Oncotarget

Research Papers: Pathology:

Identification of potential genes for human ischemic cardiomyopathy based on RNA-Seq data

Wan Li, Liansheng Li, Shiying Zhang, Ce Zhang, Hao Huang, Yiran Li, Erqiang Hu, Gun Deng, Shanshan Guo, Yahui Wang, Weimin Li and Lina Chen _

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Oncotarget. 2016; 7:82063-82073. https://doi.org/10.18632/oncotarget.13331

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Abstract

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

Correspondence to:

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

Abstract

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.


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