easyEWAS: a flexible and user-friendly R package for epigenome-wide association study.

IF 2.8 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY Bioinformatics advances Pub Date : 2025-02-13 eCollection Date: 2025-01-01 DOI:10.1093/bioadv/vbaf026
Yuting Wang, Meijie Jiang, Siyuan Niu, Xu Gao
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Abstract

Motivation: Rapid advancements in high-throughput sequencing technologies especially the Illumina DNA methylation Beadchip greatly fuelled the surge in epigenome-wide association study (EWAS), providing crucial insights into intrinsic DNA methylation modifications associated with environmental exposure, diseases, and health traits. However, current tools are complex and less user-friendly to accommodate appropriate EWAS designs and make downstream analyses and result interpretations complicated, especially for clinicians and public health professionals with limited bioinformatic skills.

Results: We integrated the current state-of-the-art EWAS analysis methods and tools to develop a flexible and user-friendly R package easyEWAS for conducting DNA methylation-based research using Illumina DNA methylation Beadchips. With easyEWAS, we provide a battery of statistical methods to support differential methylation position analysis across various scenarios, as well as differential methylation region analysis based on the DMRcate method. To facilitate result interpretation, we provide comprehensive functional annotation and result visualization functionalities. Additionally, a bootstrap-based internal validation was incorporated into easyEWAS to ensure the robustness of EWAS results. Evaluation in asthma patients as the example demonstrated that easyEWAS could simplify and streamline the conduction of EWAS and corresponding downstream analyses, thus effectively advancing DNA methylation research in public health and clinical settings.

Availability and implementation: easyEWAS is implemented as an R package and is available at https://github.com/ytwangZero/easyEWAS.

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easyEWAS:用于全表观基因组关联研究的灵活且用户友好的 R 软件包。
动机:高通量测序技术的快速发展,尤其是Illumina DNA甲基化头芯片,极大地推动了表观基因组关联研究(EWAS)的激增,为研究与环境暴露、疾病和健康特征相关的内在DNA甲基化修饰提供了重要见解。然而,目前的工具很复杂,用户使用不便,无法适应适当的EWAS设计,并使下游分析和结果解释变得复杂,特别是对于生物信息学技能有限的临床医生和公共卫生专业人员。结果:我们整合了当前最先进的EWAS分析方法和工具,开发了一个灵活且用户友好的R包easyEWAS,用于使用Illumina DNA甲基化珠芯片进行基于DNA甲基化的研究。通过easyEWAS,我们提供了一系列统计方法来支持不同情况下的差异甲基化位置分析,以及基于DMRcate方法的差异甲基化区域分析。为了方便结果解释,我们提供了全面的功能注释和结果可视化功能。此外,在easyEWAS中加入了基于自举的内部验证,以确保EWAS结果的鲁棒性。以哮喘患者为例的评估表明,easyEWAS可以简化EWAS的传导和相应的下游分析,从而有效地推进公共卫生和临床环境中的DNA甲基化研究。可用性和实现:easyEWAS是作为R包实现的,可以在https://github.com/ytwangZero/easyEWAS上获得。
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