Lipidomics Tools Guide

LMAI team works closely with the community to support lipidomics workflows. Together with LIPID MAPS we designed a Lipidomics Tools Guide. Lipidomics Tools Guide summarizes multiple software tools with open access to the academic users addressing different steps in the lipidomics data processing pipeline including lipid-oriented databases, MS data repositories, analysis of targeted and untargeted lipidomics datasets, lipid quantification, statistical analysis, visualization, and data integration solutions.

LPPtiger2 is our flagship tool for analysis of oxidized complex lipids. It provides all-in-one-solution for our epilipidomics workflow, starting with knowledge based in silico prediction of modified lipids, in silico fragmentation using accurately defined rules, and identification from LC-MS/MS datasets. It also has the function to directly generate inclusion list for PRM experiments. LPPtiger2 provides interactive HTML output with its unique six-panel-image, which allows to review, store, and share the identification results.

Fragmentation patterns of oxidized complex lipids can be quite complex and require a lot of time for validation and accurate annotation. To speed up the epilipidomics workflow, we teamed up with the group of Laura Goracci from University of Perugia and linked LPPtiger2 with Lipostar2. Lipostar2 allows high-throughput processing of lipidomics datasets, and can filter out spectra of potentially oxidized lipids, which are send to LPPtiger2 for detailed identification and annotation. Results from both lipidomics and epilipidomics annotations are combined back by the Lipostar2, significantly speeding up data processing!

Want to use LPPtiger2? Check the tutorial video which will help you to start, or contact us if you need any help!

LipidHunter2 is capable to perform bottom-up identification of lipids from LC-MS/MS and shotgun lipidomics data by resembling a workflow of manual spectra annotation. LipidHunter provides interactive HTML output with its unique six-panel-image, which allows to review, store, and share the identification results.

Modern high throughput lipidomics provides large-scale datasets reporting hundreds of lipid molecular species. However, cross-laboratory comparison, meta-analysis, and systems biology integration of in-house generated and published datasets remain challenging due to a high diversity of used lipid annotation systems, different levels of reported structural information, and shortage in links to data integration resources. To support lipidomics data integration and interoperability of experimental lipidomics with data integration tools, we developed LipidLynxX serving as a hub facilitating data flow from high-throughput lipidomics analysis to systems biology data integration. LipidLynxX allows conversion from 25 different annotation styles, cross-matching of lipid datasets with different levels of structural confirmation, and linking of diverse lipid annotations to six different tools supporting lipid ontology, pathway, and network analysis aiming systems-wide integration and functional annotation of lipidome dynamics in health and disease. LipidLynxX is a flexible, customizable open-access tool freely available for download at as well as via web-interface on LIPID MAPS, at

LipidLynxX is directly integrated into the BioPAN software by LIPID MAPS to support fast conversion of different lipid annotation styles for the pathway analysis. Read more about BioPAN here ( F1000 Research 2021).

We also connected LipidLynxX with Lipostar2, to support fast conversion of the identification results in the preferred annotation style.

Want to use LipidLynxX? Check the tutorial video which will help you to start, or contact us if you need any help!

Detailed manual for lipid annotation from tandem MS/MS spectra

Accurate annotation of lipid molecular species from LC-MS/MS datasets can be quite exhausting and requires a lot of expertise! One needs to know the correct adducts your lipids form in positive and negative ionization mode, detailed fragmentation patters and potential in-source fragments, and mapping of retention times. We did it many times and collected all the information in the form of a Manual which can be useful to the community! Feel free to download it here.

Detailed manual for annotation of oxidized complex lipids from tandem MS/MS spectra

CID fragmentation of oxidized complex lipids allows identification of the subclass of modified lipid as well as the type and position of the modification. But this requires careful analysis of the fragmentation patterns. To facilitate further high-throughput annotation of oxidized complex lipids such as oxGPLs, oxCEs and oxTGs, we compiled our results obtained by fragmentation of oxylipin standards and in vitro oxidized lipids. 

We further supplemented it with available literature data on the fragmentation of oxidized free fatty acids and complex lipids as well as available MS2 spectra from METLIN, LIPID MAPS, and MS DIAL.msp library, in form of fragmentation rules exemplified here for different modification types and positions on oxidized oleoyl (18:1), linoleoyl (18:2), and arachidonoyl (20:4) chains in PC, CE and TG lipids. If you are interested in oxidized lipids identification,  feel free to download the manual here.

Tutorial for targeted lipid analysis using Skyline

Following our philosophy of sharing our lipid knowledge with the community, we created a tutorial for the targeted analysis of lipidomics data using Skyline. The tutorial walks you through the basic steps towards the relative quantification of lipids.  Feel free to download the manual here.

Open source datasets

Metabolomics Workbench:

Open access dataset “AdipoAtlas: A Reference Lipidome for Human White Adipose Tissue” at Metabolomics Workbench Study ID ST001738, Project DOI: 10.21228/M8ZM49.


Open access dataset “Epilipidomics platform for holistic profiling of oxidized complex lipids in blood plasma of obese individuals” at MassIVE MSV000088608, Project DOI: 10.25345/C5SG5C.

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