
LipidXplorer
Desktop Win macOS LinuxIdentifies lipids from shotgun (direct-infusion) high-resolution MS data via user-defined MFQL queries.
Our mission is to provide the bioinformatic framework to understand lipids in context and create an integrative systems biology view for lipid research.
Check out the tools we develop and provide below!
Showing
The full LIFS suite, in workflow order.
Step 2
Shotgun data: LipidXplorer, then lxPostman. Targeted data: LipidCreator, then Skyline.

Identifies lipids from shotgun (direct-infusion) high-resolution MS data via user-defined MFQL queries.

R Shiny application to post-process, quality-control and quantify LipidXplorer output.

Builds targeted MS assays and in-silico spectral libraries across 60+ lipid classes, then exports them to Skyline.

Opens vendor raw files, integrates peaks and quantifies the transitions designed in LipidCreator. Developed by the MacCoss Lab, University of Washington.
Step 3
Compare whole lipidomes, find the lipids that differ, and test lipid and other omics features for GO-term enrichment.

Compares whole lipidomes through a structural-space model, with machine-learning feature selection, QC and an interactive GUI.

Interactive visualisation and analysis of lipidomics datasets in a neural-network vector space built from LIPID MAPS and SwissLipids.

GO-term enrichment for lipid, metabolite, protein and transcript features with their abundances or counts, honouring the hierarchy of lipid shorthand names.
Step 4
Report the methods behind your results, validate your files and deposit results and metadata together.

Reports the analytical, identification and quantification methods behind your results, step by step. The basis for mzTab-M metadata; PDF export and an optional Zenodo DOI.

A database for collecting, querying and sharing curated quantitative lipidomics datasets: results together with their method metadata. In beta: sign in and an account is created for you.

Web validator and REST API for mzTab 2.0-M and mzTab 1.0 reporting files.
A standard format for reporting quantitative mass spectrometry metabolomics results in a tab-separated file.
A standard for reporting and exchanging quality control metrics for mass spectrometry runs and datasets.
Every step
One naming standard, built into LipidCreator, lxPostman and LipidSpace.

Parses the many lipid nomenclatures and serialises them back to standardised LIPID MAPS shorthand. Libraries in C++, Python, Java and R.
No tool matches that task yet — ask the LIFS team.
Skyline screenshot cropped from Fig. 1c of Peng, B., Kopczynski, D., Pratt, B.S. et al. LipidCreator workbench to probe the lipidomic landscape. Nat Commun 11, 2057 (2020), licensed under CC BY 4.0.