Two-level Bayesian interaction analysis for survival data incorporating pathway information.

ABSTRACT: Genetic interactions play an important role in the progression of complex diseases, providing explanation of variations in disease phenotype missed by main genetic effects. Comparatively, there are fewer studies on survival time, given its challenging characteristics such as censoring. In recent biomedical research, two-level analysis of both genes and their involved pathways has received much attention and been demonstrated as more effective than single-level analysis. However, such analysis is usually limited to main effects. Pathways are not isolated, and their interactions have also been suggested to have important contributions to the prognosis of complex diseases. In this paper, we develop a novel two-level Bayesian interaction analysis approach for survival data. This approach is th

SUBMITTER: Qin X 

PROVIDER: S-EPMC10272285 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature