Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

中文翻译：

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EWAS数据中心：DNA甲基化阵列数据和元数据的资源。

表观基因组广泛关联研究（EWAS）已成为探索复杂性状表观遗传基础的有效策略。在过去的十年中，由于许多EWAS项目的结果，已经积累了大量的表观遗传数据，尤其是来自DNA甲基化阵列的表观遗传数据。我们介绍了EWAS数据中心（https://bigd.big.ac.cn/ewas/datahub），该资源用于收集和标准化DNA甲基化阵列数据以及归档相关的元数据。当前版本的EWAS Data Hub集成了来自75 344个样本的DNA甲基化阵列数据的全面收集，并采用有效的归一化方法来消除不同数据集之间的批处理效应。因此，利用大量高质量的DNA甲基化数据和标准化的元数据，EWAS数据中心可提供不同背景下的参考DNA甲基化概况，涉及81种组织/细胞类型（包含25个脑部和25种血细胞类型），6个祖先类别和67种疾病（包括39种癌症）。总而言之，EWAS数据中心具有巨大的前景，可以帮助检索和发现基于甲基化的生物标记物，用于表型表征，临床治疗和医疗保健。