Prediction of epitope immunogenicity for CD8+ Cell

How to interpret immunogenicity score?

A high immunogenicity score indicates increased confidence that the denoted peptide-HLA complex will trigger a T cell response, compared to another peptide with a lower immunogenicity score. However, it does not necessarily reflect the actual degree of immunogenicity, due to a lack of TCR sequence diversity information for a given individual. Specifically, the immunogenicity score reflects confidence based on experimental evidence of for immunogenicity in the training data. For example, if a single peptide (peptide-1) produced an immune response in 40 out of 40 experiments, it will result in a higher confidence observation than another peptide (peptide-2) that results in immune response 1 out of 6 experiments. DeepImmunoCNN uses a beta-binomial model to incorporate this evidence when deriving an immunogenicity potential from the training data. Hence, the output value reflects the confidence of the prediction.

When should I select the binding affinity option?

Selecting this option will additionally produce peptide-MHC binding predications in addition to immunogenicity predictions for queried peptide(s). Any valid CD8+ T cell mediated immune response requires a peptide is presented by the HLA allele and the HLA-peptide complex triggers a T-cell response. DeepImmuno-CNN predicts immunogenicity and not MHC-binding. By selecting this option, the user can assess the likelihood of both binding and immunogenicity in a single query. As such, this analysis requires approximately 30-60s additional runtime, as it calls the python package MHCflurry.

What does the label "Caveat" indicate?

In certain cases, the peptide query for a specific HLA allele, will produce unreliable results, when the HLA-allele has few immunogenicity experimental results in our training dataset. As such, DeepImmunno-CNN is not able to reliably infer its immunogenicity.