Liu Chia-Hsin, Shen Pei-Chun, Tsai Meng-Hsin, Liu Hsiu-Cheng, Lin Wen-Jen, Lai Yo-Liang, Wang Yu-De, Hung Mien-Chie, Cheng Wei-Chung
Cancer Biology and Precision Therapeutics Center, China Medical University, Taichung 404328, Taiwan.
School of Medicine, China Medical University, Taichung 404328, Taiwan.
Bioinform Adv. 2025 Mar 10;5(1):vbaf047. doi: 10.1093/bioadv/vbaf047. eCollection 2025.
Lipidomics is a rapidly expanding field focused on studying lipid species and classes within biological systems. As the field evolves, there is an increasing demand for user-friendly, open-source software tools capable of handling large and complex datasets while keeping pace with technological advancements. LipidSig, a widely used web-based platform, has been instrumental in data analysis and visualization of lipidomics. However, its limitations become evident when users want to build customized workflows. To address the limitation, we developed a companion R package, LipidSigR, based on the R code of the LipidSig web platform.
LipidSigR offers greater flexibility, allowing researchers with basic R programming skills to modify and adapt workflows according to their needs. It has been rigorously tested following CRAN guidelines to ensure compatibility and reproducibility. In demonstrating its functionality, we analyze the case with commonly used experimental design, case versus control, in lipidomics studies. Researchers can follow the use case to explore the key capabilities and build customized lipidomics data analysis workflows using LipidSigR.
LipidSigR is freely available from https://lipidsig.bioinfomics.org/lipidsigr/index.html and https://github.com/BioinfOMICS/LipidSigR.
脂质组学是一个迅速发展的领域，专注于研究生物系统中的脂质种类和类别。随着该领域的不断发展，对用户友好的开源软件工具的需求日益增加，这些工具能够处理大型复杂数据集，同时跟上技术进步的步伐。LipidSig是一个广泛使用的基于网络的平台，在脂质组学的数据分析和可视化方面发挥了重要作用。然而，当用户想要构建定制的工作流程时，其局限性就变得明显了。为了解决这一局限性，我们基于LipidSig网络平台的R代码开发了一个配套的R包LipidSigR。
LipidSigR提供了更大的灵活性，使具有基本R编程技能的研究人员能够根据自己的需求修改和调整工作流程。它已按照CRAN指南进行了严格测试，以确保兼容性和可重复性。在展示其功能时，我们分析了脂质组学研究中常用的实验设计（病例与对照）的案例。研究人员可以按照该用例探索关键功能，并使用LipidSigR构建定制的脂质组学数据分析工作流程。
LipidSigR可从https://lipidsig.bioinfomics.org/lipidsigr/index.html和https://github.com/BioinfOMICS/LipidSigR免费获取。
