title: An efficient family-based association test using multiple markers.
abstract: In genetic association studies, multiple markers are usually employed to cover a genomic region of interest for localizing a trait locus. In this report, we propose a novel multi-marker family-based association test (T(LC)) that linearly combines the single-marker test statistics using data-driven weights. We examine the type-I error rate in a numerical study and compare its power to identify a common trait locus using tag single nucleotide polymorphisms (SNPs) within the same haplotype block that the trait locus resides with three competing tests including a global haplotype test (T(H)), a multi-marker test similar to the Hotelling-T(2) test for the population-based data (T(MM)), and a single-marker test with Bonferroni's correction for multiple testing (T(B)). The type-I error rate of T(LC) is well maintained in our numeric study. In all the scenarios we examined, T(LC) is the most powerful, followed by T(B). T(MM) and T(H) are the poorest. T(H) and T(MM) have essentially the same power when parents are available. However, when both parents are missing, T(MM) is substantially more powerful than T(H). We also apply this new test on a data set from a previous association study on nicotine dependence.
authors.affiliation: Program for Population Genetics, Harvard School of Public Health, 665 Huntington Avenue, Boston, MA 02115, USA. xin_xu@harvard.edu
authors.forename: Xin
authors.initials: X
authors.lastname: Xu
authors.forename: Cyril
authors.initials: C
authors.lastname: Rakovski
authors.forename: Xiping
authors.initials: X
authors.lastname: Xu
authors.forename: Nan
authors.initials: N
authors.lastname: Laird
mesh_terms: D005190:Family; D005819:Genetic Markers / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D010290:Parents; D020641:Polymorphism, Single Nucleotide; D014029:Tobacco Use Disorder / Q000235:genetics
chemical_list: D005819:Genetic Markers