ORN: Inferring patient-specific dysregulation status of pathway modules in cancer with OR-gate Network.

ABSTRACT: Pathway level understanding of cancer plays a key role in precision oncology. However, the current amount of high-throughput data cannot support the elucidation of full pathway topology. In this study, instead of directly learning the pathway network, we adapted the probabilistic OR gate to model the modular structure of pathways and regulon. The resulting model, OR-gate Network (ORN), can simultaneously infer pathway modules of somatic alterations, patient-specific pathway dysregulation status, and downstream regulon. In a trained ORN, the differentially expressed genes (DEGs) in each tumour can be explained by somatic mutations perturbing a pathway module. Furthermore, the ORN handles one of the most important properties of pathway perturbation in tumours, the mutual exclusivity. We have

SUBMITTER: Liang L 

PROVIDER: S-EPMC8049496 | biostudies-literature | 2021 Apr

REPOSITORIES: biostudies-literature