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MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies

Based on theoretically calculated comprehensive lipid libraries, in lipidomics as many as 1000 multiple reaction monitoring (MRM) transitions can be monitored for each single run. On the other hand, lipid analysis from each MRM chromatogram requires tremendous manual efforts to identify and quantify...

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Autores principales: Tsugawa, Hiroshi, Ohta, Erika, Izumi, Yoshihiro, Ogiwara, Atsushi, Yukihira, Daichi, Bamba, Takeshi, Fukusaki, Eiichiro, Arita, Masanori
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4311682/
https://www.ncbi.nlm.nih.gov/pubmed/25688256
http://dx.doi.org/10.3389/fgene.2014.00471
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author Tsugawa, Hiroshi
Ohta, Erika
Izumi, Yoshihiro
Ogiwara, Atsushi
Yukihira, Daichi
Bamba, Takeshi
Fukusaki, Eiichiro
Arita, Masanori
author_facet Tsugawa, Hiroshi
Ohta, Erika
Izumi, Yoshihiro
Ogiwara, Atsushi
Yukihira, Daichi
Bamba, Takeshi
Fukusaki, Eiichiro
Arita, Masanori
author_sort Tsugawa, Hiroshi
collection PubMed
description Based on theoretically calculated comprehensive lipid libraries, in lipidomics as many as 1000 multiple reaction monitoring (MRM) transitions can be monitored for each single run. On the other hand, lipid analysis from each MRM chromatogram requires tremendous manual efforts to identify and quantify lipid species. Isotopic peaks differing by up to a few atomic masses further complicate analysis. To accelerate the identification and quantification process we developed novel software, MRM-DIFF, for the differential analysis of large-scale MRM assays. It supports a correlation optimized warping (COW) algorithm to align MRM chromatograms and utilizes quality control (QC) sample datasets to automatically adjust the alignment parameters. Moreover, user-defined reference libraries that include the molecular formula, retention time, and MRM transition can be used to identify target lipids and to correct peak abundances by considering isotopic peaks. Here, we demonstrate the software pipeline and introduce key points for MRM-based lipidomics research to reduce the mis-identification and overestimation of lipid profiles. The MRM-DIFF program, example data set and the tutorials are downloadable at the “Standalone software” section of the PRIMe (Platform for RIKEN Metabolomics, http://prime.psc.riken.jp/) database website.
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spelling pubmed-43116822015-02-16 MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies Tsugawa, Hiroshi Ohta, Erika Izumi, Yoshihiro Ogiwara, Atsushi Yukihira, Daichi Bamba, Takeshi Fukusaki, Eiichiro Arita, Masanori Front Genet Genetics Based on theoretically calculated comprehensive lipid libraries, in lipidomics as many as 1000 multiple reaction monitoring (MRM) transitions can be monitored for each single run. On the other hand, lipid analysis from each MRM chromatogram requires tremendous manual efforts to identify and quantify lipid species. Isotopic peaks differing by up to a few atomic masses further complicate analysis. To accelerate the identification and quantification process we developed novel software, MRM-DIFF, for the differential analysis of large-scale MRM assays. It supports a correlation optimized warping (COW) algorithm to align MRM chromatograms and utilizes quality control (QC) sample datasets to automatically adjust the alignment parameters. Moreover, user-defined reference libraries that include the molecular formula, retention time, and MRM transition can be used to identify target lipids and to correct peak abundances by considering isotopic peaks. Here, we demonstrate the software pipeline and introduce key points for MRM-based lipidomics research to reduce the mis-identification and overestimation of lipid profiles. The MRM-DIFF program, example data set and the tutorials are downloadable at the “Standalone software” section of the PRIMe (Platform for RIKEN Metabolomics, http://prime.psc.riken.jp/) database website. Frontiers Media S.A. 2015-01-30 /pmc/articles/PMC4311682/ /pubmed/25688256 http://dx.doi.org/10.3389/fgene.2014.00471 Text en Copyright © 2015 Tsugawa, Ohta, Izumi, Ogiwara, Yukihira, Bamba, Fukusaki and Arita. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Tsugawa, Hiroshi
Ohta, Erika
Izumi, Yoshihiro
Ogiwara, Atsushi
Yukihira, Daichi
Bamba, Takeshi
Fukusaki, Eiichiro
Arita, Masanori
MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies
title MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies
title_full MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies
title_fullStr MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies
title_full_unstemmed MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies
title_short MRM-DIFF: data processing strategy for differential analysis in large scale MRM-based lipidomics studies
title_sort mrm-diff: data processing strategy for differential analysis in large scale mrm-based lipidomics studies
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4311682/
https://www.ncbi.nlm.nih.gov/pubmed/25688256
http://dx.doi.org/10.3389/fgene.2014.00471
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