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

Random effects model for meta-analysis of multiple quantitative sibpair linkage studies

Z Li1, D C Rao

  • 1Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA.

Genetic Epidemiology
|January 1, 1996
PubMed
Summary

This study introduces a random effects model to combine results from quantitative trait linkage studies. This method helps assess overall genetic linkage evidence and study heterogeneity.

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

Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels.

Nature communications·2016
Same author

A Genome-wide study of blood pressure in African Americans accounting for gene-smoking interaction.

Scientific reports·2016
Same author

The effects of exercise on the lipoprotein subclass profile: A meta-analysis of 10 interventions.

Atherosclerosis·2015
Same author

Genomic and transcriptomic predictors of triglyceride response to regular exercise.

British journal of sports medicine·2015
Same author

Genome-wide association studies suggest sex-specific loci associated with abdominal and visceral fat.

International journal of obesity (2005)·2015
Same author

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

PLoS genetics·2015

Area of Science:

  • Genetics
  • Biostatistics
  • Complex Trait Analysis

Background:

  • Increasing interest in genetic effects for complex traits necessitates robust linkage analysis.
  • Replication studies in genetic linkage often yield conflicting results, highlighting the need for meta-analysis.
  • Existing methods may not adequately address heterogeneity in quantitative trait linkage studies.

Purpose of the Study:

  • To propose a novel random effects model for meta-analysis of quantitative sibpair linkage studies.
  • To provide a method for assessing aggregate evidence for genetic linkage across independent studies.
  • To evaluate heterogeneity among results from multiple quantitative trait linkage studies.

Main Methods:

  • Development of a random effects model tailored for quantitative sibpair linkage data.

Related Experiment Videos

  • Application of the model to combine regression coefficients from the Haseman and Elston sibpair method.
  • Statistical assessment of heterogeneity between independent linkage studies.

    • Main Results:

    • The proposed random effects model effectively combines results from independent sibpair linkage studies.
    • The model allows for robust assessment of overall evidence for genetic linkage.
    • It also provides a quantitative measure of heterogeneity across studies.

    Conclusions:

    • Random effects meta-analysis offers a rigorous approach to synthesizing evidence from quantitative trait linkage studies.
    • The proposed model enhances the reliability of genetic linkage detection for complex traits.
    • This method is valuable for resolving discrepancies and assessing consistency in replication studies.