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Biostatistics 4:223-229 (2003)
© 2003 Oxford University Press

Combining dependent tests for linkage or association across multiple phenotypic traits

Xin Xu, Lu Tian and L. J. Wei{dagger}

Program for Population Genetics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA
Department of Biostatistics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA wei{at}hsph.harvard.edu

{dagger}To whom correspondence should be addressed

A robust statistical method to detect linkage or association between a genetic marker and a set of distinct phenotypic traits is to combine univariate trait-specific test statistics for a more powerful overall test. This procedure does not need complex modeling assumptions, can easily handle the problem with partially missing trait values, and is applicable to the case with a mixture of qualitative and quantitative traits. In this note, we propose a simple test procedure along this line, and show its advantages over the standard combination tests for linkage or association in the literature through a data set from Genetic Analysis Workshop 12 (GAW12) and an extensive simulation study.

Keywords: Combining tests; Linkage analysis; Random effects models; Tests for association


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