Open-source software for the lipidomics workflow

Parses the many lipid nomenclatures and the LIPID MAPS shorthand into an internal data model, then serializes it back to standardized LIPID MAPS shorthand. Libraries in C++, Python, Java and R.

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

An 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 for acquisition and identification.

Open-source environment for building and analysing targeted MS methods; LipidCreator runs as a Skyline external tool. Developed by the MacCoss Lab.

Compares whole lipidomes through a structural-space model, with machine-learning feature selection, QC and an interactive GUI. Also available as a REST Docker container.

Performs transcript, protein, metabolite and lipid overexpression / enrichment analysis onto GO terms, using an internal knowledge graph synthesized from public pathway and reaction databases — and honours the hierarchical structure of lipid shorthand names.

A database for collecting, querying and sharing curated quantitative lipidomics datasets.

A standard for reporting and exchanging quality control metrics for mass spectrometry runs and datasets.

A standard format for reporting quantitative mass spectrometry metabolomics results in a tab-separated values file.

A lipidomics scoring system that rates the quality and confidence of lipid identifications, awarding points across MS, MS/MS, chromatography and ion-mobility evidence. Available as an R package and an interactive Shiny web app.