Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

RNA-seq03:21

RNA-seq

10.2K
RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while...
10.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

scPASU: A computational protocol for quantifying polyadenylation site usage and alternative polyadenylation from 3' scRNA-seq data.

STAR protocols·2026
Same author

Dissecting placental host-pathogen interactions: Rift Valley fever virus infection in early human trophoblast stem cells.

iScience·2026
Same author

Emergency preservation and resuscitation in exsanguination cardiac arrest: science fiction to future reality?

Trauma surgery & acute care open·2026
Same author

Editorial: feasibility and usability of a combat medical early warning system for simulated mass casualty triage during a naval exercise - A pilot study.

Injury·2026
Same author

Aortic cardiopulmonary resuscitation in trauma: Extracorporeal CPR with controlled reoxygenation outperforms resuscitative thoracotomy in a porcine model of exsanguination arrest.

The journal of trauma and acute care surgery·2026
Same author

Developmental reprogramming underlies chemotherapy resistance in favorable-histology Wilms tumor.

Cell reports·2026
Same journal

Protocol for semi-automatic quantitative bioimaging analysis of synapse loss.

STAR protocols·2026
Same journal

Protocol for integrated ubiquitination analysis of in vitro E3 ligase-DUB regulation and in vivo ubiquitin chain linkage characterization.

STAR protocols·2026
Same journal

Protocol for constructing multi-ancestry polygenic models using S4-Multi.

STAR protocols·2026
Same journal

Protocol for inducing deep vein thrombosis in C57BL/6J mice using the inferior vena cava stenosis model.

STAR protocols·2026
Same journal

Overcoming the challenges of genome-editing essential genes.

STAR protocols·2026
Same journal

Protocol for longitudinal two-photon calcium imaging and holographic optogenetic manipulation to investigate memory in mice.

STAR protocols·2026
See all related articles

Related Experiment Video

Updated: Aug 8, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.6K

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

Surbhi Sona1, Matthew Bradley1, Angela H Ting1

  • 1Department of Nutrition, Center for Proteomics and Bioinformatics, School of Medicine, Case Western Reserve University, Cleveland, OH 44106, USA; Genomic Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA.

STAR Protocols
|February 28, 2023
PubMed
Summary
This summary is machine-generated.

This study details methods for analyzing single-cell RNA sequencing (scRNA-seq) data to map cell types within spatial transcriptomics. Protocols using Seurat and Giotto are provided for human ureter data visualization.

Keywords:
BioinformaticsRNAseqSequencingSingle Cell

More Related Videos

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.0K
Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies
05:45

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Published on: March 29, 2024

2.5K

Related Experiment Videos

Last Updated: Aug 8, 2025

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues
10:12

Droplet Barcoding-Based Single Cell Transcriptomics of Adult Mammalian Tissues

Published on: January 10, 2019

18.6K
Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
09:19

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

Published on: July 6, 2022

5.0K
Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies
05:45

Author Spotlight: Integrating Organoid Models with Single-Cell and Spatial Transcriptomics Technologies

Published on: March 29, 2024

2.5K

Area of Science:

  • Computational Biology
  • Genomics
  • Bioinformatics

Background:

  • Spatial transcriptomics offers tissue-level gene expression but lacks single-cell resolution.
  • Computational deconvolution methods are needed to interpret spatial transcriptomic data using single-cell RNA sequencing (scRNA-seq) datasets.
  • Existing scRNA-seq analysis software can be adapted for this deconvolution task.

Purpose of the Study:

  • To provide protocols for using Seurat and Giotto packages for deconvolution of spatial transcriptomic spots.
  • To demonstrate cell-type distribution elucidation in a human ureter scRNA-seq dataset.
  • To describe the creation of an interactive web application for visualizing and sharing analysis results.

Main Methods:

  • Implementation of Seurat package for scRNA-seq data analysis and deconvolution.
  • Application of Giotto package for spatial transcriptomic data analysis.
  • Development of a stand-alone interactive web application using Seurat libraries for result visualization.

Main Results:

  • Successful deconvolution of spatial transcriptomic spots using scRNA-seq data.
  • Elucidation of cell-type distribution within the human ureter dataset.
  • Demonstration of a user-friendly web application for interactive data exploration.

Conclusions:

  • Seurat and Giotto are effective tools for deconvolving spatial transcriptomic data.
  • The developed protocols enable detailed cell-type mapping in spatial contexts.
  • Interactive web applications enhance the accessibility and sharing of complex genomic data.