ArticleFrontiers in genetics2013
Computationally efficient permutation-based confidence interval estimation for tail-area FDR.
Article in Frontiers in genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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18 citing papers in PubMed, 1 synthesis or guideline pooled it, 25 citations in OpenAlex.
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- fdrci: FDR confidence interval selection and adjustment for large-scale hypothesis testing.Bioinformatics advances · 2022Article
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- Extensive intraspecies cryptic variation in an ancient embryonic gene regulatory network.eLife · 2019Article
- Three novel genetic variants in NRF2 signaling pathway genes are associated with pancreatic cancer risk.Cancer science · 2019Article
- Genetic-Epigenetic Interactions in Asthma Revealed by a Genome-Wide Gene-Centric Search.Human heredity · 2018Article
- Differential methylation of genes in individuals exposed to maternal diabetes in utero.Diabetologia · 2017Article
- cit: hypothesis testing software for mediation analysis in genomic applications.Bioinformatics (Oxford, England) · 2016Article
- Noninvasive analysis of the sputum transcriptome discriminates clinical phenotypes of asthma.American journal of respiratory and critical care medicine · 2015Article
- Host genetic variation influences gene expression response to rhinovirus infection.PLoS genetics · 2015Article
- Assessing the effects of multiple markers in genetic association studies.Frontiers in genetics · 2015Article
- Screening-testing approaches for gene-gene and gene-environment interactions using independent statistics.Frontiers in genetics · 2013Article
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2 authors at 2 institutions in 1 country.
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No grant is acknowledged in the PubMed record.
Abstract
Challenges of satisfying parametric assumptions in genomic settings with thousands or millions of tests have led investigators to combine powerful False Discovery Rate (FDR) approaches with computationally expensive but exact permutation testing. We describe a computationally efficient permutation-based approach that includes a tractable estimator of the proportion of true null hypotheses, the variance of the log of tail-area FDR, and a confidence interval (CI) estimator, which accounts for the number of permutations conducted and dependencies between tests. The CI estimator applies a binomial distribution and an overdispersion parameter to counts of positive tests. The approach is general with regards to the distribution of the test statistic, it performs favorably in comparison to other approaches, and reliable FDR estimates are demonstrated with as few as 10 permutations. An application of this approach to relate sleep patterns to gene expression patterns in mouse hypothalamus yielded a set of 11 transcripts associated with 24 h REM sleep [FDR = 0.15 (0.08, 0.26)]. Two of the corresponding genes, Sfrp1 and Sfrp4, are involved in wnt signaling and several others, Irf7, Ifit1, Iigp2, and Ifih1, have links to interferon signaling. These genes would have been overlooked had a typical a priori FDR threshold such as 0.05 or 0.1 been applied. The CI provides the flexibility for choosing a significance threshold based on tolerance for false discoveries and precision of the FDR estimate. That is, it frees the investigator to use a more data-driven approach to define significance, such as the minimum estimated FDR, an option that is especially useful for weak effects, often observed in studies of complex diseases.
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