Vesalius: high-resolution in silico anatomization of spatial transcriptomic data using image analysis.
anatomical territories
spatial domains
spatial transcriptomics
tissue architecture
tissue heterogeneity
Journal
Molecular systems biology
ISSN: 1744-4292
Titre abrégé: Mol Syst Biol
Pays: England
ID NLM: 101235389
Informations de publication
Date de publication:
09 2022
09 2022
Historique:
revised:
18
08
2022
received:
18
04
2022
accepted:
19
08
2022
entrez:
6
9
2022
pubmed:
7
9
2022
medline:
9
9
2022
Statut:
ppublish
Résumé
Characterization of tissue architecture promises to deliver insights into development, cell communication, and disease. In silico spatial domain retrieval methods have been developed for spatial transcriptomics (ST) data assuming transcriptional similarity of neighboring barcodes. However, domain retrieval approaches with this assumption cannot work in complex tissues composed of multiple cell types. This task becomes especially challenging in cellular resolution ST methods. We developed Vesalius to decipher tissue anatomy from ST data by applying image processing technology. Vesalius uniquely detected territories composed of multiple cell types and successfully recovered tissue structures in high-resolution ST data including in mouse brain, embryo, liver, and colon. Utilizing this tissue architecture, Vesalius identified tissue morphology-specific gene expression and regional specific gene expression changes for astrocytes, interneuron, oligodendrocytes, and entorhinal cells in the mouse brain.
Identifiants
pubmed: 36065846
doi: 10.15252/msb.202211080
pmc: PMC9446088
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e11080Informations de copyright
© 2022 The Authors. Published under the terms of the CC BY 4.0 license.
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