Protocols for single-cell RNA-seq and spatial gene expression integration and interactive visualization

There is a wealth of software that utilizes single-cell RNA-seq (scRNA-seq) data to deconvolve spatial transcriptomic spots, which currently are not yet at single-cell resolution. Here we provide protocols for implementing Seurat and Giotto packages to elucidate cell-type distribution in our example...

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Detalles Bibliográficos
Autores principales: Sona, Surbhi, Bradley, Matthew, Ting, Angela H.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Protocol
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9871342/
https://www.ncbi.nlm.nih.gov/pubmed/36853708
http://dx.doi.org/10.1016/j.xpro.2023.102047
Descripción
Sumario:There is a wealth of software that utilizes single-cell RNA-seq (scRNA-seq) data to deconvolve spatial transcriptomic spots, which currently are not yet at single-cell resolution. Here we provide protocols for implementing Seurat and Giotto packages to elucidate cell-type distribution in our example human ureter scRNA-seq dataset. We also describe how to create a stand-alone interactive web application using Seurat libraries to visualize and share our results. For complete details on the use and execution of this protocol, please refer to Fink et al. (2022).(1)

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