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| Maximal Information Coefficient on Identifying Differentially Expressed Genes of Permanent Atrial Fibrillation |
1 School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
2 School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, Jiangxi, China |
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Abstract The atrial fibrillation is a common arrhythmia disease. It usually causes stroke resulting in high risk on morbidity and mortality. It can be insight into the biological processes, the functional disorders of atrial fibrillation and the genes associated with disease risks by analyzing a microarray data. A proposed novel statistical method named as maximal information coefficient (MIC) has excellent performance in exploring the relationship between twovariables. Based on the degree of relationship between the phenotypes and differentially or undifferentially expressed genes, the statistical method was introduced into the analysis of a microarray of permanent atrial fibrillations (GSE2240). Total of 41 genes were identified by the method, in which 14 genes are new differentially expressed genes. The differentially expressed genes identified by MIC were demonstrated that they were related with atrial fibrillation diseases, via the analyses of signaling pathway and enrichment in DAVID. Furthermore, MIC was used to analyze a microarray of breast cancer (GSE24037) to test the method. MIC is a nonparametric statistical method with antinoise, which leads it to be ideally suit for identifying differentially expressed genes.
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