Network analysis of GWAS data

Mark D M Leiserson; Jonathan V Eldridge; Sohini Ramachandran; Benjamin J Raphael

doi:10.1016/j.gde.2013.09.003

Network analysis of GWAS data

Curr Opin Genet Dev. 2013 Dec;23(6):602-10. doi: 10.1016/j.gde.2013.09.003. Epub 2013 Nov 26.

Authors

Mark D M Leiserson¹, Jonathan V Eldridge, Sohini Ramachandran, Benjamin J Raphael

Affiliation

¹ Department of Computer Science, Brown University, Providence, RI 02912, United States; Center for Computational Molecular Biology, Brown University, Providence, RI 02912, United States.

Abstract

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.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.
Review

MeSH terms

Computational Biology / methods
Gene Expression Profiling / methods
Gene Regulatory Networks*
Genome-Wide Association Study / methods*
Humans
Protein Interaction Mapping / methods*
Protein Interaction Maps / genetics*

Abstract

Publication types

MeSH terms

Grants and funding