Lipid-Pro: a computational lipid identification solution for untargeted lipidomics on data-independent acquisition tandem mass spectrometry platforms
Author(s) -
Zeeshan Ahmed,
Michel Mayr,
Saman Zeeshan,
Thomas Dandekar,
Martin J. Mueller,
Ágnes Fekete
Publication year - 2014
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btu796
Subject(s) - lipidomics , mass spectrometry , tandem mass spectrometry , chemistry , lipid metabolism , identification (biology) , liquid chromatography–mass spectrometry , proteomics , computational biology , chromatography , database , computer science , biochemistry , biology , botany , gene
A major challenge for mass spectrometric-based lipidomics, aiming at describing all lipid species in a biological sample, lies in the computational and bioinformatic processing of the large amount of data that arises after data acquisition. Lipid-Pro is a software tool that supports the identification of lipids by interpreting large datasets generated by liquid chromatography--tandem mass spectrometry (LC-MS/MS) using the advanced data-independent acquisition mode MS(E). In the MS(E) mode, the instrument fragments all molecular ions generated from a sample and records time-resolved molecular ion data as well as fragment ion data for every detectable molecular ion. Lipid-Pro matches the retention time-aligned mass-to-charge ratio data of molecular- and fragment ions with a lipid database and generates a report on all identified lipid species. For generation of the lipid database, Lipid-Pro provides a module for construction of lipid species and their fragments using a flexible building block approach. Hence, Lipid-Pro is an easy to use analysis tool to interpret complex MS(E) lipidomics data and also offers a module to generate a user-specific lipid database.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom