The rapid evolution of mass spectrometry (MS)-based lipidomics has enabled the 
simultaneous measurement of numerous lipid classes. With lipidomics datasets 
becoming increasingly available, lipidomic-focused software tools are required 
to facilitate data analysis as well as mining of public datasets, integrating 
lipidomics-unique molecular information such as lipid class, chain length, and 
unsaturation. To address this need, we developed lipidr, an open-source 
R/Bioconductor package for data mining and analysis of lipidomics datasets. 
lipidr implements a comprehensive lipidomic-focused analysis workflow for 
targeted and untargeted lipidomics. lipidr imports numerical matrices, Skyline 
exports, and Metabolomics Workbench files directly into R, automatically 
inferring lipid class and chain information from lipid names. Through 
integration with the Metabolomics Workbench API, users can search, download, and 
reanalyze public lipidomics datasets seamlessly. lipidr allows thorough data 
inspection, normalization, and uni- and multivariate analyses, displaying 
results as interactive visualizations. To enable interpretation of lipid class, 
chain length, and total unsaturation data, we also developed and implemented a 
novel lipid set enrichment analysis. A companion online guide with two live 
example datasets is presented at https://www.lipidr.org/. We expect that the 
ease of use and innovative features of lipidr will allow the lipidomics research 
community to gain novel detailed insights from lipidomics data.