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

12.0K
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...
12.0K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

5.6K
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...
5.6K
Gene Evolution - Fast or Slow?02:05

Gene Evolution - Fast or Slow?

7.0K
The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
In contrast, regions which code...
7.0K

You might also read

Related Articles

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

Sort by
Same author

The potential acute and chronic toxicity of cyfluthrin on the soil model organism, Eisenia fetida.

Ecotoxicology and environmental safety·2017
Same author

Ameliorative effect of vitamin E on hepatic oxidative stress and hypoimmunity induced by high-fat diet in turbot (Scophthalmus maximus).

Fish & shellfish immunology·2017
Same author

Percutaneous Vascular Interventions Versus Bypass Surgeries in Patients With Critical Limb Ischemia: A Comprehensive Meta-analysis.

Annals of surgery·2017
Same author

Silymarin protects against renal injury through normalization of lipid metabolism and mitochondrial biogenesis in high fat-fed mice.

Free radical biology & medicine·2017
Same author

Effect of complications on oncologic outcomes after pancreaticoduodenectomy for pancreatic cancer.

The Journal of surgical research·2017
Same author

Effect of crowding stress on the immune response in turbot (Scophthalmus maximus) vaccinated with attenuated Edwardsiella tarda.

Fish & shellfish immunology·2017
Same journal

Editorial: Technologies for RNA Detection.

Bio-protocol·2026
Same journal

One-Step Affinity Purification of MarathonRT Reverse Transcriptase for RNA Sequencing Applications.

Bio-protocol·2026
Same journal

Enhanced RNA-Seq Expression Profiling and Functional Enrichment in Non-model Organisms Using Custom Annotations.

Bio-protocol·2026
Same journal

Using Combined Fluorescent In Situ Hybridization With Immunohistochemistry to Co-localize mRNA in Diverse Neuronal Cell Types.

Bio-protocol·2026
Same journal

Stepwise Protocol for Alternative Splicing Analysis in Single-Cell SMART-Seq2 RNA-Seq Data.

Bio-protocol·2026
Same journal

Enriching Bacteria-Specific RNA From Host Samples Before NGS With Transcript-Capture.

Bio-protocol·2026
See all related articles

Related Experiment Video

Updated: May 10, 2025

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

3.5K

GWAS Procedures for Gene Mapping in Diverse Populations With Complex Structures.

Zhen Zuo1, Mingliang Li1, Defu Liu2

  • 1Electrical and Information Engineering College, Jilin Agricultural Science and Technology University, Jilin, Jilin, China.

Bio-Protocol
|April 28, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a streamlined protocol for genome-wide association studies (GWAS) using minimal software tools. The protocol enhances efficiency in analyzing complex population structures for gene mapping.

Keywords:
Candidate geneComplex traitFalse discoveryPrincipal componentStatistical power

More Related Videos

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

18.9K
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

10.1K

Related Experiment Videos

Last Updated: May 10, 2025

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

3.5K
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

18.9K
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

10.1K

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) are crucial for gene mapping but face challenges in diverse populations with complex genetic structures.
  • Increasing marker density and population size necessitate advanced statistical models and efficient computational tools for GWAS.
  • Existing GWAS tools offer varied statistical power, computational efficiency, and user accessibility, with some models linked to dedicated software.

Purpose of the Study:

  • To develop an efficient and accessible protocol for performing genome-wide association studies (GWAS).
  • To integrate a minimal set of software tools for comprehensive GWAS analysis, including data preprocessing and interpretation.
  • To highlight advancements in GWAS model development and application.

Main Methods:

  • Developed a protocol using BEAGLE for genotype imputation, BLINK for GWAS analysis, and GAPIT for integrated analysis and interpretation.
  • Implemented file format conversion and missing genotype imputation as key preprocessing steps.
  • Reanalyzed data from the Rice 3000 Genomes Project to validate the protocol's effectiveness.

Main Results:

  • The protocol successfully integrated file format conversion, missing genotype imputation, and GWAS analysis using a minimal software set.
  • Demonstrated the protocol's utility by reanalyzing the Rice 3000 Genomes Project data.
  • Highlighted the protocol's ability to facilitate interpretation of input data and outcome results.

Conclusions:

  • The developed protocol offers an efficient and user-friendly approach to conducting GWAS, particularly in complex populations.
  • The integration of BEAGLE, BLINK, and GAPIT provides a robust framework for advancing GWAS model development and application.
  • This protocol can aid researchers in overcoming computational and statistical challenges in modern genetic association studies.