Challenges in Lipidomics Biomarker Identification: Avoiding the Pitfalls and Improving Reproducibility.

ABSTRACT: Identification of features with high levels of confidence in liquid chromatography-mass spectrometry (LC-MS) lipidomics research is an essential part of biomarker discovery, but existing software platforms can give inconsistent results, even from identical spectral data. This poses a clear challenge for reproducibility in biomarker identification. In this work, we illustrate the reproducibility gap for two open-access lipidomics platforms, MS DIAL and Lipostar, finding just 14.0% identification agreement when analyzing identical LC-MS spectra using default settings. Whilst the software platforms performed more consistently using fragmentation data, agreement was still only 36.1% for MS² spectra. This highlights the critical importance of validation across positive and negative L

SUBMITTER: von Gerichten J 

PROVIDER: S-EPMC11356033 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature