Efficient cross-trait penalized regression increases prediction accuracy in large cohorts using secondary phenotypes
Information of genetic architectures of complex traits can be leveraged for predicting phenotypes. Here, the authors develop CTPR (Cross-Trait Penalized Regression), a method for multi-trait polygenic risk prediction using individual-level genotypes and/or summary statistics from large cohorts.
Guardado en:
Autores principales: | Wonil Chung, Jun Chen, Constance Turman, Sara Lindstrom, Zhaozhong Zhu, Po-Ru Loh, Peter Kraft, Liming Liang |
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Formato: | article |
Lenguaje: | EN |
Publicado: |
Nature Portfolio
2019
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Materias: | |
Acceso en línea: | https://doaj.org/article/bff51525773547649c9ec281d7ff076f |
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