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.
Citation： FAN Juanjuan, JI Xinyu, SHEN Sipeng, ZHANG Ruyang, WEI Yongyue, CHEN Feng. Data quality control, analysis strategy and visualization of epigenomic-wide association studies. Chinese Journal of Evidence-Based Medicine, 2021, 21(6): 721-728. doi: 10.7507/1672-2531.202012149 Copy