Benchmarking Machine-Learning Classifiers for Neoantigen Immunogenicity Prediction and the Limits of SHAP Interpretability

Personalized cancer vaccines require prioritizing, among hundreds of candidate mutant peptides, the few that will induce a T-cell response. This study asks what general-purpose machine learning achieves on that task, and whether the features such models identify as important can be trusted. We mak