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Vesalius: high-resolution in silico anatomization of spatial transcriptomic data using image analysis.
Martin, Patrick C N; Kim, Hyobin; Lövkvist, Cecilia; Hong, Byung-Woo; Won, Kyoung Jae.
Afiliação
  • Martin PCN; Department of Computational Biomedicine, Cedars-Sinai Medical Center, Hollywood, CA, USA.
  • Kim H; Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
  • Lövkvist C; Department of Computational Biomedicine, Cedars-Sinai Medical Center, Hollywood, CA, USA.
  • Hong BW; Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
  • Won KJ; Biotech Research and Innovation Centre (BRIC), University of Copenhagen, Copenhagen, Denmark.
Mol Syst Biol ; 18(9): e11080, 2022 09.
Article em En | MEDLINE | ID: mdl-36065846
ABSTRACT
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transcriptoma Limite: Animals Idioma: En Revista: Mol Syst Biol Assunto da revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Transcriptoma Limite: Animals Idioma: En Revista: Mol Syst Biol Assunto da revista: BIOLOGIA MOLECULAR / BIOTECNOLOGIA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos