集群应用程序可视化,组织和导航代谢学数据
Vinicius Hansel1, Pothuvilage Karunarathne2, Tiago Cabral Borelli1
1Department of Biomolecular Sciences, Computational Chemical Biology Laboratory, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil.
bioRxiv : the preprint server for biology
|March 3, 2025
概括
集群应用程序为代谢学中主要坐标分析 (PCoA) 提供了一个用户友好的网络应用程序,简化了对没有广泛生物信息学专业知识的研究人员进行集群和数据可视化.
科学领域:
- 代谢学 代谢学 代谢学
- 生物信息学是一种生物信息学.
- 数据可视化 数据可视化
背景情况:
- 主要组件分析 (PCA) 在代谢学中很常见,但对于集群可视化来说是不理想的.
- 代谢学数据需要专门的预处理和高效的可视化工具.
- 缺乏用户友好的工具阻碍了许多研究人员进行集群分析.
研究的目的:
- 介绍ClusterApp,这是一个用于代谢学中主要坐标分析 (PCoA) 的网络应用程序.
- 提供一种可访问的工具,用于对代谢学数据进行聚类和可视化.
- 为代谢学研究人员扩大聚类替代方案,超越PCA.
主要方法:
- 集群应用程序使用QIIME 2 Docker图像进行PCoA计算和皇帝图形可视化.
- 支持GNPS,GNPS2或用户提供的电子表格的数据输入.
- 提供通过Docker进行本地安装或集成到Jupyter笔记本.
主要成果:
- 分析了来自小鼠组织和珊瑚生命阶段的LC-MS/MS代谢数据集.
- 布雷-库蒂斯不相似度有效突出了新陈代谢变异.
- 信息通信技术规范化和自动缩放提高了聚类分辨率,并揭示了明显的样本分离.
结论:
- 集群应用程序提供了可访问的,动态的工具,用于在代谢学探索性数据分析.
- 用PCoA对情侣数据进行转换,用于多功能集群分析.
- 使研究人员能够在没有高级生物信息学专业知识的情况下发现模式.
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