Robust estimation of the false discovery rate

Bioinformatics. 2006 Aug 15;22(16):1979-87. doi: 10.1093/bioinformatics/btl328. Epub 2006 Jun 15.


Motivation: Presently available methods that use p-values to estimate or control the false discovery rate (FDR) implicitly assume that p-values are continuously distributed and based on two-sided tests. Therefore, it is difficult to reliably estimate the FDR when p-values are discrete or based on one-sided tests.

Results: A simple and robust method to estimate the FDR is proposed. The proposed method does not rely on implicit assumptions that tests are two-sided or yield continuously distributed p-values. The proposed method is proven to be conservative and have desirable large-sample properties. In addition, the proposed method was among the best performers across a series of 'real data simulations' comparing the performance of five currently available methods.

Availability: Libraries of S-plus and R routines to implement the method are freely available from

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology / methods*
  • Computer Simulation
  • Data Interpretation, Statistical
  • False Positive Reactions
  • Gene Expression Profiling / methods*
  • Microarray Analysis
  • Models, Genetic
  • Models, Statistical
  • Oligonucleotide Array Sequence Analysis
  • Pattern Recognition, Automated
  • Reproducibility of Results
  • Software