## Abstract

Multiple testing using DNA microarray gene expression data has revived the promising area of false discovery rate (FDR) in statistics. Some recent advances in FDR controlling procedures can be unified in terms of estimating the proportion of true null hypotheses, π_{0}. In the original FDR procedure π_{0} was set to its upper bound of one, the most conservative choice. The degree of conservativeness in estimating π_{0} has a direct impact on the power of FDR procedures to detect true alternative hypotheses. In this work, we examine some recent FDR procedures with respect to the following two primary aims: (1) Compare the conservativeness of estimating π_{0} (and hence FDR). (2) Evaluate the impact of (1) on the power to detect true alternative hypotheses. We also investigate the sensitivity of FDR procedures to violation of statistical assumptions, such as heterogeneity of variance and independence. The effect of varying sample sizes on the estimation of π_{0} and power is also explored. Furthermore, in our investigation of aims (1) and (2), we defined and utilized the benchmark FDR procedure. This allows for making absolute power comparisons of FDR procedures to a benchmark, in addition to making relative comparisons among FDR procedures.

Original language | English (US) |
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Pages (from-to) | 611-637 |

Number of pages | 27 |

Journal | Computational Statistics and Data Analysis |

Volume | 47 |

Issue number | 3 |

DOIs | |

State | Published - Oct 1 2004 |

## Keywords

- Differential gene expression
- DNA Microarray
- False discovery rate
- Multiple hypothesis testing
- p-Value

## ASJC Scopus subject areas

- Computational Theory and Mathematics
- Statistics, Probability and Uncertainty
- Electrical and Electronic Engineering
- Computational Mathematics
- Numerical Analysis
- Statistics and Probability