medRxivGenetic & Genomic MedicinePreprint
PrimateAI-3D outperforms AlphaMissense in real-world cohorts
David A. ParryiD, Tom Bosc, Tobias Hamp, Petko P. FizieviD, Abhishek SharmaiD, Irfahan KassamiD, Jeremy F. McRaeiD, Kyle Kai‐How FarhiD
Abstract
Accurately predicting the impact of genetic variants is essential for interpreting genomic data, yet no consensus exists on how to measure classifier performance. We prepared the most comprehensive set of benchmarks to date and applied them to the recently published models PrimateAI-3D and AlphaMissense. PrimateAI-3D outperforms AlphaMissense on rare-disease cohort and biobank benchmarks, indicating that performance on clinical databases or in vitro assays does not reliably generalize to real-world cohorts.
- organism: human
- assay: GWAS summary statistics
- research focus: variant effect prediction
- approach: benchmark study
- Citations
- 5
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