Faculty, Staff and Student Publications
Publication Date
3-17-2023
Journal
STAR Protocols
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
Graphical Abstract
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Bioinformatics Commons, Biomedical Informatics Commons, Medical Sciences Commons, Oncology Commons
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Associated Data
PMID: 36853708