Department of Integrative Biology and Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA.
Interdepartmental Program of Molecular, Cellular and Integrative Physiology, University of California, Los Angeles, 610 Charles E. Young Drive East, Los Angeles, CA 90095, USA.
Nucleic Acids Res. 2021 Jul 2;49(W1):W375-W387. doi: 10.1093/nar/gkab405.
The Mergeomics web server is a flexible online tool for multi-omics data integration to derive biological pathways, networks, and key drivers important to disease pathogenesis and is based on the open source Mergeomics R package. The web server takes summary statistics of multi-omics disease association studies (GWAS, EWAS, TWAS, PWAS, etc.) as input and features four functions: Marker Dependency Filtering (MDF) to correct for known dependency between omics markers, Marker Set Enrichment Analysis (MSEA) to detect disease relevant biological processes, Meta-MSEA to examine the consistency of biological processes informed by various omics datasets, and Key Driver Analysis (KDA) to identify essential regulators of disease-associated pathways and networks. The web server has been extensively updated and streamlined in version 2.0 including an overhauled user interface, improved tutorials and results interpretation for each analytical step, inclusion of numerous disease GWAS, functional genomics datasets, and molecular networks to allow for comprehensive omics integrations, increased functionality to decrease user workload, and increased flexibility to cater to user-specific needs. Finally, we have incorporated our newly developed drug repositioning pipeline PharmOmics for prediction of potential drugs targeting disease processes that were identified by Mergeomics. Mergeomics is freely accessible at http://mergeomics.research.idre.ucla.edu and does not require login.
Mergeomics 网络服务器是一个灵活的在线工具,用于整合多组学数据,以推导出对疾病发病机制重要的生物学途径、网络和关键驱动因素,它基于开源的 Mergeomics R 包。该网络服务器以多组学疾病关联研究(GWAS、EWAS、TWAS、PWAS 等)的汇总统计数据作为输入,具有四个功能:标记相关性过滤 (MDF) 可纠正组学标记之间已知的相关性,标记集富集分析 (MSEA) 可检测与疾病相关的生物过程,Meta-MSEA 可检查来自各种组学数据集的生物过程的一致性,以及关键驱动分析 (KDA) 可识别与疾病相关途径和网络相关的关键调节剂。在版本 2.0 中,该网络服务器进行了广泛的更新和简化,包括更新用户界面、为每个分析步骤改进了教程和结果解释、纳入了许多疾病 GWAS、功能基因组学数据集和分子网络,以实现全面的组学整合、增加功能以减少用户工作量以及提高灵活性以满足用户的特定需求。最后,我们整合了新开发的药物重定位管道 PharmOmics,用于预测通过 Mergeomics 鉴定的潜在药物。Mergeomics 可在 http://mergeomics.research.idre.ucla.edu 免费访问,无需登录。