Estimating the number of true discoveries in genome-wide association studies

Statistics in Medicine

Volumn 31, Issue 11-12, 2012, Pages 1177-1189

  Lee, Woojoo ^a   Gusnanto, A ^b   Salim, A ^c   Magnusson, P ^a   Sim, Xueling ^c   Tai, E S ^c   Pawitan, Y ^a  

^a KAROLINSKA INSTITUTE   (Sweden)

^b UNIVERSITY OF LEEDS   (United Kingdom)

^c NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Complex diseases; False discovery rate; High throughput data; Statistical genetics

Indexed keywords

ARTICLE; DATA ANALYSIS; GENETIC ASSOCIATION; GENETIC DATABASE; GENETIC MODEL; GENETIC SCREENING; MATHEMATICAL COMPUTING; METHODOLOGY; MOLECULAR GENETICS; SIMULATION; SINGLE NUCLEOTIDE POLYMORPHISM; STATISTICAL ANALYSIS;

ASIAN CONTINENTAL ANCESTRY GROUP; CHOLESTEROL, HDL; COMPUTER SIMULATION; CONFIDENCE INTERVALS; DATA INTERPRETATION, STATISTICAL; FALSE POSITIVE REACTIONS; GENETIC PREDISPOSITION TO DISEASE; GENOME-WIDE ASSOCIATION STUDY; HUMANS; MACULAR DEGENERATION; MATHEMATICAL COMPUTING; MODELS, GENETIC; POLYMORPHISM, SINGLE NUCLEOTIDE; SCHIZOPHRENIA; SINGAPORE;

EID: 84861197050     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4391     Document Type: Article

References (16)

1. Klein R, Zeiss C, Chew E et al. Complement factor H polymorphism in age-related macular degeneration. Science 2005; 308:385-389.
2. Rivera A, Fisher SA, Fritsche LG et al. Hypothetical LOC387715 is a second major susceptibility gene for age-related macular degeneration, contributing independently of complement factor H to disease risk. Human Molecular Genetics 2005; 14:3227-3236.
3. Maller J, George S, Purcell S et al. Common variation in three genes, including a noncoding variant in CFH, strongly influences risk of age-related macular degeneration. Nature Genetics 2006; 38:1055-1059.
4. Korn EL, Troendle JF, McShane LM, Simon R. Controlling the number of false discoveries: application to high-dimensional genomic data. Journal of Statistical Planning and Inference 2004; 124:379-398.
5. Meinshausen N. False discovery control for multiple tests of association under general dependence. Scandinavian Journal of Statistics 2006; 33:227-238.
6. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society (B) 1995; 57(1):289-300.
7. van der Vaart AW. Asymptotic Statistics. Cambridge University Press: Cambridge, 1998.
8. Pawitan Y, Calza S, Ploner A. Estimation of false discovery proportion under general dependence. Bioinformatics 2006; 22:3025-3031.
9. Pawitan Y, Michiels S, Koscielny S, Gusnanto A. Ploner A. False discovery rate, sensitivity and sample size for microarray studies. Bioinformatics 2005; 21:3017-3024.
10. Pawitan Y, Krishna Murthy KR, Michiels S, Ploner A. Bias in the estimation of false discovery rate in microarray studies. Bioinformatics 2005; 21:3865-3872.
11. AREDS Research Group. The Age-Related Eye Disease Research Group: a randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss. Archives of Ophthalmology 2001; 119:1417-1436.
12. Swaroop A, Branham KE, Chen W, Abecasis G. Genetic susceptibility to age-related macular degeneration: a paradigm for dissecting complex disease traits. Human Molecular Genetics 2007; 16:174-182.
13. Tai ES, Ordovas JM, Corella D et al. The TaqIB and -629C>A polymorphisms at the cholesterol ester transfer protein locus: associations with lipid levels in a multiethnic population. The 1998 Singapore National Health Survey. Clinical Genetics 2003; 63:19-30.
14. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MAR, Bender D, Maller J, Sklar P, de Bakker PIW, Daly MJ, Sham PC.PLINK: a toolset for whole-genome association and population-based linkage analysis. American Journal of Human Genetics 2007; 81:559-575.
15. Teslovich TM, Musunuru K, Smith AV et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 2010; 466:707-713.
16. International Schizophrenia Consortium. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 2009; 460:748-752.