ArticleProceedings of the National Academy of Sciences of the United States of America2020
A selective inference approach for false discovery rate control using multiomics covariates yields insights into disease risk.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 17 citations in OpenAlex.
- VBASS enables integration of single cell gene expression data in Bayesian association analysis of rare variants.Communications biology · 2023Article
- Article
- An approach to gene-based testing accounting for dependence of tests among nearby genes.Briefings in bioinformatics · 2021Article
- Leveraging auxiliary data from arbitrary distributions to boost GWAS discovery with Flexible cFDR.PLoS genetics · 2021Article
- Leveraging three-dimensional chromatin architecture for effective reconstruction of enhancer-target gene regulatory interactions.Nucleic acids research · 2021Article
- Serum Calcium Predicts Cognitive Decline and Clinical Progression of Alzheimer's Disease.Neurotoxicity research · 2021Article
- MultipleTesting.com: A tool for life science researchers for multiple hypothesis testing correction.PloS one · 2021Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
To correct for a large number of hypothesis tests, most researchers rely on simple multiple testing corrections. Yet, new methodologies of selective inference could potentially improve power while retaining statistical guarantees, especially those that enable exploration of test statistics using auxiliary information (covariates) to weight hypothesis tests for association. We explore one such method, adaptive
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.