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

Cancer Survival Analysis01:21

Cancer Survival Analysis

856
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
856
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

19.4K
Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
Copy number variations or CNVs are the structural variations that cover more than 1kb of DNA sequence. The single nucleotide polymorphism (SNP), on the other hand, is a single nucleotide change or a point mutation that is found in more than 1%...
19.4K

You might also read

Related Articles

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

Sort by
Same author

A survey on 3D object detection in real time for autonomous driving.

Frontiers in robotics and AI·2024
Same author

Applying machine learning to predict viral assembly for adeno-associated virus capsid libraries.

Molecular therapy. Methods & clinical development·2021
Same author

An artificial delay based robust guidance strategy for an interceptor with input saturation.

ISA transactions·2020
Same author

Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. II: Multivariate spike and slab priors for marker effects and derivation of approximate Bayes and fractional Bayes factors for the complete family of models.

Journal of theoretical biology·2017
Same author

Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. I: Multivariate Gaussian priors for marker effects and derivation of the joint probability mass function of genotypes.

Journal of theoretical biology·2017
Same author

Learning Precise Spike Train-to-Spike Train Transformations in Multilayer Feedforward Neuronal Networks.

Neural computation·2016

Related Experiment Video

Updated: Apr 18, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.4K

Bayclone: Bayesian nonparametric inference of tumor subclones using NGS data.

Subhajit Sengupta1, Jin Wang, Juhee Lee

  • 1Center for Biomedical Research Informatics, NorthShore University HealthSystem, USA.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|January 17, 2015
PubMed
Summary

This study introduces a new Bayesian model, the categorical Indian buffet process (cIBP), to analyze tumor heterogeneity (TH) from next-generation sequencing (NGS) data, improving subclone identification.

More Related Videos

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
15:07

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

27.4K
Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
13:24

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

12.4K

Related Experiment Videos

Last Updated: Apr 18, 2026

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.4K
VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma
15:07

VDJ-Seq: Deep Sequencing Analysis of Rearranged Immunoglobulin Heavy Chain Gene to Reveal Clonal Evolution Patterns of B Cell Lymphoma

Published on: December 28, 2015

27.4K
Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
13:24

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

Published on: April 11, 2016

12.4K

Area of Science:

  • Genomics
  • Computational Biology
  • Cancer Research

Background:

  • Tumor heterogeneity (TH) is a key challenge in cancer research, impacting treatment response and disease progression.
  • Accurate characterization of subclones and their evolutionary relationships is crucial for understanding cancer development.
  • Existing models often struggle to capture the complex clonal architecture and overlapping mutations within tumors.

Purpose of the Study:

  • To develop a novel feature allocation model for describing tumor heterogeneity using next-generation sequencing (NGS) data.
  • To extend the Indian buffet process (IBP) using a Bayesian approach to create a categorical IBP (cIBP) for subclone analysis.
  • To provide a more biologically realistic model that allows for overlapping mutations shared across subclones.

Main Methods:

  • Developed a Bayesian nonparametric model, the categorical Indian buffet process (cIBP), extending the Indian buffet process (IBP).
  • Defined subclones as vectors of categorical values representing genotypes at single nucleotide variations (SNVs).
  • Employed a feature allocation approach, allowing somatic mutations to be shared across subclones, reflecting phylogenetic clonal expansion.

Main Results:

  • The cIBP model successfully infers the number, genotypes, and proportions of subclones from NGS data.
  • Bayesian inference provides posterior probabilities, enabling estimation of subclone characteristics and their variability.
  • The model was validated on both simulated and real tumor sequencing data, demonstrating its efficacy.

Conclusions:

  • The proposed cIBP model offers a powerful and flexible framework for dissecting tumor heterogeneity.
  • This feature allocation approach provides a more accurate representation of clonal evolution compared to traditional clustering methods.
  • The BayClone software implementation facilitates the application of this novel method in cancer genomics research.