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Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring
Mass Spectrometry Imaging (MSI) is an established and still evolving technique for the spatial analysis of molecular co-location in biological samples. Nowadays, MSI is expanding into new domains such as clinical pathology. In order to increase the value of MSI data, software for visual analysis is...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907387/ https://www.ncbi.nlm.nih.gov/pubmed/33633175 http://dx.doi.org/10.1038/s41598-021-84049-4 |
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author | Wüllems, Karsten Zurowietz, Annika Zurowietz, Martin Schneider, Roland Bednarz, Hanna Niehaus, Karsten Nattkemper, Tim W. |
author_facet | Wüllems, Karsten Zurowietz, Annika Zurowietz, Martin Schneider, Roland Bednarz, Hanna Niehaus, Karsten Nattkemper, Tim W. |
author_sort | Wüllems, Karsten |
collection | PubMed |
description | Mass Spectrometry Imaging (MSI) is an established and still evolving technique for the spatial analysis of molecular co-location in biological samples. Nowadays, MSI is expanding into new domains such as clinical pathology. In order to increase the value of MSI data, software for visual analysis is required that is intuitive and technique independent. Here, we present QUIMBI (QUIck exploration tool for Multivariate BioImages) a new tool for the visual analysis of MSI data. QUIMBI is an interactive visual exploration tool that provides the user with a convenient and straightforward visual exploration of morphological and spectral features of MSI data. To improve the overall quality of MSI data by reducing non-tissue specific signals and to ensure optimal compatibility with QUIMBI, the tool is combined with the new pre-processing tool ProViM (Processing for Visualization and multivariate analysis of MSI Data), presented in this work. The features of the proposed visual analysis approach for MSI data analysis are demonstrated with two use cases. The results show that the use of ProViM and QUIMBI not only provides a new fast and intuitive visual analysis, but also allows the detection of new co-location patterns in MSI data that are difficult to find with other methods. |
format | Online Article Text |
id | pubmed-7907387 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-79073872021-03-02 Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring Wüllems, Karsten Zurowietz, Annika Zurowietz, Martin Schneider, Roland Bednarz, Hanna Niehaus, Karsten Nattkemper, Tim W. Sci Rep Article Mass Spectrometry Imaging (MSI) is an established and still evolving technique for the spatial analysis of molecular co-location in biological samples. Nowadays, MSI is expanding into new domains such as clinical pathology. In order to increase the value of MSI data, software for visual analysis is required that is intuitive and technique independent. Here, we present QUIMBI (QUIck exploration tool for Multivariate BioImages) a new tool for the visual analysis of MSI data. QUIMBI is an interactive visual exploration tool that provides the user with a convenient and straightforward visual exploration of morphological and spectral features of MSI data. To improve the overall quality of MSI data by reducing non-tissue specific signals and to ensure optimal compatibility with QUIMBI, the tool is combined with the new pre-processing tool ProViM (Processing for Visualization and multivariate analysis of MSI Data), presented in this work. The features of the proposed visual analysis approach for MSI data analysis are demonstrated with two use cases. The results show that the use of ProViM and QUIMBI not only provides a new fast and intuitive visual analysis, but also allows the detection of new co-location patterns in MSI data that are difficult to find with other methods. Nature Publishing Group UK 2021-02-25 /pmc/articles/PMC7907387/ /pubmed/33633175 http://dx.doi.org/10.1038/s41598-021-84049-4 Text en © The Author(s) 2021 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Wüllems, Karsten Zurowietz, Annika Zurowietz, Martin Schneider, Roland Bednarz, Hanna Niehaus, Karsten Nattkemper, Tim W. Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring |
title | Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring |
title_full | Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring |
title_fullStr | Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring |
title_full_unstemmed | Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring |
title_short | Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring |
title_sort | fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7907387/ https://www.ncbi.nlm.nih.gov/pubmed/33633175 http://dx.doi.org/10.1038/s41598-021-84049-4 |
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