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A selective inference approach for false discovery rate control using multiomics covariates yields insights into disease risk
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 aux...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
National Academy of Sciences
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7334489/ https://www.ncbi.nlm.nih.gov/pubmed/32522875 http://dx.doi.org/10.1073/pnas.1918862117 |