The ever-growing availability of high-quality genotypes for a multitude of 
species has enabled researchers to explore the underlying genetic architecture 
of complex phenotypes at an unprecedented level of detail using genome-wide 
association studies (GWAS). The systematic comparison of results obtained from 
GWAS of different traits opens up new possibilities, including the analysis of 
pleiotropic effects. Other advantages that result from the integration of 
multiple GWAS are the ability to replicate GWAS signals and to increase 
statistical power to detect such signals through meta-analyses. In order to 
facilitate the simple comparison of GWAS results, we present easyGWAS, a 
powerful, species-independent online resource for computing, storing, sharing, 
annotating, and comparing GWAS. The easyGWAS tool supports multiple species, the 
uploading of private genotype data and summary statistics of existing GWAS, as 
well as advanced methods for comparing GWAS results across different experiments 
and data sets in an interactive and user-friendly interface. easyGWAS is also a 
public data repository for GWAS data and summary statistics and already includes 
published data and results from several major GWAS. We demonstrate the potential 
of easyGWAS with a case study of the model organism Arabidopsis thaliana, using 
flowering and growth-related traits.