LipidSig: a web-based tool for lipidomic data analysis. Issue Volume 49:Issue W1(2021) (28th May 2021)

• Record Type: Journal Article
• Authors: Lin, Wen-Jen; Shen, Pei-Chun; Liu, Hsiu-Cheng; Cho, Yi-Chun; Hsu, Min-Kung; Lin, I-Chen; Chen, Fang-Hsin; Yang, Juan-Cheng; Ma, Wen-Lung; Cheng, Wei-Chung
• Is Part Of: Nucleic acids research. Volume 49:Issue W1(2021)
• Page Start: W336
• Page End: W345
• Publication Date: 2021-05-28
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkab419
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: With the continuing rise of lipidomic studies, there is an urgent need for a useful and comprehensive tool to facilitate lipidomic data analysis. The most important features making lipids different from general metabolites are their various characteristics, including their lipid classes, double bonds, chain lengths, etc. Based on these characteristics, lipid species can be classified into different categories and, more interestingly, exert specific biological functions in a group. In an effort to simplify lipidomic analysis workflows and enhance the exploration of lipid characteristics, we have developed a highly flexible and user-friendly web server called LipidSig. It consists of five sections, namely, Profiling, Differential Expression, Correlation, Network and Machine Learning, and evaluates lipid effects on cellular or disease phenotypes. One of the specialties of LipidSig is the conversion between lipid species and characteristics according to a user-defined characteristics table. This function allows for efficient data mining for both individual lipids and subgroups of characteristics. To expand the server's practical utility, we also provide analyses focusing on fatty acid properties and multiple characteristics. In summary, LipidSig is expected to help users identify significant lipid-related features and to advance the field of lipid biology. The LipidSig webserver is freely available at http://chenglab.cmu.edu.tw/lipidsig Graphical Abstract: