This work is licensed under a
Creative Commons Attribution 4.0 International License
.
Big Data Europe Webinar, 2016-07-06
This work has been done as part of the BioExcel CoE (www.bioexcel.eu),
a project funded by the EC H2020 program, EINFRA-5-2015 contract number 675728
Data sources integrated and linked together so that you can easily see the relationships between compounds, targets, pathways, diseases and tissues.
ChEBI, ChEMBL, ChemSpider, ConceptWiki, DisGeNET, DrugBank, FAERS, Gene Ontology, neXtProt, SureChEMBL, UniProt, WikiPathways
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ns0:reportedAdverseEvent <http://aers.data2semantics.org/resource/diagnosis/TUMOUR_LYSIS_SYNDROME> ;
ns0:reportedAdverseEvent <http://aers.data2semantics.org/resource/diagnosis/LEFT_VENTRICULAR_DYSFUNCTION> ;
ns0:reportedAdverseEvent <http://aers.data2semantics.org/resource/diagnosis/METABOLIC_ACIDOSIS> .
<http://bio2rdf.org/drugbank:DB00398>
void:inDataset <http://www.openphacts.org/bio2rdf/drugbank> ;
<http://bio2rdf.org/drugbank_vocabulary:metabolism> "Sorafenib is metabolized primarily in the liver, undergoing oxidative metabolism, mediated by CYP3A4, as well as glucuronidation mediated by UGT1A9. Sorafenib accounts for approximately 70-85% of the circulating analytes in plasma at steady- state. Eight metabolites of sorafenib have been identified, of which five have been detected in plasma. The main circulating metabolite of sorafenib in plasma, the pyridine N-oxide, shows <i>in vitro</i> potency similar to that of sorafenib. This metabolite comprises approximately 9-16% of circulating analytes at steady-state."@en ;
<http://bio2rdf.org/drugbank_vocabulary:toxicity> "The highest dose of sorafenib studied clinically is 800 mg twice daily. The adverse reactions observed at this dose were primarily diarrhea and dermatologic events. No information is available on symptoms of acute overdose in animals because of the saturation of absorption in oral acute toxicity studies conducted in animals."@en ;
<http://bio2rdf.org/drugbank_vocabulary:description> "Sorafenib (rINN), marketed as Nexavar by Bayer, is a drug approved for the treatment of advanced renal cell carcinoma (primary kidney cancer). It has also received \"Fast Track\" designation by the FDA for the treatment of advanced hepatocellular carcinoma (primary liver cancer), and has since performed well in Phase III trials.\nSorafenib is a small molecular inhibitor of Raf kinase, PDGF (platelet-derived growth factor), VEGF receptor 2 & 3 kinases and c Kit the receptor for Stem cell factor. A growing number of drugs target most of these pathways. The originality of Sorafenib lays in its simultaneous targeting of the Raf/Mek/Erk pathway."@en ;
<http://bio2rdf.org/drugbank_vocabulary:proteinBinding> "99.5% bound to plasma proteins."@en ;
<http://bio2rdf.org/drugbank_vocabulary:genericName> "Sorafenib"@en ;
<http://bio2rdf.org/drugbank_vocabulary:drugType> "investigational"@en ;
<http://bio2rdf.org/drugbank_vocabulary:drugType> "approved"@en ;
ns0:drugInteraction <http://bio2rdf.org/drugbank_resource:DB00398_DB00755> ;
ns0:drugInteraction <http://bio2rdf.org/drugbank_resource:DB00398_DB00958> ;
ns0:drugInteraction <http://bio2rdf.org/drugbank_resource:DB00398_DB06414> ;
ns0:drugInteraction <http://bio2rdf.org/drugbank_resource:DB00072_DB00398> ;
ns0:drugInteraction <http://bio2rdf.org/drugbank_resource:DB00112_DB00398> .
<http://bio2rdf.org/drugbank_resource:DB00072_DB00398>
void:inDataset <http://www.openphacts.org/bio2rdf/drugbank> ;
ns0:interactingDrug <http://bio2rdf.org/drugbank:DB00072> ;
<http://bio2rdf.org/drugbank_vocabulary:text> "DDI between Trastuzumab and Sorafenib - Trastuzumab may increase the risk of neutropenia and anemia. Monitor closely for signs and symptoms of adverse events."@en .
<http://bio2rdf.org/drugbank_resource:DB00112_DB00398>
void:inDataset <http://www.openphacts.org/bio2rdf/drugbank> ;
ns0:interactingDrug <http://bio2rdf.org/drugbank:DB00112> ;
<http://bio2rdf.org/drugbank_vocabulary:text> "DDI between Bevacizumab and Sorafenib - Monitor therapy due to increased adverse effects of sorafenib, especially hand-foot skin reaction."@en .
