lipidr: A Software Tool for Data Mining and Analysis of Lipidomics Datasets

Abstract

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, 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 allow the lipidomics research community to gain novel detailed insights from lipidomics data.

Molecular and functional profiling of apical versus basolateral small extracellular vesicles derived from primary human proximal tubular epithelial cells under inflammatory conditions

“…The acquired lipidomics data was processed in Skyline for peak integration (Maclean et al., 2010) and data for 77 lipids was exported. Lipidomics data analysis was performed using the lipidr R package (Mohamed et al., 2020). Briefly, raw data was log 2 transformed and normalized using the probabilistic quotient normalization method (Dieterle et al., 2006).…”

Chronic High-Fat Diet Induces Early Barrett’s Esophagus in Mice through Lipidome Remodeling

“…All datasets were log2 transformed and normalized using the probabilistic quotient normalization method as described by Dieterle et al [35]. Lipid information such as lipid class, number of unsaturated bonds and fatty acid chain lengths were parsed from the original lipid names using the lipidr R package [36]. Further analyses and visualizations, including principal component analysis (PCA) and lipid class boxplots were produced using lipidr [36].…”

“…Lipid information such as lipid class, number of unsaturated bonds and fatty acid chain lengths were parsed from the original lipid names using the lipidr R package [36]. Further analyses and visualizations, including principal component analysis (PCA) and lipid class boxplots were produced using lipidr [36]. The enrichment of lipid classes was determined using the LSEA (lipid set enrichment analysis method) [36].…”

“…Further analyses and visualizations, including principal component analysis (PCA) and lipid class boxplots were produced using lipidr [36]. The enrichment of lipid classes was determined using the LSEA (lipid set enrichment analysis method) [36]. Pearson correlation was used to determine the correlation between total lipid fatty acid chain lengths and the development of disease conditions.…”

New software tools, databases, and resources in metabolomics: updates from 2020

“…lipidr, is an R/Bioconductor-package for data mining and analysis of lipidomics datasets that implements a lipidomic-focused analysis workflow for targeted and untargeted lipidomics (Mohamed et al 2020 ). lipidr imports numerical matrices, Skyline exports, and Metabolomics Workbench files directly into R interface, and allows thorough data inspection, normalization, and uni- and multivariate analyses, resulting in interactive visualizations as well as a novel lipid set enrichment analysis.…”