SOFTWARE

From raw instrument files to publication-ready figures, with no programming. Profiler reads proteomics, metabolomics, lipidomics, transcriptomics and mass spectrometry imaging data (through MSI2Profiler) and walks through the whole analysis.

• Raw file conversion (Bruker, Waters, Thermo), quality control and preprocessing
• Interactive visualisation and differential analysis
• Machine-learning classification and regression, with SHAP and LIME explanations
• Pathway enrichment (ORA and GSEA, 100+ databases)
• Survival and longitudinal analysis, one-click HTML report

Article
Zirem Y, Ledoux L, Fournier I, Salzet M. Profiler: an open web platform for multi-omics analysis. Bioinformatics 2026;42(1):btaf644. doi:10.1093/bioinformatics/btaf644

Web access
prism-profiler.univ-lille.fr

Local version
github.com/yanisZirem/prism-profiler
Fully offline, with the MSI2Profiler companion tool. No account.

Test data
github.com/yanisZirem/Profiler_v1_requests_datatests
MaxQuant, DIA-NN and PEAKS outputs, Bruker and Waters raw files, multi-omics tables, survival and longitudinal sets, user manual.

ionScell extracts single-cell spectra directly from mass spectrometry imaging data, without a co-registered microscopy image or manual annotation. Cell boundaries are derived from the total ion current image and watershed segmentation, then each cell spectrum is quality-controlled and grouped into molecular subpopulations.

• Adaptive thresholding and watershed segmentation
• Six-metric spectral quality control
• Soft clustering and differential analysis
• Per-cell ion maps and embedded lipid annotation

Article
ionScell enables microscopy-independent single-cell spectral extraction from MALDI mass spectrometry imaging. Preprint, Research Square, 2026. 
doi:10.21203/rs.3.rs-9874513/v1

Local version
github.com/yanisZirem/ionScell
Open source, MIT licence. Also runs online in Google Colab, no installation.

Test data
doi:10.5281/zenodo.20070096
Public Zenodo deposit.

imsCORE packages the PRISM tissue analysis workflow into a point-and-click application. It takes one or several imzML files, builds a tissue mask from the TIC image, and offers two modes.

• Segmentation — unsupervised, by bisecting k-means validated with local silhouette scores, with UMAP, cluster spectra and discriminant ions
• Classification — applies a model trained in Profiler (.pkl) pixel by pixel, giving probability maps and class ratios per sample

Article
Lagache L, Zirem Y, Le Rhun É, Fournier I, Salzet M. Predicting protein pathways associated to tumor heterogeneity by correlating spatial lipidomics and proteomics: the dry proteomic concept. Mol Cell Proteomics 2025;24(1):100891. 
doi:10.1016/j.mcpro.2024.100891

Protocol
Zirem Y, Ledoux L, Salzet M, Fournier I. Protocol to analyze 1D and 2D mass spectrometry data from glioblastoma tissues for cancer diagnosis and immune cell identification. STAR Protoc 2024;5(3):103285. 
doi:10.1016/j.xpro.2024.103285

Local version, code & test data
github.com/yanisZirem/imsCORE

Sentinel is an automated PRISM pipeline for multiplex immunohistochemistry data acquired by mass spectrometry imaging with TAG-Mass technology. It turns raw imzML data into an integrated spatial and immunological analysis of the tumour immune microenvironment (TIME), from marker-level ion images to immune landscape characterisation and literature-informed scoring.

• Individual marker maps, composite images, prognostic overlays and functional-group visualisations to explore the spatial organisation of immune signals
• Curated marker annotations and weighted immune contributions, giving a Global Weighted Immune Score (WIS), an immune phenotype and a provisional prognostic category
• Automated reporting: a self-contained HTML report with embedded visualisations, a multi-sheet Excel workbook and a collection of publication-quality figures

Article
Goossen A, et al. A universal modular high-plex MALDI mass spectrometry imaging platform (TAG-Mass). Preprint, Research Square. researchsquare.com/article/rs-9525563

Availability
The complete Sentinel pipeline, source code, documentation and associated test data are planned for release following publication of the dedicated article.