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Clinical Knowledge Graph

version: 1.0

A Python project that allows you to analyse proteomics and clinical data, and integrate and mine knowledge from multiple biomedical databases widely used nowadays.

Abstract

abstract abstract

The promise of precision medicine is to deliver personalized treatment based on the unique physiology of each patient. This concept was fueled by the genomic revolution, but it is now evident that integrating other types of omics data, like proteomics, into the clinical decision-making process will be essential to accomplish precision medicine goals. However, quantity and diversity of biomedical data, and the spread of clinically relevant knowledge across myriad biomedical databases and publications makes this exceptionally difficult. To address this, we developed the Clinical Knowledge Graph (CKG), an open source platform currently comprised of more than 16 million nodes and 220 million relationships to represent relevant experimental data, public databases and the literature. The CKG also incorporates the latest statistical and machine learning algorithms, drastically accelerating analysis and interpretation of typical proteomics workflows. We use several biomarker studies to illustrate how the CKG may support, enrich and accelerate clinical decision-making.

Cloning and installing

Installation requires >= 80 GB of disk space. See details here.

The setting up of the CKG includes several steps and might take a few hours (if you are building the database from scratch). However, we have prepared documentation and manuals that will guide through every step. To get a copy of the GitHub repository on your local machine, please open a terminal windown and run:

$ git clone https://github.com/MannLabs/CKG.git

This will create a new folder named “CKG” on your current location. To access the documentation, use the ReadTheDocs link above, or open the html version stored in the CKG folder CKG/docs/build/html/index.html. After this, follow the instructions in “First Steps” and “Getting Started”.

Warning

If git is not installed in your machine, please follow this tutorial to install it.

Features

  • Cross-platform: Mac, and Linux are officially supported. Instructions for Windows exist.

  • Docker container runs all neccessary steps to setup the CKG.

Disclaimer

This resource is intended for research purposes and must not substitute a doctor’s medical judgement or healthcare professional advice.

Important Note

The databases provided within the Clinical Knowledge Graph (CKG) have their own licenses and the use of CKG still requires compliance with these data use restrictions. Please, visit the data sources directly for more information:

Source type

Source

URL

Reference

Database

UniProt

https://www.uniprot.org/

https://www.ncbi.nlm.nih.gov/pubmed/29425356

Database

TISSUES

https://tissues.jensenlab.org/

https://www.ncbi.nlm.nih.gov/pubmed/29617745

Database

STRING

https://string-db.org/

https://www.ncbi.nlm.nih.gov/pubmed/30476243

Database

STITCH

http://stitch.embl.de/

https://www.ncbi.nlm.nih.gov/pubmed/26590256

Database

SMPDB

https://smpdb.ca/

https://www.ncbi.nlm.nih.gov/pubmed/24203708

Database

SIGNOR

https://signor.uniroma2.it/

https://www.ncbi.nlm.nih.gov/pubmed/31665520

Database

SIDER

http://sideeffects.embl.de/

https://www.ncbi.nlm.nih.gov/pubmed/26481350

Database

RefSeq

https://www.ncbi.nlm.nih.gov/refseq/

https://www.ncbi.nlm.nih.gov/pubmed/26553804

Database

Reactome

https://reactome.org/

https://www.ncbi.nlm.nih.gov/pubmed/31691815

Database

PhosphoSitePlus

https://www.phosphosite.org/

https://www.ncbi.nlm.nih.gov/pubmed/25514926

Database

Pfam

https://pfam.xfam.org/

https://www.ncbi.nlm.nih.gov/pubmed/30357350

Database

OncoKB

https://www.oncokb.org/

https://www.ncbi.nlm.nih.gov/pubmed/28890946

Database

MutationDs

https://www.ebi.ac.uk/intact/resources/datasets#mutationDs

https://www.ncbi.nlm.nih.gov/pubmed/30602777

Database

Intact

https://www.ebi.ac.uk/intact/

https://www.ncbi.nlm.nih.gov/pubmed/24234451

Database

HPA

https://www.proteinatlas.org/

https://www.ncbi.nlm.nih.gov/pubmed/21572409

Database

HMDB

https://hmdb.ca/

https://www.ncbi.nlm.nih.gov/pubmed/29140435

Database

HGNC

https://www.genenames.org/

https://www.ncbi.nlm.nih.gov/pubmed/30304474

Database

GwasCatalog

https://www.ebi.ac.uk/gwas/

https://www.ncbi.nlm.nih.gov/pubmed/30445434

Database

FooDB

https://foodb.ca/

Database

DrugBank

https://www.drugbank.ca/

https://www.ncbi.nlm.nih.gov/pubmed/29126136

Database

DisGeNET

https://www.disgenet.org/

https://www.ncbi.nlm.nih.gov/pubmed/25877637

Database

DISEASES

https://diseases.jensenlab.org/

https://www.ncbi.nlm.nih.gov/pubmed/25484339

Database

DGIdb

http://www.dgidb.org/

https://www.ncbi.nlm.nih.gov/pubmed/29156001

Database

CORUM

https://mips.helmholtz-muenchen.de/corum/

https://www.ncbi.nlm.nih.gov/pubmed/30357367

Database

Cancer Genome Interpreter

https://www.cancergenomeinterpreter.org/

https://www.ncbi.nlm.nih.gov/pubmed/29592813

Ontology

Disease Ontology

https://disease-ontology.org/

https://www.ncbi.nlm.nih.gov/pubmed/30407550

Ontology

Brenda Tissue Ontology

https://www.brenda-enzymes.org/ontology.php?ontology_id=3

https://www.ncbi.nlm.nih.gov/pubmed/25378310

Ontology

Experimental Factor Ontology

https://www.ebi.ac.uk/efo/

https://www.ncbi.nlm.nih.gov/pubmed/20200009

Ontology

Gene Ontology

http://geneontology.org/

https://www.ncbi.nlm.nih.gov/pubmed/27899567

Ontology

Human Phenotype Ontology

https://hpo.jax.org/

https://www.ncbi.nlm.nih.gov/pubmed/27899602

Ontology

SNOMED-CT

http://www.snomed.org/

https://www.ncbi.nlm.nih.gov/pubmed/27332304

Ontology

Protein Modification Ontology

https://www.ebi.ac.uk/ols/ontologies/mod

https://www.ncbi.nlm.nih.gov/pubmed/23482073

Ontology

Molecular Interactions Ontology

https://www.ebi.ac.uk/ols/ontologies/mi

https://www.ncbi.nlm.nih.gov/pubmed/23482073

Ontology

Mass Spectrometry Ontology

https://www.ebi.ac.uk/ols/ontologies/ms

https://www.ncbi.nlm.nih.gov/pubmed/23482073

Ontology

Units Ontology

https://bioportal.bioontology.org/ontologies/UO

https://www.ncbi.nlm.nih.gov/pubmed/23060432