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Related Experiment Videos

Detecting linkage for a complex disease using simulated extended pedigrees

A L DeStefano1, L A Cupples, R H Myers

  • 1Department of Neurology, School of Medicine, Boston University, MA 02118, USA.

Genetic Epidemiology
|January 1, 1997
PubMed
Summary

This study evaluated two strategies for gene linkage analysis using simulated pedigree data. A two-stage approach identified fewer true positives but also fewer false positives compared to a full genome screen in both replicates.

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Area of Science:

  • Genetics
  • Statistical genetics
  • Quantitative trait loci (QTL) analysis

Background:

  • Quantitative traits are influenced by multiple genes and environmental factors.
  • Accurate identification of genes contributing to quantitative traits is crucial for understanding complex diseases.
  • Simulated data provides a controlled environment for evaluating genetic analysis methods.

Purpose of the Study:

  • To examine the relationship between quantitative traits (Q1-Q5), environmental factors, age, and sex.
  • To identify genes contributing to quantitative traits using linkage analysis.
  • To evaluate two strategies for utilizing a second dataset in linkage analysis.

Main Methods:

  • Used simulated extended pedigree data from the Genetic Analysis Workshop 10.

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  • Employed a forward selection procedure to build regression models for each trait.
  • Performed two-point sib-pair analysis on residuals using SIBPAL, evaluating two strategies for a second dataset: a two-stage approach and a repeat genome-wide screen.

    • Main Results:

    • The two-stage approach identified 9 regions in the second replicate (p < 0.05), with 4 true positives and 5 false positives.
    • A repeat genome-wide screen identified 20 regions in both replicates (p < 0.05), with 5 true positives.
    • The two-stage approach had a higher false negative rate, while the full screen increased the false positive rate.

    Conclusions:

    • The choice of linkage analysis strategy impacts the balance between true positives, false positives, and false negatives.
    • A two-stage approach with stringent initial criteria may miss true linkages (false negatives).
    • Conducting two complete genome screens in a split-sample design may be beneficial for some genetic studies.