A new method for disease-related gene prioritization
Prioritizing genes according to their association with a disease allows researchers to explore genes in more informed ways. Although some useful algorithms have been developed, they are based on single gene importance, gene interaction networks, or gene modules with little consideration of relative gene importance in the context of modules. In this paper, we propose to prioritize genes considering both individual genes and their affiliated modules, and utilize Gene Ontology (GO) based fuzzy measure value as well as known disease genes as heuristics. The performance of our method is comprehensively validated by using both simulated and real datasets. Results show that our method outperforms other methods in terms of disease-related gene prioritization. This work will aid researchers in the understanding of the genetic architecture of complex diseases, and improve the accuracy of diagnosis and the effectiveness of therapy.