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Related Experiment Videos

Association testing in a linked region using large pedigrees.

Rita M Cantor1, Gary K Chen, Päivi Pajukanta

  • 1Department of Human Genetics, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA 90095-7088, USA. rcantor@mednet.ucla.edu

American Journal of Human Genetics
|January 20, 2005
PubMed
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This study presents a computational method for analyzing genetic linkage and association simultaneously. The approach aids in identifying genetic variations linked to diseases, particularly in family-based studies.

Area of Science:

  • Genetics
  • Statistical genetics
  • Computational biology

Background:

  • Joint linkage and association analysis is crucial for understanding complex genetic diseases.
  • Existing methods may not adequately handle both linkage and association simultaneously.
  • Accurate estimation of genetic parameters is essential for reliable results.

Purpose of the Study:

  • To describe the computer implementation of a novel scheme for joint linkage and association analysis.
  • To develop a computational package (Mendel) for estimating recombination and linkage-disequilibrium parameters.
  • To perform likelihood-ratio tests for linkage, association, and their simultaneous assessment.

Main Methods:

  • Implementation of a joint linkage and association analysis model in the Mendel software package.

Related Experiment Videos

  • Estimation of recombination and linkage-disequilibrium parameters.
  • Likelihood-ratio tests for linkage alone, association alone, and combined linkage and association.

    • Main Results:

    • The Mendel package successfully implements the joint analysis scheme.
    • Application to Finnish pedigrees with familial combined hyperlipidemia demonstrated potential.
    • Identification of associated single nucleotide polymorphism (SNP) haplotypes in the presence of linkage was illustrated.

    Conclusions:

    • The implemented method provides a powerful tool for genetic analysis.
    • Accurate haplotype frequency estimates are critical for the validity of the analysis.
    • This approach can aid in identifying genetic factors underlying complex diseases.