Are a set of microarrays independent of each other?

Annals of Applied Statistics

Volumn 3, Issue 3, 2009, Pages 922-942

  Efron, Bradley ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

Effective sample size; Matrix normal distribution; Permutation tests; Row and column correlations; Total correlation

Indexed keywords

EID: 77949509397     PISSN: 19326157     EISSN: 19417330     Source Type: Journal    
DOI: 10.1214/09-AOAS236     Document Type: Article

References (16)

1. Anderson, T. W. (2003). An Introduction to Multivariate Statistical Analysis 3rd ed. Wiley, New York.
2. Benjamini, Y. and Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. J. Roy. Statist. Soc. Ser. B 57 289-300.
3. Bolstad, B. M., Irizarry, R. A., Åstrand, M. and Speed, T. P. (2003). Comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics 19 185-193. Available at http://web.mit.edu/biomicro/education/RMA.pdf.
4. Callow, M., Dudoit, S., Gong, E., Speed, T. and Rubin, E. (2000). Microarray expression profiling identifies genes with altered expression in HDL-deficient mice. Genome Research 10 2022-2029.
5. Efron, B. (2004). Large-scale simultaneous hypothesis testing: The choice of a null hypothesis. J. Amer. Statist. Assoc. 99 96-104.
6. Efron, B. (2007a). Correlation and large-scale simultaneous significance testing. J. Amer. Statist. Assoc. 102 93-103.
7. Efron, B. (2007b). Size, power, and false discovery rates. Ann. Statist. 351351-1377.
8. Efron, B. (2008). Microarrays, empirical Bayes, and the two-groups model (with discussion and rejoinder). Statist. Sci. 23 1-47.
9. Johnson, D. E. and Graybill, F. A. (1972). An analysis of a two-way model with interaction and no replication. J. Amer. Statist. Assoc. 67 862-868.
10. Johnson, N. L. and Kotz, S. (1970). Continuous Univariate Distributions 1. Houghton Mifflin Company, Boston.
11. Mardia, K., Kent, J. and Bibby, J. (1979). Multivariate Analysis. Academic Press, London/San Diego.
12. Owen, A. B. (2005). Variance of the number of false discoveries. J. Roy. Statist. Soc. Ser. B 67 411-426.
13. Qiu, X., Brooks, A. I., Klebanov, L. and Yakovlev, A. (2005). The effects of normalization on the correlation structure of microarray data. BMC Bioinformatics 6 120. Available at http://www.biomedcentral.com/1471-2105/6/120.
14. Qiu, X., Klebanov, L. and Yakovlev, A. (2005). Correlation between gene expression levels and limitations of the empirical Bayes methodology for finding differentially expressed genes. Statist. Appl. Genet. Mol. Bio. 4, article 34. Available at http://www.bepress.com/sagmb/vol4/iss1/art34.
15. Singh, D., Febbo, P. G., Ross, K., Jackson, D. G., Manola, J., Ladd, C., Tamayo, P., Renshaw, A. A., D'Amico, A. V., Richie, J. P., Lander, E. S., Loda, M., Kantoff, P. W., Golub, T. R. and Sellers, W. R. (2002). Gene expression correlates of clinical prostate cancer behavior. Cancer Cell 1 203-209.
16. Tusher, V. G., Tibshirani, R. and Chu, G. (2001). Significance analysis of microarrays applied to the ionizing radiation response. Proc. Nat. Acad. Sci. USA 98 5116-5121. Available at http://www.pnas.org/cgi/content/full/98/9/5116.