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

11.1K
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...
11.1K

You might also read

Related Articles

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

Sort by
Same author

Circular RNAs: promising biomarkers for diagnosis, prognosis and therapy in oral squamous cell carcinoma.

Nucleosides, nucleotides & nucleic acids·2026
Same author

Mapping the Molecular Evolution and Role of Wild Rice GLYIII Protein-Encoding Genes in Abiotic Stress Response.

Biochemical genetics·2026
Same author

Prophylactic Inhaled Pattern Recognition Receptor Agonists Reprogram Lung Epithelial Response and Prevent Type 2 Allergic Inflammation.

European journal of immunology·2026
Same author

Effect of <i>ABCG2</i> genetic polymorphisms on the transport of anti-seizure medications in hCMEC/D3 cell lines.

Cytotechnology·2026
Same author

Application of interpretable machine learning to analyze DNA methylation sites in the progression from oral Leukoplakia to oral squamous cell carcinoma.

Integrative biology : quantitative biosciences from nano to macro·2026
Same author

Structural stability of two promising keratinases in human hair degrading ionic liquids: paving the way for more efficient and sustainable keratin extraction.

Journal of biomolecular structure & dynamics·2025

Related Experiment Video

Updated: Nov 20, 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

18.9K

A hitchhiker's guide to single-cell transcriptomics and data analysis pipelines.

Richa Nayak1, Yasha Hasija1

  • 1Department of Biotechnology, Delhi Technological University, Delhi 110042, India.

Genomics
|January 24, 2021
PubMed
Summary

Single-cell transcriptomics (SCT) offers unprecedented cellular insights by analyzing gene expression at the individual cell level. This review details the SCT workflow, analysis methods, and its revolutionary potential in biology and disease research.

Keywords:
Computational approachMachine learningSingle-cell RNA sequencingSingle-cell data analysisSingle-cell transcriptomics

More Related Videos

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

2.9K
Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

30.3K

Related Experiment Videos

Last Updated: Nov 20, 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

18.9K
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

2.9K
Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

30.3K

Area of Science:

  • Genomics
  • Computational Biology
  • Molecular Biology

Background:

  • Single-cell transcriptomics (SCT) generates high-resolution cellular transcription data, surpassing bulk analysis limitations.
  • It is essential for identifying cellular heterogeneity, rare cell populations, and lineage trajectories.

Purpose of the Study:

  • To provide a comprehensive review of the single-cell transcriptomics workflow, from experiments to data analysis.
  • To discuss current trends, challenges, and machine learning applications in SCT data analysis.

Main Methods:

  • Review of experimental protocols and computational pipelines for SCT data processing.
  • Discussion of statistical and machine learning approaches for analyzing complex SCT datasets.

Main Results:

  • Detailed overview of the entire SCT workflow, including data generation and analysis strategies.
  • Exploration of various analytical pipelines and their suitability for different research questions.

Conclusions:

  • SCT is a powerful tool revolutionizing cellular biology and disease understanding.
  • Future prospects include advanced machine learning methods and diverse applications of scRNA-seq data.