Lin Qiong, Wagner Wolfgang, Zenke Martin
Institute for Biomedical Engineering-Cell Biology, RWTH Aachen University Medical School, Aachen, Germany.
Methods Mol Biol. 2013;1049:21-33. doi: 10.1007/978-1-62703-547-7_3.
This chapter covers the genome-wide DNA methylation analysis using microarray platforms, such as Illumina Infinium HumanMethylation27 BeadChips or HumanMethylation450 BeadChips. Using our previously published ovarian cancer dataset (Bauerschlag et al., Oncology 80:12-20, 2011), we introduce the underlying design principles of these methylation array platforms and describe common yet effective bioinformatic strategies for data analysis, including data preprocessing, clustering methods, and differential methylation tests. We also describe the downstream analytic techniques for the results derived from the methylation array, i.e., gene set enrichment analysis and sequence-based motif analysis, which can be utilized for generating biological hypotheses.
本章介绍了使用微阵列平台进行全基因组DNA甲基化分析，如Illumina Infinium HumanMethylation27 BeadChips或HumanMethylation450 BeadChips。利用我们之前发表的卵巢癌数据集（Bauerschlag等人，《肿瘤学》80:12 - 20，2011），我们介绍了这些甲基化阵列平台的基本设计原理，并描述了常见且有效的数据分析生物信息学策略，包括数据预处理、聚类方法和差异甲基化测试。我们还描述了从甲基化阵列得出的结果的下游分析技术，即基因集富集分析和基于序列的基序分析，这些技术可用于生成生物学假设。
