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High-dimensional variable selection for ordinal outcomes with error control
Many high-throughput genomic applications involve a large set of potential covariates and a response which is frequently measured on an ordinal scale, and it is crucial to identify which variables are truly associated with the response. Effectively controlling the false discovery rate (FDR) without...
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| Опубликовано в: : | Brief Bioinform |
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| Главные авторы: | , |
| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
Oxford University Press
2020
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| Предметы: | |
| Online-ссылка: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7820886/ https://ncbi.nlm.nih.gov/pubmed/32031572 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bib/bbaa007 |
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