Two-stage false discovery rate in microarray studies

References

• Arratia, R., L. Goldstein, and L. Gordon. 1990. Poisson approximation and the Chen-Stein method. Statistical Science 5 (4):403–24. doi:10.1214/ss/1177012015.
   Google Scholar
• Benjamini, Y., and Y. Hochberg. 1995. Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B 57 :289–300. doi:10.1111/j.2517-6161.1995.tb02031.x.
   Web of Science ®Google Scholar
• Benjamini, Y., and D. Yekutieli. 2001. Under dependency. The Annals of Statistics 29 :1165–88. doi:10.1214/aos/1013699998.
   Web of Science ®Google Scholar
• Capanu, M., and V. E. Seshan. 2015. False discovery rates for rare variants from sequenced data. Genetic Epidemiology 39 (2):65–76. doi:10.1002/gepi.21880.
   PubMed Web of Science ®Google Scholar
• Chen, L. H. Y. 1975. Poisson approximation for dependent trials. The Annals of Probability 3 (3):534–45.
   Web of Science ®Google Scholar
• Colquhoun, D. 2014. An investigation of the false discovery rate and the misinterpretation of p-values. Royal Society Open Science 1 (3):140216. doi:10.1098/rsos.140216.
   PubMed Web of Science ®Google Scholar
• Dudoit, S., J. P. Shaffer, and J. C. Block. 2003. Multiple hypothesis testing in microarray experiments. Statistical Science 18 (1):71–103. doi:10.1214/ss/1056397487.
   Web of Science ®Google Scholar
• Genovese, C., and L. Wasserman. 2004. A stochastic process approach to false discovery control. The Annals of Statistics 32 :1035–61. doi:10.1214/009053604000000283.
   Web of Science ®Google Scholar
• Glickman, M. E., S. R. Rao, and M. R. Schultz. 2014. False discovery rate control is a recommended alternative to Bonferroni-type adjustments in health studies. Journal of Clinical Epidemiology 67 (8):850–7.
   PubMed Web of Science ®Google Scholar
• Golub, T. R., D. K. Slonim, P. Tamayo, C. Huard, M. Gaasenbeek, J. P. Mesirov, H. Coller, M. L. Loh, J. R. Downing, M. A. Caligiuri, et al. 1999. Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 286 (5439):531–7. doi:10.1126/science.286.5439.531.
   PubMed Web of Science ®Google Scholar
• Gossmann, A., S. Cao, D. Brzyski, L. J. Zhao, H. W. Deng, and Y. P. Wang. 2017. A sparse regression method for group-wise feature selection with false discovery rate control. IEEE/ACM Transactions on Computational Biology and Bioinformatics Issue No. (01).
   Google Scholar
• Junning, L., S. Yonggang, and W. T. Arthur. 2016. Transformation invariant control of voxel-wise false discovery rate. IEEE Xplore: IEEE Transactions on Medical Imaging 35 (10):2243–57.
   PubMed Web of Science ®Google Scholar
• Kang, M., and P. K. Sen. 2008. Kendall tau type rank statistics in genomic data. Applications of Mathematics 3 :207–21. doi:10.1007/s10492-008-0005-1.
   Web of Science ®Google Scholar
• Keich, U., A. Kertesz-Farkas, and W. S. Noble. 2015. Improved false discovery rate estimation procedure for shotgun proteomics. Journal of Proteome Research 14 (8):3148–61. doi:10.1021/acs.jproteome.5b00081.
   PubMed Web of Science ®Google Scholar
• Kevin, H., L. Yanming, Z. Ji, L. Hongliang, E. L. Jeffrey, I. A. Christopher, H. Terry, J. Jiashun, L. Huazhen, W. Qinyi, and L. Yi. 2016. Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates. Bioinformatics 32 (1):50–7.
   PubMed Web of Science ®Google Scholar
• Lin, Y. T., and W. C. Lee. 2015. Importance of presenting the variability of the false discovery rate control. BMC Genetics 16 :97.
   PubMed Web of Science ®Google Scholar
• Philip, T. R., S. Armin, L. Feihan, H. Lei, and, and P. Erika. 2012. Paradoxical results of adaptive false discovery rate procedures in neuroimaging studies. Neuroimage 63 (4):1833–40.
   PubMed Web of Science ®Google Scholar
• Pounds, S., and C. Cheng. 2004. Improving false discovery rate estimation. Bioinformatics 20 (11):1737–45. doi:10.1093/bioinformatics/bth160.
   PubMed Web of Science ®Google Scholar
• Pounds, S., and S. W. Morris. 2003. Estimating the occurrence of false positives and false negatives in microarray studies by approximating and partitioning the empirical distribution of p-values. Bioinformatics 19 (10):1236–42. doi:10.1093/bioinformatics/btg148.
   PubMed Web of Science ®Google Scholar
• Sarkar, S. K. 2004. FDR-controlling stepwise procedures and their false negative rates. Journal of Statistical Planning and Inference 125 (1–2):119–37. doi:10.1016/j.jspi.2003.06.019.
   Web of Science ®Google Scholar
• Sen, P. K. 2008. Kendall’s tau in high-dimensional genomic parsimony. Institute of Mathematical Statistics Collection Series 3 :251–66.
   Google Scholar
• Stephens, M. 2017. False discovery rates: A new deal. Biostatistics (Oxford, England) 18 (2):275–94.
   PubMed Web of Science ®Google Scholar
• Storey, J. 2002. A direct approach to false discovery rates, it. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64 (3):479–98. doi:10.1111/1467-9868.00346.
   Web of Science ®Google Scholar
• Storey, J., J. E. Taylor, and D. Siegmund. 2004. Strong control, conservative point estimation, and simultaneous conservative consistency of false discovery rates: A unified approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 66 (1):187–205. doi:10.1111/j.1467-9868.2004.00439.x.
   Google Scholar
• Sun, W., and T. Cai. 2009. Large-scale multiple testing under dependency. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 71 (2):393–424. doi:10.1111/j.1467-9868.2008.00694.x.
   Google Scholar