Behavior of QQ-plots and Genomic Control in studies of gene-environment interaction

PLoS ONE

Volumn 6, Issue 5, 2011, Pages

  Voorman, Arend ^a   Lumley, Thomas ^a   McKnight, Barbara ^a   Rice, Kenneth ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHM; ARTICLE; COMPUTER SIMULATION; CONTROLLED STUDY; ENVIRONMENTAL EXPOSURE; FUNCTIONAL GENOMICS; GENE CONTROL; GENE LOCUS; GENETIC ASSOCIATION; GENETIC VARIABILITY; GENOTYPE ENVIRONMENT INTERACTION; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; PHENOTYPIC VARIATION; SINGLE NUCLEOTIDE POLYMORPHISM; ENVIRONMENT; GENOMICS; HUMAN;

ENVIRONMENT; GENOME-WIDE ASSOCIATION STUDY; GENOMICS; HUMANS;

EID: 79955936872     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0019416     Document Type: Article

References (18)

1. Hunter DJ, (2005) Gene-environment interactions in human diseases. Nat Rev Genet 6: 287-298.
2. Thomas D, (2010) Gene-environment-wide association studies: emerging approaches. Nat Rev Genet 11: 259-272.
3. Pearson T, Manolio T, (2008) How to interpret a genome-wide association study. Jama 299: 1335.
4. Devlin B, Roeder K, (1999) Genomic control for association studies. Biometrics 55: 997-1004.
5. Ganesh S, Zakai N, van Rooij F, Soranzo N, Smith A, et al. (2009) Multiple loci inuence erythrocyte phenotypes in the CHARGE Consortium. Nature genetics 41: 1191-1198.
6. Nolte I, Wallace C, Newhouse S, Waggott D, Fu J, et al. (2009) Common genetic variation near the phospholamban gene is associated with cardiac repolarisation: meta-analysis of three genome-wide association studies. PLoS One 4: e6138.
7. Price A, Patterson N, Plenge R, Weinblatt M, Shadick N, et al. (2006) Principal components analysis corrects for stratification in genome-wide association studies. Nature genetics 38: 904-909.
8. Zhang F, Wang Y, Deng H, (2008) Comparison of population-based association study methods correcting for population stratification. PLoS One 3: 3392.
9. Draper N, Smith H, (1998) Applied regression analysis. 706 John Wiley and Sons. New York.
10. Cox D, (2006) Principles of statistical inference Cambridge Univ Pr.
11. White H, (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48: 817-838.
12. StataCorp (2009) Stata statistical software: Release 11.
13. Zeileis A, (2004) Econometric computing with hc and hac covariance matrix estimators. Journal of Statistical Software 11: 1-17.
14. Zeileis A, (2006) Object-oriented computation of sandwich estimators. Journal of Statistical Software 16: 1-16.
15. Therneau T, original R port by Thomas Lumley (2009) survival: Survival analysis, including penalised likelihood. URL http://CRAN.R-project.org/package=survival. Accessed 2011 April 7. R package version 2.35-4.
16. Royall R, (1986) Model robust confidence intervals using maximum likelihood estimators. International Statistical Review/Revue Internationale de Statistique 54: 221-226.
17. Glazer NL, Felix JF, Dörr M, Chen MH, Schmidt R, et al. (2010) Genome-wide meta-analyses of snp by environmental factor interactions on echocardiographic traits: a charge-echogen study. In Press.
18. R Development Core Team (2009) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org. ISBN 3-900051-07-0.