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

Association and linkage with quantitative traits

T M King1, D Zhu, C I Amos

  • 1Department of Epidemiology, University of Texas M.D. Anderson Cancer Center, Houston 77030, USA.

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

Genetic variants in the folate metabolic pathway genes predict cutaneous melanoma-specific survival.

The British journal of dermatology·2020
Same author

Innovations in risk-stratification and treatment of Veterans with oropharynx cancer; roadmap of the 2019 Field Based Meeting.

Oral oncology·2019
Same author

Genome-wide association study across European and African American ancestries identifies a SNP in DNMT3B contributing to nicotine dependence.

Molecular psychiatry·2017
Same author

Genome-wide meta-analysis reveals common splice site acceptor variant in CHRNA4 associated with nicotine dependence.

Translational psychiatry·2015
Same author

Genome-wide association study identifies HLA 8.1 ancestral haplotype alleles as major genetic risk factors for myositis phenotypes.

Genes and immunity·2015
Same author

Photoemission from diamond films and substrates into water: dynamics of solvated electrons and implications for diamond photoelectrochemistry.

Faraday discussions·2014
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

This study compared association and linkage analyses for quantitative trait Q1. Association studies identified a major gene, while linkage analysis revealed residual genetic effects and two minor genes.

Area of Science:

  • Quantitative genetics
  • Statistical genetics
  • Genomic analysis

Background:

  • Quantitative traits are influenced by multiple genetic and environmental factors.
  • Understanding genetic architecture is crucial for trait prediction and breeding.

Purpose of the Study:

  • To compare association and linkage study approaches for quantitative trait analysis.
  • To identify genetic and non-genetic predictors of trait Q1.
  • To explore the simulated genome for linkage and major genes.

Main Methods:

  • Utilized simulated data from Genetic Analysis Workshop 9 (GAW9).
  • Performed association studies to detect gene-trait associations.
  • Conducted linkage studies to identify chromosomal regions influencing the trait.

Related Experiment Videos

Main Results:

  • Association analysis identified a primary major gene directly linked to trait Q1.
  • Linkage analysis indicated residual genetic effects mediated through other traits.
  • Adjusting Q1 for genetically correlated traits (Q2, Q3) masked effects of MG2 and MG3, reducing detection power.

Conclusions:

  • Association studies are effective for detecting major genes influencing quantitative traits.
  • Linkage analysis can reveal complex genetic architectures, including indirect effects.
  • Careful consideration of covariate adjustments is necessary in genetic analyses to avoid masking true effects.