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

Quantitative similarity-based association tests using population samples.

S Zhang1, H Zhao

  • 1Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT 06520, USA.

American Journal of Human Genetics
|August 2, 2001
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

[Detection of anti-HAV, anti-HBV, anti-HCV and anti-HEV antibodies in the patients with sporadic acute hepatitis in Beijing during 1995-2000].

Zhonghua shi yan he lin chuang bing du xue za zhi = Zhonghua shiyan he linchuang bingduxue zazhi = Chinese journal of experimental and clinical virology·2002
Same author

Chiral synthesis and enzymatic resolution of (S)-(-)piperazine-2-carboxylic acid using enzyme alcalase.

Enantiomer·2002
Same author

[The model of piggyback orthotopic liver transplantation in pigs].

Hunan yi ke da xue xue bao = Hunan yike daxue xuebao = Bulletin of Hunan Medical University·2002
Same author

[The manifestations of 496 cases with thyroid-related immune orbitopathy and normal thyroid function].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology·2002
Same author

[A study of cytokines in pathogenesis of thyroid-related immune orbitopathy].

[Zhonghua yan ke za zhi] Chinese journal of ophthalmology·2002
Same author

[Analysis of hepatitis G virus genotypes in some areas of China].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]·2002
Same journal

Linkage disequilibrium and allelic heterogeneity explain variation in coronary artery disease risk at 9p21 across populations and reduced effect in Africans.

American journal of human genetics·2026
Same journal

Genome-wide association study and predictors of neonatal blood cell traits in Hispanic newborns.

American journal of human genetics·2026
Same journal

Comparison of methods for assessing effects of risk factors on disease progression in Mendelian randomization under index event bias.

American journal of human genetics·2026
Same journal

Deciding "what" to screen for and "when": The importance of natural history information.

American journal of human genetics·2026
Same journal

Homologous recombination deficiency-driven genomic instability in ovarian cancer as an indicator of BRCA1 and BRCA2 variant pathogenicity.

American journal of human genetics·2026
Same journal

Individuals who deviate from polygenic expectation are enriched for damaging variants in genes linked to rare disease.

American journal of human genetics·2026
See all related articles

We developed a new method, quantitative similarity-based association test (QSAT), to accurately detect genetic associations with traits in diverse populations. QSAT is more powerful than traditional family-based designs and robust to population stratification.

Area of Science:

  • Genetics
  • Population Genetics
  • Statistical Genetics

Background:

  • Genetic association studies with unrelated individuals risk bias from population stratification.
  • Family-based designs are robust but often less powerful and more costly.
  • Existing methods for structured populations have limitations.

Purpose of the Study:

  • To propose a novel statistical method, the quantitative similarity-based association test (QSAT).
  • To identify associations between genetic markers and quantitative traits in unrelated individuals from structured populations.
  • To offer a robust and powerful alternative to existing association study designs.

Main Methods:

  • Developed QSAT, a quantitative similarity-based association test.
  • Utilized genotype data from independent markers to infer subpopulation structure between individuals.

Related Experiment Videos

  • Integrated subpopulation information into the association test for a candidate marker and quantitative trait.

    • Main Results:

    • QSAT demonstrated a correct type I error rate, proving robust against population stratification.
    • Simulation studies showed QSAT possesses higher statistical power compared to family-based association designs.
    • The method performed well using both coalescent models and empirical population genetics data.

    Conclusions:

    • QSAT is a reliable method for genetic association studies in structured populations using unrelated individuals.
    • QSAT offers improved power and robustness, addressing limitations of current approaches.
    • This method enhances the feasibility and cost-effectiveness of genetic association research.