The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Controlling the false discovery rate in behavior genetics research
Abstract
The screening of many endpoints when comparing groups from different strains, searching for some statistically significant difference, raises the multiple comparisons problem in its most severe form. Using the 0.05 level to decide which of the many endpoints' differences are statistically significant, the probability of finding a difference to be significant even though it is not real increases far beyond 0.05. The traditional approach to this problem has been to control the probability of making even one such error--the Bonferroni procedure being the most familiar procedure achieving such control. However, the incurred loss of power stemming from such control led many practitioners to neglect multiplicity control altogether. The False Discovery Rate (FDR), suggested by Benjamini and Hochberg [J Royal Stat Soc Ser B 57 (1995) 289], is a new, different, and compromising point of view regarding the error in multiple comparisons. The FDR is the expected proportion of false discoveries among the discoveries, and controlling the FDR goes a long way towards controlling the increased error from multiplicity while losing less in the ability to discover real differences. In this paper we demonstrate the problem in two studies: the study of exploratory behavior [Behav Brain Res (2001)], and the study of the interaction of strain differences with laboratory environment [Science 284 (1999) 1670]. We explain the FDR criterion, and present two simple procedures that control the FDR. We demonstrate their increased power when used in the above two studies.
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In the citing paper
“Individual group statistics were calculated using Mann and Whitney tests and corrected for multiple testing when necessary, according to the false discovery rate method previously described [48, 49].”
From The Resistin/TLR4/miR-155-5p axis: a novel signaling pathway in the onset of hypothalamic neuroinflammation (2025) · cites this paper as [49]
In the citing paper
“All p values were adjusted for multiple comparisons with the FDR algorithm (Benjamini et al., 2001).”
From Mechanisms underlying microbial-mediated changes in social behavior in mouse models of autism spectrum disorder (2019) · cites this paper as Benjamini et al., 2001
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
Self-citationThe control of the false discovery rate in multiple testing under dependency
Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490
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
Self-citationGenetics of Mouse Behavior: Interactions with Laboratory Environment
Crabbe, J. C., Wahlsten, D., & Dudek, B. C. (1999) · Science · doi:10.1126/science.284.5420.1670 · Cited by 1,666
Klockars, A. J., & Sax, G. (1986) · Sage eBooks · doi:10.4135/9781412985185 · Cited by 1,015
Yekutieli, D., & Benjamini, Y. (1999) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(99)00041-5 · Cited by 738
Self-citationMultiple Comparisons Procedures
Cabral, H. (2008) · Circulation · doi:10.1161/circulationaha.107.700971 · Cited by 312
Williams, V. S. L., Jones, L. V., & Tukey, J. W. (1999) · Journal of Educational and Behavioral Statistics · doi:10.2307/1165261 · Cited by 251
Benjamini, Y., & Liu, W. (1999) · Journal of Statistical Planning and Inference · doi:10.1016/s0378-3758(99)00040-3 · Cited by 242
Self-citationA New Approach to the Problem of Multiple Comparisons in the Genetic Dissection of Complex Traits
Weller, J. I., Song, J. Z., Heyen, D. W., Lewin, H. A., & Ron, M. (1998) · Genetics · doi:10.1093/genetics/150.4.1699 · Cited by 179
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Helmink, B. A., Reddy, S. M., Gao, J., Zhang, S., Basar, R., Thakur, R., Yizhak, K., Sade-Feldman, M., Blando, J., Han, G., et al. (2020) · Nature · doi:10.1038/s41586-019-1922-8 · Cited by 2,731
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“All p-values were adjusted for multiple comparisons with the FDR algorithm (Benjamini et al., 2001).”
MethodInfluentialCatalytic in vivo protein knockdown by small-molecule PROTACs
Bondeson, D. P., Mares, A., Smith, I. E. D., Ko, E., Campos, S., Miah, A. H., Mulholland, K. E., Routly, N., Buckley, D. L., Gustafson, J. L., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1858 · Cited by 1,356
Microbial reconstitution reverses maternal diet-induced social and synaptic deficits in offspring
Buffington, S. A., Di Prisco, G. V., Auchtung, T. A., Ajami, N. J., Petrosino, J. F., & Costa-Mattioli, M. (2016) · Cell · doi:10.1016/j.cell.2016.06.001 · Cited by 1,163
Metadata
- Authors
- Benjamini, Y., Drai, D., Elmer, G., Kafkafi, N., & Golani, I.
- Affiliations
- Tel Aviv University (IL)
- National Institute on Drug Abuse (US)
- Corresponding author
- Benjamini, Yoav
- Venue
- Behavioural Brain Research
- Publisher
- Elsevier BV
- Published
- 2001-11
- Volume
- 125
- Issue
- 1-2
- Pages
- 279-284
- ISSN
- 0166-4328 (ISSN-L)
- OpenAlex
- W2145025818
- Cited by
- 4,146
- References
- 15
- Citations by year
- 2026: 187 · 2025: 231 · 2024: 219 · 2023: 237 · 2022: 278 · 2021: 301 · 2020: 276 · 2019: 277 · 2018: 207 · 2017: 225 · 2016: 208 · 2015: 171 · 2014: 207 · 2013: 215 · 2012: 175
- FWCI
- 28.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Behavioural Brain Research (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r01ns040234-03)
- National Institute of Neurological Disorders and Stroke (1R01 NS 40234-01)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- false discovery rate, multiple comparisons, multiplicity control, Bonferroni procedure, statistical power, inbred mouse strains, exploratory behavior, laboratory conditions, behavioral genetics
- MeSH terms
- Animals, Brain, Exploratory Behavior, Genetics, Behavioral, Mice, Inbred Strains, Phenotype, Reproducibility of Results, Bias, Mice
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