Academic Journal
Φ-Space ST: A platform-agnostic method to identify cell states in spatial transcriptomics studies.
| Τίτλος: | Φ-Space ST: A platform-agnostic method to identify cell states in spatial transcriptomics studies. |
|---|---|
| Συγγραφείς: | Mao J; Melbourne Integrative Genomics, School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC 3010, Australia., Choi J; Bioinformatics and Cellular Genomics, St Vincent's Institute of Medical Research, Fitzroy, VIC 3065, Australia., Lê Cao KA; Melbourne Integrative Genomics, School of Mathematics and Statistics, The University of Melbourne, Parkville, VIC 3010, Australia. Electronic address: kimanh.lecao@unimelb.edu.au. |
| Πηγή: | Cell reports methods [Cell Rep Methods] 2026 Aug 17; Vol. 6 (8), pp. 101483. Date of Electronic Publication: 2026 Jun 12. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Inc Country of Publication: United States NLM ID: 9918227360606676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2667-2375 (Electronic) Linking ISSN: 26672375 NLM ISO Abbreviation: Cell Rep Methods Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: [New York] : Elsevier Inc., [2021]- |
| Ιατρικοί όροι (MeSH): | Spatial Transcriptomics*/methods , Transcriptome*/genetics, Humans ; Single-Cell Gene Expression Analysis |
| Περίληψη: | We introduce Φ-Space ST, a platform-agnostic method to identify continuous cell states in spatial transcriptomics (ST) data using multiple scRNA-seq references. For ST with supercellular resolution, Φ-Space ST achieves interpretable cell-type deconvolution with significantly faster computation. For subcellular resolution, Φ-Space ST annotates cell states without cell segmentation, leading to highly insightful spatial niche identification. Φ-Space ST harmonizes annotations derived from multiple scRNA-seq references and provides interpretable characterizations of disease cell states by leveraging healthy references. We validate Φ-Space ST in four case studies involving CosMx, Visium, Xenium, and Stereo-seq platforms for various cancer tissues. Our method revealed niche-specific enriched cell types and distinct cell-type co-presence patterns that distinguish tumor from non-tumor tissue regions. These findings highlight the potential of Φ-Space ST as a robust and scalable tool for ST data analysis for understanding complex tissues and pathologies. (Copyright © 2026 The Author(s). Published by Elsevier Inc. All rights reserved.) |
| Competing Interests: | Declaration of interests The authors declare they have no competing interests. |
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| Contributed Indexing: | Keywords: CP: cancer biology; CP: computational biology; cell states; cell type deconvolution; spatial niches; spatial transcriptomics |
| Entry Date(s): | Date Created: 20260612 Date Completed: 20260817 Latest Revision: 20260823 |
| Update Code: | 20260823 |
| PubMed Central ID: | PMC13494538 |
| DOI: | 10.1016/j.crmeth.2026.101483 |
| PMID: | 42285101 |
| Βάση Δεδομένων: | MEDLINE |
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