Abstract
Immunopeptidomics interrogates the peptide repertoire presented on the cell surface by major histocompatibility complex (MHC) molecules for T cell immune recognition. Advanced mass-spectrometry-based techniques have enabled rapid accumulation of immunopeptidomic data, posing a significant challenge for automated and efficient analysis of these large-scale datasets. To tackle this challenge, we introduced Immunolyser 1.0, a computational pipeline to streamline key analyses of immunopeptidomic data, including peptide length distribution, motif analysis, peptide clustering, and peptide-MHC binding prediction. Here, we present Immunolyser 2.0 with upgraded functionalities and an improved user interface. Major updates in Immunolyser 2.0 include (i) expanded functionality allowing analysis of murine immunopeptidomic datasets; (ii) a novel algorithm, MHC-TP, to predict the MHC class I haplotype in silico where genetic MHC typing is unavailable, ethically restricted, or cost-prohibitive for large-scale datasets; (iii) an offline and operation system-independent version of Immunolyser to ensure data privacy and enable the analysis of datasets of any size; and (iv) upgraded Pepscanner module with an interactive visualisation of peptide alignment to source proteins and the option for users to upload a background proteome for source protein analysis. With these enhancements, Immunolyser 2.0 provides an expanded analysis with fast, effective, and practical solutions for peptide-centric analysis of human and murine immunopeptidomic datasets. Such analysis further advances our understanding of antigen processing and presentation and supports the development of antigen-specific immunotherapies. Immunolyser 2.0 is accessible at https://immunolyser.erc.monash.edu/, the source code and standalone version are freely available for academic purposes at https://github.com/PurcellLab/Immunolyser.