PRIMe: A method for characterization and evaluation of pleiotropic regions from multiple genome-wide association studies

Bioinformatics

Volumn 27, Issue 9, 2011, Pages 1201-1206

  Huang, Jie ^a,b   Johnson, Andrew D ^a,b   O'Donnell, Christopher J ^a,b,c  

^a FRAMINGHAM HEART STUDY   (United States)

^b NATIONAL HEART LUNG AND BLOOD INSTITUTE   (United States)

^c MASSACHUSETTS GENERAL HOSPITAL   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; COMPUTER PROGRAM; COMPUTER SIMULATION; GENETIC ASSOCIATION; GENOMICS; HUMAN; HUMAN GENOME; METHODOLOGY; MULTIVARIATE ANALYSIS; PHENOTYPE; PLEIOTROPY; STATISTICAL MODEL;

COMPUTER SIMULATION; GENETIC PLEIOTROPY; GENOME, HUMAN; GENOME-WIDE ASSOCIATION STUDY; GENOMICS; HUMANS; MODELS, STATISTICAL; MULTIVARIATE ANALYSIS; PHENOTYPE; SOFTWARE;

EID: 79954520229     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btr116     Document Type: Article

References (32)

1. Barrett,J.C. et al. (2009) Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nat Genet., 41, 703-707.
2. Church,C. et al. (2010) Overexpression of Fto leads to increased food intake and results in obesity. Nat. Genet., 42, 1086-1092.
3. Conneely,K.N. and Boehnke,M. (2007) So Many Correlated Tests, So Little Time! Rapid Adjustment of P Values for Multiple Correlated Tests. Am. J. Hum. Genet., 81, 1158-1168.
4. de Bakker,P.I. et al. (2005) Efficiency and power in genetic association studies. Nat. Genet., 37, 1217-1223.
5. Ferreira,M.A. and Purcell,S. M. (2009) A multivariate test of association. Bioinformatics, 25, 132-133.
6. Foster,K.R. et al. (2004) Pleiotropy as a mechanism to stabilize cooperation. Nature, 431, 693-696.
7. Frazer,K.A. et al. (2007)A second generation human haplotype map of over 3.1 million SNPs. Nature, 449, 851-861.
8. Ganesh,S.K. et al. (2009) Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium. Nat. Genet., 41, 1191-1198.
9. Hindorff,L.A. et al. (2009) Potential etiologic and functional implications of genomewide association loci for human diseases and traits. Proc. Natl Acad. Sci. USA, 106, 9362-9367.
10. Hodgkin,J. (1998) Seven types of pleiotropy. Int. J. Dev. Biol., 42, 501-505.
11. Huang,J. et al. (2010) Cross-disorder genomewide analysis of schizophrenia, bipolar disorder, and depression. Am. J. Psychiatry, 167, 1254-1263.
12. Hunt,K.A. et al. (2008) Newly identified genetic risk variants for celiac disease related to the immune response. Nat. Genet., 40, 395-402.
13. Johnson,A.D. and O'Donnell,C.J. (2009) An open access database of genome-wide association results. BMC Med. Genet., 10, 6.
14. Kitsios,G.D. and Zintzaras,E. (2009) Genomic convergence of genome-wide investigations for complex traits. Ann. Hum. Genet., 73 (Pt 5), 514-519.
15. Lange,C. et al. (2003) A multivariate family-based association test using generalized estimating equations: FBAT-GEE. Biostatistics, 4, 195-206.
16. Levy,D. et al. (2009) Genome-wide association study of blood pressure and hypertension. Nat. Genet., 41, 677-687.
17. Liu,J. et al. (2009) Bivariate association analyses for the mixture of continuous and binary traits with the use of extended generalized estimating equations. Genet. Epidemiol., 33, 217-227.
18. Lumley,T. and Rice,K. (2010) Potential for revealing individual-level information in genome-wide association studies. JAMA, 303, 659-660.
19. Mailman,M.D. et al. (2007) The NCBI dbGaP database of genotypes and phenotypes. Nat. Genet., 39, 1181-1186.
20. Pe'er,I. et al. (2008) Estimation of the multiple testing burden for genomewide association studies of nearly all common variants. Genet. Epidemiol., 32, 381-385.
21. Psaty,B.M. et al. (2009) Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium: Design of prospective meta-analyses of genome-wide association studies from 5 cohorts. Circ. Cardiovasc. Genet., 2, 73-80.
22. Purcell,S. et al. (2007) PLINK: a tool set for whole-genome association and populationbased linkage analyses. Am. J. Hum. Genet., 81, 559-575.
23. Pyeritz,R.E. (1989) Pleiotropy revisited: molecular explanations of a classic concept. Am. J. Med. Genet., 34, 124-134.
24. Sirota,M. et al. (2009) Autoimmune disease classification by inverse association with SNP alleles. PLoS Genet., 5, e1000792.
25. Soranzo,N. et al. (2009) A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nat. Genet., 41, 1182-1190.
26. Stearns,F.W. (2010) One hundred years of pleiotropy: a retrospective. Genetics, 186, 767-773.
27. Teslovich,T.M. et al. (2010) Biological, clinical and population relevance of 95 loci for blood lipids. Nature, 466, 707-713.
28. Thorisson,G.A. et al. (2005) The International HapMap Project Web site. Genome Res., 15, 1592-1593.
29. Tyler,A.L. et al. (2009) Shadows of complexity: what biological networks reveal about epistasis and pleiotropy. Bioessays, 31, 220-227.
30. WTCCC (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447, 661-678.
31. Yang,Q. et al. (2010) Analyze multivariate phenotypes in genetic association studies by combining univariate association tests. Genet Epidemiol., 34, 444-454.
32. Zou,L. et al. (2008) Systematic analysis of pleiotropy in C. elegans early embryogenesis. PLoS Comput. Biol., 4, e1000003.