v2 Build Details

Release: `v2.0.0`

(Click Figure to Enlarge)

Release Updates

All statistics featured on this page reflect the initial build for this release. As of January 2021 builds are generated on a monthly schedule.

Build Data: Build Data under this release are publicly available and can be accessed through Zenodo:

https://zenodo.org/doi/10.5281/zenodo.7030039

New Data Sources:

The Protein Ontology (created a new human version of the Protein Ontology)
The Uber-Anatomy Ontology
The Sequence Ontology
Human Protein Atlas data including transcript expression in cell and tissue types
Variant data from ClinVar
Gene-gene interactions from GeneMania
Included additional data from Reactome and UniProt

New Functionality:

Added build options (see here for more details): full, partial, and post-closure
Added options to construct the knowledge graph using a subclass-based or instance-based approach (see here for more information)
Added Data_Preparation.ipynb Jupyter Notebook to aid in the creation of mapping, filtering, and labeling datasets
Added Ontology_Cleaning.ipynb Jupyter Notebook to aid in cleaning and preprocessing ontology data
Added generates_dependency_documents.py to assist users with the creation of required input documents
Knowledge graph can be constructed using primary edges or primary and inverse edges
Added metadata for instance data nodes to knowledge graph (see here for details)
Improved reproducibility by providing detailed metadata on all downloaded data sources
Removed redundant resource download
Added explicit typing to all functions and class attributes
Modified OWL-NETS to decode OWL-encoded classes and triples (see here for more information)
- Added OWLNETS_Example_Application.ipynb Jupyter Notebook to provide an example of how to use OWL-NETS independent of building a knowledge graph
Provide a Networkx MultiDiGraph graph for each full build (.gpickle). Note that this representation includes keys for nodes and edges (node: key = URI; edge: predicate_key = MD5 hash of triple "s_uri" + "p_uri" + "o_uri"). Each edge also has a default weight of 0.0.
Added DockerHub containers to build pkt_kg
Added Blazegraph SPARQL Endpoint: http://sparql.pheknowlator.com/blazegraph/#query

Jupyter Notebooks

Main.ipynb
Data_Preparation.ipynb
Ontology_Cleaning.ipynb
OWLNETS_Example_Application.ipynb
RDF_Graph_Processing_Example.ipynb

Ontologies

Downloaded Resource Information:

ontology source list
ontology source metadata

Ontologies: The specific ontologies used in the knowledge graph, including class and axiom counts, are shown in the table below. The counts below are from the May 2021 build.

Ontology	Class Count (un-cleaned)	Triple Count (un-cleaned)	Class Count (cleaned)	Triple Count (cleaned)
Cell Line Ontology (cell)	`111,712`	`1,387,096`	`11,696`	`1,422,153`
Chemical Entities of Biological Interest (chemical)	`156,098`	`5,264,571`	`137,592`	`5,190,485`
Gene Ontology (gobp, gomf, gocc)	`62,237`	`1,425,434`	`55,807`	`1,343,218`
MonDO Disease Ontology (disease)	`55,478`	`2,313,343`	`52,937`	`2,277,245`
Human Phenotype Ontology (phenotype)	`38,843`	`884,999`	`38,530`	`885,379`
Human Protein Ontology (protein)	`148,243`	`2,079,356`	`148,243`	`2079277`
Pathway Ontology (pathway)	`2,642`	`35,291`	`2600`	`34,901`
Relation Ontology (relations)	`116`	`7,970`	`115`	`7,873`
Sequence Ontology (genes, variants)	`2,910`	`44,655`	`2,569`	`41,980`
Uber-Anatomy Ontology (anatomy)	`28,738`	`752,291`	`27,170`	`734,768`
The Vaccine Ontology (vaccine)	`7,089`	`86,454`	`7,085`	`89,764`

NOTE. Please see the Ontology_Cleaning.ipynb Jupyter Notebook for details on how the ontologies were preprocessed before being added to the knowledge graph.

Creation of Mapping, Filtering, and Labeling Data

To create the edge types listed in the tables above, several additional files were needed. For more details on these data sources, please see the Data_Preparation.ipynb Jupyter Notebook.

Ontology Class-Instance/Subclass Node Mapping: subclass_construction_map.pkl

Relations Data:
See the relations_directory README.md for more information.

Relations and Inverse Relations ➞ INVERSE_RELATIONS.txt
Relations and Labels ➞ RELATIONS_LABELS.txt

Node Metadata:
See the node_directory README.md for more information.

Node Metadata Dictionary ➞ node_metadata_dict.pkl

{
'nodes': {
    'http://www.ncbi.nlm.nih.gov/gene/1': {
        'Label': 'A1BG',
        'Description': "A1BG has locus group protein-coding' and is located on chromosome 19 (19q13.43).",
        'Synonym': 'HYST2477alpha-1B-glycoprotein|HEL-S-163pA|ABG|A1B|GAB'} ... },
'relations': {
    'http://purl.obolibrary.org/obo/RO_0002533': {
        'Label': 'sequence atomic unit',
        'Description': 'Any individual unit of a collection of like units arranged in a linear order',
        'Synonym': 'None'} ... }
}

Edge Data

Data Download and Creation Dates: May 2021

Master Edge Lists: Master_Edge_List_Dict.json

Edge List: Whenever possible, we limit edges to homo Sapiens concepts that are supported by some type of evidence. For the exact specifications, please see the resource_info.txt. The counts shown in the table below reflect all edges, including those containing nodes without metadata, that were added to the base ontologies (counts shown above). The counts below do not include the merged ontologies. The counts below are from the May 2021 build.

Edge	Edge Relation (Inverse relation)	Subject Count	Edge Count (Rels / Rels+InvRels)	Object Count
chemical-disease	substance that treats (is treated by substance)	`4,290`	`170,675` / `341,350`	`4,574`
chemical-gene	interacts with	`462`	`16,699` / `33,398`	`11,981`
chemical-gobp	molecularly interacts with	`1,338`	`288,921` / `557,842`	`1,584`
chemical-gocc	molecularly interacts with	`1,086`	`44,553` / `89,106`	`250`
chemical-gomf	molecularly interacts with	`1,105`	`26,165` / `52,330`	`208`
chemical-pathway	participates in (has participant)	`2,105`	`28,691` / `57,382`	`2,213`
chemical-phenotype	substance that treats (is treated by substance)	`4,055`	`108,452` / `216,904`	`1,721`
chemical-protein	interacts with	`4,179`	`65,124` / `130,248`	`6,389`
🔧 ~~chemical-rna~~	~~interacts with~~	~~`2,403`~~	~~`3,860,355` / `7,720,710`~~	~~`179,380`~~
disease-phenotype	has phenotype (phenotype of)	`11,746`	`414,193` / `828,386`	`9,717`
gene-disease	causes or contributes to	`5,035`	`12,735` / `12,735`	`4,429`
gene-gene	genetically interacts with	`247`	`1,668` / `3,336`	`263`
gene-pathway	participates in (has participant)	`10,371`	`107,025` / `214,050`	`1,860`
gene-phenotype	causes or contributes to	`6,785`	`23,516` / `23,516`	`1,530`
gene-protein	has gene product (gene product of)	`19,327`	`19,534` / `39,068`	`19,143`
gene-rna	transcribed to (transcribed from	`25,529`	`182,736` / `365,472`	`179,870`
gobp-pathway	realized in response to	`471`	`665` / `665`	`665`
pathway-gocc	has component	`11,134`	`15,846` / `15,846`	`99`
pathway-gomf	has function (function of)	`2,412`	`2,416` / `4,832`	`726`
protein-anatomy	located in (location of)	`10,747`	`30,682` / `61,364`	`68`
protein-catalyst	molecularly interacts with	`3,025`	`24,967` / `49,934`	`3,734`
protein-cell	located in (location of)	`10,045`	`75,318` / `150,636`	`128`
protein-cofactor	molecularly interacts with	`1,585`	`1,999` / `3,998`	`44`
protein-gobp	participates in (has participant)	`17,527`	`137,812` / `275,624`	`12,246`
protein-gocc	located in (location of)	`18,427`	`81,602` / `163,204`	`1,757`
protein-gomf	has function (function of)	`17,779`	`68,633` / `137,266`	`4,324`
protein-pathway	participates in (has participant)	`10,886`	`117,585` / `235,170`	`2,480`
protein-protein	molecularly interacts with	`14,230`	`618,069` / `618,069`	`14,230`
rna-anatomy	located in (location of)	`29,115`	`444,668` / `889,336`	`103`
rna-cell	located in (location of)	`14,038`	`65,156` / `130,312`	`130`
rna-protein	ribosomally translates to (ribosomal translation of)	`44,144`	`44,147` / `88,294`	`19,200`
variant-disease	causes or contributes to	`13,297`	`38,129` / `38,129`	`3,621`
variant-gene	causally influences (causally influenced by)	`121,790`	`121,790` / `243,580`	`3,236`
variant-phenotype	causes or contributes to	`1,824`	`2,526` / `2,526`	`373`

Rels: Relations Only; Rels+InvRels: Relations and Inverse Relations.
🔧 Edge removed from workflow on April 10, 2021.

Knowledge Graph Output

Data: https://zenodo.org/doi/10.5281/zenodo.7030039

There are several options for generating knowledge graphs, which is indicated by the file name for each type of generated output:

CONSTRUCTION APPROACH

Resource: resources/construction_approach/README.md

subclass: Non-ontology data are added to existing ontology data using rdfs:subClassOf
instance: Non-ontology data are added to existing ontology data using rdf:type. Please see here for additional information.

RELATIONS

Resource: resources/relations_data/README.md

RelationsOnly: The knowledge graph has been built with a single set of edge relations.
InverseRelations: The knowledge graph has been built with the standard set of relations, and if available, the InverseObjectProperties of the standard relations. With one caveat - if the original standard relation is a type of interaction (e.g. interacts_with, molecularly interacts with) and the provided edge list is not symmetric (meaning both sides of the interaction are not included in the provided edge list), then the interaction-related relation will be reused to represent the missing interactions.

OWL SEMANTICS

Resource: OWL-NETS 2.0

OWL: The knowledge graph has not been filtered.
OWLNETS: The knowledge graph has been filtered to decode OWL-encoded classes and triples.

SEMANTIC CONSISTENCY

Resource: OWL-NETS 2.0
Currently, the program is configured to output the results from OWL-NETS in two ways: (1) run the program as-is or (2) run the program as-is with an additional step to "purify" the output by ensuring that the resulting OWL-NETS graph is completely consistent with the specified knowledge graph construction approach (i.e. subclass or instance-based). The "purified" output will include _SUBCLASS_purified_ or _INSTANCE_purified_ in the file names.

Knowledge Graph Data

Three different types of files are included in the table below:

Knowledge Graphs: The knowledge graph can be downloaded in two different formats (note that all BNodes or anonymous nodes have been converted to URIRefs under the pkt_bnode namespace (https://github.com/callahantiff/PheKnowLator/pkt/bnode/)):
- RDFLib Graph serialized and saved in several formats:
  - Logic Only Subset (.nt; N-Triples) - contains all axioms not used to create annotations or annotation assertions
  - Annotations Only Subset (.nt; N-Triples) - only annotations or annotation assertions
  - Full Knowledge Graph (.nt; N-Triples) - Contains logic subset and annotations.
- Networkx MultiDiGraph saved as an .gpickle file. Note that this representation includes keys for nodes and edges (node: key = URI; edge: predicate_key = MD5 hash of triple "s_uri" + "p_uri" + "o_uri"). Each edge also has a default weight of 0.0.
OWL-NETS Results: A pickled (.pickle) nested dictionary where each outer key is an anonymous node and the two inner keys contain: (1) a dictionary of owl-encoded triples and (2) a set of owl-decoded triples.

Details		Files	Triples	Nodes	Relations
Merged Ontology Data		PheKnowLator_MergedOntologies.owl	13,740,214	5,460,874	349

RELATIONS
Subclass Construction	OWL	PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL.nt PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_AnnotationsOnly.nt PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_LogicOnly.nt PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_NetworkxMultiDiGraph.gpickle	69,722,287	20,727,369	347
Subclass Construction	OWL Decoded	PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_OWLNETS.nt PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_OWLNETS_NetworkxMultiDiGraph.gpickle PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_OWLNETS_decoding_dict.pkl Semantic Consistency PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_SUBCLASS_purified_OWLNETS.nt PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_SUBCLASS_purified_OWLNETS_NetworkxMultiDiGraph.gpickle PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_SUBCLASS_purified_OWLNETS_decoding_dict.pkl	14,978,059 14,979,239	1,169,694 1,169,694	326 325

Instance Construction	OWL	PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL.nt PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_AnnotationsOnly.nt PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_LogicOnly.nt PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_NetworkxMultiDiGraph.gpickle	31,023,015	7,861,294	362
Instance Construction	OWL Decoded	PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_OWLNETS.nt PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_OWLNETS_NetworkxMultiDiGraph.gpickle PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_OWLNETS_decoding_dict.pkl Semantic Consistency PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_INSTANCE_purified_OWLNETS.nt PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_INSTANCE_purified_OWLNETS_NetworkxMultiDiGraph.gpickle PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_INSTANCE_purified_OWLNETS_decoding_dict.pkl	13,438,644 16,431,676	1,169,694 1,169,694	325 324
INVERSE RELATIONS
Subclass Construction	OWL	PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL.nt PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_AnnotationsOnly.nt PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_LogicOnly.nt PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_NetworkxMultiDiGraph.gpickle	80,083,419	23,317,651	347
Subclass Construction	OWL Decoded	PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_OWLNETS.nt PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_OWLNETS_NetworkxMultiDiGraph.gpickle PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_OWLNETS_decoding_dict.pkl Semantic Consistency PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_SUBCLASS_purified_OWLNETS.nt PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_SUBCLASS_purified_OWLNETS_NetworkxMultiDiGraph.gpickle PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_SUBCLASS_purified_OWLNETS_decoding_dict.pkl	17,554,862 17,556,042	1,169,694 1,169,694	333 332

Instance Construction	OWL	PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL.nt PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_AnnotationsOnly.nt PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_LogicOnly.nt PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_NetworkxMultiDiGraph.gpickle	33,610,732	7,861,294	371
Instance Construction	OWL Decoded	PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_OWLNETS.nt PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_OWLNETS_NetworkxMultiDiGraph.gpickle PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_OWLNETS_decoding_dict.pkl Semantic Consistency PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_INSTANCE_purified_OWLNETS.nt PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_INSTANCE_purified_OWLNETS_NetworkxMultiDiGraph.gpickle PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_INSTANCE_purified_OWLNETS_decoding_dict.pkl	15,649,013 19,154,150	1,169,694 1,169,694	331 330

Edge List Output

Data: https://zenodo.org/doi/10.5281/zenodo.7030039

Three different types of files are included in the table below:

Integer Labels: a tab-delimited .txt file containing three columns, one for each part of a triple (i.e. subject, predicate, object). The subject, predicate, and object identifiers have been mapped to integers.
Identifier Labels: a tab-delimited .txt file containing three columns, one for each part of a triple (i.e. subject, predicate, object). Both the subject and object identifiers have not been mapped to integers.
Identifier-Integer Map: a .json file containing a dictionary where the keys are node identifiers and the values are integers.

Details	Subclass Construction	Instance Construction
RELATIONS
OWL	PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_Triples_Integers.txt PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_SUBCLASS_purified_Triples_Integers.txt	PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_Triples_Integers.txt PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_INSTANCE_purified_Triples_Integers.txt
	PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_Triples_Identifiers.txt PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_SUBCLASS_purified_Triples_Identifiers.txt	PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_Triples_Identifiers.txt PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_INSTANCE_purified_Triples_Identifiers.txt
	PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_Triples_Integer_Identifier_Map.json PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_SUBCLASS_purified_Triples_Integer_Identifier_Map.json	PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_Triples_Integer_Identifier_Map.json PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_INSTANCE_purified_Triples_Integer_Identifier_Map.json

OWL Decoded	PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_Triples_Integers.txt PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_SUBCLASS_purified_Triples_Integers.txt	PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_Triples_Integers.txt PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_INSTANCE_purified_Triples_Integers.txt
	PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_Triples_Identifiers.txt PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWLSUBCLASS_purified__Triples_Identifiers.txt	PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_Triples_Identifiers.txt PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_INSTANCE_purified_Triples_Identifiers.txt
	PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_Triples_Integer_Identifier_Map.json PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_SUBCLASS_purified_Triples_Integer_Identifier_Map.json	PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_Triples_Integer_Identifier_Map.json PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_INSTANCE_purified_Triples_Integer_Identifier_Map.json
INVERSE RELATIONS
OWL	PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_Triples_Integers.txt PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_SUBCLASS_purified_Triples_Integers.txt	PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_Triples_Integers.txt PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_INSTANCE_purified_Triples_Integers.txt
	PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_Triples_Identifiers.txt PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_SUBCLASS_purified_Triples_Identifiers.txt	PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_Triples_Identifiers.txt PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_INSTANCE_purified_Triples_Identifiers.txt
	PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_Triples_Integer_Identifier_Map.json PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_SUBCLASS_purified_Triples_Integer_Identifier_Map.json	PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_Triples_Integer_Identifier_Map.json PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_INSTANCE_purified_Triples_Integer_Identifier_Map.json

OWL Decoded	PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_Triples_Integers.txt PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_SUBCLASS_purified_Triples_Integers.txt	PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_Triples_Integers.txt PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_INSTANCE_purified_Triples_Integers.txt
	PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_Triples_Identifiers.txt PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_SUBCLASS_purified_Triples_Identifiers.txt	PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_Triples_Identifiers.txt PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_INSTANCE_purified_Triples_Identifiers.txt
	PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_Triples_Integer_Identifier_Map.json PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_SUBCLASS_purified_Triples_Integer_Identifier_Map.json	PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_Triples_Integer_Identifier_Map.json PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_INSTANCE_purified_Triples_Integer_Identifier_Map.json

Metadata Output

Data: https://zenodo.org/doi/10.5281/zenodo.7030039

Each file is a tab-delimited .txt file that contains the following columns:

entity_type (e.g. "NODES", "RELATIONS", or "NA" if not a owl:Class. owl:NamedIndividual, owl:ObjectProperty, or owl:AnnotationProperty)
integer_id (e.g. 1 - the integer used to represent this URI in the Edge List output)
entity_uri (e.g. "GO_0048252")
label (e.g. "lauric acid metabolic process")
description/definition (e.g. "The chemical reactions and pathways involving lauric acid, a fatty acid with the formula CH3(CH2)10COOH. Derived from vegetable sources.")
synonym (e.g. "lauric acid metabolism|n-dodecanoic acid metabolic process|n-dodecanoic acid metabolism")

NOTE. For knowledge graphs that do not employ OWL decoding, there will be entries with values of NA for entity_type. This is expected for these types of builds; a value of NA is used for all nodes and relations that are not an owl:Class, owl:NamedIndividual, or owl:ObjectProperty.

Example Metadata:

entity_type	integer_id	entity_uri	label	description/definition	synonym
NODES	0	http://www.ncbi.nlm.nih.gov/gene/388324	INCA1	INCA1 has locus group 'protein-coding' and is located on chromosome 17 (map_location: 17p13.2)	HSD45protein INCA1
NODES	1	http://www.ncbi.nlm.nih.gov/gene/92106	OXNAD1	OXNAD1 has locus group 'protein-coding' and is located on chromosome 3 (map_location: 3p25.1-p24.3)	oxidoreductase NAD-binding domain-containing protein 1
RELATIONS	2	http://purl.obolibrary.org/obo/RO_0002533	sequence atomic unit	Any individual unit of a collection of like units arranged in a linear order	NA

Available Output Files:

Detail	Subclass Construction	Instance Construction
RELATIONS
OWL	PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_NodeLabels.txt PheKnowLator_v2.0.0_full_subclass_relationsOnly_OWL_SUBCLASS_purified_NodeLabels.txt	PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_NodeLabels.txt PheKnowLator_v2.0.0_full_instance_relationsOnly_OWL_INSTANCE_purified_NodeLabels.txt
OWL Decoded	PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_NodeLabels.txt PheKnowLator_v2.0.0_full_subclass_relationsOnly_noOWL_SUBCLASS_purified_NodeLabels.txt	PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_NodeLabels.txt PheKnowLator_v2.0.0_full_instance_relationsOnly_noOWL_INSTANCE_purified_NodeLabels.txt
INVERSE RELATIONS
OWL	PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_NodeLabels.txt PheKnowLator_v2.0.0_full_subclass_inverseRelations_OWL_SUBCLASS_purified_NodeLabels.txt	PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_NodeLabels.txt PheKnowLator_v2.0.0_full_instance_inverseRelations_OWL_INSTANCE_purified_NodeLabels.txt
OWL Decoded	PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_NodeLabels.txt PheKnowLator_v2.0.0_full_subclass_inverseRelations_noOWL_SUBCLASS_purified_NodeLabels.txt	PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_NodeLabels.txt PheKnowLator_v2.0.0_full_instance_inverseRelations_noOWL_INSTANCE_purified_NodeLabels.txt

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This project is licensed under Apache License 2.0 - see the LICENSE.md file for details. If you intend to use any of the information on this Wiki, please provide the appropriate attribution by citing this repository:

@misc{callahan_tj_2019_3401437,
  author       = {Callahan, TJ},
  title        = {PheKnowLator},
  month        = mar,
  year         = 2019,
  doi          = {10.5281/zenodo.3401437},
  url          = {https://doi.org/10.5281/zenodo.3401437}
}

Project Information

Tutorials and Use Cases

Tutorials
- Implementing OWL-NETS
- Processing an RDF Graph
Use Cases
- Drug Safety
  - KG-based Investigation of Drug-Outcome Pairs

Releases

Benchmarks and Builds
- Archived

Human Disease KG Builds

Archived Builds
- v1.0.0
  - September 3, 2019
- v2.0.0
- v2.1.0
- v3.0.2
  - October 18, 2021
  - November 01, 2021

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v2 Build Details

Release: `v2.0.0`

Release Updates

Jupyter Notebooks

Ontologies

Creation of Mapping, Filtering, and Labeling Data

Edge Data

Knowledge Graph Output

CONSTRUCTION APPROACH

RELATIONS

OWL SEMANTICS

SEMANTIC CONSISTENCY

Knowledge Graph Data

Edge List Output

Metadata Output

Project Information

Tutorials and Use Cases

Releases

Human Disease KG Builds

FAQs

Enabling Reproducible Research

Clone this wiki locally

v2 Build Details

Release: v2.0.0

Release Updates

Jupyter Notebooks

Ontologies

Creation of Mapping, Filtering, and Labeling Data

Edge Data

Knowledge Graph Output

CONSTRUCTION APPROACH

RELATIONS

OWL SEMANTICS

SEMANTIC CONSISTENCY

Knowledge Graph Data

Edge List Output

Metadata Output

Project Information

Tutorials and Use Cases

Releases

Human Disease KG Builds

FAQs

Enabling Reproducible Research

Clone this wiki locally

Release: `v2.0.0`