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

15.0K
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...
15.0K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.7K
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...
6.7K
Genetic Screens02:46

Genetic Screens

5.4K
Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing  genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...
5.4K

You might also read

Related Articles

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

Sort by
Same author

Laparoscopic <i>versus</i> open liver resection following transarterial radioembolization for hepatocellular carcinoma: a retrospective propensity score-matched study.

Annals of surgical treatment and research·2026
Same author

Protocol to purify human and mouse cytokines using an endotoxin-free Escherichia coli-based platform.

STAR protocols·2026
Same author

Hepatic Congestion-linked Intrahepatic Biliary Strictures After Living Donor Liver Transplantation.

Transplantation·2026
Same author

MOCDT: multi-cancer detection and tissue-of-origin classification via cfDNA multi-modal integration.

Bioinformatics (Oxford, England)·2026
Same author

Anatomical risk stratification for major portal vein complications in dual portal vein living donor liver transplantation: a retrospective cohort study.

Annals of surgical treatment and research·2026
Same author

Genetic Causes and Ankle Instability in Hypermobile Ehlers-Danlos Syndrome (hEDS): An Integrated Analysis Using Whole-Exome Sequencing and Stress Imaging.

Journal of clinical medicine·2026

Related Experiment Video

Updated: Nov 30, 2025

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

10.4K

GMStool: GWAS-based marker selection tool for genomic prediction from genomic data.

Seongmun Jeong1, Jae-Yoon Kim1,2, Namshin Kim3,4

  • 1Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, 34141, Republic of Korea.

Scientific Reports
|November 13, 2020
PubMed
Summary

GMStool enhances genomic prediction by selecting optimal single nucleotide polymorphism markers. This new tool improves quantitative phenotype prediction accuracy compared to existing methods.

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
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

3.6K

Related Experiment Videos

Last Updated: Nov 30, 2025

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

10.4K
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
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

3.6K

Area of Science:

  • Genomics
  • Bioinformatics
  • Computational Biology

Background:

  • Genomic data accessibility enables phenotype prediction.
  • Genomic prediction uses single nucleotide polymorphism (SNP) markers.
  • Marker selection is crucial for prediction accuracy.

Purpose of the Study:

  • Introduce GMStool for optimal marker selection and phenotype prediction.
  • Improve accuracy in quantitative phenotype prediction.

Main Methods:

  • Genome-wide association study (GWAS) based heuristic search.
  • Statistical and machine/deep-learning models for prediction.
  • Evaluation on real datasets with four phenotypes.

Main Results:

  • GMStool identified optimal marker sets.
  • Achieved higher prediction performance than using all or GWAS-top markers.
  • Demonstrated improved accuracy for quantitative phenotypes.

Conclusions:

  • GMStool offers a novel approach for marker selection in genomic prediction.
  • Expected to advance quantitative phenotype prediction studies.
  • Tool is available in R on GitHub.