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

14.6K
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...
14.6K
Genomics02:02

Genomics

37.8K
Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
37.8K

You might also read

Related Articles

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

Sort by
Same author

How can biological databases support the new UN mechanism for benefit-sharing from digital sequence information?

Scientific data·2026
Same author

Correction: AgroLD: a knowledge graph for the plant sciences.

BMC genomic data·2026
Same author

Navigating Fusarium wilt of bananas: a ready-to-use subset of resistant <i>Musa</i> genotypes.

Frontiers in plant science·2026
Same author

Going wild in banana breeding enables Fusarium-resistant hybrids with improved fruit quality.

Nature communications·2026
Same author

Haplotype-resolved genome assembly of Musella lasiocarpa reveals the critical role of structural variations in chromosomal and genome evolution.

Genomics·2026
Same author

Major differences in the dynamics of haematological and biochemical variables between trypanotolerant and susceptible cattle during Trypanosoma congolense infection.

BMC veterinary research·2025
Same journal

Mapping the 3D Chromosome Organization of a Biosynthetic Gene Cluster by Capture Hi-C (CHi-C).

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Mapping the 3D Chromosome Organization of Streptomyces by Hi-C.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

CUT&Tag Epigenomic Profiling of Biosynthetic Gene Clusters in Arabidopsis thaliana.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Rhizobium rhizogenes-Mediated Hairy Root Transformation Protocol for Lotus japonicus and Other Legumes.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Characterization of Bioactive Saponins from Sea Cucumbers.

Methods in molecular biology (Clifton, N.J.)·2026
Same journal

Methods for Functional Validation of Terpenoid Metabolic Clusters in Nicotiana benthamiana and Aspergillus oryzae.

Methods in molecular biology (Clifton, N.J.)·2026
See all related articles

Related Experiment Video

Updated: Oct 6, 2025

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

39.3K

Managing High-Density Genotyping Data with Gigwa.

Guilhem Sempéré1,2,3, Pierre Larmande4,5, Mathieu Rouard3,6

  • 1CIRAD, UMR INTERTRYP, Montpellier, France.

Methods in Molecular Biology (Clifton, N.J.)
|January 17, 2022
PubMed
Summary
This summary is machine-generated.

Managing large genomic variation data from high-density genotyping is challenging. This guide introduces Gigwa, a scalable application for efficiently handling millions of single nucleotide polymorphism (SNP) markers from next-generation sequencing data.

Keywords:
INDELsInteroperabilityNoSQL databaseSNP markersVCFWeb tool

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.3K
Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
09:30

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform

Published on: August 17, 2022

3.2K

Related Experiment Videos

Last Updated: Oct 6, 2025

Infinium Assay for Large-scale SNP Genotyping Applications
13:33

Infinium Assay for Large-scale SNP Genotyping Applications

Published on: November 19, 2013

39.3K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.3K
Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
09:30

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform

Published on: August 17, 2022

3.2K

Area of Science:

  • Genomics
  • Bioinformatics

Background:

  • Next-generation sequencing (NGS) technologies facilitate high-density genotyping across numerous samples.
  • SNP calling pipelines generate millions of genetic markers requiring rigorous filtering for diverse analyses.
  • Managing and handling large genomic variation datasets presents a significant computational challenge for many applications.

Purpose of the Study:

  • To provide a practical guide for efficient management of large genomic variation data.
  • To introduce Gigwa as a user-friendly, scalable, and versatile application for genomic data handling.

Main Methods:

  • Utilizing Gigwa for the management of large-scale genotyping files.
  • Demonstrating the application's deployment on web servers and local machines.

Main Results:

  • Gigwa enables efficient handling of millions of single nucleotide polymorphism (SNP) markers.
  • The application offers a scalable and versatile solution for genomic data management.

Conclusions:

  • Gigwa provides an effective solution for managing the increasing volume of genomic variation data generated by high-density genotyping.
  • The application's flexibility in deployment makes it accessible for various research settings.