4.4 Article

Network analysis of GWAS data

期刊

CURRENT OPINION IN GENETICS & DEVELOPMENT
卷 23, 期 6, 页码 602-610

出版社

CURRENT BIOLOGY LTD
DOI: 10.1016/j.gde.2013.09.003

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资金

  1. Career Award at the Scientific Interface from the Burroughs Wellcome Fund
  2. Alfred P. Sloan Research Fellowship
  3. National Human Genome Research Institute [R01HG005690]
  4. NSF CAREER Award [CCF-1053753]
  5. NSF [IIS-1016648]
  6. Pew Charitable Trusts as a Pew Scholar in the Biomedical Sciences
  7. NSF Graduate Research Fellowship [DGE 0228243]
  8. Direct For Computer & Info Scie & Enginr
  9. Division of Computing and Communication Foundations [1053753] Funding Source: National Science Foundation
  10. Div Of Information & Intelligent Systems
  11. Direct For Computer & Info Scie & Enginr [1016648] Funding Source: National Science Foundation

向作者/读者索取更多资源

Genome-wide association studies (GWAS) identify genetic variants that distinguish a control population from a population with a specific trait. Two challenges in GWAS are: (1) identification of the causal variant within a longer haplotype that is associated with the trait; (2) identification of causal variants for polygenic traits that are caused by variants in multiple genes within a pathway. We review recent methods that use information in protein-protein and protein-DNA interaction networks to address these two challenges.

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