Cell2location maps fine-grained cell types in spatial transcriptomics.
Journal
Nature biotechnology
ISSN: 1546-1696
Titre abrégé: Nat Biotechnol
Pays: United States
ID NLM: 9604648
Informations de publication
Date de publication:
05 2022
05 2022
Historique:
received:
15
11
2020
accepted:
28
10
2021
pubmed:
15
1
2022
medline:
20
5
2022
entrez:
14
1
2022
Statut:
ppublish
Résumé
Spatial transcriptomic technologies promise to resolve cellular wiring diagrams of tissues in health and disease, but comprehensive mapping of cell types in situ remains a challenge. Here we present сell2location, a Bayesian model that can resolve fine-grained cell types in spatial transcriptomic data and create comprehensive cellular maps of diverse tissues. Cell2location accounts for technical sources of variation and borrows statistical strength across locations, thereby enabling the integration of single-cell and spatial transcriptomics with higher sensitivity and resolution than existing tools. We assessed cell2location in three different tissues and show improved mapping of fine-grained cell types. In the mouse brain, we discovered fine regional astrocyte subtypes across the thalamus and hypothalamus. In the human lymph node, we spatially mapped a rare pre-germinal center B cell population. In the human gut, we resolved fine immune cell populations in lymphoid follicles. Collectively, our results present сell2location as a versatile analysis tool for mapping tissue architectures in a comprehensive manner.
Identifiants
pubmed: 35027729
doi: 10.1038/s41587-021-01139-4
pii: 10.1038/s41587-021-01139-4
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
661-671Subventions
Organisme : Wellcome Trust
ID : 213555/Z/18/Z
Pays : United Kingdom
Informations de copyright
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.
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