B1372
Title: CARMA: Novel Bayesian model for fine-mapping in GWAS meta-analyses and multi-ethnic
Authors: Zikun Yang - Columbia University (United States) [presenting]
Linxi Liu - University of Pittsburgh (United States)
Iuliana Ionita-Laza - Columbia University (United States)
Abstract: Fine-mapping is commonly used to identify putative causal variants genome-wide significant loci. A Bayesian model is proposed for fine-mapping that has several advantages over existing methods, including flexible specification of the prior distribution of effect sizes, joint modelling of summary statistics and functional annotations and accounting for discrepancies between summary statistics and external linkage disequilibrium in meta-analyses. Furthermore, this fine-mapping method is extended to multi-ethnic and admixed populations, employing a Bayesian adaptive prior to account for effect size heterogeneity across ethnicities. A novel extension of the fine-mapping method has also been proposed for admixed populations, where the genetic structure of the individuals is composited from multiple ancestries.
