GwasWA: A GWAS one-stop analysis platform from WGS data to variant effect assessment

Abstract

Using the accumulated whole-genome sequencing (WGS) data and assessing the functional effects of genetic variants, particularly non-coding variants, help identify new and rare variants and decipher the molecular mechanisms underlying diseases and traits but presents significant challenges. GwasWA is a comprehensive and efficient platform to identify causal variants and assess their functional effects based on WGS data. It covers the entire workflow from downloading and processing WGS data to detecting associated variants and assessing their functional effects with optimized configurations, standardized input/output formats, personalized analysis options, data visualization, and parallel processing capability that is crucial for large-scale studies. Applying GwasWA to real datasets identified three novel genes related to seed size and revealed the regulatory mechanism underlying the linkage between a human non-coding variant, rs80067372, and tumor necrosis factor levels. These results highlight the capability of GwasWA to detect novel variants based on WGS data and provide comprehensive insights into the molecular mechanisms underlying the association of variants with diseases and traits, thus contributing to medicine and biology. GwasWA and its documentation are freely available at https://github.com/unicorn-23/GwasWA.