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

Measuring gene-disease association using a general pair method

P J Ward1, C Bonaïti-Pellié

  • 1INSERM U351, Institut Gustave-Roussy, Villejuif, France.

Genetic Epidemiology
|January 1, 1995
PubMed
Summary
This summary is machine-generated.

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

Uncertainty and Bias in Global to Regional Scale Assessments of Current and Future Coastal Flood Risk.

Earth's future·2021
Same author

Flood risk assessments at different spatial scales.

Mitigation and adaptation strategies for global change·2018
Same author

Water scarcity hotspots travel downstream due to human interventions in the 20th and 21st century.

Nature communications·2017
Same author

The world's road to water scarcity: shortage and stress in the 20th century and pathways towards sustainability.

Scientific reports·2016
Same author

Training-Induced Functional Gains following SCI.

Neural plasticity·2016
Same author

Lost food, wasted resources: global food supply chain losses and their impacts on freshwater, cropland, and fertiliser use.

The Science of the total environment·2012
Same journal

Applying Bayesian Multivariable Mendelian Randomisation to Prioritise Candidate Causal Traits From High-Dimensional Data: Illustration From Estimation of the Effect of Maternal Metabolites on Offspring Birthweight.

Genetic epidemiology·2026
Same journal

Individualized Bayesian Inference Identifies Novel Genetic Variants for Parkinson's Disease.

Genetic epidemiology·2026
Same journal

DRIVE v3: Command Line Application for Identity-by-Descent Haplotype Clustering in Large Biobank Scale Data.

Genetic epidemiology·2026
Same journal

Deep Unsupervised Domain Adaptation for Translating Cancer Dependency Maps From Cell Lines to Breast Cancer Tumor Genomics.

Genetic epidemiology·2026
Same journal

Polygenic Risk Scores for Incident Dementia in the Multi-Ethnic Study of Atherosclerosis.

Genetic epidemiology·2026
Same journal

Outcome and Exposure Polygenic Risk Scores Can Help Reduce Information Bias and Selection Bias in Regression Estimates From Biobank Data.

Genetic epidemiology·2026
See all related articles

The general-pair-method (GPM) successfully identified genetic associations with disease status at specific chromosomal loci. This nonparametric method enhances statistical power by analyzing all individual pairs, regardless of genetic relatedness.

Area of Science:

  • Genetics
  • Statistical genetics
  • Bioinformatics

Background:

  • Identifying genetic loci associated with disease is crucial for understanding disease etiology.
  • Existing methods may have limitations in handling diverse genetic relatedness within study populations.

Purpose of the Study:

  • To apply the general-pair-method (GPM) to analyze the Problem 1 dataset for disease-associated chromosomal loci.
  • To leverage GPM's ability to incorporate all pairwise genetic relatedness for increased statistical power.

Main Methods:

  • Utilized the general-pair-method (GPM), a nonparametric, identity-by-state approach.
  • Analyzed pairwise contrasts across different pedigrees, including control groups, to maximize test statistic power.
  • Applied GPM within a candidate gene association study framework.

Related Experiment Videos

Main Results:

  • GPM successfully identified significant associations between disease status and locus 31 on chromosome 1.
  • GPM also identified a significant association between disease status and locus 23 on chromosome 5.
  • No significant associations were detected at other chromosomal loci, consistent with the null hypothesis.

Conclusions:

  • The general-pair-method is effective in detecting gene-disease associations, even with complex genetic relatedness.
  • The findings highlight specific chromosomal loci potentially involved in the studied disease.
  • Further investigation into the identified loci is warranted to elucidate their role in disease pathogenesis.