Meta-analysis of genetic association studies and adjustment for multiple testing of correlated SNPs and traits

Genetic Epidemiology

Volumn 34, Issue 7, 2010, Pages 739-746

  Conneely, Karen N ^a   Boehnke, Michael ^b  

^a EMORY UNIVERSITY SCHOOL OF MEDICINE   (United States)

^b UNIVERSITY OF MICHIGAN   (United States)

Author keywords

Association study; Meta analysis; Multiple testing; SNPs

Indexed keywords

ARTICLE; ERROR; FEASIBILITY STUDY; GENETIC ASSOCIATION; GENETIC TRAIT; GENOTYPE; META ANALYSIS; SIMULATION; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL ANALYSIS;

COMPUTER SIMULATION; DATABASES, GENETIC; GENOME-WIDE ASSOCIATION STUDY; HUMANS; META-ANALYSIS AS TOPIC; MODELS, GENETIC; MOLECULAR EPIDEMIOLOGY; POLYMORPHISM, SINGLE NUCLEOTIDE; PROSPECTIVE STUDIES; QUANTITATIVE TRAIT, HERITABLE; RETROSPECTIVE STUDIES;

EID: 77958558614     PISSN: 07410395     EISSN: 10982272     Source Type: Journal    
DOI: 10.1002/gepi.20538     Document Type: Article

References (23)

1. Armitage P. 1955. Tests for linear trends in proportions and frequencies. Biometrics 11:375-386.
2. 2 tests. Biometrics 10:417-451.
3. Conneely KN, 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. Dudbridge F. 2006. A note on permutation tests in multistage association scans. Am J Hum Genet 78:1094-1095.
5. Dudbridge F, Gusnanto A. 2008. Estimation of significance thresholds for genomewide association scans. Genet Epidemiol 32:227-334.
6. Genz A. 1992. Numerical computation of multivariate normal probabilities. J Comput Graph Stat 1:141-149.
7. Genz A, Bretz F, Hothorn T. 2007. mvtnorm: multivariate normal and t distribution. R package version 0.8-0.
8. Li Y, Willer C, Sanna S, Abecasis G. 2009. Genotype imputation. Annu Rev Genomics Hum Genet 10:387-406.
9. Lin DY. 2006. Evaluating statistical significance in two-stage genomewide association studies. Am J Hum Genet 78:505-509.
10. Lin DY, Zeng D. 2009. Meta-analysis of genome-wide association studies: no efficiency gain in using individual participant data. Genet Epidemiol 32:60-66.
11. Mantel N. 1963. Chi-square tests with 1 degree of freedom - extensions of the Mantel-Haenszel procedure. J Am Stat Assoc 58:690-700.
12. Mantel N, Haenszel W. 1959. Statistical aspects of the analysis of data from retrospective studies of disease. J Natl Cancer Inst 22:719-748.
13. Nelson MR, Bryc K, King KS, Indap A, Boyko AR, Novembre J, Briley LP, Maruyama Y, Waterworth DM, Waeber G, Vollenweider P, Oksenberg JR, Hauser SL, Stirnadel HA, Kooner JS, Chambers JC, Jones B, Mooser V, Bustamante CD, Roses AD, Burns DK, Ehm MG, Lai EH. 2008. The Population Reference Sample, POPRES: a resource for population, disease, and pharmacological genetics research. Am J Hum Genet 83:347-358.
14. Pearson K. 1904. Report on certain enteric fever inoculation statistics. BMJ 3:1243-1246.
15. Pfeiffer RM, Gail MH, Pee D. 2009. On combining data from genome-wide association studies to discover disease-associated SNPs. Stat Sci 24:547-560.
16. R Development Core Team. 2008. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria ().
17. Sasieni PD. 1997. From genotypes to genes: doubling the sample size. Biometrics 53:1253-1261.
18. Schäfer J, Strimmer K. 2005. A shrinkage approach to large-scale covariance-matrix estimation and implications for functional genomics. Stat Appl Genet Mol Biol 4:Article 32.
19. Šidák Z. 1967. Rectangular confidence regions for the means of multivariate normal distributions. J Am Stat Assoc 62:626-633.
20. Skol AD, Scott LJ, Abecasis GR, Boehnke M. 2006. Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat Genet 38:209-213.
21. Skol AD, Scott LJ, Abecasis GR, Boehnke M. 2007. Optimal designs for two-stage genome-wide association studies. Genet Epidemiol 31:776-788.
22. Wang Y, Fu W, Xie F, Wang Y, Chu X, Wang H, Shen M, Wang Y, Wang Y, Sun W, Lei R, Yang L, Wu H, Foo J, Liu J, Jin L, Huang W. 2010. Common polymorphisms in ITGA2, PON1 and THBS2 are associated with coronary atherosclerosis in a candidate gene association study of the Chinese Han population. J Hum Genet 55:490-494.
23. Woolf B. 1955. On estimating the relation between blood group and disease. Ann Human Genet 19:251-253.