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immunogenicity-scoring

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Rank and prioritize neoantigen/epitope candidates by likely T-cell response using NeoFox feature annotation, PRIME2.0, BigMHC-IM, the Łuksza/Balachandran fitness model (agretopicity + foreignness), and pVACtools tiering. Encodes the field's hard truths that immunogenicity is the least-solved layer (dedicated scores ~AUROC 0.6-0.7, modest PPV), that scores are valid only for RANKING within one patient (never absolute go/no-go or cross-patient), that DAI has anchor-inflation and WT-denominator traps, and that stacking weak correlated scores into one number is a red flag. Use when ordering a candidate list for a vaccine. Binding lives in mhc-binding-prediction; calling in neoantigen-prediction.

When to use

• Ranking neoantigen candidates
• Prioritizing epitope candidates
• Ordering candidate lists for a vaccine
• Annotating presentation and recognition features
• Using NeoFox feature annotation
• Applying pVACtools tiering
• Calculating PRIME2.0 scores
• Calculating BigMHC-IM scores

When not to use

• Absolute go/no-go immunogenicity verdicts
• Cross-patient comparison
• Cross-allele comparison
• MHC binding prediction
• Neoantigen calling
• Class II immunogenicity prediction
• Using ImmunoBERT as an immunogenicity predictor

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