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%...
Variability: Analysis01:11

Variability: Analysis

Measures of variability are statistical metrics that reveal the dispersion pattern within a dataset. They are pivotal in biostatistics, providing insights into the heterogeneity within health and biological data. Variability signifies the degree to which data points diverge from one another, helping researchers understand the potential range of values and associated uncertainty within the data.
The range is a simple measure of variability, indicating the difference between the highest and...
Statistical Analysis: Overview01:11

Statistical Analysis: Overview

When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
One of the most commonly used statistical quantifiers is the mean, which is the ratio between the sum of the numerical values of all results and the...
Calculating and Interpreting the Linear Correlation Coefficient01:11

Calculating and Interpreting the Linear Correlation Coefficient

The correlation coefficient, r, developed by Karl Pearson in the early 1900s, is numerical and provides a measure of strength and direction of the linear association between the independent variable, x, and the dependent variable, y. Hence, it is also known as the Pearson product-moment correlation coefficient. It can be calculated using the following equation:

You might also read

Related Articles

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

Sort by
Same author

Alveolar niche disruption and aberrant epithelial reprogramming are early hallmarks of idiopathic pulmonary fibrosis.

bioRxiv : the preprint server for biology·2026
Same author

CMIP as a novel candidate gene for neurodevelopmental and neuropsychiatric disorders.

European journal of human genetics : EJHG·2026
Same author

In vitro and in silico modelling of ROS1-positive non-small cell lung cancer reveals fusion-dependent tyrosine kinase inhibitor responses.

Molecular oncology·2026
Same author

An Adnp frameshift variant disrupts Wnt signalling inducing chromatocytoskeletal defects and autism-related behaviour in male mice.

EBioMedicine·2026
Same author

Polymorphic CGG repeats in gene regulation and disease.

American journal of human genetics·2026
Same author

Telomere Dysfunction and Proteostasis Decline Define Distinct Pathways of Cellular Senescence in the Human Respiratory Tract.

Aging cell·2026

Related Experiment Video

Updated: Jun 5, 2026

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo
08:32

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

Published on: May 4, 2018

CNV-WebStore: online CNV analysis, storage and interpretation.

Geert Vandeweyer1, Edwin Reyniers, Wim Wuyts

  • 1Department of Medical Genetics, University Hospital Antwerp, Antwerp, Belgium.

BMC Bioinformatics
|January 7, 2011
PubMed
Summary

CNV-WebStore is a new online platform for analyzing copy number variations (CNVs) from microarray data. It simplifies data interpretation for clinicians and lab technicians in daily practice.

More Related Videos

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

In Vivo Multimodal Imaging and Analysis of Mouse Laser-Induced Choroidal Neovascularization Model
09:56

In Vivo Multimodal Imaging and Analysis of Mouse Laser-Induced Choroidal Neovascularization Model

Published on: January 21, 2018

Related Experiment Videos

Last Updated: Jun 5, 2026

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo
08:32

Neurovascular Network Explorer 2.0: A Simple Tool for Exploring and Sharing a Database of Optogenetically-evoked Vasomotion in Mouse Cortex In Vivo

Published on: May 4, 2018

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information
09:37

Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

Published on: August 15, 2019

In Vivo Multimodal Imaging and Analysis of Mouse Laser-Induced Choroidal Neovascularization Model
09:56

In Vivo Multimodal Imaging and Analysis of Mouse Laser-Induced Choroidal Neovascularization Model

Published on: January 21, 2018

Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Microarray technology enables high-resolution genomic aberration analysis.
  • Functional interpretation of large genomic datasets is a significant bottleneck.
  • There is a need for centralized, user-friendly CNV data management and interpretation systems.

Purpose of the Study:

  • To present CNV-WebStore, an online platform for processing and interpreting microarray data.
  • To streamline the analysis of copy number variations (CNVs) in a clinical setting.
  • To facilitate the implementation of high-resolution array platforms.

Main Methods:

  • Developed CNV-WebStore, an integrated online platform.
  • Included tools for CNV analysis, parent of origin, and uniparental disomy detection.
  • Integrated data visualization, gene prioritization, automated literature searching, genome browser linking, and public database annotation.

Main Results:

  • CNV-WebStore processes and interprets microarray data for clinical applications.
  • The platform supports Illumina BeadArray and other microarray platforms.
  • Features include CNV analysis, parent of origin/uniparental disomy detection, and result reporting.

Conclusions:

  • CNV-WebStore provides an intuitive interface for copy number data presentation.
  • It serves as a valuable tool for both laboratory technicians and clinicians.
  • The platform enhances daily clinical practice by simplifying CNV data interpretation.