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

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 ma...

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Autores principales: Manzini, Stefano, Busnelli, Marco, Colombo, Alice, Kiamehr, Mostafa, Chiesa, Giulia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7415148/
https://www.ncbi.nlm.nih.gov/pubmed/32770020
http://dx.doi.org/10.1038/s41598-020-70259-9
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author Manzini, Stefano
Busnelli, Marco
Colombo, Alice
Kiamehr, Mostafa
Chiesa, Giulia
author_facet Manzini, Stefano
Busnelli, Marco
Colombo, Alice
Kiamehr, Mostafa
Chiesa, Giulia
author_sort Manzini, Stefano
collection PubMed
description 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.
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spelling pubmed-74151482020-08-11 liputils: a Python module to manage individual fatty acid moieties from complex lipids Manzini, Stefano Busnelli, Marco Colombo, Alice Kiamehr, Mostafa Chiesa, Giulia Sci Rep Article 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. Nature Publishing Group UK 2020-08-07 /pmc/articles/PMC7415148/ /pubmed/32770020 http://dx.doi.org/10.1038/s41598-020-70259-9 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Manzini, Stefano
Busnelli, Marco
Colombo, Alice
Kiamehr, Mostafa
Chiesa, Giulia
liputils: a Python module to manage individual fatty acid moieties from complex lipids
title liputils: a Python module to manage individual fatty acid moieties from complex lipids
title_full liputils: a Python module to manage individual fatty acid moieties from complex lipids
title_fullStr liputils: a Python module to manage individual fatty acid moieties from complex lipids
title_full_unstemmed liputils: a Python module to manage individual fatty acid moieties from complex lipids
title_short liputils: a Python module to manage individual fatty acid moieties from complex lipids
title_sort liputils: a python module to manage individual fatty acid moieties from complex lipids
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7415148/
https://www.ncbi.nlm.nih.gov/pubmed/32770020
http://dx.doi.org/10.1038/s41598-020-70259-9
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