文档介绍：ATHENA: A TOOL FOR M ETA -DIMENSIONAL ANALYSIS APPLIED TO GENOTYPES AND GENE E XPRESSION DATA TO PR EDICT HDL CHOLESTERO L LEVELS EM ILY R. HOLZINGER ? Center for Human ics Research , Vanderbilt University Nashville, TN 37232, USA Email: .******@ SCOTT M. DUDEK Center for Systems Genomics, Pennsylvania State University University Park, PA 16803, USA Email: sud ******@ ALEX T. FRASE Center for Systems Genomics, Pennsylvania State University University Park, PA 16803, USA Email: alex.******@ RONALD M. KRAUSS Children’s Hospital Oakland Research Institute Oakland, CA 94609, USA Email: rkrauss@ MARISA W. MEDINA Children’s Hospital Oakland Research Institute Oakland, CA 94609, USA Email: mwmedina@ MARYLYN D. RITCHIE Center for Systems Genomics, Pennsylvania State University University Park, PA 16803, U SA Email: marylyn.******@ Technology is driving the field of human ic s research with advances in techniques to generate high -throughput data that interroga te various levels of biological regulation. With this massive amount of es the important task of using powerful bioinformatics techniques to sift through the noise to find true signals that predict various human traits. A popular analytical method thus far has been the genome -wide association study (GWAS), which assesses the associat ion of single nucleotide polymorphism s (SNP s ) with the trait of interest. Unfortunately, GWAS has not been able to explain a substantial proportion of the estimated heritability for plex traits. Due to the plex nature of biology, this phe nomenon could be a factor of the simplistic study design. A more powerful analysis may be a systems biology approach that integrates different types of data, or a meta -dimensional analysis. For this study we used the Analysis Tool for Heritable and En work Associations (ATHENA) to integrate high -throughput SNPs and gene expression variables (EVs) to predict high -density