Gene identification using true discovery rate degree of association sets and estimates corrected for regression to the mean

Statistics in Medicine

Volumn 29, Issue 1, 2010, Pages 33-45

  Crager, Michael R ^a  

^a Genomic Health Inc   (United States)

Author keywords

Gene identification; Interval hypothesis; Regression to the mean; Selection bias; TDRDA set

Indexed keywords

ARTICLE; ASSOCIATION; BAYES THEOREM; GENE EXPRESSION; GENE IDENTIFICATION; HUMAN; OUTCOME ASSESSMENT; REGRESSION ANALYSIS; STATISTICAL ANALYSIS; STATISTICAL MODEL;

BREAST NEOPLASMS; DISEASE-FREE SURVIVAL; FEMALE; GENE EXPRESSION PROFILING; HUMANS; MODELS, GENETIC; MODELS, STATISTICAL; RNA, NEOPLASM;

EID: 74849125933     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3789     Document Type: Article

References (20)

1. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, Series B 1995; 57:289-300.
2. Storey JD, Taylor JE, Siegmund D. Strong control, conservative point estimation, and simultaneous conservative consistency of false discovery rates: a unified approach. Journal of the Royal Statistical Society, Series B 2004; 66:187-205.
3. Zhu D, Hero AO, Quin ZS, Swaroop A. High throughput screening of co-expressed gene pairs with controlled false discovery rate (FDR) and minimum acceptable strength (MAS). Journal of Computational Biology 2005; 12:1029-1045.
4. Benjamini Y, Yekutieli D. False discovery rate-adjusted multiple confidence intervals for selected parameters. Journal of the American Statistical Association 2005; 100:71-81. DOI: 10.1198/ 016214504000001907.
5. Lewin A, Richardson S, Marshal C, Glazier A, Aitman T. Bayesian modeling of differential gene expression. Biometrics 2006; 62:1-9. DOI: 10.1111/j.1541-0420.2005.00394.x.
6. Van de Wiel MA, Kim KI. Estimating the false discovery rate using nonparametric deconvolution. Biometrics 2007; 63:806-815. DOI: 10.1111/j.1541-0420.2006.00736.x.
7. Tusher V, Tibshirani R, Chu G. Significance analysis of microarrays applied to the ionizing radiation response. Proceedings of the National Academy of Sciences 2001; 98:5116-5121.
8. Smyth G. Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Statistical Applications in Genetics and Molecular Biology 2004; 3:1-25. Article 3.
9. Storey JD. A direct approach to false discovery rates. Journal of the Royal Statistical Society, Series B 2002; 64:479-498.
10. Benjamini Y, Yekutieli D. The control of the false discovery rate in multiple testing under dependency. The Annals of Statistics 2001; 29:1165-1188.
11. Garner C. Upward bias in odds ratio estimates from genome-wide association studies. Genetic Epidemiology 2007; 31:288-295. DOI: 10.1002/gepi.20209.
12. Zöllner S, Pritchard J. Overcoming the winner's curse: estimating penetrance parameters from case-control data. American Journal of Human Genetics 2007; 80:605-615. DOI: 10.1086/512821.
13. Zhong H, Prentice RL. Bias-reduced estimators and confidence intervals for odds ratios in genome-wide association studies. Biostatistics 2008; 9:612-634. DOI: 10.1092/biostatistics/kxn001.
14. Jeffries N. Ranking bias in association studies. Human Heredity 2009; 67:267-275. DOI: 10.1159/000194979.
15. Senn S. Regression to the mean. Statistical Methods in Medical Research 1997; 6:99-102.
16. Stigler SM. Regression to the mean, historically considered. Statistical Methods in Medical Research 1997; 6:103-114.
17. Efron B, Tibshirani R. Empirical Bayes methods and false discovery rates for microarrays. Genetic Epidemiology 2002; 23:70-86. DOI: 10.1002/gepi.01124.
18. Davis CE. The effect of regression to the mean in epidemiologic and clinical studies. American Journal of Epidemiology 1976; 26:781-795.
19. Wang Y, Klijn JGM, Zhang Y, Sieuwerts AM, Look MP, Yang F, Talantov D, Timmermans M, Meijer-van Gelder ME, Yu J, Jatkoe T, Berns EMJJ, Atkins D, Foekens JA. Gene-expression profiles to predict distant metastasis of lymph-node negative primary breast cancer. The Lancet 2005; 365:671-679.
20. Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, Desmedt C, Ignatiadis M, Sengstag T, Schutz F, Goldstein DR, Piccart M, Delorenzi M. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Research 2008; 10:R65. DOI: 10.1186/bcr2124.