表观基因组
破译
背景(考古学)
全基因组关联研究
计算生物学
DNA甲基化
混淆
表观遗传学
遗传关联
生物
数据科学
生物信息学
计算机科学
遗传学
医学
单核苷酸多态性
基因型
病理
基因
基因表达
古生物学
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2020-01-01
卷期号:: 591-613
被引量:3
标识
DOI:10.1016/b978-0-12-819414-0.00029-x
摘要
Since their inception less than a decade ago, epigenome-wide association studies (EWAS) have become widely adopted to help decipher disease etiology and to identify disease-specific biomarkers. In this chapter we will address the concept of EWAS by providing a background on genetic epidemiology studies to set a historical context for the initiation of genome-wide association studies (GWAS) that paved the way for widespread adoption of EWAS. We will introduce the field of epigenetics focusing on DNA methylation and address specific considerations for EWAS study design, sample selection, sample heterogeneity and confounding. Lastly, will review past, present and emerging technologies for genome-wide DNA methylation detection that can be used to perform EWAS studies, to showcase their advantages and shortcomings.
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