BaySyn: Bayesian Evidence Synthesis for Multi-system Multiomic Integration.

ABSTRACT: The discovery of cancer drivers and drug targets are often limited to the biological systems - from cancer model systems to patients. While multiomic patient databases have sparse drug response data, cancer model systems databases, despite covering a broad range of pharmacogenomic platforms, provide lower lineage-specific sample sizes, resulting in reduced statistical power to detect both functional driver genes and their associations with drug sensitivity profiles. Hence, integrating evidence across model systems, taking into account the pros and cons of each system, in addition to multiomic integration, can more efficiently deconvolve cellular mechanisms of cancer as well as learn therapeutic associations. To this end, we propose BaySyn - a hierarchical Bayesian evidence synthesis framew

SUBMITTER: Bhattacharyya R 

PROVIDER: S-EPMC10652956 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature