Comparison of multivariate tests for genetic linkage

Christopher I. Amos, Mariza De Andrade, Dakai K. Zhu

Research output: Contribution to journalArticle

77 Scopus citations

Abstract

Objectives: Multivariate tests for linkage can provide improved power over univariate tests but the type I error rates and comparative power of commonly used methods have not previously been compared. Here we studied the behavior of bivariate formulations of the variance component (VC) and Haseman-Elston (H-E) approaches. Methods: We compared through simulation studies the bivariate H-E test with the unconstrained bivariate VC approach and with a VC approach in which the major-gene correlation is constrained to ± 1. We also compared these methods to univariate methods. Results: Bivariate approaches are more powerful than univariate analyses unless the traits are very highly positively correlated. The power of the bivariate H-E test was less than the VC procedures. The constrained test was often less powerful than the unconstrained test. The empirical distributions of the bivariate H-E test and the unconstrained bivariate VC test conformed with asymptotic distributions for samples of 100 or more sibships of size 4. Conclusions: The unconstrained VC test is valuable for testing for preliminary linkages using multivariate phenotypes. The bivariate H-E test was less powerful than the bivariate VC tests.

Original languageEnglish (US)
Pages (from-to)133-144
Number of pages12
JournalHuman Heredity
Volume51
Issue number3
DOIs
StatePublished - Mar 6 2001

Keywords

  • Linkage
  • Multivariate analysis
  • Statistical genetics
  • Variance components

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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