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SeqUIaSCOPE: multi-omics data integration platform for single-patient clinical oncology pathway exploration.

Kateřina Jurásková·Petra Pokorná·Kristián Kováč·Nicolas Blavet·Anna Molíková·Martin Demko·Vojtěch Bystrý
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Abstract

SUMMARY: SeqUIaSCOPE is an open-source platform designed for routine clinical oncology diagnostics through case-centric integration and visualization of genomic variants, fusion events, and expression profiles. The platform combines molecular-level validation via embedded genome browsing with systems-level interpretation through dynamic pathway visualization, enabling geneticists to assess how alterations converge across biological networks. Flexible reporting with customizable templates accommodates diverse institutional requirements, while secure cluster-based or local deployment ensures compliance with data protection policies, making advanced multi-omics diagnostics accessible to academic and clinical institutions. AVAILABILITY AND IMPLEMENTATION: SeqUIaSCOPE is freely available on GitHub at https://github.com/BioIT-CEITEC/sequiascope under the MIT license and archived at Zenodo (https://zenodo.org/records/21338445). Due to the sensitive nature of patient data, the repository provides simulated datasets that mimic the structure of real clinical data for testing and exploration. Documentation and a live demo accompany these datasets, allowing users to explore the application without any prior setup. The repository also includes a Helm chart for Kubernetes deployment and Docker containers for local deployment, ensuring compatibility across Linux, macOS, and Windows. No user registration is required, and all data remains on local or institutional infrastructure.

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HumansSoftwareMultiomicsGenomicsNeoplasmsComputational BiologyMedical OncologyJournal Article

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Kateřina Jurásková, Petra Pokorná, Kristián Kováč, Nicolas Blavet, Anna Molíková, Martin Demko, Vojtěch Bystrý. 2026-08-31. SeqUIaSCOPE: multi-omics data integration platform for single-patient clinical oncology pathway exploration.. https://doi.org/10.1093/bioinformatics%2Fbtag630

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