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massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics

INTRODUCTION: Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools. OBJECTIVES: We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue. METHODS: massPix produces single...

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Detalles Bibliográficos
Autores principales: Bond, Nicholas J., Koulman, Albert, Griffin, Julian L., Hall, Zoe
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608769/
https://www.ncbi.nlm.nih.gov/pubmed/28989334
http://dx.doi.org/10.1007/s11306-017-1252-5
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author Bond, Nicholas J.
Koulman, Albert
Griffin, Julian L.
Hall, Zoe
author_facet Bond, Nicholas J.
Koulman, Albert
Griffin, Julian L.
Hall, Zoe
author_sort Bond, Nicholas J.
collection PubMed
description INTRODUCTION: Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools. OBJECTIVES: We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue. METHODS: massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries. RESULTS: Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering. CONCLUSION: massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications.
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spelling pubmed-56087692017-10-05 massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics Bond, Nicholas J. Koulman, Albert Griffin, Julian L. Hall, Zoe Metabolomics Short Communication INTRODUCTION: Mass spectrometry imaging (MSI) experiments result in complex multi-dimensional datasets, which require specialist data analysis tools. OBJECTIVES: We have developed massPix—an R package for analysing and interpreting data from MSI of lipids in tissue. METHODS: massPix produces single ion images, performs multivariate statistics and provides putative lipid annotations based on accurate mass matching against generated lipid libraries. RESULTS: Classification of tissue regions with high spectral similarly can be carried out by principal components analysis (PCA) or k-means clustering. CONCLUSION: massPix is an open-source tool for the analysis and statistical interpretation of MSI data, and is particularly useful for lipidomics applications. Springer US 2017-09-21 2017 /pmc/articles/PMC5608769/ /pubmed/28989334 http://dx.doi.org/10.1007/s11306-017-1252-5 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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.
spellingShingle Short Communication
Bond, Nicholas J.
Koulman, Albert
Griffin, Julian L.
Hall, Zoe
massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics
title massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics
title_full massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics
title_fullStr massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics
title_full_unstemmed massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics
title_short massPix: an R package for annotation and interpretation of mass spectrometry imaging data for lipidomics
title_sort masspix: an r package for annotation and interpretation of mass spectrometry imaging data for lipidomics
topic Short Communication
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608769/
https://www.ncbi.nlm.nih.gov/pubmed/28989334
http://dx.doi.org/10.1007/s11306-017-1252-5
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