4.8 Article

Biological interpretation of genome-wide association studies using predicted gene functions

期刊

NATURE COMMUNICATIONS
卷 6, 期 -, 页码 -

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/ncomms6890

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资金

  1. Danish Council for Independent Research Medical Sciences (FSS) The Alfred Benzon Foundation
  2. Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development, NIH
  3. Netherlands Organization for Scientific Research [916-10135, 917-14374]
  4. Horizon Breakthrough grant from the Netherlands Genomics Initiative [92519031]
  5. European Community's Health Seventh Framework Programme (FP7) [259867]
  6. National Institute of Diabetes and Digestive and Kidney Diseases [2R01DK075787]
  7. EUNICE KENNEDY SHRIVER NATIONAL INSTITUTE OF CHILD HEALTH & HUMAN DEVELOPMENT [ZIAHD000640] Funding Source: NIH RePORTER
  8. NATIONAL CANCER INSTITUTE [P30CA071789] Funding Source: NIH RePORTER
  9. NATIONAL HEART, LUNG, AND BLOOD INSTITUTE [R01HL117078] Funding Source: NIH RePORTER
  10. NATIONAL INSTITUTE OF ARTHRITIS AND MUSCULOSKELETAL AND SKIN DISEASES [R01AR063759, UH2AR067677] Funding Source: NIH RePORTER
  11. NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES [P30DK020572, R01DK075787] Funding Source: NIH RePORTER
  12. NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [U01GM092691] Funding Source: NIH RePORTER
  13. NATIONAL INSTITUTE ON AGING [ZIAAG000675] Funding Source: NIH RePORTER
  14. MRC [MR/K013351/1, MR/N01104X/1, G1001799] Funding Source: UKRI
  15. Lundbeck Foundation [R190-2014-3904] Funding Source: researchfish
  16. Medical Research Council [MR/K006584/1, MR/N01104X/1, G1001799, MR/K013351/1] Funding Source: researchfish
  17. National Institute for Health Research [NF-SI-0611-10170, NF-SI-0513-10059, NF-SI-0611-10219, NF-SI-0514-10027] Funding Source: researchfish
  18. NNF Center for Basic Metabolic Research [Pers Group] Funding Source: researchfish
  19. Chief Scientist Office [CZB/4/672] Funding Source: researchfish

向作者/读者索取更多资源

The main challenge for gaining biological insights from genetic associations is identifying which genes and pathways explain the associations. Here we present DEPICT, an integrative tool that employs predicted gene functions to systematically prioritize the most likely causal genes at associated loci, highlight enriched pathways and identify tissues/cell types where genes from associated loci are highly expressed. DEPICT is not limited to genes with established functions and prioritizes relevant gene sets for many phenotypes.

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