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 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.

ggVolcanoR: A Shiny app for customizable visualization of differential expression datasets.

Volcano and other analytical plots (e.g., correlation plots, upset plots, and heatmaps) serve as important data visualization methods for transcriptomic and proteomic analyses. Customizable generation of these plots is fundamentally important for a better understanding of dysregulated expression data and is therefore instrumental for the ensuing pathway analysis and biomarker identification. Here, we present an R-based Shiny application, termed ggVolcanoR, to allow for customizable generation and visualization of volcano plots, correlation plots, upset plots, and heatmaps for differential expression datasets, via a user-friendly interactive interface in both local executable version and web-based application without requiring programming expertise. Compared to currently existing packages, ggVolcanoR offers more practical options to optimize the generation of publication-quality volcano and other analytical plots for analyzing and comparing dysregulated genes/proteins across multiple differential expression datasets. In addition, ggVolcanoR provides an option to download the customized list of the filtered dysregulated expression data, which can be directly used as input for downstream pathway analysis. The source code of ggVolcanoR is available at https://github.com/KerryAM-R/ggVolcanoR and the webserver of ggVolcanoR 1.0 has been deployed and is freely available for academic purposes at https://ggvolcanor.erc.monash.edu/.