A0446
Title: Knockoff-based statistics for the identification of putative causal loci in genetic studies
Authors: Iuliana Ionita-Laza - Columbia University (United States) [presenting]
Abstract: Knockoff-based methods are becoming increasingly popular due to their enhanced power for locus discovery and their ability to prioritize putative causal variants in a genome-wide analysis. However, generating knockoffs is computationally and memory expensive, and applying this methodology to genetics is nontrivial. Scalable knockoff-based methods for biobank-sized data for population-based designs and related extensions to family-based designs are discussed. Applications are shown in several large-scale genomic studies, including the UK biobank data.
