Robbins, empirical Bayes and microarrays

Annals of Statistics

Volumn 31, Issue 2, 2003, Pages 366-378

  Efron, Bradley ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

False discovery rate; Missing species; q value; Simultaneous inference; Stein estimation

Indexed keywords

EID: 0038364283     PISSN: 00905364     EISSN: None     Source Type: Journal    
DOI: 10.1214/aos/1051027871     Document Type: Review

References (18)

1. BENJAMINI, Y. and HOCHBERG, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat. Methodol. 57 289-300.
2. BENJAMINI, Y. and YEKUTIELI, Y. (2001). The control of the false discovery rate in multiple testing under dependency. Ann. Statist. 29 1165-1188.
3. EFRON, B. and MORRIS, C. (1973). Stein's estimation rule and its competitors-an empirical Bayes approach. J. Amer. Statist. Assoc. 68 117-130.
4. EFRON, B. and MORRIS, C. (1975). Data analysis using Stein's estimator and its generalizations. J. Amer. Statist. Assoc. 70 311-319.
5. EFRON, B., STOREY, J. and TIBSHIRANI, R. (2001). Microarrays, empirical Bayes methods, and false discovery rates. Technical report, Stanford Univ. Available online from http://www-stat.stanford.edu/~tibs/research.html.
6. EFRON, B. and THISTED, R. (1976). Estimating the number of unseen species: How many words did Shakespeare know? Biometrika 63 435-447.
7. EFRON, B. and THISTED, R. (1987). Did Shakespeare write a newly-discovered poem? Biometrika 74 445-455.
8. EFRON, B., TIBSHIRANI, R., STOREY, J. and TUSHER, V. (2001). Empirical Bayes analysis of a microarray experiment. J. Amer. Statist. Assoc. 96 1151-1160.
9. FISHER, R., CORBET, A. and WILLIAMS, C. (1943). The relation between the number of species and the number of individuals in a random sample of an animal population. Journal of Animal Ecology 12 42-58.
10. GENOVESE, C. and WASSERMAN, L. (2002). Operating characteristics and extensions of the false discovery rate procedure. J. R. Stat. Soc. Ser. B Stat. Methodol. 64 499-517.
11. GOOD, I. and TOULMIN, G. (1956). The number of new species, and the increase in population coverage, when a sample is increased. Biometrika 43 45-63.
12. HANNAN, J. and ROBBINS, H. (1955). Asymptotic solutions of the compound decision problem for two completely specified distributions. Ann. Math. Statist. 26 37-51.
13. NEWTON, M., KENDZIORSKI, C., RICHMOND, C., BLATTNER, F. and TSUI, K. (2001). On differential variability of expression ratios: Improving statistical inference about gene expression changes from microarray data. J. Computational Biology 8 37-52.
14. ROBBINS, H. (1951). Asymptotically subminimax solutions of compound statistical decision problems. Proc. Second Berkeley Symp. Math. Statist. Probab. 1 131-148. Univ. California Press, Berkeley.
15. ROBBINS, H. (1956). An empirical Bayes approach to statistics. Proc. Third Berkeley Symp. Math. Statist. Probab. 1 157-163. Univ. California Press, Berkeley.
16. ROBBINS, H. (1964). The empirical Bayes approach to statistical decision problems. Ann. Math. Statist. 35 1-20.
17. STOREY, J. (2001). The false discovery rate: A Bayesian interpretation and the q-value. Technical report, Stanford Univ. Available online from http://www.stat.berkeley.edu/~storey.
18. TUSHER, V., TIBSHIRANI, R. and CHU, G. (2001). Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98 5116-5121.