全表观基因组关联研究的数据质控、分析流程和可视化

Data quality control, analysis strategy and visualization of epigenomic-wide association studies

表观遗传是指在基因遗传序列不变的前提下,外界和内在环境因素对基因产生修饰作用,导致基因表达水平或功能发生改变,进而对多种表型或疾病结局产生影响,近年来愈发受到关注。其中,DNA的甲基化修饰已被证实与人类发育和疾病发生发展密切相关。而全基因组尺度的甲基化检测所产生的高维度基因组学数据,能够较为全面地体现基因组层面整体和局部的表观遗传修饰情况,已成为该领域的主要研究内容之一。本文基于全基因组甲基化芯片数据,总结该类组学数据的质控流程,常见表观遗传组学关联性的统计分析方法和思路,以及基于SAS JMP Genomics 10软件的主要结果的可视化实现,为同类研究提供参考。

Epigenetics refers to the modification effect of external and internal environmental factors on genes under the premise of the unaltered genetic sequence, leading to changes in gene expression level or function, and thereby affecting various phenotypes or disease outcomes. In recent years, epigenetics has attracted increasing attention. Among them, DNA methylation has been shown to be closely related to human development and the development of disease.However, the high-dimensional omics data generated by genome-wide methylation detection can comprehensively reflect the overall and local epigenetic modifications at the genome level, which has become one of the main research contents in this field. Based on genome-wide methylation chip data, this paper summarized the quality control process of this omics data, common epigenetic omics correlation statistical analysis methods and ideas, and visualization realization of main results based on SAS JMP Genomics 10 software, so as to provide reference for similar studies.