PINBPA: Cytoscape app for network analysis of GWAS data

Bioinformatics

Volumn 31, Issue 2, 2015, Pages 262-264

  Wang, Lili ^a   Matsushita, Takuya ^b   Madireddy, Lohith ^b   Mousavi, Parvin ^a   Baranzini, Sergio E ^b  

^a QUEEN S UNIVERSITY   (Canada)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; COMPUTER PROGRAM; DATA MINING; GENETIC ASSOCIATION; HUMAN; PROCEDURES; PROTEIN PROTEIN INTERACTION; PROTEOMICS;

ALGORITHMS; DATA MINING; GENOME-WIDE ASSOCIATION STUDY; HUMANS; PROTEIN INTERACTION MAPS; PROTEOMICS; SOFTWARE;

EID: 84928990843     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btu644     Document Type: Article

References (17)

1. Akula, N. et al. (2011) A network-based approach to prioritize results from genome-wide association studies. PLoS One, 6, E24220.
2. Baranzini, S.E. et al. (2009) Pathway and network-based analysis of genome-wide association studies in multiple sclerosis. Hum. Mol. Genet., 18, 2078-2090.
3. Huang Da, W. et al. (2009) Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res., 37, 1-13.
4. Ideker, T. et al. (2002) Discovering regulatory and signalling circuits in molecular interaction networks. Bioinformatics, 18 (Suppl. 1), S233-S240.
5. International Multiple Sclerosis Genetics Consortium. (2013) Network-based multiple sclerosis pathway analysis with gwas data from 15, 000 cases and 30, 000 controls. Am. J. Hum. Genet., 92, 854-865.
6. Jia, P. et al. (2011) dmGWAS: dense module searching for genome-wide association studies in protein-protein interaction networks. Bioinformatics, 27, 95-102.
7. Khatri, P. et al. (2012) Ten years of pathway analysis: current approaches and outstanding challenges. PLoS Comput. Biol., 8, e1002375.
8. Kohler, S. et al. (2008) Walking the interactome for prioritization of candidate disease genes. Am. J. Hum. Genet., 82, 949-958.
9. Lage, K. et al. (2007) A human phenome-interactome network of protein complexes implicated in genetic disorders. Nat. Biotechnol., 25, 309-316.
10. Lee, P.H. et al. (2012) INRICH: interval-based enrichment analysis for genome-wide association studies. Bioinformatics, 28, 1797-1799.
11. Liu, J.Z. et al. (2010) A versatile gene-based test for genome-wide association studies. Am. J. Hum. Genet., 87, 139-145.
12. Rossin, E.J. et al. (2011) Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology. PLos Genet., 7, e1001273.
13. Shannon, P. et al. (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res., 13, 2498-2504.
14. Wang, K. et al. (2007) Pathway-based approaches for analysis of genomewide association studies. Am. J. Hum. Genet., 81, 1278-1283.
15. Welter, D. et al. (2014) The NHGRI GWAS catalog, a curated resource of SNP-trait associations. Nucleic Acids Res., 42, D1001-D1006.
16. Whitlock, M.C. (2005) Combining probability from independent tests: the weighted z-method is superior to fisher's approach. J. Evol. Biol., 18, 1368-1373.
17. Yaspan, B.L. et al. (2011) Genetic analysis of biological pathway data through gen-omic randomization. Hum. Genet., 129, 563-571.