Title: A Bayesian method to prioritizing candidate pathways association and gene ranking
Authors: Shu-Ju Lin - Academia Sinica (Taiwan) [presenting]
Tzu-Pin Lu - National Taiwan University (Taiwan)
Chuhsing Kate Hsiao - National Taiwan University (Taiwan)
Abstract: Cancer is an important topic of global concern. Some cancer are closely related to genetic aberrations. In order to reduce costs, providing a prioritized list may help to find key genes. Currently, methods for screening genes associated with diseases are roughly classified into three types, such as the single marker test, gene set analysis methods, and pathway analysis, to provide candidate genes or candidate gene sets. However, due to the large number of bio markers, scientists need to face the issue of multiple testing with single marker test. Gene sets found may be a good indicator to cluster, but it is difficult to explain in biology. To overcome the limitations, we consider simultaneously several competing pathways, incorporate the relationship between pathways, and account for the relationship between genes under pathway information. In the simulation, our method controls the type I error well and correctly find true key genes. This novel method identifies the primary pathway of breast cancer as the Jak-STAT signaling pathway, and further identifies 37 key genes in this pathway. In the glioblastoma multiforme study, this method identifies Long-term potentiation as the primary pathway, and from which four key genes are identified.