OmicsBridge：连接多组学数据集并探索临床相关性的 Shiny 界面
OmicsBridge: A Shiny-based Interface for Bridging Omics Datasets and Exploring Clinical Relevance
OmicsBridge 是一个基于 R/Shiny 的免费、平台无关界面，用于整合和可视化多种组学数据集，提供超过 50 个可视化与分析模块，并作为集中式数据库减少重复上传数据。研究以 T 细胞趋化因子 CXCL10 表达为案例，通过多组学整合识别其病理生理相关分子决定因素、探索潜在机制并评估与癌症患者结局的关联。该工具旨在帮助缺乏专门生物信息学支持的实验室高效挖掘组学数据的临床相关性并生成假设，演示界面与本地部署源代码均已公开。
来源：Bioinformatics Advances · doi.org
Motivation
Comprehensive omics datasets are now routinely generated across diverse biological conditions, including in laboratories without dedicated bioinformatics support. When integrated and analyzed collectively, these datasets can uncover biologically meaningful relationships and molecular targets with potential clinical relevance. However, efficient integration and exploration of these datasets often require advanced computational workflows. Many existing tools are optimized for single-omics analysis or require users to re-upload datasets for each session, which becomes increasingly time-consuming and inefficient as dataset accumulate.
Results
We developed OmicsBridge, an intuitive and user-friendly platform for integrating and visualizing diverse omics datasets. OmicsBridge supports over 50 visualization and analysis modules, that help researchers identify genes with functional and clinical relevance and generate hypotheses. It also serves as a centralized database for efficient data storage and retrieval, reducing repetitive data uploads and improving data accessibility and workflow efficiency. As a case study, we used OmicsBridge to identify pathophysiologically relevant molecular determinants of T-cell chemoattractant CXCL10 expression, explore the underlying mechanisms, and assess their association with cancer patient outcomes through multi-omics integration.
Availability and implementation
OmicsBridge is freely available and platform-independent. A demo web interface is accessible at https://omicsbridge.dkfz.de, and the R/Shiny source code for local deployment is available at https://github.com/htsmto/OmicsBridge.