scDOT: optimal transport for mapping senescent cells in spatial transcriptomics
The low resolution of spatial transcriptomics data necessitates additional information for optimal use. We developed scDOT, which combines spatial transcriptomics and single cell RNA sequencing to improve the ability to reconstruct single cell resolved spatial maps and identify senescent cells. scDOT integrates optimal transport and expression deconvolution to learn non-linear couplings between cells and spots and to infer cell placements. Application of scDOT to lung spatial transcriptomics data improves on prior methods and allows the identification of the spatial organization of senescent cells, their neighboring cells and novel genes involved in cell-cell interactions that may be driving senescence.
Authors
- Gloria Pryhuber (ORCID: https://orcid.org/0000-0002-9185-3994)
- Jose Lugo-Martinez (ORCID: https://orcid.org/0000-0002-6312-1577)
- Lorena Rosas (ORCID: https://orcid.org/0009-0005-9054-3045)
- Toren Finkel (ORCID: https://orcid.org/0000-0002-0726-3546)
- Marta Bueno (ORCID: https://orcid.org/0000-0001-7140-9899)
- Qin Ma (ORCID: https://orcid.org/0000-0002-3264-8392)
- Euxhen Hasanaj (ORCID: https://orcid.org/0000-0002-6940-8683)
- Irfan Rahman (ORCID: https://orcid.org/0000-0003-2274-2454)
- Ziv Bar‐Joseph (ORCID: https://orcid.org/0000-0003-3430-6051)
- Peiran Jiang (ORCID: https://orcid.org/0000-0003-1586-7806)
- Nam D. Nguyen (ORCID: https://orcid.org/0000-0002-2939-5806)
- Mélanie Königshoff (ORCID: https://orcid.org/0000-0001-9414-5128)
- Ana Lucia Mora (ORCID: https://orcid.org/0000-0003-1653-8318)
- Timur O. Khaliullin (ORCID: https://orcid.org/0000-0003-1638-9228)
- José Antonio Ovando-Ricárdez
- Dongmei Li (ORCID: https://orcid.org/0000-0001-9140-2483)
- Mauricio Rojas (ORCID: https://orcid.org/0000-0001-9059-4022)
- Oliver Eickelberg
Institutions
- University of Pittsburgh (US)
- University of Rochester Medical Center (US)
- Lung Institute (US)
- The Ohio State University (US)
- Carnegie Mellon University (US)
Publication Details
- Journal
- Genome biology
- Published
- 2024-11-08
- DOI
- https://doi.org/10.1186/s13059-024-03426-0
- Citations
- 6
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 1.40
Funders
- National Institutes of Health