Editorial: Statistical Methods, Computing and Resources for Genome-Wide Association Studies. Frontiers in Genetics

Hailan Liu , Lide Han , Guolian Kang , Min Zhang and Riyan Cheng

doi: 10.3389/fgene.2021.714894

Hailan Liu：Maize Research Institute of Sichuan Agricultural University, China

Abstract:Thanks to the recent advances in genotyping technologies, genome-wide association studies (GWAS) have been an established approach to identifying genetic variants that influence certain characteristics of economic or scientific interest in plants, animals and humans. Applications of GWAS cover a wide range of areas in genetics and have enhanced our understanding of the genetic mechanisms in diseases, physiological or behavioral traits and have generated promises in agriculture, medicine and wildlife conservation. Despite great success, GWAS remains challenged by statistical modeling and computing. This collection of twelve articles presents a variety of interesting scientific problems and novel approaches in GWAS.