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

Family-based association studies.

H Zhao1

  • 1Yale University School of Medicine, New Haven, Connecticut 06520, USA. hongyu.zhao@yale.edu

Statistical Methods in Medical Research
|April 20, 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

Asymptotic online FWER control for dependent test statistics.

Statistical methods in medical research·2026
Same journal

Regression analysis of misclassified current status data with potentially unknown test accuracy.

Statistical methods in medical research·2026
Same journal

Bayesian multivariate linear mixed-effects models with varied association structures.

Statistical methods in medical research·2026
Same journal

Inference about the ratio of age-standardized rates between two overlapping populations.

Statistical methods in medical research·2026
Same journal

A robust neural network with random effects for subject-specific prediction of clustered count data.

Statistical methods in medical research·2026
Same journal

A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints.

Statistical methods in medical research·2026
See all related articles

Family-based association designs offer a powerful and robust approach for identifying complex disease genes. These methods overcome limitations of traditional linkage and case-control studies, especially concerning population stratification.

Area of Science:

  • Genetics
  • Biostatistics
  • Human Genome Research

Background:

  • Shift from Mendelian to complex disease gene discovery.
  • Limitations of traditional linkage and case-control studies (power, population stratification bias).
  • Emergence of family-based designs as a robust alternative.

Purpose of the Study:

  • Review family-based association designs for complex disease gene identification.
  • Discuss statistical method extensions and applications.
  • Explore implications of genomic resources for these designs.

Main Methods:

  • Description of basic family-based association design (e.g., transmission disequilibrium test).
  • Review of extensions for multiallelic markers, multiple siblings, incomplete genotypes, and general pedigrees.

Related Experiment Videos

  • Discussion of advanced methods for quantitative traits, X-linked genes, linked markers, imprinting, and gene-environment interactions.

    • Main Results:

    • Family-based designs demonstrate higher power and robustness against population substructure.
    • Various statistical extensions enhance applicability to diverse genetic scenarios.
    • Genomic resources facilitate broader application of these designs.

    Conclusions:

    • Family-based association designs are crucial for dissecting complex diseases.
    • Methodological advancements and genomic data integration will accelerate gene discovery.
    • These approaches are vital for leveraging the Human Genome Project's findings.