泛癌症DNA甲基化位点聚类分析

doi:10.3969/j.issn.1001-2400.2018.04.005

Abstract

Abstract:

There have been many studies on DNA methylation, but most researches are for a single cancer, individual genes or smaller regions of the gene. In view of the problem, this paper proposes a clustering-based method and analyzes DNA methylation from the perspective of the Pan-cancer at the whole genome level. First, methylation levels of the multiple cancer types are analyzed by SAM and the differential methylation sites are screened out. Also, by calculating the correlation between methylation and gene expression, common regulatory sites are identified. Then AP clustering is carried out at differential methylation sites. Finally, GO and KEGG are adopted for gene annotation and enrichment analysis. Experiments are performed on six categories of cancers from the Pan-cancer project in TCGA. 2184 differential methylation sites and 9 clusters are obtained based on SAM and AP. Experimental results show that the relationship between methylation and gene expression is complex rather than simple positive or negative correlation. From the results of GO and KEGG, we also conclude that the corresponding genes in clusters have been enriched in multiple cancer-related pathways, and are of good biological interpretation.

Key words: pattern recognition, deoxyribonucleic acid methylation, differential site, clustering analysis, gene expression

YANG Liying;YANG Shengnan;YUAN Xiguo;GENG Fangge;ZHANG Junying. Analyzing pan-cancer DNA methylation patterns via clustering[J].Journal of Xidian University, 2018, 45(4): 23-28.

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Analyzing pan-cancer DNA methylation patterns via clustering

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