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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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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. |
format | Online Article Text |
id | pubmed-7415148 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
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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