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整合了海量全基因组关联分析（Genome-Wide Association Study，GWAS）汇总统计数据，并通过统一标准化的精细定位分析流程，筛选得到可靠的因果变异集合。该数据库目前收录了超过3000条公开完整的GWAS汇总统计数据集，且通过常态化人工审编，数据集规模将持续扩充。本数据库采用PAINTOR、CAVIARBF与FINEMAP三款当前顶尖的精细定位工具，对GWAS显著位点内的全部遗传变异进行因果概率估算。用户可通过交互式因果区块浏览器浏览这些全面的因果关联信息与相关统计数据，还可针对样本量或人群特征各异的多项研究，在变异、基因、性状三个层面开展因果关联关系的对比分析。通过整合海量的碱基分辨率与等位基因特异性功能注释信息，可进一步对筛选出的因果变异进行功能解读与注释分析。本数据库的构建宗旨，在于为科研人员筛选、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工具支撑。

搜集汇总

背景与挑战

背景概述

CAUSALdb是一个整合了超过13,000个公共全GWAS汇总统计数据的数据集，通过统一的精细定位处理来识别因果变异的可信集合。它利用先进的精细定位工具估计GWAS显著位点中所有遗传变异的因果概率，并提供交互式可视化工具供用户探索。该数据集还支持在变异、基因和性状水平上跨不同样本规模或人群的研究比较因果关系，并整合功能注释以进一步解释因果变异，旨在帮助研究人员便捷、精确地选择和优先考虑因果变异进行深入研究。