args(level) +def format_query(self, listIds: list, dictPerson: dict, dictCondition: dict, dictProcedures: dict, dictMeasures: dict, dictExposures: dict, dictTreatments: dict)-> list: list_format = [] for person_id in listIds: dictId = {"id":person_id} @@ -152,22 +156,24 @@ def format_query(listIds: list, dictPerson: dict, dictCondition: dict, dictProce list_format.append(dictId) return list_format -def retrieveRecords(listIds: list) -> list: - dictPerson = get_individuals_person(listIds) # List with Id, sex, ethnicity - dictCondition = get_individuals_condition(listIds) # List with al the diseases per Id - dictProcedures = get_individuals_procedure(listIds) - dictMeasures = get_individuals_measures(listIds) - dictExposures = get_individuals_exposures(listIds) - dictTreatments = get_individuals_treatments(listIds) - - dictPerson = search_ontologies(dictPerson) - dictCondition = search_ontologies(dictCondition) - dictProcedures = search_ontologies(dictProcedures) - dictMeasures = search_ontologies(dictMeasures) - dictExposures = search_ontologies(dictExposures) - dictTreatments = search_ontologies(dictTreatments) - - docs = format_query(listIds, dictPerson, dictCondition, dictProcedures, dictMeasures, dictExposures, dictTreatments) +@log_with_args(level) +def retrieveRecords(self, listIds: list) -> list: + dictPerson = get_individuals_person(self, listIds) # List with Id, sex, ethnicity + dictCondition = get_individuals_condition(self, listIds) # List with al the diseases per Id + dictProcedures = get_individuals_procedure(self, listIds) + dictMeasures = get_individuals_measures(self, listIds) + dictExposures = get_individuals_exposures(self, listIds) + dictTreatments = get_individuals_treatments(self, listIds) + + matView = materialised_view_exists() + dictPerson = search_ontologies(self, dictPerson, matView) + dictCondition = search_ontologies(self, dictCondition, matView) + dictProcedures = search_ontologies(self, dictProcedures, matView) + dictMeasures = search_ontologies(self, dictMeasures, matView) + dictExposures = search_ontologies(self, dictExposures, matView) + dictTreatments = search_ontologies(self, dictTreatments, matView) + + docs = format_query(self, listIds, dictPerson, dictCondition, dictProcedures, dictMeasures, dictExposures, dictTreatments) return docs @@ -202,7 +208,6 @@ def get_individuals(self, entry_id: Optional[str], qparams: RequestParams, datas else: resultQuery = [(countIds, listId) for listId in listIds ] - LOG.debug(f"Final query {resultQuery}") if not resultQuery: return schema, 0, 0, {}, dataset # Different response depending the granularity @@ -213,7 +218,7 @@ def get_individuals(self, entry_id: Optional[str], qparams: RequestParams, datas # Record response count = resultQuery[0][0] listIds = [str(record[1]) for record in resultQuery] - docs = retrieveRecords(listIds) + docs = retrieveRecords(self, listIds) return schema, count, count, docs, dataset diff --git a/beacon/connections/omopcdm/reindex.py b/beacon/connections/omopcdm/reindex.py new file mode 100644 index 0000000..95259a2 --- /dev/null +++ b/beacon/connections/omopcdm/reindex.py @@ -0,0 +1,75 @@ +import conf +import psycopg2 + +uri = "postgresql://{}:{}@{}:{}/{}".format( + conf.database_user, + conf.database_password, + conf.database_host, # Ex: localhost + conf.database_port, # Ex: 5432 + conf.database_name, +) + +client = psycopg2.connect(uri) + + +# Create materialised view from the vocabulary used in the database +MaterialisedView = """ + -- Create a materialized view to store all relevant concept_ids + DROP MATERIALIZED VIEW IF EXISTS search_ontologies_view; + + CREATE MATERIALIZED VIEW search_ontologies_view AS + WITH relevant_concepts AS ( + -- Aggregate all concept_ids referenced in the data tables + SELECT gender_concept_id as concept_id FROM cdm.person + UNION + SELECT race_concept_id as concept_id FROM cdm.person + UNION + SELECT condition_concept_id as concept_id FROM cdm.condition_occurrence + UNION + SELECT procedure_concept_id as concept_id FROM cdm.procedure_occurrence + UNION + SELECT measurement_concept_id as concept_id FROM cdm.measurement + UNION + SELECT unit_concept_id as concept_id FROM cdm.measurement + UNION + SELECT observation_concept_id as concept_id FROM cdm.observation + UNION + SELECT unit_concept_id as concept_id FROM cdm.observation + UNION + SELECT drug_concept_id as concept_id FROM cdm.drug_exposure + UNION + SELECT disease_status_concept_id as concept_id FROM cdm.specimen + UNION + SELECT anatomic_site_concept_id as concept_id FROM cdm.specimen + ) + SELECT + DISTINCT c.concept_id, + c.concept_name, + c.vocabulary_id, + c.concept_code + FROM + vocabularies.concept c + INNER JOIN + relevant_concepts rc + ON + c.concept_id = rc.concept_id + """ + +# Index vocabulary +indexQuery = """ + CREATE INDEX IF NOT EXISTS idx_concept_id ON search_ontologies_view (concept_id); + """ + +# Query executor +def queryExecutor(query): + cur = client.cursor() + cur.execute(query) + +# try: +# queryExecutor(MaterialisedView) +# queryExecutor(indexQuery) +# print("Index and store procedure done") +# except: +# print("Index and store procedure could not be