Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes

European Journal of Human Genetics

Volumn 25, Issue 2, 2017, Pages 240-245

  Cook, James P ^a   Mahajan, Anubha ^b   Morris, Andrew P ^a,b  

^a UNIVERSITY OF LIVERPOOL   (United Kingdom)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ALLELE; ARTICLE; BIOBANK; CASE CONTROL STUDY; COHORT ANALYSIS; CONFOUNDING VARIABLE; EFFECT SIZE; GENETIC ASSOCIATION STUDY; HUMAN; INVERSE VARIANCE; LINEAR REGRESSION ANALYSIS; LOGISTIC REGRESSION ANALYSIS; MEASUREMENT ERROR; PHENOTYPE; POPULATION GENETICS; PRIORITY JOURNAL; SAMPLE SIZE; SIMULATION; VARIANCE; BIOLOGICAL MODEL; GENOME-WIDE ASSOCIATION STUDY; META ANALYSIS (TOPIC); PROCEDURES; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA;

GENOME-WIDE ASSOCIATION STUDY; HUMANS; LINEAR MODELS; META-ANALYSIS AS TOPIC; MODELS, GENETIC; PHENOTYPE;

EID: 84995489193     PISSN: 10184813     EISSN: 14765438     Source Type: Journal    
DOI: 10.1038/ejhg.2016.150     Document Type: Article

References (22)

1. Kang HM, Sul JH, Service SK, et al: Variance component model to account for sample structure in genome-wide association studies. Nat Genet 2010; 42: 348-354.
2. Zhang Z, Ersoz E, Lai CQ, et al: Mixed linear model approach adapted for genome-wide association studies. Nat Genet 2010; 42: 355-360.
3. Price AL, Zaitlen NA, Reich D, Patterson N: New approaches to population stratification in genome-wide association studies. Nat Rev Genet 2010; 11: 459-463.
4. Lippert C, Listgarten J, Liu Y, Kadie CM, Davidson RI, Heckerman D: FaST linear mixed models for genome-wide association studies. Nat Methods 2011; 8: 833-835.
5. Listgarten J, Lippert C, Kadie CM, Davidson RI, Eskin E, Heckerman D: Improved linear mixed models for genome-wide association studies. Nat Methods 2012; 9: 525-526.
6. Zhou X, Stephens M: Genome-wide efficient mixed-model analysis for association studies. Nat Genet 2012; 44: 821-824.
7. Svishcheva GR, Axenovich TI, Belonogova NM, van Duijn CM, Aulchenko YS: Rapid variance components-based method for whole-genome association analysis. Nat Genet 2012; 44: 1166-1170.
8. Yang J, Benyamin B, McEvoy BP, et al: Common SNPs explain a large proportion of the heritability for human height. Nat Genet 2010; 42: 565-569.
9. Zaitlen N, Kraft P: Heritability in the genome-wide association era. Hum Genet 2012; 131: 1655-1664.
10. Pirinen M, Donnelly P, Spencer CCA: Efficient computation with a linear mixed model on large-scale genetic data sets with applications to genetic studies. Ann App Stat 2013; 7: 369-390.
11. Yang J, Zaitlen NA, Goddard ME, Visscher PM, Price AL: Advantages and pitfalls in the application mixed-model association methods. Nat Genet 2014; 46: 100-106.
12. Hayeck TJ, Zaitlen NA, Loh P-R, et al: Mixed model with correction for case-control ascertainment increases association power. Am J Hum Genet 2015; 96: 720-730.
13. Ma C, Blackwell T, Boehnke M, Scott LJ, GoT2D Investigators: Recommended joint and meta-analysis strategies for case-control association testing of single low-count variants. Genet Epidemiol 2013; 37: 539-550.
14. Willer CJ, Li Y, Abecasis GR: METAL: fast and efficient meta-analysis of genome-wide association scans. Bioinf 2010; 26: 2190-2191.
15. Magi R, Morris AP: GWAMA: software for genome-wide association meta-analysis. BMC Bioinf 2010; 11: 288.
16. Liu DJ, Peloso GM, Zhan X, et al: Meta-analysis of gene-level tests for rare variant association. Nat Genet 2014; 46: 200-204.
17. Roden DM, Pulley JM, Basford MA, et al: Development of a large-scale de-identified DNA biobank to enable personalised medicine. Clin Pharmacol Ther 2008; 84: 362-369.
18. Tayo BO, Teil M, Tong L, et al: Genetic background of patients from a university medical center in Manhattan: implications for personalized medicine. PLoS One 2011; 6: e19166.
19. Leitsalu L, Haller T, Esko T, et al: Cohort profile: Estonian Biobank of the Estonian Genome Center, University of Tartu. Int J Epidemiol 2015; 44: 1137-1147.
20. Sudlow C, Gallacher J, Allen N, et al: UK Biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med 2015; 12: e1001779.
21. Conomos MP, Laurie CA, Stilp AM, et al: Genetic diversity and association studies in US Hispanic/Latino populations: applications in the Hispanic Community Health Study/Study of Latinos. Am J Hum Genet 2016; 92: 165-184.
22. Chen H, Wang C, Conomos MP, et al: Control for population structure and relatedness for binary traits in genetic association studies via logistic mixed models. Am J Hum Genet 2016; 98: 653-666.