Bayesian variable selection in a Cox proportional hazards model with the "Sum of Single Effects" prior
采用单效应之和先验的 Cox 比例风险模型贝叶斯变量选择
Motivated by genetic fine-mapping applications, we introduce a new approach to Bayesian variable selection regression (BVSR) for time-to-event (TTE) outcomes. This new approach is designed to deal with the specific challenges that arise in genetic fine-mapping, including: the presence of very strong correlations among the covariates, often exceeding 0.99; very large data sets containing potentially thousands of covariates and hundreds of thousands of samples. We accomplish…