AlloPipe and Its Web Server Allogenomics: From Genomic Data to Candidate Minor Histocompatibility Antigens

While transplantation outcomes are closely linked to HLA compatibility, minor histocompatibility antigens (mHAgs)-peptides embedded in HLA molecules bearing amino acid differences within the donor/recipient pair-also contribute to T-cell alloreactivity, especially in HLA-matched pairs. Because mHAgs initially arise from non-synonymous genomic polymorphisms, we and others have focused on genomic data to approximate mHAgs load. However, most teams based their strategies on genotyping data, which only allows the study of polymorphisms that are already known and well described at the population level. Nowadays, no publicly available software exists that can facilitate unbiased identification of mHAgs candidates from whole-exome or whole-genome sequencing data. We present AlloPipe, a bioinformatics tool designed for this purpose. AlloPipe operates in two sequential steps: Allo-Count, which accurately identifies directional amino acid mismatches, and Allo-Affinity, which reconstructs peptides around these mismatches and returns their affinity for HLA class I molecules. With its ability to process rapidly large datasets in modest-scale computing infrastructures in a clinically relevant timeframe, AlloPipe makes possible the implementation of class I restricted mHAgs approximation into clinical decisions, such as immunosuppressive therapy optimization or donor selection. This open-source software offers a flexible choice of tools at each step of the analysis, especially when predicting affinity towards HLA molecules. It is available locally and via a web interface, making potential mHAgs predictions more accessible and actionable in clinical practice.