The Department of Biostatistics presents a regular speaker series each semester, generally on Thursday afternoon each week. Diverse experts lecture on their work in biostatistics.
Trans-eQTLs explain a substantial proportion of expression variation, yet are challenging to be detected and replicated since their effects often act in a tissue-specific manner. Many trans-effects are mediated via cis-gene expression and some of those effects are shared across tissue types/conditions. In order to detect robust cis-mediated trans-associations, we proposed a Cross-Condition Mediation method (CCmed-gene). We analyzed data from multiple brain tissue types of the Genotype-Tissue Expression (GTEx) project, and identified 9,631 cis- and trans-gene pairs with gene-level trans-association and mediation effects, many of which showed evidence of replication in other datasets. In order to detect trans-genes for GWAS SNPs of a complex trait, we further developed CCmed-GWAS, and applied it to identify suspected trans-genes associated with 108 known schizophrenia susceptibility loci. To validate the trait-associations of the suspected trans-genes, we conducted validation analyses using a newly proposed two-sample Mendelian Randomization method, MR-Robin, in which we harnessed GWAS summary statistics from the Psychiatric Genomics Consortium and multitissue eQTL statistics from GTEx.
Last Updated On Monday, February 24, 2020 by Wang, Jiebiao
Created On Wednesday, December 18, 2019
For information on seminars and events in the department, contact: