A novel similarity score based on gene ranks to reveal genetic relationships among diseases.

Knowledge of similarities among diseases can contribute to uncovering common genetic mechanisms. Based on ranked gene lists, a couple of similarity measures were proposed in the literature. Notice that they may suffer from the determination of cutoff or heavy computational load, we propose a novel similarity score among diseases based on gene ranks. Simulation studies under various scenarios demonstrate that has better performance than existing rank-based similarity measures. Application of in gene expression data of 18 cancer types from The Cancer Genome Atlas shows that is superior in clarifying the genetic relationships among diseases and demonstrates the tendency to cluster the histologically or anatomically related cancers together, which is analogous to the pan-cancer studies. Moreover, with simpler form and faster computation is more robust for higher levels of noise than existing methods and provides a basis for future studies on genetic relationships among diseases. In addition, a measure is developed to gauge the magnitude of association of anindividual gene with diseases. By using the genes and biological processes significantly associated with colorectal cancer are detected.