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Score test for detecting linkage to quantitative traits.

H Putter1, L A Sandkuijl, J C van Houwelingen

  • 1Department of Medical Statistics, Leiden University Medical Center, Leiden, The Netherlands. h.putter@lumc.nl

Genetic Epidemiology
|May 2, 2002
PubMed
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This study introduces a score test for quantitative trait locus linkage analysis, proving its mathematical equivalence to an optimal Haseman-Elston method for sib-pairs. This finding theoretically explains observed similarities in power between these genetic linkage detection methods.

Area of Science:

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

Background:

  • Two primary methods for detecting quantitative trait linkage to markers are Haseman-Elston regression and variance components likelihood-ratio tests.
  • These methods have established advantages and disadvantages, frequently compared in existing literature.
  • Previous simulation studies suggest similar power between the variance components likelihood-ratio test and an optimal Haseman-Elston method.

Purpose of the Study:

  • To derive a score test for the variance component associated with a specific quantitative trait locus.
  • To demonstrate the mathematical equivalence of this score test to a recently proposed optimal Haseman-Elston method for sib-pair analysis.
  • To provide a theoretical basis for the empirical findings of similar power between these genetic linkage analysis approaches.

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Main Methods:

  • Derivation of a score test for the variance component attributable to a quantitative trait locus.
  • Mathematical comparison of the derived score test with a specific version of the Haseman-Elston method for sib-pairs.
  • Asymptotic equivalence analysis between score tests and likelihood-ratio tests for large sample sizes.

Main Results:

  • The derived score test is mathematically equivalent to an optimal Haseman-Elston method that optimally combines sum squared and difference squared of sibs' centered phenotypes.
  • The variance components likelihood-ratio test is asymptotically equivalent to this optimal Haseman-Elston test for large sample sizes.
  • This equivalence provides a theoretical explanation for the similar power observed in simulation studies.

Conclusions:

  • The score test offers a theoretical explanation for the comparable performance of the variance components likelihood-ratio test and the optimal Haseman-Elston method.
  • The score test framework can be naturally extended for analyzing more than two subjects and multivariate phenotypes.
  • This work unifies theoretical understanding and practical application in genetic linkage detection.