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. Author manuscript; available in PMC: 2024 Apr 1.
Published in final edited form as: Nat Genet. 2023 Sep 25;55(10):1757–1768. doi: 10.1038/s41588-023-01501-z

Fig. 6 |. Prediction accuracy of five binary traits in 23andMe, Inc. datasets.

Fig. 6 |

The data are from five populations: EUR (averaged n ≈ 2.37 million), AFR (averaged n ≈ 109,000), Latino (averaged n ≈ 401,000), EAS (averaged n ≈ 86,000) and SAS (averaged n ≈ 24,000). The datasets are randomly split into 70%, 20% and 10% for training, tuning and validation datasets, respectively. The adjusted AUC values were reported based on the validation dataset accounting for PCs 1–5, sex and age. The red dashed line represents the prediction performance of EUR PRS generated using a single-ancestry method (best of CT or LDpred2) in the EUR population. Analyses were restricted to the ~2.0 million SNPs that are included in Hapmap3, the MEGA chips array or both. PolyPred-S+ and PRS-CSx analyses were further restricted to ~1.3 million HM3 SNPs as implemented in the provided software. All approaches were trained using data from the EUR and the target populations. CT-SLEB and PRS-CSx were also evaluated using training data from five ancestries. From top to bottom, five binary traits are displayed in the following order: (1) any CVD; (2) depression; (3) migraine diagnosis; (4) SBMN; and (5) morning person.