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Cell-GPS (COSTE Windows Application): Cophenetic Spatial Topology Embedding for multiscale tissue architecture analysis in spatial omics

Authors: Hu, Taobo; Long, Mengping; Nilsson, Mats;

Cell-GPS (COSTE Windows Application): Cophenetic Spatial Topology Embedding for multiscale tissue architecture analysis in spatial omics

Abstract

This record provides Cell-GPS, the standalone Windows application of COSTE (Cophenetic Spatial Topology Embedding), a computational framework for quantifying multiscale tissue architecture from spatial omics data. COSTE captures global spatial organization beyond local neighborhood analysis by embedding cell-type or transcript spatial relationships into a hierarchical metric space and deriving the Spatial Separation Score (SSS) to measure spatial separation between populations. As described in the associated manuscript, COSTE is parameter-free, density-independent, and can operate at both the cell-type level and the single-transcript level without requiring cell segmentation. It has been demonstrated on spatial transcriptomics datasets (e.g., pulmonary fibrosis and triple-negative breast cancer), where it delineates tissue structures, identifies spatially defined subpopulations, and reveals disease-related architectural patterns. Cell-GPS is a GUI no-code workflow that can be used directly without programming experience and is designed to support interactive spatial omics analysis. File: CellGPS.exe (~445.77 MB) Checksum (MD5): 4624fda684bbbc1c21586c1e34f01289 For questions/support, please open an issue on the project repository or contact the corresponding author.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average