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

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

12.9K
Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
12.9K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.9K
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...
5.9K

You might also read

Related Articles

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

Sort by
Same author

Comparing Pulmonary Telerehabilitation and Center-Based Pulmonary Rehabilitation for Effectiveness and Adherence in Chronic Obstructive Pulmonary Disease: Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Journal of medical Internet research·2026
Same author

The timing of the commencement of pulmonary rehabilitation in hospitalized patients with acute exacerbation of COPD: a systematic review and network meta-analysis.

BMC medicine·2026
Same author

A systematic characterization of fibroblast subtypes and heterogeneity.

iScience·2025
Same author

A novel stability analysis method of switched systems with unstable modes based on PDT switching sequence list.

ISA transactions·2025
Same author

SeekPCMdb: knowledge on disease-associated protein-coding mutations.

Nucleic acids research·2025
Same author

WebCMap: an R package for high-throughput connectivity analysis within the CMap framework.

Bioinformatics advances·2025

Related Experiment Video

Updated: May 7, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
05:01

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

4.7K

Network.assisted analysis to prioritize GWAS results: principles, methods and perspectives.

Peilin Jia, Zhongming Zhao

    Human Genetics
    |October 15, 2013
    PubMed
    Summary

    Network-assisted analysis (NAA) enhances genome-wide association studies (GWAS) by analyzing gene networks. This approach improves the interpretation and prioritization of genes and markers for complex diseases.

    More Related Videos

    Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
    08:27

    Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

    Published on: July 27, 2021

    4.6K
    Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
    04:41

    Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

    Published on: January 9, 2020

    20.2K

    Related Experiment Videos

    Last Updated: May 7, 2026

    A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information
    05:01

    A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

    Published on: July 1, 2020

    4.7K
    Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization
    08:27

    Large-Scale Multi-Omics Genome-Wide Association Studies Mo-GWAS: Guidelines for Sample Preparation and Normalization

    Published on: July 27, 2021

    4.6K
    Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
    04:41

    Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

    Published on: January 9, 2020

    20.2K

    Area of Science:

    • Genetics
    • Bioinformatics
    • Systems Biology

    Background:

    • Genome-wide association studies (GWAS) are crucial for identifying genetic variants associated with complex diseases.
    • Traditional single marker-based tests in GWAS have identified numerous disease-associated single nucleotide polymorphisms (SNPs).
    • Network-assisted analysis (NAA) is an emerging field that applies network-related approaches to GWAS data for advanced analysis.

    Purpose of the Study:

    • To review methodologies and strategies for NAA of GWAS data.
    • To highlight how NAA can enhance the interpretation and prioritization of candidate genes and markers.
    • To discuss applications, options, and potential caveats of NAA in various disease studies.

    Main Methods:

    • Review of existing literature on NAA methodologies for GWAS data.
    • Discussion of approaches that identify subnetworks and assess combined gene effects.
    • Exploration of methods prioritizing genes based on network interconnections.

    Main Results:

    • NAA offers advantages over traditional methods by defining subnetworks guided by GWAS data, without pre-defined pathways.
    • NAA can enhance the interpretation and prioritization of candidate genes and markers identified through GWAS.
    • NAA has demonstrated utility in studying various human diseases and traits.

    Conclusions:

    • NAA is a valuable approach for advanced analysis of GWAS data, improving biological insights.
    • The flexibility of NAA in defining subnetworks offers a powerful tool for genetic research.
    • Further exploration of NAA methodologies and applications holds significant promise for understanding complex diseases.