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Extracting replicable associations across multiple studies: Empirical Bayes algorithms for controlling the false discovery rate
In almost every field in genomics, large-scale biomedical datasets are used to report associations. Extracting associations that recur across multiple studies while controlling the false discovery rate is a fundamental challenge. Here, we propose a new method to allow joint analysis of multiple stud...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2017
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5576761/ https://www.ncbi.nlm.nih.gov/pubmed/28821015 http://dx.doi.org/10.1371/journal.pcbi.1005700 |