Oral Presentation 24th Annual Lorne Proteomics Symposium 2019

Lipidr: targeted lipidomics analysis workflow in R (#29)

Ahmed Mohamed 1 , Jeffrey Molendijk 1 2 , Thi-My-Tham Nguyen 2 , Johanna Barclay 3 , Federico Torta 4 , Markus Wenk 4 5 , Mark Hodson 6 , Michelle M Hill 1 2
  1. QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
  2. The University of Queensland Diamantina Institute, Woolloongabba, QLD, Australia
  3. Mater Research Institute, The University of Queensland, Translational Research Institute, Woolloongabba, QLD, Australia
  4. Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Medical Dr, Singapore
  5. Department of Biological Sciences, National University of Singapore, Singapore
  6. Victor Chang Research Institute, Sydney, NSW, Australia

Mass spectrometry (MS)-based lipidomics is an emerging field, which enables simultaneous measurement of numerous lipid classes. In particular, multiple reaction monitoring (MRM) MS assays measure targeted lipids with high quantitative precision and reproducibility. Several methods have been reported for lipidomics analysis, which target different lipid molecules depending on the biological applications. While spectrum inspection and peak integration are often performed in Skyline or other vendor software, strikingly, software tools are still lacking for downstream analysis of targeted lipidomics, hampering data interpretation. Moreover, although molecular information such as chain length and unsaturation is readily obtained in MS experiments, it is not utilized in current downstream analysis workflows. Here, we present lipidr, an easy-to-use R package implementing a complete workflow for downstream analysis of lipidomics data. lipidr parses results exported from Skyline directly into R, allowing integration into current analysis frameworks. lipidr allows data inspection, normalization, univariate and multivariate analysis, displaying informative visualizations. We also implemented a novel Lipid Set Enrichment Analysis (LSEA), harnessing molecular information such as lipid class, chain length and unsaturation. We demonstrate the use of lipidr, along with in-house developed MRM assays, to analyse serum lipids from mice fed an experimental high-fat diet. A companion step-by-step guide is provided with lipidr allowing users effectively utilize the package, even with limited programming experience.