BASS: multi-scale and multi-sample analysis enables accurate cell type clustering and spatial domain detection in spatial transcriptomic studies

Spatial transcriptomic studies are reaching single-cell spatial resolution, with data often collected from multiple tissue sections. Here, we present a computational method, BASS, that enables multi-scale and multi-sample analysis for single-cell resolution spatial transcriptomics. BASS performs cel...

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Veröffentlicht in:Genome Biology Jg. 23; H. 1; S. 168
Hauptverfasser: Li, Zheng, Zhou, Xiang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: London BioMed Central 04.08.2022
Springer Nature B.V
BMC
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ISSN:1474-760X, 1474-7596, 1474-760X
Online-Zugang:Volltext
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Zusammenfassung:Spatial transcriptomic studies are reaching single-cell spatial resolution, with data often collected from multiple tissue sections. Here, we present a computational method, BASS, that enables multi-scale and multi-sample analysis for single-cell resolution spatial transcriptomics. BASS performs cell type clustering at the single-cell scale and spatial domain detection at the tissue regional scale, with the two tasks carried out simultaneously within a Bayesian hierarchical modeling framework. We illustrate the benefits of BASS through comprehensive simulations and applications to three datasets. The substantial power gain brought by BASS allows us to reveal accurate transcriptomic and cellular landscape in both cortex and hypothalamus.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1474-760X
1474-7596
1474-760X
DOI:10.1186/s13059-022-02734-7