Immunolyser: A web-based computational pipeline for analysing and mining immunopeptidomic data

• DOI: 10.1016/j.csbj.2023.02.033
• Publication Date: 2023-02-20T04:25:55Z
• Authors: Prithvi Raj Munday; Joshua Fehring; Jerico Revote; Kirti Pandey; Mohammad Shahbazy; Katherine E. Scull; Sri H. Ramarathinam; Pouya Faridi; Nathan P. Croft; Asolina Braun; Chen Li; Anthony W. Purcell
• Keywords: Interface (matter)

Immunopeptidomics has made tremendous contributions to our understanding of antigen processing and presentation, by identifying quantifying antigenic peptides presented on the cell surface Major Histocompatibility Complex (MHC) molecules. Large complex immunopeptidomics datasets can now be routinely generated using Liquid Chromatography-Mass Spectrometry techniques. The analysis this data - often consisting multiple replicates/conditions rarely follows a standard pipeline, hindering reproducibility depth immunopeptidomic data. Here, we present Immunolyser, an automated pipeline designed facilitate computational with minimal initial setup. Immunolyser brings together routine analyses, including peptide length distribution, motif analysis, sequence clustering, peptide-MHC binding affinity prediction, source protein analysis. provides user-friendly interactive interface via its webserver is freely available for academic purposes at https://immunolyser.erc.monash.edu/. open-access code downloaded GitHub repository: https://github.com/prmunday/Immunolyser. We anticipate that will serve as prominent effortless reproducible