The usage of Genome-Wide Association Studies (GWAS) continues to grow in the discovery and development of disease models; however, they are often restricted to interrogation within predefined European ancestry populations. With the continued development of scalable and cost-effective technologies like low-pass whole genome sequencing (LP-WGS), however, this flaw has been addressed by enabling inexpensive genome-wide variant data generation without pre-defined population limitations.

In this webinar, Dr. Louie will first review the science behind LP-WGS technology, which uses computation methods, such as imputation, and discuss advantages and considerations of LP-WGS when compared to traditional genotyping arrays and other whole genome or targeted approaches. Jeremy Li will then review the main results from Gencove’s recently-published paper in Genome Research comparing the performance of LP-WGS to that of commonly-used genotyping arrays in the context of GWAS and polygenic risk scores. Iris Kalka will conclude the webinar by discussing her current work at the Weizmann Institute of Science constructing a cohort consisting of 10,000 healthy individuals, all of whom are deeply phenotyped and genotyped using LP-WGS, in the hopes to unravel novel early disease markers with the potential of becoming drug targets.

Register here.