Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

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...

You might also read

Related Articles

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

Sort by

Same author

Carbon peaking pathways for topographic-constrained megacities: multi-scenario simulations and regional comparisons based on Chongqing.

Scientific reports·2026

Same author

Atacformer: A transformer-based foundation model for analysis and interpretation of ATAC-seq data.

bioRxiv : the preprint server for biology·2025

Same author

Taming the reference genome jungle: the refget sequence collection standard.

bioRxiv : the preprint server for biology·2025

Same author

ConceptDrift: leveraging spatial, temporal and semantic evolution of biomedical concepts for hypothesis generation.

Bioinformatics (Oxford, England)·2025

Same author

Bioconductor's Computational Ecosystem for Genomic Data Science in Cancer.

Methods in molecular biology (Clifton, N.J.)·2025

Same author

AI-readiness Criteria for Biomedical Data.

bioRxiv : the preprint server for biology·2024

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

Search research articles

Related Experiment Video

Updated: Nov 24, 2025

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

IGD: high-performance search for large-scale genomic interval datasets.

Jianglin Feng¹, Nathan C Sheffield^1,2,3,4

¹Center for Public Health Genomics, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA.

Bioinformatics (Oxford, England)

|December 28, 2020

Summary

This summary is machine-generated.

We developed the integrated genome database (IGD) to efficiently search large genomic interval datasets. This tool significantly speeds up analysis and reduces memory usage for billions of genomic regions.

More Related Videos

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Published on: August 5, 2008

Related Experiment Videos

Last Updated: Nov 24, 2025

Infinium Assay for Large-scale SNP Genotyping Applications

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER

Published on: June 23, 2012

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Technical Demonstration of Whole Genome Array Comparative Genomic Hybridization

Published on: August 5, 2008

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Large-scale genome projects generate vast amounts of genomic interval data.
Analyzing and integrating these large datasets presents significant computational challenges.
Current methods struggle to efficiently handle the scale of modern genomic data.

Purpose of the Study:

To introduce a novel method and tool, the integrated genome database (IGD).
To overcome limitations in examining and integrating large-scale genomic interval datasets.
To enable faster and more memory-efficient analysis of genomic regions.

Main Methods:

Development of the integrated genome database (IGD).
Implementation of a novel linear binning method.
Creation of a tool for searching genome interval datasets.

Main Results:

Achieved search speeds over three orders of magnitude faster than existing approaches.
Reduced memory usage to one hundredth of conventional methods.
Enabled scalable analysis of billions of genomic regions.

Conclusions:

The integrated genome database (IGD) offers a significant advancement in genomic data analysis.
IGD provides a highly efficient solution for handling large-scale genomic interval datasets.
This method facilitates deeper understanding of DNA function through improved data integration and analysis.