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LipidCreator

Generation of targeted MS assays for lipids

Description

LipidCreator is a lipid building block-based workbench and knowledge base for the automated generation of targeted lipidomics mass spectrometry assays and in-silico spectral libraries. Assay generation can be conducted with a graphical user interface (GUI) or on the command line, covering lipids of the following categories: sphingolipids (SL), glycerolipids (GL), glycerophospholipids (PL), sterols and its derivates, and fatty acids, including mediators (LM). LipidCreator can calculate masses for lipid species and their derived fragment ions, covering over 60 lipid classes and a lipid array of 1012 lipid molecules with a consensus nomenclature.

Technical Information

License:
MIT (academic) / commercial license (commercial use)
GUI:
Yes
CLI:
Yes
Desktop client:
Yes
Web platform:
No
Input formats:
CSV
Output formats:
CSV
Platforms:
Linux,
Windows
Programming languages:
C#
Publications:
PMID:32345972

Tasks

3) Analysis of targeted lipidomics datasets (SRM, MRM, PRM)
Strategies:
DIA,
PRM,
MRM,
SRM
Covered lipid sub classes:
5 out of 8 LIPID MAPS categories (PL, GL, SP, ST, FA)
Number of transitions in the database:
NA, on-fly/on-demand transition generation
Experimentally optimized transitions:
1,487
Computationally optimized transitions:
1,487
Public repository transitions:
NA
Transitions for different collision energies available:
Yes
Algorithms:
LipidCreator generate in-silico spectral libraries and assays for targeted lipidomics analysis; requires skyline for the information for identification and quantification.
Quantification:
Relative and absolute (support building calibration curves)
Interactive analysis and visualization support:
Yes
Scores:
Library Probability Score via Skyline
Spectra annotation:
Yes
Other features:
In silico Spectral Library & Collision Energy Optimization,
Support heavy labelled isotopes,
Support user defined fragments
Workflow integration:
It can be integrated into KNIME and Galaxy workflows via command line interface