Multi-PGS enhances polygenic prediction by combining 937 polygenic scores

Multi-PGS enhances polygenic prediction by combining 937 polygenic scores

Abstract The predictive performance of polygenic scores (PGS) is largely dependent on the number of samples available to train the PGS. Increasing the sample size for a specific phenotype is expensive and takes time, but this sample size can be effectively increased by using genetically correlated p...

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Bibliografische gegevens
Hoofdauteurs: Clara Albiñana, Zhihong Zhu, Andrew J. Schork, Andrés Ingason, Hugues Aschard, Isabell Brikell, Cynthia M. Bulik, Liselotte V. Petersen, Esben Agerbo, Jakob Grove, Merete Nordentoft, David M. Hougaard, Thomas Werge, Anders D. Børglum, Preben Bo Mortensen, John J. McGrath, Benjamin M. Neale, Florian Privé, Bjarni J. Vilhjálmsson
Formaat: Artikel
Taal:English
Gepubliceerd in: Nature Portfolio 2023-08-01
Reeks:Nature Communications
Online toegang:https://doi.org/10.1038/s41467-023-40330-w

Internet

https://doi.org/10.1038/s41467-023-40330-w

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