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Accurate error control in high-dimensional association testing using conditional false discovery rates
High-dimensional hypothesis testing is ubiquitous in the biomedical sciences, and informative covariates may be employed to improve power. The conditional false discovery rate (cFDR) is a widely used approach suited to the setting where the covariate is a set of p-values for the equivalent hypothese...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
2021
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7612315/ https://www.ncbi.nlm.nih.gov/pubmed/33682201 http://dx.doi.org/10.1002/bimj.201900254 |