Comparisons of power of statistical methods for gene-environment interaction analyses

European Journal of Epidemiology

Volumn 28, Issue 10, 2013, Pages 785-797

  Ege, Markus J ^a   Strachan, David P ^b  

^a LUDWIG MAXIMILIANS UNIVERSITY   (Germany)

^b ST GEORGE S HOSPITAL   (United Kingdom)

Author keywords

False positive rate; Gene environment interaction; Genome wide testing; Statistical modeling; True positive rate

Indexed keywords

ARTICLE; CONTROLLED STUDY; GENE FREQUENCY; GENE LOCUS; GENETIC ASSOCIATION; GENETIC MODEL; GENOME ANALYSIS; GENOTYPE ENVIRONMENT INTERACTION; NULL HYPOTHESIS; PREVALENCE; SIMULATION; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL ANALYSIS; STATISTICAL MODEL;

COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; FALSE POSITIVE REACTIONS; GENE-ENVIRONMENT INTERACTION; GENETIC LOCI; GENOME-WIDE ASSOCIATION STUDY; HUMANS; MODELS, GENETIC; MODELS, STATISTICAL; POLYMORPHISM, SINGLE NUCLEOTIDE;

EID: 84886524046     PISSN: 03932990     EISSN: 15737284     Source Type: Journal    
DOI: 10.1007/s10654-013-9837-4     Document Type: Article

References (14)

1. Thomas D. Gene-environment-wide association studies: emerging approaches. Nat Rev Genet. 2010;11(4):259-72.
2. Piegorsch WW, Weinberg CR, Taylor JA. Non-hierarchical logistic models and case-only designs for assessing susceptibility in population-based case-control studies. Stat Med. 1994;13(2):153-62. (Pubitemid 24017109)
3. Mukherjee B, Ahn J, Gruber SB, Rennert G, Moreno V, Chatterjee N. Tests for gene-environment interaction from case-control data: a novel study of type I error, power and designs. Genet Epidemiol. 2008;32(7):615-26.
4. Mukherjee B, Chatterjee N. Exploiting gene-environment independence for analysis of case-control studies: an empirical Bayes-type shrinkage estimator to trade-off between bias and efficiency. Biometrics. 2008;64(3):685-94.
5. Kraft P, Yen YC, Stram DO, Morrison J, Gauderman WJ. Exploiting gene-environment interaction to detect genetic associations. Hum Hered. 2007;63(2):111-9.
6. Murcray CE, Lewinger JP, Gauderman WJ. Gene-environment interaction in genome-wide association studies. Am J Epidemiol. 2009;169(2):219-26.
7. Ege MJ, Strachan DP, Cookson WO, Moffatt MF, Gut I, Lathrop M, et al. Gene-environment interaction for childhood asthma and exposure to farming in Central Europe. J Allergy Clin Immunol. 2011;127(1):138-44.
8. Murcray CE, Lewinger JP, Conti DV, Thomas DC, Gauderman WJ. Sample size requirements to detect gene-environment interactions in genome-wide association studies. Genet Epidemiol. 2011;35(3):201-10.
9. Mukherjee B, Ahn J, Gruber SB, Chatterjee N. Testing gene-environment interaction in large-scale case-control association studies: possible choices and comparisons. Am J Epidemiol. 2012;175(3):177-90.
10. Dudbridge F, Gusnanto A. Estimation of significance thresholds for genomewide association scans. Genet Epidemiol. 2008;32(3):227-34. (Pubitemid 351550369)
11. Chatterjee N, Wacholder S. Invited commentary: efficient testing of gene-environment interaction. Am J Epidemiol. 2009;169(2):231-3. doi: 10.1093/aje/kwn352.
12. Thomas DC, Lewinger JP, Murcray CE, Gauderman WJ. Invited commentary: GE-Whiz! ratcheting gene-environment studies up to the whole genome and the whole exposome. Am J Epidemiol. 2012;175(3):203-7.
13. Wason JM, Dudbridge F. A general framework for two-stage analysis of genome-wide association studies and its application to case-control studies. Am J Hum Genet. 2012;90(5):760-73.
14. Kooperberg C, Leblanc M. Increasing the power of identifying gene × gene interactions in genome-wide association studies. Genet Epidemiol. 2008;32(3):255-63. (Pubitemid 351550372)