created") +queryExecutor(MaterialisedView) +queryExecutor(indexQuery) diff --git a/beacon/connections/omopcdm/sql/basic_queries.sql b/beacon/connections/omopcdm/sql/basic_queries.sql index 3cc3910..7345133 100644 --- a/beacon/connections/omopcdm/sql/basic_queries.sql +++ b/beacon/connections/omopcdm/sql/basic_queries.sql @@ -16,4 +16,13 @@ WHERE vocabulary_id = :vocabulary_id and concept_code = :concept_code SELECT concept_name as label, vocabulary_id || ':' || concept_code as id FROM vocabularies.concept -WHERE concept_id = :concept_id \ No newline at end of file +WHERE concept_id = :concept_id +Limit 1 + +-- name: sql_get_ontology_view^ +-- Get ontology in materialised view +SELECT concept_name as label, + vocabulary_id || ':' || concept_code as id +FROM search_ontologies_view +WHERE concept_id = :concept_id +Limit 1 \ No newline at end of file diff --git a/beacon/connections/omopcdm/utils.py b/beacon/connections/omopcdm/utils.py index 87353d0..5cbc876 100644 --- a/beacon/connections/omopcdm/utils.py +++ b/beacon/connections/omopcdm/utils.py @@ -1,4 +1,6 @@ from beacon.connections.omopcdm.__init__ import client +from beacon.logs.logs import log_with_args, LOG +from beacon.conf.conf import level import itertools import aiosql from pathlib import Path @@ -21,12 +23,26 @@ def queryExecutor(query): records = cur.fetchall() return records -def search_ontology(concept_id): - records = basic_queries.sql_get_ontology(client, concept_id=concept_id) - return records +# Check if a materialised view exists in the given the R/W permissions +def materialised_view_exists(): + + query = """ + SELECT count(*) + FROM pg_matviews + WHERE matviewname = 'search_ontologies_view'; + """ + result = queryExecutor(query) + return result[0][0] > 0 +def search_ontology(concept_id, matView): + if matView: + records = basic_queries.sql_get_ontology_view(client, concept_id=concept_id) + else: + records = basic_queries.sql_get_ontology(client, concept_id=concept_id) + return records -def search_ontologies(dictValues): +@log_with_args(level) +def search_ontologies(self, dictValues, matView): for person_id, listVariableValues in dictValues.items(): # For each id for dictVariableValue in listVariableValues: # For each object of the list for variable, value in dictVariableValue.items(): @@ -35,7 +51,7 @@ def search_ontologies(dictValues): if value == 0: dictVariableValue[variable] = {'id':"None:No matching concept", 'label':"No matching concept"} continue - records = search_ontology(value) + records = search_ontology(value, matView) if records: label = records[0] id = records[1] From de9812d0f3a2fd80c919b695f996d8afbf32307d Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Wed, 8 Jan 2025 14:02:43 +0100 Subject: [PATCH 18/20] add files to ignore --- .gitignore | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index 7e38acf..940a3ef 100644 --- a/.gitignore +++ b/.gitignore @@ -7,4 +7,6 @@ beacon/connections/mongo/data/rarediseases beacon/connections/mongo/data/rd-connect *.vcf.gz beacon/connections/mongo/data/db/* -!beacon/connections/mongo/data/db/dir.txt \ No newline at end of file +!beacon/connections/mongo/data/db/dir.txt +beacon/permissions/__main__.py +beacon/source/manage.py \ No newline at end of file From aa50f2707e4327a1957efa18dd885a9eed4fd5ab Mon Sep 17 00:00:00 2001 From: API version update Date: Wed, 8 Jan 2025 13:09:49 +0000 Subject: [PATCH 19/20] api version automatically generated --- beacon/conf/api_version.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/beacon/conf/api_version.yml b/beacon/conf/api_version.yml index f1a43e1..0c3383c 100644 --- a/beacon/conf/api_version.yml +++ b/beacon/conf/api_version.yml @@ -1 +1 @@ -api_version: v2.0-eeabc63 +api_version: v2.0-6bb8796 From 3d65934cedadcfd5ce47e900178b6648b2911d19 Mon Sep 17 00:00:00 2001 From: SergiAguilo Date: Wed, 8 Jan 2025 15:50:47 +0100 Subject: [PATCH 20/20] Add hardcoded database --- beacon/connections/omopcdm/datasets.py | 5 ++--- beacon/permissions/datasets/public_datasets.yml | 3 ++- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/beacon/connections/omopcdm/datasets.py b/beacon/connections/omopcdm/datasets.py index 09bfe31..a214809 100644 --- a/beacon/connections/omopcdm/datasets.py +++ b/beacon/connections/omopcdm/datasets.py @@ -17,9 +17,8 @@ def get_full_datasets(self, entry_id: Optional[str], qparams: RequestParams): @log_with_args(level) def get_list_of_datasets(self): - datasets = get_full_datasets( None, None) - beacon_datasets = [ r for r in datasets ] - return beacon_datasets + datasets, count, schema = get_full_datasets(self, None, None) + return datasets @log_with_args(level) def get_dataset_with_id(self, entry_id: Optional[str], qparams: RequestParams): diff --git a/beacon/permissions/datasets/public_datasets.yml b/beacon/permissions/datasets/public_datasets.yml index 8d2520d..0e4e220 100644 --- a/beacon/permissions/datasets/public_datasets.yml +++ b/beacon/permissions/datasets/public_datasets.yml @@ -3,4 +3,5 @@ public_datasets: - CINECA_dataset - rd-connect_dataset - coadread_tcga_pan_can_atlas_2018 -- COVID_pop11_fin_2 \ No newline at end of file +- COVID_pop11_fin_2 +- cdm \ No newline at end of file