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bioRxiv · 10.64898/2026.08.04.742705

FOCUS: end-to-end preprocessing, alignment and resolution-matched integration of spatial multi-omics data

Venturelli, L.·Jacobs, J.·Sifrim, A.
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Abstract

SummaryIntegrating spatial multi-omics data requires coordinated preprocessing, cross-modality alignment and feature registration across modalities that differ in file format, coordinate system and spatial resolution. No existing tool addresses this pipeline end-to-end from raw experimental files till aligned data object. We present FOCUS, an open-source Python package that takes raw data from spatial transcriptomics, mass spectrometry imaging, Raman spectroscopy imaging and brightfield or fluorescence microscopy through modality-specific preprocessing, interactive spatial alignment and resolution-matching registration to a unified MuData object, driven by a single configuration file. Its modular, registry-based architecture allows straightforward extension to additional modalities. FOCUS is accessible via a command-line interface, a browser-based GUI and a Python API. Availability and implementationFOCUS is implemented in Python 3.11, with a browser-based GUI built on a Vue.js 3 frontend served by a Flask backend. Source code, documentation and container recipes are available at https://github.com/sifrimlab/FOCUS; a versioned release is archived on Zenodo (10.5281/zenodo.21700038). Outputs use the AnnData and MuData formats and are directly compatible with the scverse ecosystem.

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Venturelli, L., Jacobs, J., Sifrim, A.. 2026-08-09. FOCUS: end-to-end preprocessing, alignment and resolution-matched integration of spatial multi-omics data. https://doi.org/10.64898/2026.08.04.742705

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