Protocols for Single-Cell RNA-Seq and Spatial Gene Expression Integration and Interactive Visualization

Authors

Surbhi Sona
Matthew Bradley
Angela H Ting

Publication Date

3-17-2023

Journal

STAR Protocols

DOI

10.1016/j.xpro.2023.102047

PMID

36853708

PMCID

PMC9871342

PubMedCentral® Posted Date

January 2023

PubMedCentral® Full Text Version

Post-print

Abstract

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).

Keywords

Humans, Sequence Analysis, RNA, Single-Cell Gene Expression Analysis, Single-Cell Analysis, Gene Expression Profiling, Transcriptome, Bioinformatics, Single Cell, Sequencing, RNAseq

Published Open-Access

yes

Recommended Citation

Surbhi Sona, Matthew Bradley, and Angela H Ting, "Protocols for Single-Cell RNA-Seq and Spatial Gene Expression Integration and Interactive Visualization" (2023). Faculty, Staff and Student Publications. 2202.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/2202