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

Epistasis Analysis01:09

Epistasis Analysis

5.5K
Although Mendel chose seven unrelated traits in peas to study gene segregation, most traits involve multiple gene interactions that create a spectrum of phenotypes. When the interaction of various genes or alleles at different locations influences a phenotype, this is called epistasis. Epistasis often involves one gene masking or interfering with the expression of another (antagonistic epistasis). Epistasis often occurs when different genes are part of the same biochemical pathway. The...
5.5K
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
Epistasis01:39

Epistasis

49.1K
In addition to multiple alleles at the same locus influencing traits, numerous genes or alleles at different locations may interact and influence phenotypes in a phenomenon called epistasis. For example, rabbit fur can be black or brown depending on whether the animal is homozygous dominant or heterozygous at a TYRP1 locus. However, if the rabbit is also homozygous recessive at a locus on the tyrosinase gene (TYR), it will have an unshaded coat that appears white, regardless of its TYRP1...
49.1K
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
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

17.5K
A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
17.5K

You might also read

Related Articles

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

Sort by
Same author

Statistical knockoffs improve biomarker discovery from transcriptomic data.

Briefings in bioinformatics·2026
Same author

The Human Pleiotropic Map of GWAS Associations and Therapeutic Implications.

bioRxiv : the preprint server for biology·2026
Same author

Genetic liability to psoriasis predicts severe disease outcomes.

Genome medicine·2025
Same author

Multimodal BEHRT: transformers for multimodal electronic health records to predict breast cancer prognosis.

Frontiers in oncology·2025
Same author

Sparse multitask group Lasso for genome-wide association studies.

PLoS computational biology·2025
Same author

Assessing Random Forest self-reproducibility for optimal short biomarker signature discovery.

Briefings in bioinformatics·2025

Related Experiment Video

Updated: Nov 28, 2025

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

13.3K

Novel methods for epistasis detection in genome-wide association studies.

Lotfi Slim1,2, Clément Chatelain2, Chloé-Agathe Azencott1,3

  • 1CBIO-Centre for Computational Biology, Mines ParisTech, Paris, France.

Plos One
|November 30, 2020
PubMed
Summary

We introduce epiGWAS, a novel method for detecting gene-gene interactions to explain missing heritability in common diseases. This approach efficiently identifies interactions between a target SNP and the genome, outperforming traditional 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
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

Related Experiment Videos

Last Updated: Nov 28, 2025

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

13.3K
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
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

Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Genome-wide association studies (GWAS) aim to identify genetic variants underlying common diseases.
  • A significant portion of heritability for common diseases remains unexplained by identified loci.
  • Epistasis (gene-gene interaction) is a leading hypothesis for this 'missing heritability'.

Purpose of the Study:

  • To develop and validate epiGWAS, a new computational approach for detecting epistasis.
  • To identify interactions between a single nucleotide polymorphism (SNP) and the broader genome, moving beyond pairwise testing.

Main Methods:

  • Developed epiGWAS, a novel statistical framework inspired by causal inference from randomized clinical trials.
  • Incorporated linkage disequilibrium considerations into the epistasis detection model.
  • Compared epiGWAS performance against existing state-of-the-art epistasis detection techniques.

Main Results:

  • EpiGWAS demonstrated superior performance in identifying pairwise interactions compared to classical methods.
  • Evaluations on both simulated and real genetic datasets confirmed the efficacy of the proposed approach.
  • The method successfully identified significant gene-gene interactions, contributing to understanding disease genetics.

Conclusions:

  • EpiGWAS offers a powerful and efficient method for detecting epistasis, addressing the challenge of missing heritability.
  • The approach provides a valuable tool for uncovering complex genetic architectures of common diseases.
  • This work highlights the importance of considering gene-gene interactions in genetic studies.