Abstract

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.

Details

Title
Fast visual exploration of mass spectrometry images with interactive dynamic spectral similarity pseudocoloring
Author
Wüllems Karsten 1 ; Zurowietz Annika 2 ; Zurowietz Martin 3 ; Schneider, Roland 2 ; Bednarz, Hanna 2 ; Niehaus Karsten 2 ; Nattkemper Tim W 4 

 Bielefeld University, International Research Training Group “Computational Methods for the Analysis of the Diversity and Dynamics of Genomes”, Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128); Bielefeld University, Biodata Mining Group, