UKIN Combines New and Prior Information with Guided Network Propagation to Accurately Identify Disease Genes.

ABSTRACT: Protein interaction networks provide a powerful framework for identifying genes causal for complex genetic diseases. Here, we introduce a general framework, uKIN, that uses prior knowledge of disease-associated genes to guide, within known protein-protein interaction networks, random walks that are initiated from newly identified candidate genes. In large-scale testing across 24 cancer types, we demonstrate that our network propagation approach for integrating both prior and new information not only better identifies cancer driver genes than using either source of information alone but also readily outperforms other state-of-the-art network-based approaches. We also apply our approach to genome-wide association data to identify genes functionally relevant for several complex diseases. Over

SUBMITTER: Hristov BH 

PROVIDER: S-EPMC7821437 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature