On estimating the proportion of true null hypotheses for false discovery rate controlling procedures in exploratory DNA microarray studies

Danh V. Nguyen

Research output: Contribution to journalArticle

11 Citations (Scopus)

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, π0. In the original FDR procedure π0 was set to its upper bound of one, the most conservative choice. The degree of conservativeness in estimating π0 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 π0 (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 π0 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 languageEnglish (US)
Pages (from-to)611-637
Number of pages27
JournalComputational Statistics and Data Analysis
Volume47
Issue number3
DOIs
StatePublished - Oct 1 2004

Fingerprint

DNA Microarray
Microarrays
Gene expression
Null hypothesis
Proportion
DNA
Statistics
Testing
Conservativeness
False
Microarray
Benchmark
Power Comparison
Multiple Testing
Alternatives
Gene Expression Data
Microarray Data
Sample Size
Upper bound

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

Cite this

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