A unified approach to false discovery rate estimation
Top Cited Papers
Open Access
- 9 July 2008
- journal article
- research article
- Published by Springer Science and Business Media LLC in BMC Bioinformatics
- Vol. 9 (1), 1-14
- https://doi.org/10.1186/1471-2105-9-303
Abstract
False discovery rate (FDR) methods play an important role in analyzing high-dimensional data. There are two types of FDR, tail area-based FDR and local FDR, as well as numerous statistical algorithms for estimating or controlling FDR. These differ in terms of underlying test statistics and procedures employed for statistical learning. A unifying algorithm for simultaneous estimation of both local FDR and tail area-based FDR is presented that can be applied to a diverse range of test statistics, including p-values, correlations, z- and t-scores. This approach is semipararametric and is based on a modified Grenander density estimator. For test statistics other than p-values it allows for empirical null modeling, so that dependencies among tests can be taken into account. The inference of the underlying model employs truncated maximum-likelihood estimation, with the cut-off point chosen according to the false non-discovery rate. The proposed procedure generalizes a number of more specialized algorithms and thus offers a common framework for FDR estimation consistent across test statistics and types of FDR. In comparative study the unified approach performs on par with the best competing yet more specialized alternatives. The algorithm is implemented in R in the "fdrtool" package, available under the GNU GPL from http://strimmerlab.org/software/fdrtool/ and from the R package archive CRAN.Keywords
This publication has 27 references indexed in Scilit:
- Microarrays, Empirical Bayes and the Two-Groups ModelStatistical Science, 2008
- Estimating the Proportion of True Null Hypotheses, with application to DNA Microarray DataJournal of the Royal Statistical Society Series B: Statistical Methodology, 2005
- A comparative review of estimates of the proportion unchanged genes and the false discovery rateBMC Bioinformatics, 2005
- An empirical Bayes approach to inferring large-scale gene association networksBioinformatics, 2004
- Large-Scale Simultaneous Hypothesis TestingJournal of the American Statistical Association, 2004
- The positive false discovery rate: a Bayesian interpretation and the q-valueThe Annals of Statistics, 2003
- Statistical significance for genomewide studiesProceedings of the National Academy of Sciences of the United States of America, 2003
- Operating Characteristics and Extensions of the False Discovery Rate ProcedureJournal of the Royal Statistical Society Series B: Statistical Methodology, 2002
- Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple TestingJournal of the Royal Statistical Society: Series B (Methodological), 1995
- Plots of P-values to evaluate many tests simultaneouslyBiometrika, 1982