LipidMS

LipidMS: Lipid annotation for LC-MS/MS data


In the last years, lipidomics has emerged as a rapidly evolving tool in many fields of science. In our laboratory, we are particularly interested in unravelling the complex role of the wide range of lipids in the pathogenesis of disease (e.g. cancer). To this end, we are deeply committed in the development of workflows and tools focused on improving lipidome analysis and lipid annotation when liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS) approaches are used.

LipidMS
LipidMS is an R-package aimed to confidentially identify complex lipids in untargeted LC-MS DIA and DDA data analysis. The lipid identification is based on a set of fragmentation and intensity rules which allow to annotate lipids at different levels of confidence. A recent update of LipidMS allowed batch data processing from a number of mass spectrometry vendors (i.e., Thermo, Agilent). Currently, the data analysis workflow is also available as a web-based tool with a user-friendly interface.

New features included in LipidMS v3.0:
- Batch data processing: LipidMS covers the whole data processing workflow from peak-picking to alignment, grouping, peak filling and lipid annotation.
- New lipid classes: plasmanyl and plasmenyl PC and PE, acylceramides and ceramides phosphate.
- Lipid annotation for DIA and DDA data: from LipidMS 2.0 both acquisitions modes are implemented for annotation.
- Improved graphical outputs for lipid annotation.

Citation:
1. LipidMS: An R Package for Lipid Annotation in Untargeted Liquid Chromatography-Data Independent Acquisition-Mass Spectrometry Lipidomics. Anal Chem, 2019. (doi:10.1021/acs.analchem.8b03409) .
2. LipidMS 3.0: an R-package and a web-based tool for LC-MS/MS data processing and lipid annotation. bioRxiv, 2022. (doi.org/10.1101/2022.02.25.476005) .

References:
1. Peak-picking algorithm has been imported from enviPick R-package (Martin Loos) (https://CRAN.R-project.org/package=enviPick) .

LipidMS: Lipid annotation for LC-MS/MS data


LipidMS: Lipid annotation for LC-MS/MS data


dmzagglom (in ppm)
m/z tolerance used for partitioning and clustering. 15 by default.
drtagglom (in seconds)
rt window used for partitioning (in seconds). 500 by default.
drtclust (in seconds)
rt window used for clustering (in seconds). By default, 100 for MS1 and 200 for MS2.
minpeak
minimum number of measurements required for a peak. By default, 5 for MS1 and 4 for MS2.
minint
minimum intensity of a peak. By default, 1000 for MS1 and 100 for MS2.
drtgap (in seconds)
maximum rt gap length to be filled. 5 by default.
drtminpeak (in seconds)
minimum rt width of a peak. 15 by default. At least minpeak within the drtminpeak window are required to define a peak.
drtmaxpeak (in seconds)
maximum rt width of a single peak. By default, 100 for MS1 and 200 for MS2.
maxeicpeaks
maximum number of peaks within one EIC. By default, 5 for MS1 and 10 for MS2.
weight
weight for assigning measurements to a peak. By default, 2 for MS1 and 3 for MS2.
SN
signal-to-noise ratio. By default, 3 for MS1 and 2 for MS2.
SB
signal-to-base ratio. By default, 3 for MS1 and 2 for MS2.
dmzIso (in ppm)
mass tolerance for isotope matching. 5 by default.
drtIso
rt window for isotope matching. 5 by default.

LipidMS: Lipid annotation for LC-MS/MS data


dmzalign
mass tolerance between peak groups for alignment (in ppm). 5 by default.
drtalign
maximum rt distance between peaks for alignment (in seconds). 30 by default.
span
span parameter for loess rt smoothing. 0.4 by default.
minsamplesfracalign
minimum samples fraction represented in each cluster used for alignment. 0.75 by default.
dmzgroup
mass tolerance between peak groups for grouping (in ppm). 5 by default.
drtagglomgroup
maximum rt distance in mz partitions for grouping (in seconds). 30 by default. It shouldn't be smaller than drtgroup.
drtgroup
maximum rt distance between peaks for grouping (in seconds). 15 by default.
minsamplesfracgroup
minimum samples fraction represented in each cluster used for grouping. 0.25 by default.

LipidMS: Lipid annotation for LC-MS/MS data


dmzprecursor
mass tolerance for precursor ions. 5 by default.
dmzproducts
mass tolerance for product ions. 10 by default.
rttol
total rt window for coelution between precursor and product ions. 5 by default.
coelcutoff
coelution score threshold between parent and fragment ions. Only applied if rawData info is supplied. 0.7 by default.


LipidMS: Lipid annotation for LC-MS/MS data


LipidMS: Lipid annotation for LC-MS/MS data


Tutorials


Example workflow and data files


Source code


Old versions


Contact

Input data formats and tutorials can be found at the above links but, in case you have further questions or you find any bug, please send an email to maribel_alcoriza@iislafe.es with the required information (input data and parameters).

License

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

Citation:
1. LipidMS: An R Package for Lipid Annotation in Untargeted Liquid Chromatography-Data Independent Acquisition-Mass Spectrometry Lipidomics. Anal Chem, 2019. (doi:10.1021/acs.analchem.8b03409) .
References:
1. Peak-picking algorithm has been imported from enviPick R-package (Martin Loos) (https://CRAN.R-project.org/package=enviPick) .

LipidMS is intended to be used for research purposes only, without any medical objective.
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