Linux Container technology
..light-weight "virtual" virtual machine
A container is started from a image
Images downloaded from Docker Hub
Dockerfile: Layer-based recipe
Philosophy: One service, one image → microservices
Cloud's best friend: scalable, reproducible, customizable
Which images to download
Which data volumes to use
Which network ports are exposed
How are containers linked
How to start/stop the containers
$ docker-compose up -d
# Open PHACTS platform
# Docker Compose configuration
explorer:
image: openphacts/explorer2
ports:
- "3001:3000"
links:
- api
environment:
- API_URL=http://localhost:3002
#restart: always
api:
image: openphacts/ops-linkeddataapi
ports:
- "3002:80"
links:
- ims
- memcached
- virtuoso:sparql
# SPARQL server
virtuoso:
build: virtuoso-ops
ports:
- "3003:8890"
volumes_from:
- virtuosodata
virtuosodata:
image: busybox
volumes:
- /virtuoso
mysqldata:
image: busybox
volumes:
- /var/lib/mysql
mysql:
image: mysql
volumes_from:
- mysqldata
environment:
- MYSQL_ROOT_PASSWORD=uCie0ahgah
- MYSQL_DATABASE=ims
- MYSQL_USER=ims
- MYSQL_PASSWORD=ims
ims:
image: openphacts/identitymappingservice
ports:
- "3004:8080"
links:
- mysql
memcached:
image: memcached
mysqlstaging:
container_name: ops-mysqlstaging
image: openphacts/identitymappingservice-staging
links:
- mysql
# Populate RDF from virtuoso backup download
virtuosostaging:
build: virtuosodata-frombackup
volumes_from:
- virtuosodata
# To customize RDF dataloading, comment OUT the above 'virtuosostaging' block,
# uncomment the below block, and then run
# docker-compose up -d virtuosostagingrdf
#
## BEGIN custom loading
### Download from data.openphacts.org
#openphactsrdf:
# build: openphacts-rdf
# volumes:
# # To specify alternative data folder, use instad:
# # - /media/big-SSD/download:/download
# # - /media/big-SSD/staging:/staging
# - /download
# - /staging
# # /download
#
### Load into virtuoso
#virtuosostagingrdf:
# build: virtuosodata-fromrdf
# volumes_from:
# - virtuosodata
# - openphactsrdf
### END custom loading
## Future services
#elasticsearch:
# container_name: ops-elasticsearch
# image: elasticsearch
## TODO: Data loading
#ops-search:
# container_name: ops-search
# image: openphacts/ops-search
Docker Hub maximum image size: 10 GB
Open PHACTS data (compressed): ~30 GB
Open PHACTS data (installed): ~200 GB
Solution: Added staging Docker containers
Download from https://data.openphacts.org/
Verify consistency
Import into Virtuso and mySQL
RDF datasets
RDF linksets
VoID metadata/provenance
mySQL-imported linksets
Virtuoso-imported datasets
→ Maven repository
release data as software
→Research Objects
propagate metadata
Hardware requirements:
Prerequisites:
Follow the GitHub tutorial exactly, customize later
Install latest Docker and Docker Compose
Just testing on Windows or OS X?
.. modify Docker's Linux VM to have enough disk and memory
Firewall? Different settings depend on your firewall details.
Don't worry - Docker is containerized!
..you won't break your machine
curl -L https://github.com/openphacts/ops-docker/archive/master.tar.gz | tar xzv
cd ops-docker-master
sudo docker-compose pull
$ sudo docker-compose up --no-recreate -d mysqlstaging virtuosostaging
$ sudo docker-compose logs mysqlstaging virtuosostaging
ops-mysqlstaging | mySQL staging finished
ops-mysqlstaging exited with code 0
ops-virtuosostaging | 09:13:35 --> Backup file # 675 [0x3F02-0x74-0x8A]
ops-virtuosostaging | 09:13:36 --> Backup file # 676 [0x3F02-0x74-0x8A]
ops-virtuosostaging | 09:13:37 End of restoring from backup, 6751701 pages
ops-virtuosostaging | 09:13:37 Server exiting
ops-virtuosostaging | Loading completed
ops-virtuosostaging exited with code 0
$ sudo docker-compose up --no-recreate -d
$ sudo docker-compose logs --tail=5
http://localhost:3001/ Explorer
http://localhost:3002/ API
http://localhost:3003/ SPARQL
http://localhost:3004/QueryExpander Identity Mapping
Different Open PHACTS 2.1 licensing options:
Non-Commercial users: Everything
Commercial users: No DrugBank, partial SureChembl
Open PHACTS members: Full SureChembl
Most queries have separate fragments per dataset
..which could be executed on separate microservices
Better cloud scalability
Easier to test upgrades of individual datasets
But still need "API" layer to do Identity Mapping
and selecting datasets to query
BioExcel approach: Spin up virtual machine when an Open PHACTS workflow is started
Workflow bound dynamically to VM instance(s)
Scalability (exclusive access)
Reproducibility (independent/fixed OPS install)
Tool descriptions - exposed in bio.tools
Make it easier to add third-party data:
datasets, linksets, queries, API calls
..so pharma industry can mix in their in-house data
.. so academics can upgrade and expand datasets
More tooling,
more documentation,
or more training?