A0668
Title: Exploring cross-trait genetic architectures: Statistical models, computational challenges, and the BIGA platform
Authors: Bingxin Zhao - University of Pennsylvania (United States) [presenting]
Abstract: Numerous statistical models have been proposed to analyze cross-trait genetic architectures utilizing summary statistics from genome-wide association studies (GWAS). However, systematically analyzing high-dimensional GWAS summary statistics presents logistical and computational challenges. The BIGA platform, a website, is introduced that offers unified data analysis pipelines and centralized data resources. A framework that implements statistical genetics tools on a cloud computing platform has been developed and integrated with extensive curated GWAS datasets. Furthermore, the recent theoretical analyses of the LD score regression (LDSC), a widely-used method for inferring heritability and genetic correlation using GWAS summary statistics, are discussed. The consistency and asymptotic normality of LDSC-based estimators are demonstrated, and the key factors that influence their performance are identified.
