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. © 2006 Oxford University Press.
CITATION STYLE
Pounds, S., & Cheng, C. (2006). Robust estimation of the false discovery rate. Bioinformatics, 22(16), 1979–1987. https://doi.org/10.1093/bioinformatics/btl328
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