Xiong Yichun, Wei Yanjun, Gu Yue, Zhang Shumei, Lyu Jie, Zhang Bin, Chen Chuangeng, Zhu Jiang, Wang Yihan, Liu Hongbo, Zhang Yan
College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China.
Dan L. Duncan Cancer Center, Department of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX 77030, USA.
Nucleic Acids Res. 2017 Jan 4;45(D1):D888-D895. doi: 10.1093/nar/gkw1123. Epub 2016 Nov 29.
The human disease methylation database (DiseaseMeth, http://bioinfo.hrbmu.edu.cn/diseasemeth/) is an interactive database that aims to present the most complete collection and annotation of aberrant DNA methylation in human diseases, especially various cancers. Recently, the high-throughput microarray and sequencing technologies have promoted the production of methylome data that contain comprehensive knowledge of human diseases. In this DiseaseMeth update, we have increased the number of samples from 3610 to 32 701, the number of diseases from 72 to 88 and the disease-gene associations from 216 201 to 679 602. DiseaseMeth version 2.0 provides an expanded comprehensive list of disease-gene associations based on manual curation from experimental studies and computational identification from high-throughput methylome data. Besides the data expansion, we also updated the search engine and visualization tools. In particular, we enhanced the differential analysis tools, which now enable online automated identification of DNA methylation abnormalities in human disease in a case-control or disease-disease manner. To facilitate further mining of the disease methylome, three new web tools were developed for cluster analysis, functional annotation and survival analysis. DiseaseMeth version 2.0 should be a useful resource platform for further understanding the molecular mechanisms of human diseases.
人类疾病甲基化数据库（DiseaseMeth，网址：http://bioinfo.hrbmu.edu.cn/diseasemeth/）是一个交互式数据库，旨在呈现人类疾病尤其是各类癌症中异常DNA甲基化的最完整集合与注释。最近，高通量微阵列和测序技术推动了包含人类疾病全面知识的甲基化组数据的产生。在本次DiseaseMeth更新中，我们将样本数量从3610个增加到32701个，疾病数量从72种增加到88种，疾病-基因关联从216201个增加到679602个。DiseaseMeth 2.0版本基于对实验研究的人工整理和高通量甲基化组数据的计算识别，提供了一份扩展的疾病-基因关联综合列表。除了数据扩展，我们还更新了搜索引擎和可视化工具。特别是，我们增强了差异分析工具，现在这些工具能够以病例对照或疾病-疾病的方式在线自动识别人类疾病中的DNA甲基化异常。为便于进一步挖掘疾病甲基化组，我们开发了三个新的网络工具用于聚类分析、功能注释和生存分析。DiseaseMeth 2.0版本应该是进一步理解人类疾病分子机制的有用资源平台。
