Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-specific effects via GAUDI
Sun, Q.; Rowland, B. T.; Chen, J.; Mikhaylova, A. V.; Avery, C.; Peters, U.; Lundin, J.; Matise, T.; Buyske, S.; Tao, R.; Mathias, R. A.; Reiner, A. P.; Auer, P. L.; Cox, N. J.; Kooperberg, C.; Thornton, T.; Raffield, L. M.; Li, Y.
Show abstract
Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods have focused only on individuals with one primary continental ancestry, thus poorly accommodating recently-admixed individuals. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals by explicitly modeling ancestry-specific effects and jointly estimating ancestry-shared effects. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses.
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