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

Immunopeptidomics has made tremendous contributions to our understanding of antigen processing and presentation, by identifying and quantifying antigenic peptides presented on the cell surface by Major Histocompatibility Complex (MHC) molecules. Large and complex immunopeptidomics datasets can now b...

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Bibliographic Details
Published in:Computational and structural biotechnology journal 2023-01, Vol.21, p.1678-1687
Main Authors: Munday, Prithvi Raj, Fehring, Joshua, Revote, Jerico, Pandey, Kirti, Shahbazy, Mohammad, Scull, Katherine E., Ramarathinam, Sri H., Faridi, Pouya, Croft, Nathan P., Braun, Asolina, Li, Chen, Purcell, Anthony W.
Format: Article
Language:English
Subjects:
Antigen processing and presentation
antigens
automation
biotechnology
data collection
Immunopeptidomics
Internet
liquid chromatography
major histocompatibility complex
mass spectrometry
Peptide analysis
peptides
prediction
Software/Web Server
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Summary:Immunopeptidomics has made tremendous contributions to our understanding of antigen processing and presentation, by identifying and quantifying antigenic peptides presented on the cell surface by Major Histocompatibility Complex (MHC) molecules. Large and complex immunopeptidomics datasets can now be routinely generated using Liquid Chromatography-Mass Spectrometry techniques. The analysis of this data – often consisting of multiple replicates/conditions – rarely follows a standard data processing pipeline, hindering the reproducibility and depth of analysis of immunopeptidomic data. Here, we present Immunolyser, an automated pipeline designed to facilitate computational analysis of immunopeptidomic data with a minimal initial setup. Immunolyser brings together routine analyses, including peptide length distribution, peptide motif analysis, sequence clustering, peptide-MHC binding affinity prediction, and source protein analysis. Immunolyser provides a user-friendly and interactive interface via its webserver and is freely available for academic purposes at https://immunolyser.erc.monash.edu/. The open-access source code can be downloaded at our GitHub repository: https://github.com/prmunday/Immunolyser. We anticipate that Immunolyser will serve as a prominent computational pipeline to facilitate effortless and reproducible analysis of immunopeptidomic data.
ISSN:2001-0370
2001-0370
DOI:10.1016/j.csbj.2023.02.033