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Nonparametric tests for linkage with dependent sib pairs

A Collins1, N E Morton

  • 1Human Genetics Group, University of Southampton, Princess Anne Hospital, UK.

Human Heredity
|November 1, 1995
PubMed
Summary

Sibling pair linkage tests for quantitative traits and affection status were simulated. Using all sibling pairs, even with redundancy, is crucial for efficient testing and reliable results, especially with equal weighting.

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Area of Science:

  • Genetics
  • Biostatistics
  • Statistical genetics

Background:

  • Sibling pair linkage analysis is a common method for identifying genes associated with diseases or quantitative traits.
  • The efficiency and reliability of these tests depend on how sibship data is utilized and weighted.

Purpose of the Study:

  • To examine the performance of sibling pair linkage tests under various conditions using simulation.
  • To evaluate the impact of data redundancy and weighting schemes on test power and accuracy.

Main Methods:

  • Simulations were conducted to analyze sibling pair linkage tests for quantitative traits and affection status.
  • Both equally and unequally weighted pairs were considered under the null hypothesis of no linkage.
  • The Fisher z(r) test was compared to t(r) tests with conjectured degrees of freedom.

Main Results:

  • Redundancy in sibling pairs increases with sibship size, but all pairs are necessary for efficient testing.
  • Unequal weighting reduces statistical power and degrades the goodness of fit to theoretical distributions.
  • The Fisher z(r) test with equally weighted pairs demonstrated greater reliability compared to t(r) tests.

Conclusions:

  • Maximizing the use of available sibling pairs, despite redundancy, is essential for robust linkage analysis.
  • Equal weighting and the Fisher z(r) test are recommended for reliable sibling pair linkage studies, with simulation needed for significance levels in small or redundant datasets.

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