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Guiding the choice of informatics software and tools for lipidomics research applications.

Authors :
Ni Z
Wölk M
Jukes G
Mendivelso Espinosa K
Ahrends R
Aimo L
Alvarez-Jarreta J
Andrews S
Andrews R
Bridge A
Clair GC
Conroy MJ
Fahy E
Gaud C
Goracci L
Hartler J
Hoffmann N
Kopczyinki D
Korf A
Lopez-Clavijo AF
Malik A
Ackerman JM
Molenaar MR
O'Donovan C
Pluskal T
Shevchenko A
Slenter D
Siuzdak G
Kutmon M
Tsugawa H
Willighagen EL
Xia J
O'Donnell VB
Fedorova M
Source :
Nature methods [Nat Methods] 2023 Feb; Vol. 20 (2), pp. 193-204. Date of Electronic Publication: 2022 Dec 21.
Publication Year :
2023

Abstract

Progress in mass spectrometry lipidomics has led to a rapid proliferation of studies across biology and biomedicine. These generate extremely large raw datasets requiring sophisticated solutions to support automated data processing. To address this, numerous software tools have been developed and tailored for specific tasks. However, for researchers, deciding which approach best suits their application relies on ad hoc testing, which is inefficient and time consuming. Here we first review the data processing pipeline, summarizing the scope of available tools. Next, to support researchers, LIPID MAPS provides an interactive online portal listing open-access tools with a graphical user interface. This guides users towards appropriate solutions within major areas in data processing, including (1) lipid-oriented databases, (2) mass spectrometry data repositories, (3) analysis of targeted lipidomics datasets, (4) lipid identification and (5) quantification from untargeted lipidomics datasets, (6) statistical analysis and visualization, and (7) data integration solutions. Detailed descriptions of functions and requirements are provided to guide customized data analysis workflows.<br /> (© 2022. Springer Nature America, Inc.)

Details

Language :
English
ISSN :
1548-7105
Volume :
20
Issue :
2
Database :
MEDLINE
Journal :
Nature methods
Publication Type :
Academic Journal
Accession number :
36543939
Full Text :
https://doi.org/10.1038/s41592-022-01710-0