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Biobank-scale methods and projections for sparse polygenic prediction from machine learning
In this paper we characterize the performance of linear models trained via widely-used sparse machine learning algorithms. We build polygenic scores and examine performance as a function of training set size, genetic ancestral background, and training method. We show that predictor performance is mo...
| Autores principales: | , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356957/ https://www.ncbi.nlm.nih.gov/pubmed/37468507 http://dx.doi.org/10.1038/s41598-023-37580-5 |