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bioRxiv · 10.64898/2026.08.09.743742

dbverse scales spatial omics analysis with embedded analytical databases

Ruiz, E. C.·Jarzabek, V.·Chen, J.·Rizvanov, T.·Amin, I.·Dries, R.
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Abstract

Spatial omics datasets are increasing in size and complexity, exceeding the memory of standard computers and thereby limiting data analysis. Here we present dbverse, a framework for larger-than-memory matrix, spatial and genomic data analysis in embedded analytical databases. Benchmarks show dbverse provides orders of magnitude runtime improvements relative to established in-memory and file-backed methods for core operations in single-cell and spatial omics analysis. We integrated dbverse with Giotto Suite, scaling end-to-end preprocessing of millions of cells and enabling spatial alternative polyadenylation analysis as demonstrated on a Visium HD 3' ovarian clear cell carcinoma sample. The dbverse framework provides an interoperable database foundation for larger-than-memory spatial omics analysis on ordinary computers.

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Ruiz, E. C., Jarzabek, V., Chen, J., Rizvanov, T., Amin, I., Dries, R.. 2026-08-18. dbverse scales spatial omics analysis with embedded analytical databases. https://doi.org/10.64898/2026.08.09.743742

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