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

You might also read

Related Articles

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

Sort by
Same author

Transcriptional repression by TGIF2 coordinates neurogenic priming and neural stem cell maintenance.

Science advances·2026
Same author

A biomimetic miniaturized in vitro model to target early markers of neonatal pulmonary vascular injury.

American journal of physiology. Lung cellular and molecular physiology·2026
Same author

Longitudinal clinical proteomics reveals pneumonia type-specific protein biomarkers and autoantibodies.

JCI insight·2026
Same author

Progenitor Resilience and the Early Onset of Chronic Lung Diseases: NHLBI workshop report.

American journal of respiratory cell and molecular biology·2026
Same author

The pleuroparenchymal fibroelastosis atlas reveals aberrant cell states and their zonation as an alternate roadmap to lung fibrosis.

Science advances·2026
Same author

Non-destructive transcriptomics via vesicular export.

Nature communications·2026
Same journal

Genetic origins and constraints of evolutionary innovation.

Nature reviews. Genetics·2026
Same journal

Single-cell four-omics with CHARM.

Nature reviews. Genetics·2026
Same journal

Molecular integration of seasonal temperature signals in flowering time control.

Nature reviews. Genetics·2026
Same journal

RBPscan measures protein-RNA interactions in living cells.

Nature reviews. Genetics·2026
Same journal

Revisiting retinal and macular degeneration in the genomics era.

Nature reviews. Genetics·2026
Same journal

How evolution builds three morphs from one genome.

Nature reviews. Genetics·2026
See all related articles

Related Experiment Video

Updated: Aug 4, 2025

Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

30.0K

Best practices for single-cell analysis across modalities.

Lukas Heumos1,2,3, Anna C Schaar1,4,5, Christopher Lance1,6

  • 1Institute of Computational Biology, Department of Computational Health, Helmholtz Munich, Munich, Germany.

Nature Reviews. Genetics
|March 31, 2023
PubMed
Summary
This summary is machine-generated.

Navigating single-cell (multi-)omic analysis is challenging. This review summarizes benchmarking studies to suggest best-practice workflows for common analysis steps, aiding both new and experienced researchers.

More Related Videos

Author Spotlight: Advancing Biomedical Research Through Single Cell Analysis
07:59

Author Spotlight: Advancing Biomedical Research Through Single Cell Analysis

Published on: December 22, 2023

2.7K
Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques
09:48

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

7.5K

Related Experiment Videos

Last Updated: Aug 4, 2025

Transcriptome Analysis of Single Cells
07:27

Transcriptome Analysis of Single Cells

Published on: April 25, 2011

30.0K
Author Spotlight: Advancing Biomedical Research Through Single Cell Analysis
07:59

Author Spotlight: Advancing Biomedical Research Through Single Cell Analysis

Published on: December 22, 2023

2.7K
Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques
09:48

Discrimination and Characterization of Heterocellular Populations Using Quantitative Imaging Techniques

Published on: June 30, 2017

7.5K

Area of Science:

  • Single-cell biology
  • Computational biology
  • Genomics

Background:

  • Single-cell technologies enable high-throughput molecular profiling across modalities (e.g., transcriptomics, epigenomics, proteomics, spatial).
  • The integration of multi-omic single-cell data is crucial for comprehensive biological insights.
  • The growing complexity of single-cell analysis tools necessitates guidance for researchers.

Purpose of the Study:

  • To provide a comprehensive overview of best-practice workflows for single-cell (multi-)omic analysis.
  • To guide researchers, from novices to advanced users, through the landscape of available computational tools.
  • To consolidate findings from independent benchmarking studies to inform method selection.

Main Methods:

  • Review and synthesis of independent benchmarking studies for unimodal and multimodal single-cell analyses.
  • Comparative analysis of popular computational methods where independent benchmarks are unavailable.
  • Focus on common analysis steps across various single-cell data modalities.

Main Results:

  • Identification of recommended best-practice workflows for key single-cell (multi-)omic analysis steps.
  • A curated comparison of frequently used computational tools and their performance.
  • Guidance on navigating the increasing diversity of single-cell analysis methodologies.

Conclusions:

  • This article serves as a crucial entry point and guide for single-cell (multi-)omic data analysis.
  • Adoption of suggested best-practice workflows can enhance the efficiency and reliability of biological discovery.
  • The review aims to empower researchers to effectively utilize the expanding toolkit for single-cell data interpretation.