Tools - LIFS Tools web portal

This virtual reporting checklist summarises key details of all steps of lipidomic workflows, such as how to collect and store samples, extract lipids, perform mass spectrometric analysis, perform data processing, and how to report results (see related commentary). This questionnaire will create a PDF document that may be linked to any study containing lipidomic data. The aim is to give editors and reviewers an easy overview regarding the quality and completeness of lipidomic data, to further harmonise the field, and to improve the quality of lipidomic analyses. When using the reporting checklist, please cite the checklist.

Go to 'Reporting Checklist' server

Citing the checklist
Please reference the minimal reporting checklist by citing the following publication:
McDonald, J.G., Ejsing, C.S., Kopczynski, D. et al. Introducing the lipidomics minimal reporting checklist Nature Metabolism 4(9), 1086-1088 (2022). https://doi.org/10.1038/s42255-022-00628-3
Kopczynski, D., Ejsing, C.S., McDonald, J.G.et al. The lipidomics reporting checklist a framework for transparency of lipidomic experiments and repurposing resource data Journal of lipid research 65(9), (2024). https://doi.org/10.1016/j.jlr.2024.100621

MAPtoGO is the first tool designed for GO term enrichment analysis across the three major MS-based omics fields: proteomics, lipidomics, metabolomics, and transcriptomics. It begins with a background list of identified biomolecules and a separate list of (differentially) regulated biomolecules, mapping each entry through proteins involved in metabolic reactions. GO term analysis is conducted using a statistical test that is based on this mapping. Depending on the chosen domain—biological process, molecular function, cellular compartment, physical or chemical properties, or metabolic and signaling pathways—the analysis generates a ranked list of GO terms, each accompanied by a p-value.

Go to 'MAPtoGO' server

The LipidXte web application provides automatic correction for lipid HCD MS/MS spectra from Orbitrap instruments and is dedicated to supporting accurate quantification of molecular lipid species. The application is specifically designed to support easy access to established correction functions with minimum interference requirements.

Kai Schuhmann, HongKee Moon, Henrik Thomas, Jacobo Miranda Ackerman, Michael Groessl, Nicolai Wagner, Markus Kellmann, Ian Henry, André Nadler, and Andrej Shevchenko.
Quantitative Fragmentation Model for Bottom-Up Shotgun Lipidomics.
Analytical Chemistry 2019 91 (18), 12085-12093
DOI: 10.1021/acs.analchem.9b03270

Reference validator for mzTab 2.0-M

mzTab 2.0 for metabolomics is a data exchange format for mass-spectrometry-based experimental data from the "omics" and neighboring sciences, focusing on small molecules like metabolites and lipids.

It is hierarchically organized, from metadata to summary information to ms features and evidence,
captures quantitative and qualitative information about reported molecules for individual ms runs and aggregated across study variables,
follows minimum recommended reporting guidelines for omics experiments, and
provides structural, logical and semantic (controlled vocabulary terms) validation.

This application provides a web-based validator for mzTab 2.0-M and the prior mzTab version 1.0 (mainly for proteomics) below, and a REST API for programmatic validation against mzTab 2.0-M.

It is based on the jmzTab-M reference implementation.