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

Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.8K
Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...
6.8K
Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

18.5K
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%...
18.5K
Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

14.4K
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...
14.4K
Tumor Progression02:07

Tumor Progression

7.1K
Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
7.1K

You might also read

Related Articles

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

Sort by
Same author

scProca: A Cross-Attention-Enhanced Deep Generative Model for Single-Cell Transcriptomics and Proteomics Integration and Imputation.

IEEE journal of biomedical and health informatics·2025
Same author

scVIC: deep generative modeling of heterogeneity for scRNA-seq data.

Bioinformatics advances·2024
Same author

RobustTree: An adaptive, robust PCA algorithm for embedded tree structure recovery from single-cell sequencing data.

Frontiers in genetics·2023
Same author

DeepDetect: Deep Learning of Peptide Detectability Enhanced by Peptide Digestibility and Its Application to DIA Library Reduction.

Analytical chemistry·2023
Same author

A repository for the publication and sharing of heterogeneous materials data.

Scientific data·2022
Same author

BiTSC 2: Bayesian inference of tumor clonal tree by joint analysis of single-cell SNV and CNA data.

Briefings in bioinformatics·2022
Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026
Same journal

SpaMFG: a Spatial Multi-omics Integration Method based on Feature Grouping.

Bioinformatics (Oxford, England)·2026
Same journal

CSCN: Inference of Cell-Specific Causal Networks Using Single-Cell RNA-Seq Data.

Bioinformatics (Oxford, England)·2026
Same journal

Sparse CCA-Based Mediation Analysis with High-Dimensional Exposures and Mediators.

Bioinformatics (Oxford, England)·2026
Same journal

Enhancing Cross-Context Generalization in Drug Perturbation Prediction with a Multimodal Conditional Diffusion Framework.

Bioinformatics (Oxford, England)·2026
Same journal

Primer Design through Submodular Function Estimation.

Bioinformatics (Oxford, England)·2026
See all related articles

Related Experiment Video

Updated: Dec 26, 2025

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.1K

RobustClone: a robust PCA method for tumor clone and evolution inference from single-cell sequencing data.

Ziwei Chen1,2, Fuzhou Gong1,2, Lin Wan1,2

  • 1NCMIS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.

Bioinformatics (Oxford, England)
|March 12, 2020
PubMed
Summary
This summary is machine-generated.

RobustClone accurately infers tumor clonal evolution from error-prone single-cell sequencing (SCS) data. This computational framework reconstructs subclonal genotypes and evolutionary trees for both single-cell single nucleotide variation (scSNV) and single-cell copy-number variation (scCNV) data.

More Related Videos

Microfluidics-based High-throughput Circulating Tumor Cell Sorting and Single-cell Sequencing Technology
09:45

Microfluidics-based High-throughput Circulating Tumor Cell Sorting and Single-cell Sequencing Technology

Published on: November 14, 2025

405
Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

19.8K

Related Experiment Videos

Last Updated: Dec 26, 2025

Comparative Lesions Analysis Through a Targeted Sequencing Approach
08:16

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

7.1K
Microfluidics-based High-throughput Circulating Tumor Cell Sorting and Single-cell Sequencing Technology
09:45

Microfluidics-based High-throughput Circulating Tumor Cell Sorting and Single-cell Sequencing Technology

Published on: November 14, 2025

405
Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing
11:02

Detecting Somatic Genetic Alterations in Tumor Specimens by Exon Capture and Massively Parallel Sequencing

Published on: October 18, 2013

19.8K

Area of Science:

  • Computational biology
  • Genomics
  • Cancer research

Background:

  • Single-cell sequencing (SCS) offers insights into tumor heterogeneity by characterizing clonal genotypes and phylogenetic relationships.
  • SCS data are often error-prone, posing significant challenges for computational analysis.

Purpose of the Study:

  • To develop an efficient computational framework for inferring tumor clonal evolution from error-prone SCS data.
  • To accurately recover subclonal genotypes and reconstruct evolutionary trees.

Main Methods:

  • Developed RobustClone, an efficient computational framework utilizing extended robust principal component analysis for low-rank matrix decomposition.
  • RobustClone is a model-free method applicable to single-cell single nucleotide variation (scSNV) and single-cell copy-number variation (scCNV) data.
  • The method is designed to be efficient and scalable for large datasets.

Main Results:

  • RobustClone outperforms state-of-the-art methods in accuracy and efficiency on large-scale simulated datasets.
  • Validated on scSNV and scCNV datasets, RobustClone accurately recovers genotype matrices and infers subclonal evolution trees.
  • Revealed spatial progression patterns of subclonal evolution in a large-scale breast cancer scCNV dataset.

Conclusions:

  • RobustClone provides an accurate and efficient solution for analyzing error-prone SCS data to understand tumor clonal evolution.
  • The framework's model-free nature and scalability make it broadly applicable to various SCS data types and sizes.
  • Demonstrated utility in uncovering complex evolutionary dynamics within tumors, including spatial progression.