tooluniverse-gwas-finemapping

Identify and prioritize causal variants at GWAS loci using statistical fine-mapping and locus-to-gene predictions.

Genome-wide association studies (GWAS) identify genomic regions associated with traits, but linkage disequilibrium (LD) makes it difficult to pinpoint the causal variant. Fine-mapping uses Bayesian statistical methods to compute the posterior probability that each variant is causal, given the GWAS summary statistics.

Credible Sets A credible set is a minimal set of variants that contains the causal variant with high confidence (typically 95% or 99%). Each variant in the set has a posterior probability of being causal, computed using methods like:

使用统计精细映射和基因座到基因预测来识别 GWAS 位点的因果变异并确定其优先顺序。计算因果变异的后验概率，通过 L2G 预测将变异与基因联系起来，注释功能后果，并建议验证策略。当需要精细绘制 GWAS 位点、优先考虑因果变异、识别可信集或将 GWAS 信号与因果基因联系起来时使用。 来源：mims-harvard/tooluniverse。