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 Experiment Videos

Search for a gene x environment interaction: G x E hunt.

J N Bailey1, M A Suchard, S L Smalley

  • 1Department of Psychiatry, University of California, Los Angeles, USA.

Genetic Epidemiology
|December 22, 1999
PubMed
Summary

This study introduces a novel method for identifying gene-environment interactions (G x Es). The approach successfully detected a significant G x E near specific gene loci using simulated data, advancing genetic research.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

The evolutionary history of hepaciviruses.

bioRxiv : the preprint server for biology·2023
Same author

Metagenomic sequencing at the epicenter of the Nigeria 2018 Lassa fever outbreak.

Science (New York, N.Y.)·2019
Same author

Genomic and epidemiological monitoring of yellow fever virus transmission potential.

Science (New York, N.Y.)·2018
Same author

A need to know.

The Physician and sportsmedicine·2016
Same author

Are General Practitioners Willing and Able to Provide Genetic Services for Common Diseases?

Journal of genetic counseling·2015
Same author

Prevalence and severity of anthelmintic resistance in ovine gastrointestinal nematodes in Australia (2009-2012).

Australian veterinary journal·2014

Area of Science:

  • Genetics
  • Bioinformatics
  • Statistical Genetics

Background:

  • Gene-environment interactions (G x Es) play a crucial role in complex diseases.
  • Identifying these interactions is challenging but essential for understanding disease etiology.

Purpose of the Study:

  • To develop and validate a new statistical method for detecting gene-environment interactions.
  • To apply this method to simulated data to assess its efficacy.

Main Methods:

  • Developed a novel method to identify gene-environment interactions (G x Es).
  • Utilized simulated data (GAW11, Problem 2) for method testing.
  • Stratified affected sibling pairs (ASPs) based on an environmental factor (E1).
  • Analyzed identity-by-descent (IBD) sharing rates on chromosomes 3 and 5 within stratified ASP groups.

Related Experiment Videos

Main Results:

  • Successfully identified an environmental factor (E1) associated with the simulated disorder.
  • Inferred the presence of a G x E near loci 3G44 and 3G45.
  • Observed significant differences in IBD sharing rates between stratified groups, indicating interaction.

Conclusions:

  • The developed method is effective in identifying gene-environment interactions using simulated data.
  • The findings highlight the importance of considering G x Es in genetic studies.
  • The method provides a promising approach for future genetic research.