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Nature Biotechnology

Identifying 3D signal overlaps in spatial transcriptomics data with ovrlpy

Tiesmeyer, Berlin Institute Of Health At Charité Universitätsmedizin Berlin, Center Of Digital Health, Berlin, Freie Universität Berlin, Department Of Mathematics, Computer Science, Müller-Bötticher, Malt, Ma 2026-02-10 · Science, Technology
myndfocal
Imaging-based spatially resolved transcriptomics can localize transcripts within tissue sections in three dimensions. However, cell segmentation, which assigns transcripts to cells, is usually performed in two dimensions and spatial doublets in the vertical dimension result in segmented cells containing transcripts originating from multiple cell types. Here we present a computational tool called ovrlpy that identifies overlapping cells, tissue folds and inaccurate cell segmentation by analyzing transcript localization in three dimensions. Ovrlpy identifies overlapping cell signals in the vertical dimension of spatial transcriptomics data.

The ovrlpy project was conceptualized during the de.NBI BioHackathon SpaceHack project in Lutherstadt-Wittenberg (December 2022); we thank the organizers of and participants in the de.NBI BioHackathon SpaceHack project. We thank T. Rheude for establishing an analogy of 2D analysis of tissue sections to the flat earth conspiracy. This research has received funding from the Federal Ministry of Education and Research of Germany in the framework of SAGE (project number 031L0265, S.T. and N.M.-B.) and CNAScope (grant no. 01KD2443, A.M.), the German Research Foundation (DFG TRR 412, Project-ID 35081457, N.I. and F.J.T.), ELIXIR Spatial2Galaxy (N.I.) and the project grant (no. 2024-02533, S.M.-S. and M.N.) from the Swedish Research Council. We thank the GESTALT community for positive engagement and ideas. We thank the following people for useful discussion and sharing data on tissue preparation and other artifacts: H. C. Etchevers, Aix Marseille University, for the Visium mouse heart samples with folds, smears and slippage; T. Conrad, Berlin Institute of Health at Charité, F. Baumgartner and U. Keller, Charité—Universitätsmedizin Berlin, for the Xenium human uveal melanoma sample with detachment; O. Raineteau, G. Marcy and C. Dégletagne, Cancer Research Center of Lyon, for the Xenium mouse brain samples with tissue folds; and M. Grillo and C. M. Langseth, Stockholm University, for the ISS and Xenium multiple sclerosis samples with signal smearing.

— Source: Nature Biotechnology (https://www.nature.com/articles/s41587-026-03004-8)

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