EpiGraphDB documentaion

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Web API

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EpiGraphDB R package

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The increasing availability of complex, high-dimensional epidemiological data necessitates innovative and scalable approaches to harness its potential to address research questions of biomedical importance. EpiGraphDB is an analytical platform and database that aims to address this challenge, supporting data mining in epidemiology.

Our core objectives are to:

  • Develop approaches for the appropriate application and interpretation of causal inference in systematic automated analyses of many phenotypes using data from a rich array of bioinformatic resources.
  • Apply data mining approaches to the same integrated dataset to make novel discoveries about disease mechanisms and potential interventions relevant to population health

Note EpiGraphDB is currently in beta. There may be issues/errors with data, queries and analyse! We welcome any feedback to feedback@epigraphdb.org.

Funding sources

  • EpiGraphDB receives core funding from the UK Medical Research Council as part of the Data Mining Epidemiological Relationships programme in the MRC Integrative Epidemiology Unit.
  • The pQTL browser was developed as part of a collaboration between the MRC IEU, GlaxoSmithKline and Biogen, and is described here
  • The MR-EvE data within EpiGraphDB has been produced by Gibran Hemani on a Wellcome Sir Henry Dale fellowship
  • Pathway data and network analysis methods have been supported by funding from Cancer Research UK

Data sources

EpiGraphDB integrates data generated at the MRC IEU with data from a range of third party sources. These include:

 

node count
Disease 3,312
Pathway 2,179
Gene 22,219
Gtex 53
Literature 1,871,731
Protein 21,558
MeshTerm 29,380
UMLS 4,682
Efo 21,864
Snp 45,022
Semmed 462,750
Gwas 21,281
Drug 3,061
MeshTree 58,744
Event 11,868

 

relationship count
DRUG_TO_PROTEIN 22,438
PROTEIN_TO_LITERATURE 107,559
EVENT_IN_PATHWAY 12,488
EFO_EXACT 363
INTACT_NOT_INTERACTS_WITH 699
STRING_INTERACT_WITH 390,222
UMLS_SEM_OBJECT 462,750
GWAS_COR 73,853
EFO_FUZZY 452
MESH_HIERARCHY 58,744
XQTL_MR_GENE_GWAS 9,163,028
PROTEIN_TO_DISEASE 668
MR 1,727,240
PROTEIN_IN_EVENT 13,484
PATHWAY_TO_DISEASE 600
EXPRESSED_IN 704,420
SNP_GENE 10,906
SEM 2,537,738
DRUG_TO_DISEASE 162
EFO_CHILD_OF 26,562
PRECEDING_EVENT 10,418
METAMAP_LITE 30,412
MESH_EXACT 161
GENE_TO_LITERATURE 766
UMLS_SEM_SUBJECT 462,750
PROTEIN_IN_PATHWAY 9,281
XQTL_MR 3,324,150
MRE_STUDY_SNP 29,767
CPIC 356
EFO_ZOOMA 45,538
MESH_TO_DISEASE 3,318
PATHWAY_TO_LITERATURE 8,952
TRAIT_NLP 2,119,498
OBS_COR 186,315
XQTL_MR_SNP_GENE 35,646
DRUG_TO_LITERATURE 243
MESH_FUZZY 1,046
OPENTARGETS_DRUG_TO_TARGET 6,042
INTACT_INTERACTS_WITH 188,872
MESH_PARENT 58,626
GWAS_TO_LITERATURE 21,281
GENE_TO_PROTEIN 20,762
MESH_MANUAL 1,279