Research Papers: Pathology:
Identification of potential genes for human ischemic cardiomyopathy based on RNA-Seq data
Metrics: PDF 1005 views | HTML 1310 views | ?
Wan Li1,*, Liansheng Li1,*, Shiying Zhang1,*, Ce Zhang2,*, Hao Huang1, Yiran Li1, Erqiang Hu1, Gui Deng1, Shanshan Guo1, Yahui Wang1, Weimin Li3 and Lina Chen1
1 College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang, China
2 Department of internal medicine, Heilongjiang Commercial Hospital, Harbin, Heilongjiang, China
3 Department of Cardiology, the First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
* These authors contributed equally to this work
Lina Chen, email:
Weiming Li, email:
Keywords: RNA-Seq; canonical correlation analysis; co-expression network; ischemic cardiomyopathy; Pathology Section
Received: August 02, 2016 Accepted: October 07, 2016 Published: November 12, 2016
Ischemic cardiomyopathy (ICM) is an important cause of heart failure, yet no ICM disease genes were stored in any public databases. Mutations of genes provided by RNA-Seq data could set a foundation for a variety of biological processes. This also made it possible to elucidate the mechanism and identify potential genes for ICM. In this paper, an integrated co-expression network was constructed using univariate and bivariate canonical correlation analysis for RNA-Seq data of human ICM samples. Three ICM-related modules were recognized after comparing between Pearson correlation coefficients of ICM samples and normal controls. Furthermore, 32 ICM potential genes were identified from ICM-related modules considering protein-protein interactions. Most of these genes were verified to be involved in ICM and diseases caused it by OMIM and literature. Our study could provide a novel perspective for potential gene identification and the pathogenesis for ICM and other complex diseases.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.