The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
A Direct Approach to False Discovery Rates
Abstract
Summary: Multiple-hypothesis testing involves guarding against much more complicated errors than single-hypothesis testing. Whereas we typically control the type I error rate for a single-hypothesis test, a compound error rate is controlled for multiple-hypothesis tests. For example, controlling the false discovery rate FDR traditionally involves intricate sequential p-value rejection methods based on the observed data. Whereas a sequential p-value method fixes the error rate and estimates its corresponding rejection region, we propose the opposite approach—we fix the rejection region and then estimate its corresponding error rate. This new approach offers increased applicability, accuracy and power. We apply the methodology to both the positive false discovery rate pFDR and FDR, and provide evidence for its benefits. It is shown that pFDR is probably the quantity of interest over FDR. Also discussed is the calculation of the q-value, the pFDR analogue of the p-value, which eliminates the need to set the error rate beforehand as is traditionally done. Some simple numerical examples are presented that show that this new approach can yield an increase of over eight times in power compared with the Benjamini–Hochberg FDR method.
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“The 2982 MLG that contained over 100 genes were tested for enrichment or depletion in individuals with ACVD (218 ACVD cases and 187 controls) according to the non-parametric method, Wilcoxon rank-sum test, and controlled for multiple testing (q-value <0.05)55, 60.”
From The gut microbiome in atherosclerotic cardiovascular disease (2017) · cites this paper as [60]
Citations
Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
An Introduction to the Bootstrap
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An Introduction to the Bootstrap
Efron, B., & Tibshirani, R. J. (1993) · doi:10.1007/978-1-4899-4541-9 · Cited by 21,230
In silico prediction of protein-protein interactions in human macrophages
Souiai, O., Guerfali, F. Z., Miled, S. B., Brun, C., & Benkahla, A. (2014) · BMC Research Notes · doi:10.1186/1756-0500-7-157 · Cited by 10,785
Significance analysis of microarrays applied to the ionizing radiation response
Tusher, V. G., Tibshirani, R., & Chu, G. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.091062498 · Cited by 10,568
The positive false discovery rate: a Bayesian interpretation and the q-value
Storey, J. D. (2003) · The Annals of Statistics · doi:10.1214/aos/1074290335 · Cited by 2,204
Self-citationOn the adaptive control of the false discovery rate in multiple testing with independent statistics
Benjamini, Y., & Hochberg, Y. (2000) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986025001060 · Cited by 2,015
Empirical Bayes analysis of a microarray experiment
Efron, B., Tibshirani, R., Storey, J. D., & Tusher, V. (2001) · Journal of the American Statistical Association · doi:10.1198/016214501753382129 · Cited by 1,733
Self-citationYekutieli, D., & Benjamini, Y. (1999) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(99)00041-5 · Cited by 738
Benjamini, Y., & Liu, W. (1999) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(99)00040-3 · Cited by 242
The role of statistics in the data revolution?
Friedman, J. H. (2001) · International Statistical Review · doi:10.1111/j.1751-5823.2001.tb00474.x · Cited by 64
Responses to Ionizing Radiation
Ichikawa, S. (1981) · Springer eBooks · doi:10.1007/978-3-642-68090-8_8 · Cited by 28
Research works printed but not linked: 1
- Storey, 2001, Estimating false discovery rates under dependence, with applications to DNA microarrays
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Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259
MEME SUITE: tools for motif discovery and searching
Bailey, T. L., Boden, M., Buske, F. A., Frith, M., Grant, C. E., Clementi, L., Ren, J., Li, W. W., & Noble, W. S. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp335 · Cited by 10,648
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
Self-citationMootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., et al. (2015) · Science · doi:10.1126/science.1262110 · Cited by 5,062
Metadata
- Authors
- Storey, J. D.
- Affiliations
- Stanford University (US)
- Corresponding author
- Storey, John D.
- ORCID
- Storey, John D.
- Venue
- Journal of the Royal Statistical Society Series B: Statistical Methodology
- Publisher
- Oxford University Press (OUP)
- Published
- 2002-08-01
- Volume
- 64
- Issue
- 3
- Pages
- 479-498
- ISSN
- 1369-7412 (ISSN-L)
- 1467-9868
- OpenAlex
- W2105381419
- Cited by
- 5,603
- References
- 12
- Citations by year
- 2026: 164 · 2025: 183 · 2024: 239 · 2023: 245 · 2022: 201 · 2021: 278 · 2020: 249 · 2019: 249 · 2018: 279 · 2017: 274 · 2016: 297 · 2015: 255 · 2014: 340 · 2013: 348 · 2012: 363
- FWCI
- 96.71
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of the Royal Statistical Society Series B (Statistical Methodology) (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Science Foundation
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Keywords
- false discovery rate, multiple comparisons, Q-value, Benjamini-Hochberg procedure, statistical power
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