CalPred is a framework that adjusts polygenic score (PGS) prediction intervals based on joint modeling of multiple contexts, such as age, sex and genetic ancestry. PGS show pervasive context-specific accuracy, suggesting that accounting for this will improve portability across contexts.
- Kangcheng Hou
- Ziqi Xu
- Bogdan Pasaniuc