Lipidomic analyses address the problem of characterizing the lipid components of given cells, tissues and organisms by means of chromatographic separations coupled to high-resolution, tandem mass spectrometry analyses. A number of software tools have been developed to help in the daunting task of mass spectrometry signal processing and cleaning, peak analysis and compound identification, and a typical finished lipidomic dataset contains hundreds to thousands of individual molecular lipid species. To provide researchers without a specific technical expertise in mass spectrometry the possibility of broadening the exploration of lipidomic datasets, we have developed liputils, a Python module that specializes in the extraction of fatty acid moieties from individual molecular lipids. there is no prerequisite data format, as liputils extracts residues from RefMet-compliant textual identifiers and from annotations of other commercially available services. We provide three examples of real- world data processing with liputils, as well as a detailed protocol on how to readily process an existing dataset that can be followed with basic informatics skills.

liputils: a python module to manage individual fatty acid moieties from complex lipids / S. Manzini, M. Busnelli, A. Colombo, M. Kiamehr, G. Chiesa. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 10:1(2020 Aug 07), pp. 13368.1-13368.9.

liputils: a python module to manage individual fatty acid moieties from complex lipids

S. Manzini
Co-primo
Software
;
M. Busnelli
Co-primo
Writing – Original Draft Preparation
;
A. Colombo
Writing – Review & Editing
;
G. Chiesa
Ultimo
Funding Acquisition
2020

Abstract

Lipidomic analyses address the problem of characterizing the lipid components of given cells, tissues and organisms by means of chromatographic separations coupled to high-resolution, tandem mass spectrometry analyses. A number of software tools have been developed to help in the daunting task of mass spectrometry signal processing and cleaning, peak analysis and compound identification, and a typical finished lipidomic dataset contains hundreds to thousands of individual molecular lipid species. To provide researchers without a specific technical expertise in mass spectrometry the possibility of broadening the exploration of lipidomic datasets, we have developed liputils, a Python module that specializes in the extraction of fatty acid moieties from individual molecular lipids. there is no prerequisite data format, as liputils extracts residues from RefMet-compliant textual identifiers and from annotations of other commercially available services. We provide three examples of real- world data processing with liputils, as well as a detailed protocol on how to readily process an existing dataset that can be followed with basic informatics skills.
Python; Lipidomics; omics, mass spectrometry; bioinformatics
Settore BIO/14 - Farmacologia
Settore BIO/16 - Anatomia Umana
Settore BIO/17 - Istologia
Personalized diagnostics and treatment of high risk coronary artery disease patients
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/782663
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