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 Experiment Video

Updated: May 13, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

Exploring Intratumor Heterogeneity in Cancer: A Comparative Evaluation of Clustering Methods.

Paulo Henrique Ribeiro1, Adenilso da Silva Simao2

  • 1Federal Institute of São Paulo, Barretos, Brazil.

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
|May 12, 2026
PubMed
Summary

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

Analysis of clonal evolution in cancer: A computational perspective.

Journal of bioinformatics and computational biology·2025
Same author

Exploring the Influence of Gene Networks on Driver Gene Classification.

Journal of computational biology : a journal of computational molecular cell biology·2025
See all related articles

Mean-Shift and Affinity Propagation (AP) effectively analyze cancer's intratumor heterogeneity (ITH) using variant allele frequency (VAF) mutation data. These methods offer reliable clustering for ITH exploration, outperforming others in validation metrics.

Area of Science:

  • Genomics
  • Computational Biology
  • Cancer Research

Background:

  • Intratumor heterogeneity (ITH) significantly influences cancer progression and treatment response.
  • Characterizing ITH is essential for understanding tumor evolution and developing targeted therapies.
  • Variant allele frequency (VAF) of mutations provides a valuable metric for exploring ITH.

Purpose of the Study:

  • To comparatively evaluate the performance of six clustering algorithms for characterizing ITH based on mutation VAFs.
  • To identify the most effective clustering methods for exploratory ITH analysis.
  • To provide a computational resource for future ITH studies.

Main Methods:

  • Utilized The Cancer Genome Atlas (TCGA) data from three cancer types.
  • Applied six clustering algorithms: DBSCAN, Variational Bayesian Gaussian Mixture Model, HDBSCAN, OPTICS, Affinity Propagation (AP), and Mean-Shift.
Keywords:
cancer genomicsclustering algorithmsgenetic mutationsintratumor heterogeneity

More Related Videos

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
07:54

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Published on: October 25, 2011

Related Experiment Videos

Last Updated: May 13, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
07:54

Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence

Published on: October 25, 2011

  • Evaluated clustering results using cluster distribution analysis and four internal validation metrics.

    • Main Results:

    • DBSCAN and Variational Bayesian Gaussian Mixture Model showed limitations in cluster identification.
    • HDBSCAN and OPTICS displayed high variability in cluster numbers.
    • Mean-Shift and AP demonstrated consistent performance and superior validation metric scores.
    • Mean-Shift and AP proved more reliable and consistent than HDBSCAN and OPTICS.

    Conclusions:

    • Mean-Shift and Affinity Propagation (AP) are promising, accessible methods for initial ITH exploratory analysis using VAF data.
    • These algorithms offer robust and consistent clustering for characterizing intratumor heterogeneity.
    • A Google Colab computational pipeline is available to support future research in ITH analysis.