Basic Medical School, Anhui Medical University, Hefei 230022, China.
National Center for Protein Sciences (Beijing), Beijing Proteome Research Center, Beijing Institute of Lifeomics, Beijing 102206, China.
Bioinformatics. 2023 Dec 1;39(12). doi: 10.1093/bioinformatics/btad708.
A variety of computational methods have been developed to identify functionally related gene modules from genome-wide gene expression profiles. Integrating the results of these methods to identify consensus modules is a promising approach to produce more accurate and robust results. In this application note, we introduce COMMO, the first web server to identify and analyze consensus gene functionally related gene modules from different module detection methods. First, COMMO implements eight state-of-the-art module detection methods and two consensus clustering algorithms. Second, COMMO provides users with mRNA and protein expression data for 33 cancer types from three public databases. Users can also upload their own data for module detection. Third, users can perform functional enrichment and two types of survival analyses on the observed gene modules. Finally, COMMO provides interactive, customizable visualizations and exportable results. With its extensive analysis and interactive capabilities, COMMO offers a user-friendly solution for conducting module-based precision medicine research.
COMMO web is available at https://commo.ncpsb.org.cn/, with the source code available on GitHub: https://github.com/Song-xinyu/COMMO/tree/master.
已经开发了多种计算方法来从全基因组基因表达谱中识别功能相关的基因模块。整合这些方法的结果以识别共识模块是产生更准确和稳健结果的一种有前途的方法。在本应用说明中，我们介绍了 COMMO，这是第一个用于从不同模块检测方法中识别和分析共识基因功能相关基因模块的网络服务器。首先，COMMO 实现了八种最先进的模块检测方法和两种共识聚类算法。其次，COMMO 为用户提供了来自三个公共数据库的 33 种癌症类型的 mRNA 和蛋白质表达数据。用户也可以上传自己的数据进行模块检测。第三，用户可以对观察到的基因模块执行功能富集和两种类型的生存分析。最后，COMMO 提供了交互式、可定制的可视化和可导出的结果。凭借其广泛的分析和交互功能，COMMO 为基于模块的精准医学研究提供了一个用户友好的解决方案。
COMMO 网络可在 https://commo.ncpsb.org.cn/ 上访问，其源代码可在 GitHub 上获得：https://github.com/Song-xinyu/COMMO/tree/master。
