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

14.5K
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...
14.5K
Evolutionary Relationships through Genome Comparisons02:54

Evolutionary Relationships through Genome Comparisons

6.4K
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...
6.4K
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

339
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
339

You might also read

Related Articles

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

Sort by
Same author

An 11-gene blood transcriptomic signature reflects a sepsis-associated host-response pattern across public cohorts.

Frontiers in medicine·2026
Same author

A dish-to-biobank framework links β-cell nutrient-stress programs to genetic and dietary risk for Type 2 Diabetes.

bioRxiv : the preprint server for biology·2026
Same author

Low-Density Lipoprotein Cholesterol and Dementia Risk: Integrating Mendelian Randomization and Target Trial Emulation Within the Heart-Brain Axis.

medRxiv : the preprint server for health sciences·2026
Same author

Mitochondria-associated endoplasmic reticulum membrane (MAM): roles in innate immunity dysregulation.

Cell communication and signaling : CCS·2026
Same author

Cardiovascular Disease Subtypes and Alzheimer's Disease: Phenotypic and Genetic Associations in the UK Biobank and All of Us Research Program.

Journal of the American Heart Association·2026
Same author

Hypoxia-induced downregulation of cAMP drives Ganoderic acid biosynthesis and restricts biofilm development in Ganoderma lucidum.

Food research international (Ottawa, Ont.)·2026

Related Experiment Video

Updated: Oct 1, 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

3.9K

Gene-based association tests using GWAS summary statistics and incorporating eQTL.

Xuewei Cao1, Xuexia Wang2, Shuanglin Zhang1

  • 1Department of Mathematical Sciences, Michigan Technological University, Houghton, MI, 49931, USA.

Scientific Reports
|March 4, 2022
PubMed
Summary

Overall is a new gene-based association test that integrates multiple genetic variant tests and expression quantitative trait locus (eQTL) data. This powerful method improves the identification of genes associated with complex diseases using genome-wide association study (GWAS) summary statistics.

More Related Videos

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.1K
An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

23.0K

Related Experiment Videos

Last Updated: Oct 1, 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

3.9K
Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay EMSA and DNA-affinity Precipitation Assay DAPA

Published on: August 21, 2016

13.1K
An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations
10:17

An Allele-specific Gene Expression Assay to Test the Functional Basis of Genetic Associations

Published on: November 3, 2010

23.0K

Area of Science:

  • Genetics
  • Statistical Genetics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) explain limited heritability for complex diseases.
  • Gene-based analyses aggregate variants, and transcriptome-wide association studies (TWAS) link gene expression to traits.
  • Existing methods face challenges in fully capturing genetic contributions to complex diseases.

Purpose of the Study:

  • To develop a powerful and efficient gene-based association test called Overall.
  • To integrate multiple gene-based tests and expression quantitative trait locus (eQTL) data.
  • To improve the identification of genes associated with complex diseases using GWAS summary statistics.

Main Methods:

  • Developed the Overall gene-based association test using an extended Simes procedure.
  • Integrated three traditional gene-based association tests and eQTL information.
  • Utilized GWAS summary statistics for analysis.

Main Results:

  • Overall demonstrated excellent control of type I error rates in simulations.
  • Overall exhibited higher statistical power compared to existing methods.
  • Applied to schizophrenia and lipid GWAS datasets, Overall identified more significant trait-associated genes.

Conclusions:

  • Overall is a powerful and computationally efficient gene-based association test.
  • The method enhances the biological interpretability of identified trait-associated genes.
  • Overall improves gene discovery for complex diseases compared to existing approaches.