TrambaHLApan: a transformer and mamba-based neoantigen prediction method considering both antigen presentation and immunogenicity

Neoantigens represent ideal targets for tumor immunotherapy. This study introduces TrambaHLApan, a neoantigen prediction method that utilizes Transformer and Mamba models to consider both antigen presentation potential (TrambaHLApan-EL) and immunogenicity (TrambaHLApan-IM).

Data S1: Antigen presentation training set
Data S2: Immunogenicity training set
Data S3: Allele24 independent antigen presentation test dataset
Data S4: Allele36 independent antigen presentation test set
Data S5: Cancer neoantigen immunogenicity test set (GBM)
Data S6: Cancer neoantigen immunogenicity test set (MANAFEST)
fivefold_val_flags(DataS1): Five-fold cross-validation division file for DataS1
fivefold_val_flags(DataS2): Five-fold cross-validation division file for DataS2