LipidFinder is an open-source Python workflow which searches a number of
different databases to obtain putative identification of lipids, and assigns
them to a class based on the LIPID MAPS classification system. The software
quickly distinguishes and quantifies lipid-like features from contaminants,
adducts and noise in high resolution liquid chromatography/mass spectrometry
(LC/MS) datasets that have been pre-aligned using XCMS.
Note that your data needs to be high resolution MS (e.g. at least 60,000ppm)
and with long chromatography to separate isobaric lipids. The approach is not
suitable for shotgun lipidomics, MS/MS or low resolution datasets. Data
provided in our demo section used an Orbitrap Elite Mass Spectrometer, but
the software is MS platform independent.
We recommend the user to read the detailed
about LipidFinder before using the first time. Additionally, we have performed a
comparison analysis between XCMS (with different configurations) and XCMS + LipidFinder.
You can see the results
LipidFinder: A computational workflow for discovery of lipids identifies eicosanoid-phosphoinositides in platelets.
A. O'Connor, C.J. Brasher, D.A. Slatter, S.W. Meckelmann, J.I. Hawksworth, S.M. Allen and V.B. O'Donnell.
JCI Insight. 2017;2(7):e91634. doi:10.1172/jci.insight.91634
LipidFinder's source code for workstations is available on GitHub (https://github.com/ODonnell-Lipidomics/LipidFinder
which includes a parameter optimiser, multiple database classification and user manuals.
If you have any comments or suggestions, please send an e-mail to: