Generate a meta knowledge graph of how biomedical concepts are connected based on SmartAPI Specifications with built-in filtering capabilities
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pnpm i @biothings-explorer/smartapi-kg
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Import and Initialize
const kg = require("@biothings-explorer/smartapi-kg") //initiate a new knowledge graph class let meta_kg = new kg.default()
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Load the Meta Knowledge Graph (meta-kg)
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Option 1: Load Meta-KG from SmartAPI specs with translator tag specified
//async load knowledge graph from SmartAPI await meta_kg.constructMetaKG()
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Option 2: Load Meta-KG from SmartAPI specs with translator tag as well as ReasonerStdAPI with /predicates endpoint
await meta_kg.constructMetaKG(includeReasoner=true);
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Option 3: Load Meta-KG from SmartAPI specs with tags equal to biothings
await meta_kg.constructMetaKG(includeReasoner = false, {tag: "biothings"});
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Option 4: Load Meta-KG from SmartAPI specs with team name equal to Text Mining Provider
await meta_kg.constructMetaKG(includeReasoner = false, {teamName: "Text Mining Provider"});
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Option 5: Load Meta-KG from SmartAPI specs with component equal to KP
await meta_kg.constructMetaKG(includeReasoner = false, {component: "KP"});
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Option 6: Load Meta-KG for a specific SmartAPI spec with SmartAPI ID
await meta_kg.constructMetaKG(includeReasoner = false, {smartAPIID: "5076f09382b38d56a77e376416b634ca"});
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Option 7: Load Meta-KG from a local copy of SmartAPI specs included in the package
//Alternatively, you can also sync load SmartAPI specs from a local copy within the package meta_kg.constructMetaKGSync();
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Option 8: Load Meta-KG from file path you specify
const path = require("path"); // provide file path storing your SmartAPI file const file_path = path.resolve(__dirname, '../data/smartapi_multiomics_kp_query.json'); let meta_kg = new MetaKG(file_path); meta_kg.constructMetaKGSync();
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Option 9: Load Meta-KG from data you specify
const smartapiSpecs = {} // This should contain your smartapi specs: could be from file read, redis, etc. const predicates = [] // This should contain predicates data on TRAPI APIs (optional) let meta_kg = new MetaKG(); meta_kg.constructMetaKGSync(includeReasoner = true, { predicates, smartapiSpecs });
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Option 10: Load Meta-KG from operations you specify
const meta_kg_old = new MetaKG(); meta_kg_old.constructMetaKGSync(); const ops = meta_kg_old.ops; // ops can be transfered over a network/threads since it just stores JSON // loading a new MetaKG from the operations const meta_kg = new MetaKG(undefined, undefined, ops);
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Option 11: Load Meta-KG with an api list
meta_kg.constructMetaKGSync(includeReasoner=true, {apiList: [ { id: '09c8782d9f4027712e65b95424adba79', name: 'MyVariant.info API' }, { id: '59dce17363dce279d389100834e43648', name: 'MyGene.info API' } ]});
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Filter the Meta-KG for specific associations based on input, output, predicate, or api combinations.
//filter based on predicate meta_kg.filter({predicate: 'treats'}) //filter based on predicate and input_id meta_kg.filter({predicate: 'treats', input_id: 'CHEMBL.COMPOUND'}) //filter based on predicate and input_type meta_kg.filter({predicate: ['treats', 'physically_interacts_with'], input_type: 'SmallMolecule'}) //filter based on input_type, output_type and api meta_kg.filter({ api: "Automat PHAROS API", input_type: "SmallMolecule", output_type: "Gene" });
pnpm run test
👤 Jiwen Xin
- Website: http://github.com/kevinxin90
- Github: @kevinxin90
Contributions, issues and feature requests are welcome!
Feel free to check issues page.
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Copyright © 2020 Jiwen Xin.
This project is ISC licensed.
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