Cell segmentation-free inference of cell types from in situ transcriptomics data

Cell segmentation-free inference of cell types from in situ transcriptomics data

Inaccurate cell segmentation has been the major problem for cell-type identification and tissue characterization of the in situ spatially resolved transcriptomics data. Here we show a robust cell segmentation-free computational framework (SSAM), for identifying cell types and tissue domains in 2D an...

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Bibliographic Details
Main Authors: Jeongbin Park, Wonyl Choi, Sebastian Tiesmeyer, Brian Long, Lars E. Borm, Emma Garren, Thuc Nghi Nguyen, Bosiljka Tasic, Simone Codeluppi, Tobias Graf, Matthias Schlesner, Oliver Stegle, Roland Eils, Naveed Ishaque
Format: Article
Language:English
Published: Nature Publishing Group 2021-06-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-021-23807-4

Internet

https://doi.org/10.1038/s41467-021-23807-4

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