title: Combining dependent tests for linkage or association across multiple phenotypic traits.
abstract: 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.
authors.affiliation: Program for Population Genetics, Harvard School of Public Health, 667 Huntington Ave, Boston, MA 02115, USA.
authors.forename: Xin
authors.initials: X
authors.lastname: Xu
authors.forename: Lu
authors.initials: L
authors.lastname: Tian
authors.forename: L J
authors.initials: LJ
authors.lastname: Wei
mesh_terms: D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D008040:Genetic Linkage / Q000235:genetics*; D005819:Genetic Markers / Q000235:genetics; D014644:Genetic Variation; D006801:Humans; D016014:Linear Models; D008957:Models, Genetic; D010641:Phenotype
chemical_list: D005819:Genetic Markers