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

Quantitative Analysis01:12

Quantitative Analysis

1.5K
Quantitative analysis is a technique for measuring the amount of specific constituents in a sample. When the sample's composition is unknown, qualitative analysis is performed first to identify its components, which ensures that the correct substances are measured during the quantitative phase.
In quantitative analysis, two key measurements are made: the sample quantity and a property proportional to the amount of the analyte (the substance being analyzed). This forms the basis of the...
1.5K
Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

15.0K
Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
15.0K
Load along a Single Axis01:29

Load along a Single Axis

648
In structural engineering, the analysis of beams subjected to varying loads is a critical aspect of understanding the behavior and performance of these structural elements. A common scenario involves a beam subjected to a combination of different load distributions.
Consider a beam of length L subjected to a varying load, which is a combination of parabolic and trapezoidal load distribution along the x-axis. In this case, it is essential to determine the resultant loads, their locations, and...
648
Single Pipe Systems01:24

Single Pipe Systems

466
In pipe flow analysis, problems are typically categorized into three types — Type I, Type II, and Type III — based on the known parameters and the desired outcome. Each type of problem addresses specific engineering requirements using fluid properties, pipe characteristics, and operational conditions.
In a Type I problem, fluid properties (density and viscosity), pipe characteristics (including diameter, length, and surface roughness), and the flow rate or average velocity are...
466
Quantitative Aspects of Drug-Receptor Interaction01:30

Quantitative Aspects of Drug-Receptor Interaction

1.8K
The receptor occupancy theory connects a drug's response to the number of occupied receptors. With higher drug concentrations, more receptors are occupied, leading to increased responses. The formation of drug-receptor complexes involves association and dissociation rates, which reach equilibrium when the forward and backward reactions are equal. The equilibrium association constant (Ka) and its inverse, the equilibrium dissociation constant (Kd), indicate drug affinity. Higher Ka and lower...
1.8K
Angular Momentum: Single Particle01:10

Angular Momentum: Single Particle

7.9K
Angular momentum is directed perpendicular to the plane of the rotation, and its magnitude depends on the choice of the origin. The perpendicular vector joining the linear momentum vector of an object to the origin is called the “lever arm.” If the lever arm and linear momentum are collinear, then the magnitude of the angular momentum is zero. Therefore, in this case, the object rotates about the origin such that it lies on the rim of the circumference defined by the lever arm...
7.9K

You might also read

Related Articles

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

Sort by
Same author

Compound models and Pearson residuals for single-cell RNA-seq data without UMIs.

Genome biology·2026
Same author

Identification and comparison of orthologous cell types from primate embryoid bodies shows limits of marker gene transferability.

eLife·2026
Same author

<i>Mir147</i> Limits the Contribution of Non-Foamy Macrophages to Atherosclerosis.

Circulation·2026
Same author

Systematic evaluation of single-cell multimodal data integration enhances cell type resolution and discovery of clinically relevant states in complex tissues.

Genome biology·2026
Same author

Reconstitution of the uterine immune milieu after uterus or hematopoietic stem cell transplantation.

Science translational medicine·2026
Same author

Galectin-1 induces macrophage immunometabolic reprogramming, modulates T cell immunity and attenuates atherosclerotic plaque formation.

Atherosclerosis·2025
Same journal

Multi-view knowledge-guided flow subgraphs with substructure initialization for explainable DDI prediction.

Briefings in functional genomics·2026
Same journal

Genetically supported mediators linking peripheral metabolism to cerebral ischemia: a multi-omics characterization of HMGCR, TLR4, and MMP9 in angina pectoris and stroke.

Briefings in functional genomics·2026
Same journal

Language model-based self-training reduces labeled data requirements by 99% for biological sequence classification.

Briefings in functional genomics·2026
Same journal

Whole-transcriptome sequencing reveals hypoxic esophageal squamous cell carcinoma-derived migrasomes driving cancer-associated fibroblast activation.

Briefings in functional genomics·2026
Same journal

An integrative meta-analysis of SARS-CoV-2 RNA-protein interactomes identifies conserved host factors shared with other RNA viruses.

Briefings in functional genomics·2026
Same journal

Retraction and replacement of: An integrated complete-genome sequencing and systems biology approach to predict antimicrobial resistance genes in the virulent bacterial strains of Moraxella catarrhalis.

Briefings in functional genomics·2026
See all related articles

Related Experiment Video

Updated: Feb 12, 2026

Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

30.7K

Quantitative single-cell transcriptomics.

Christoph Ziegenhain1, Beate Vieth1, Swati Parekh1

  • 1Anthropology and Human Genomics, Department of Biology II, Ludwig-Maximilians University, Großhaderner Str. 2, Martinsried, Germany.

Briefings in Functional Genomics
|March 27, 2018
PubMed
Summary
This summary is machine-generated.

Single-cell RNA sequencing (scRNA-seq) offers powerful insights into cellular diversity. This review compares experimental protocols and computational methods for scRNA-seq data analysis.

More Related Videos

Isolation and Transcriptome Analysis of Plant Cell Types
08:53

Isolation and Transcriptome Analysis of Plant Cell Types

Published on: April 7, 2023

2.2K
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

3.5K

Related Experiment Videos

Last Updated: Feb 12, 2026

Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

30.7K
Isolation and Transcriptome Analysis of Plant Cell Types
08:53

Isolation and Transcriptome Analysis of Plant Cell Types

Published on: April 7, 2023

2.2K
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

3.5K

Area of Science:

  • Molecular Biology
  • Genomics
  • Bioinformatics

Background:

  • Single-cell RNA sequencing (scRNA-seq) is revolutionizing biological research by enabling the study of cellular heterogeneity.
  • Numerous scRNA-seq protocols and data analysis tools have emerged, necessitating guidance for researchers.
  • Understanding cellular heterogeneity and molecular networks is crucial in modern biology.

Purpose of the Study:

  • To provide a comprehensive review of existing single-cell RNA sequencing protocols.
  • To compare and contrast various computational methods for scRNA-seq data processing and analysis.
  • To assist researchers in selecting appropriate experimental and analytical approaches for their specific research questions.

Main Methods:

  • Review of over 50 single-cell RNA sequencing experimental protocols.
  • Benchmarking methodologies for experimental protocol evaluation.
  • Comparison of essential computational methods including mapping, filtering, normalization, batch correction, and differential expression analysis.

Main Results:

  • Detailed overview of the principles behind diverse scRNA-seq protocols.
  • Comparative analysis of data processing and analysis tools for scRNA-seq.
  • Guidance on selecting optimal methods based on research objectives.

Conclusions:

  • The rapid evolution of scRNA-seq necessitates informed choices in experimental design and data analysis.
  • This review aims to empower researchers to effectively utilize scRNA-seq for biological discovery.
  • Choosing the right protocol and analysis pipeline is key to successfully resolving cellular heterogeneity.