Subpathway-GMir: identifying miRNA-mediated metabolic subpathways by integrating condition-specific genes, microRNAs, and pathway topologies.

Li Feng, Yanjun Xu, Yunpeng Zhang, Zeguo Sun, Junwei Han, Chunlong Zhang, Haixiu Yang, Desi Shang, Fei Su, Xinrui Shi, Shang Li, Chunquan Li, Xia Li

Index: Oncotarget 6 , 39151-64, (2015)

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Abstract

MicroRNAs (miRNAs) regulate disease-relevant metabolic pathways. However, most current pathway identification methods fail to consider miRNAs in addition to genes when analyzing pathways. We developed a powerful method called Subpathway-GMir to construct miRNA-regulated metabolic pathways and to identify miRNA-mediated subpathways by considering condition-specific genes, miRNAs, and pathway topologies. We used Subpathway-GMir to analyze two liver hepatocellular carcinomas (LIHC), one stomach adenocarcinoma (STAD), and one type 2 diabetes (T2D) data sets. Results indicate that Subpathway-GMir is more effective in identifying phenotype-associated metabolic pathways than other methods and our results are reproducible and robust. Subpathway-GMir provides a flexible platform for identifying abnormal metabolic subpathways mediated by miRNAs, and may help to clarify the roles that miRNAs play in a variety of diseases. The Subpathway-GMir method has been implemented as a freely available R package.