Bioinformatics Unit. GENYO. Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, Granada, Spain.
Atrys Health, Barcelona, Spain.
Bioinformatics. 2019 Sep 15;35(18):3257-3262. doi: 10.1093/bioinformatics/btz096.
The identification of differentially methylated regions (DMRs) among phenotypes is one of the main goals of epigenetic analysis. Although there are several methods developed to detect DMRs, most of them are focused on detecting relatively large differences in methylation levels and fail to detect moderate, but consistent, methylation changes that might be associated to complex disorders.
We present mCSEA, an R package that implements a Gene Set Enrichment Analysis method to identify DMRs from Illumina450K and EPIC array data. It is especially useful for detecting subtle, but consistent, methylation differences in complex phenotypes. mCSEA also implements functions to integrate gene expression data and to detect genes with significant correlations among methylation and gene expression patterns. Using simulated datasets we show that mCSEA outperforms other tools in detecting DMRs. In addition, we applied mCSEA to a previously published dataset of sibling pairs discordant for intrauterine hyperglycemia exposure. We found several differentially methylated promoters in genes related to metabolic disorders like obesity and diabetes, demonstrating the potential of mCSEA to identify DMRs not detected by other methods.
mCSEA is freely available from the Bioconductor repository.
Supplementary data are available at Bioinformatics online.
在表型之间识别差异甲基化区域（DMRs）是表观遗传分析的主要目标之一。尽管已经开发了几种方法来检测 DMRs，但大多数方法都侧重于检测甲基化水平的相对较大差异，而无法检测可能与复杂疾病相关的中等但一致的甲基化变化。
我们提出了 mCSEA，这是一个 R 包，它实现了一种基因集富集分析方法，用于从 Illumina450K 和 EPIC 阵列数据中识别 DMRs。它特别适用于检测复杂表型中的微妙但一致的甲基化差异。mCSEA 还实现了整合基因表达数据的功能，并检测出甲基化和基因表达模式之间存在显著相关性的基因。使用模拟数据集，我们表明 mCSEA 在检测 DMRs 方面优于其他工具。此外，我们将 mCSEA 应用于先前发表的宫内高血糖暴露的同胞对不一致的数据集。我们在与肥胖和糖尿病等代谢紊乱相关的基因中发现了几个差异甲基化的启动子，证明了 mCSEA 识别其他方法未检测到的 DMRs 的潜力。
mCSEA 可从 Bioconductor 存储库免费获得。
补充数据可在 Bioinformatics 在线获得。
