title: Genetic association test for multiple traits at gene level.
abstract: Genome-wide association studies (GWASs) at the gene level are commonly used to understand biological mechanisms underlying complex diseases. In general, one response or outcome is used to present a disease of interest in such studies. In this study, we consider a multiple traits association test from the gene level. We propose and examine a class of test statistics that summarizes the association information between single nucleotide polymorphisms (SNPs) and each of the traits. Our simulation studies demonstrate the advantage of gene-based multiple traits association tests when multiple traits share common genes. Using our proposed tests, we reanalyze the dataset from the Study of Addiction: Genetics and Environment (SAGE). Our result validates previous findings while presenting stronger evidence for consideration of multiple traits.
authors.affiliation: Department of Biostatistics, Yale University School of Medicine, New Haven, Connecticut 06520, USA.
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Guo
authors.forename: Zhifa
authors.initials: Z
authors.lastname: Liu
authors.forename: Xueqin
authors.initials: X
authors.lastname: Wang
authors.forename: Heping
authors.initials: H
authors.lastname: Zhang
mesh_terms: D000437:Alcoholism / Q000235:genetics; D003198:Computer Simulation; D005260:Female; D005796:Genes; D055106:Genome-Wide Association Study; D018398:Homeodomain Proteins / Q000235:genetics; D006801:Humans; D015810:Linkage Disequilibrium; D008297:Male; D008957:Models, Genetic; D015233:Models, Statistical; D016017:Odds Ratio; D020641:Polymorphism, Single Nucleotide; D040641:Quantitative Trait Loci; D019966:Substance-Related Disorders / Q000235:genetics; D014157:Transcription Factors / Q000235:genetics
chemical_list: D018398:Homeodomain Proteins; C435984:PKNOX2 protein, human; D014157:Transcription Factors