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

Comparing Copy Number Variations and SNPs02:26

Comparing Copy Number Variations and SNPs

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%...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Genome Copying Errors02:46

Genome Copying Errors

DNA replication is a well-evolved process that copies millions of base pairs with high fidelity during each cell division. Occasionally a wrong base or a long stretch of wrong bases may get added to the daughter strands. If the errors are left unchecked, cells might accumulate several mutations that might endanger their  survival. Therefore, the copying errors are checked and repaired at three levels.

You might also read

Related Articles

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

Sort by
Same author

Simultaneous Immunofluorescence-Based In Situ mRNA Expression and Protein Detection in Bone Marrow Biopsy Samples.

Bio-protocol·2026
Same author

Robust causal gene network estimation for large-scale single-cell perturbation screens using reduced control function.

bioRxiv : the preprint server for biology·2026
Same author

Development of an automated, imaging-based preoperative screening model for early identification of malnutrition in an abdominal surgery cohort.

medRxiv : the preprint server for health sciences·2026
Same author

Factors Associated with Adherence to Recommended Colorectal Surveillance Intervals in Lynch Syndrome.

Cancers·2026
Same author

Rejoinder to the discussion on "INTACT: A method for integration of longitudinal physical activity data from multiple sources".

Biometrics·2026
Same author

INTACT: a method for integration of longitudinal physical activity data from multiple sources.

Biometrics·2026
Same journal

Instrumental Variable Estimation of Marginal Structural Mean Models for Time-Varying Treatment.

Journal of the American Statistical Association·2026
Same journal

Semiparametric Joint Modeling for Survival Analysis with Longitudinal Covariates.

Journal of the American Statistical Association·2026
Same journal

Dimension Reduction for Large-Scale Federated Data: Statistical Rate and Asymptotic Inference.

Journal of the American Statistical Association·2026
Same journal

Facilitating Heterogeneous Effect Estimation via Statistically Efficient Categorical Modifiers.

Journal of the American Statistical Association·2026
Same journal

Nonparametric Density Estimation of a Long-Term Trend from Repeated Semicontinuous Data.

Journal of the American Statistical Association·2026
Same journal

Functional Integrative Bayesian Analysis of High-dimensional Multiplatform Clinicogenomic Data.

Journal of the American Statistical Association·2026
See all related articles

Related Experiment Video

Updated: May 12, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Optimal Sparse Segment Identification with Application in Copy Number Variation Analysis.

X Jessie Jeng1, T Tony Cai, Hongzhe Li

  • 1postdoctoral fellow in the Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA 19104.

Journal of the American Statistical Association
|April 2, 2013
PubMed
Summary
This summary is machine-generated.

This study introduces a new method for detecting short DNA segments in noisy data, improving upon existing techniques. The likelihood ratio selection (LRS) procedure reliably identifies segments, enhancing copy number variation analysis.

Keywords:
DNA copy numberLikelihood ratio selectionmultiple testingsignal detection

More Related Videos

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
09:16

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Published on: February 21, 2015

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

Related Experiment Videos

Last Updated: May 12, 2026

Detection of Copy Number Alterations Using Single Cell Sequencing
09:45

Detection of Copy Number Alterations Using Single Cell Sequencing

Published on: February 17, 2017

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants
09:16

Array Comparative Genomic Hybridization (Array CGH) for Detection of Genomic Copy Number Variants

Published on: February 21, 2015

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

Area of Science:

  • Genomics
  • Statistical Signal Processing
  • Bioinformatics

Background:

  • DNA copy number variation (CNV) analysis is crucial for understanding genetic disorders.
  • High-density single nucleotide polymorphism (SNP) data presents challenges due to noise and unknown segment characteristics.
  • Accurate detection of sparse, short segments is essential for reliable CNV identification.

Purpose of the Study:

  • To develop a statistical method for detecting and identifying sparse, short segments in noisy one-dimensional data.
  • To characterize the statistically identifiable regions for segment detection.
  • To introduce an efficient likelihood ratio selection (LRS) procedure for segment identification.

Main Methods:

  • Statistical characterization of segment identifiability in the presence of Gaussian white noise.
  • Development of an efficient likelihood ratio selection (LRS) procedure.
  • Asymptotic optimality analysis of the LRS method.

Main Results:

  • The LRS procedure reliably separates signal segments from noise within identifiable regions.
  • Simulations and real data analysis demonstrate the effectiveness of the LRS method.
  • The LRS procedure shows improved power for detecting true segments compared to standard methods.

Conclusions:

  • The proposed LRS procedure offers a statistically sound and efficient approach for segment detection in noisy data.
  • This method significantly enhances the identification of DNA copy number variations from SNP data.
  • The LRS procedure provides a powerful tool for genomic data analysis and signal processing.