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Plate IV.47 · Publications

Identifying 3D signal overlaps in spatial transcriptomics data with ovrlpy

Article in Nature Biotechnology, 10 February 2026.

Open accessSpatial, Omics Data

  1. Sebastian Tiesmeyer
  2. Niklas Müller-Bötticher
  3. Alexander Malt
  4. Leyao Ma
  5. Sergio Marco-Salas
  6. Paul Kiessling
  7. Paul Horn
  8. Adrien Guillot
  9. Louis B. Kuemmerle
  10. Frank Tacke
  11. Fabian J. Theis
  12. Christoph Kuppe
  13. Mats Nilsson
  14. Roland Eils
  15. Brian Long
  16. Naveed Ishaque

Abstract

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.

Versions2

  1. PublishedNature Biotechnology10.1038/s41587-026-03004-8
  2. PreprintbioRxiv10.1101/2025.01.13.632601

Cite

@article{tiesmeyer2026identifying,
  title = {{Identifying 3D signal overlaps in spatial transcriptomics data with ovrlpy}},
  author = {Tiesmeyer, Sebastian and Müller-Bötticher, Niklas and Malt, Alexander and Ma, Leyao and Marco-Salas, Sergio and Kiessling, Paul and Horn, Paul and Guillot, Adrien and Kuemmerle, Louis B. and Tacke, Frank and Theis, Fabian J. and Kuppe, Christoph and Nilsson, Mats and Eils, Roland and Long, Brian and Ishaque, Naveed},
  journal = {Nature Biotechnology},
  publisher = {Springer Science and Business Media LLC},
  year = {2026},
  month = feb,
  doi = {10.1038/s41587-026-03004-8},
  url = {https://doi.org/10.1038/s41587-026-03004-8},
  pmid = {41667711}
}
.bib file