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

Abnormal Proliferation02:23

Abnormal Proliferation

Under normal conditions, most adult cells remain in a non-proliferative state unless stimulated by internal or external factors to replace lost cells. Abnormal cell proliferation is a condition in which the cell's growth exceeds and is uncoordinated with normal cells. In such situations, cell division persists in the same excessive manner even after cessation of the stimuli, leading to persistent tumors. The tumor arises from the damaged cells that replicate to pass the damage to the daughter...

You might also read

Related Articles

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

Sort by
Same author

SPADE: Spatial transcriptomics and pathology alignment using a mixture of data experts for an expressive latent space.

Medical image analysis·2026
Same author

Primary Cardiac Angiosarcoma Leading to Tamponade and Fatal Right Atrial Rupture.

JACC. Case reports·2026
Same author

Contextual computation by competitive protein dimerization networks.

Cell·2026
Same author

Invasive transmural fungal infection as a rare cause of thoracic aortic occlusion.

Journal of vascular surgery cases and innovative techniques·2025
Same author

Isolated osseous Rosai-Dorfman disease: a case report and review of literature.

Skeletal radiology·2025
Same author

Contextual computation by competitive protein dimerization networks.

Cell·2025

Related Experiment Video

Updated: Jun 14, 2026

Continuous Fluorescence-Based Endonuclease-Coupled DNA Methylation Assay to Screen for DNA Methyltransferase Inhibitors
06:07

Continuous Fluorescence-Based Endonuclease-Coupled DNA Methylation Assay to Screen for DNA Methyltransferase Inhibitors

Published on: August 5, 2022

When Seeing Is Not Believing: Understanding Uniform Manifold Approximation and Projection (UMAP) and t-Distributed

Benjamin Emert1

  • 1Department of Pathology and Laboratory Medicine, University of California Los Angeles, David Geffen School of Medicine, Los Angeles, California.

Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc
|June 12, 2026
PubMed
Summary

DNA methylation profiling aids tumor classification. This review guides interpreting visualization tools like UMAP and t-SNE, emphasizing transparent reporting and validation for robust pathology research.

Keywords:
dimensionality reductionmethylationmolecular pathologyuniform manifold approximation and projection

More Related Videos

Methyl-binding DNA capture Sequencing for Patient Tissues
08:40

Methyl-binding DNA capture Sequencing for Patient Tissues

Published on: October 31, 2016

Multiomics Analysis of TMEM200A as a Pan-Cancer Biomarker
07:47

Multiomics Analysis of TMEM200A as a Pan-Cancer Biomarker

Published on: September 15, 2023

Related Experiment Videos

Last Updated: Jun 14, 2026

Continuous Fluorescence-Based Endonuclease-Coupled DNA Methylation Assay to Screen for DNA Methyltransferase Inhibitors
06:07

Continuous Fluorescence-Based Endonuclease-Coupled DNA Methylation Assay to Screen for DNA Methyltransferase Inhibitors

Published on: August 5, 2022

Methyl-binding DNA capture Sequencing for Patient Tissues
08:40

Methyl-binding DNA capture Sequencing for Patient Tissues

Published on: October 31, 2016

Multiomics Analysis of TMEM200A as a Pan-Cancer Biomarker
07:47

Multiomics Analysis of TMEM200A as a Pan-Cancer Biomarker

Published on: September 15, 2023

Area of Science:

  • Genomic Medicine
  • Computational Pathology
  • Bioinformatics

Background:

  • DNA methylation profiling is crucial for tumor classification in pathology.
  • Dimensionality reduction techniques like UMAP and t-SNE are used to visualize sample relationships.
  • These visualization methods are sensitive to data preprocessing and parameter choices, impacting interpretation.

Purpose of the Study:

  • To provide key considerations for interpreting and reporting visualization and classification methods in methylation-based tumor studies.
  • To offer recommendations for standardized reporting to ensure scientific rigor.
  • To guide researchers in diagnostic settings for accurate interpretation of methylation data.

Main Methods:

  • Technical review of dimensionality reduction techniques (UMAP, t-SNE) in methylation studies.
  • Outline of reporting standards for preprocessing, parameters, and validation.
  • Development of an accompanying online notebook for exploring parameter effects on visualizations.

Main Results:

  • Visualization tools are not classification algorithms and their output is parameter-dependent.
  • Recommendations for transparent reporting of methods and parameters are crucial.
  • Pairing visualizations with quantitative analyses and independent validation enhances reliability.

Conclusions:

  • Standardized reporting and validation are essential for reproducible and rigorous methylation-based tumor classification.
  • Understanding the limitations and proper interpretation of visualization techniques is key for diagnostic applications.
  • This review promotes best practices for utilizing DNA methylation data in pathology research.