CAUSALdb

CAUSALdb integrates large numbers of GWAS summary statistics and identifies credible sets of causality by uniformly processed fine-mapping. The database incorporates over 3,000 public full GWAS summary data, and the number will be constantly accumulating according to our timely curation. It estimates causal probabilities of all genetic variants in the GWAS significant loci using three state-of-the-art fine-mapping tools including PAINTOR, CAVIARBF and FINEMAP. These comprehensive causalities and statistics can be explored in an interactive causal block viewer. Users can also compare causal relations on variant-level, gene-level and trait-level across studies of distinct sample size or population. By integrating massive base-wise and allele-specific functional annotations, causal variants could be further interpreted. The objective of this database is to ensure that its convenience and precision for researchers to select and prioritize causal variants for further study.

CAUSALdb整合了大量全基因组关联研究（Genome-Wide Association Study, GWAS）汇总统计数据，并通过统一流程开展精细定位（fine-mapping）以识别可信的因果变异集。该数据库目前收录超过3000条公开完整的GWAS汇总统计数据集，且通过我们的定期人工审编，数据规模将持续扩充。本数据库采用PAINTOR、CAVIARBF与FINEMAP三款前沿精细定位工具，对GWAS显著关联位点内的全部遗传变异估算其因果概率。用户可通过交互式因果区块查看器浏览上述全面的因果关联信息与统计数据。此外，用户还可针对不同样本量或研究人群的数据集，在变异、基因与性状三个层面开展跨研究的因果关联对比分析。通过整合海量碱基层面与等位基因特异性功能注释信息，可进一步对因果变异进行功能层面的解读与阐释。本数据库的研发目标，是为研究人员筛选、优先级排序候选因果变异以开展后续研究，提供便捷且精准的辅助支持。