Identifying and interpreting the genetic causality of complex traits is a major task in the post-GWAS era. Although several statistical fine-mappings have been used in many recent GWASs to estimate potential causal variants, the complexity of data representation as well as discrepancies of the applied statistical methods have inhibited systematic and valuable curation. Nowadays, an increasing amount of summary-level GWAS data has become publicly available, which provides unprecedented opportunities to gain in-depth understanding of the genetic mechanisms of complex traits via integrative analysis. However, no resources have leveraged published GWAS summary statistics to comprehensively fine-map causal variants and annotate their potential mechanisms. Herein, we performed strict quality control process and finally selected 3,052 fine-mappable GWAS summary statistics. We developed a unique user-friendly platform called CAUSALdb that integrates a repository of high-quality GWAS summary statistics, identifies potential causal variants by three state-of-the-art fine-mapping tools, and offers comprehensive variant annotations.
