CBDCEM: An effective centrality based differential co-expression method for critical gene finding

Recent years have seen rise in applications of differential co-expression analysis (DCE) for disease biomarker identification. This paper presents a centrality-based hub-gene centric method called Centrality Based Differ-ential Co-Expression Method (CBDCEM), for crucial gene finding for critical diseases. A prominent task of DCE is the identification of hub-gene(s) for each differentially co-expressed module. We propose a consensus-based algorithm that employs seven centrality measures to detect hub-genes. Our method has been validated on three Esophageal Squamous Cell Carcinoma (ESCC) datasets and is found to perform well for denser modules. Through comparison of our proposed hub-gene finding algorithm with 4 other hub-gene finding methods, we have observed that the former was able to identify unique potential biomarkers that were undetected by the rest. CBDCEM is able to identify 15 genes as potential biomarkers for ESCC. Eleven other genes identified by CBDCEM have some evidence of being potential biomarkers for other Squamous Cell Carcinoma and can be considered candidates for ESCC, but require further in-depth validation.