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Processing methods for differential analysis of LC/MS profile data
BACKGROUND: Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order...
Autores principales: | , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2005
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1187873/ https://www.ncbi.nlm.nih.gov/pubmed/16026613 http://dx.doi.org/10.1186/1471-2105-6-179 |
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author | Katajamaa, Mikko Orešič, Matej |
author_facet | Katajamaa, Mikko Orešič, Matej |
author_sort | Katajamaa, Mikko |
collection | PubMed |
description | BACKGROUND: Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order to elucidate the observed phenotypes and discover biomarkers. One of the major challenges in this domain remains development of better solutions for processing of LC/MS data. RESULTS: We present a software package MZmine that enables differential LC/MS analysis of metabolomics data. This software is a toolbox containing methods for all data processing stages preceding differential analysis: spectral filtering, peak detection, alignment and normalization. Specifically, we developed and implemented a new recursive peak search algorithm and a secondary peak picking method for improving already aligned results, as well as a normalization tool that uses multiple internal standards. Visualization tools enable comparative viewing of data across multiple samples. Peak lists can be exported into other data analysis programs. The toolbox has already been utilized in a wide range of applications. We demonstrate its utility on an example of metabolic profiling of Catharanthus roseus cell cultures. CONCLUSION: The software is freely available under the GNU General Public License and it can be obtained from the project web page at: . |
format | Text |
id | pubmed-1187873 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-11878732005-08-18 Processing methods for differential analysis of LC/MS profile data Katajamaa, Mikko Orešič, Matej BMC Bioinformatics Software BACKGROUND: Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order to elucidate the observed phenotypes and discover biomarkers. One of the major challenges in this domain remains development of better solutions for processing of LC/MS data. RESULTS: We present a software package MZmine that enables differential LC/MS analysis of metabolomics data. This software is a toolbox containing methods for all data processing stages preceding differential analysis: spectral filtering, peak detection, alignment and normalization. Specifically, we developed and implemented a new recursive peak search algorithm and a secondary peak picking method for improving already aligned results, as well as a normalization tool that uses multiple internal standards. Visualization tools enable comparative viewing of data across multiple samples. Peak lists can be exported into other data analysis programs. The toolbox has already been utilized in a wide range of applications. We demonstrate its utility on an example of metabolic profiling of Catharanthus roseus cell cultures. CONCLUSION: The software is freely available under the GNU General Public License and it can be obtained from the project web page at: . BioMed Central 2005-07-18 /pmc/articles/PMC1187873/ /pubmed/16026613 http://dx.doi.org/10.1186/1471-2105-6-179 Text en Copyright © 2005 Katajamaa and Orešič; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Katajamaa, Mikko Orešič, Matej Processing methods for differential analysis of LC/MS profile data |
title | Processing methods for differential analysis of LC/MS profile data |
title_full | Processing methods for differential analysis of LC/MS profile data |
title_fullStr | Processing methods for differential analysis of LC/MS profile data |
title_full_unstemmed | Processing methods for differential analysis of LC/MS profile data |
title_short | Processing methods for differential analysis of LC/MS profile data |
title_sort | processing methods for differential analysis of lc/ms profile data |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1187873/ https://www.ncbi.nlm.nih.gov/pubmed/16026613 http://dx.doi.org/10.1186/1471-2105-6-179 |
work_keys_str_mv | AT katajamaamikko processingmethodsfordifferentialanalysisoflcmsprofiledata AT oresicmatej processingmethodsfordifferentialanalysisoflcmsprofiledata |