Machine learning optimized polygenic scores for blood cell traits identify sex-specific trajectories and genetic correlations with disease
In this issue of Cell Genomics, Xu et al. report a comprehensive analysis of the genetics of 26 blood cell traits, leveraging data from two large biobanks to construct and make available machine-learning optimized polygenic scores (PGSs). In addition to delivering insights into the biology and clinical associations of these traits, the authors evaluate and provide recommendations on methods for PGS construction.
British Heart Foundation (None)
British Heart Foundation (RG/18/13/33946)
European Commission Horizon 2020 (H2020) Societal Challenges (101016775)
National Institute for Health Research (IS-BRC-1215-20014)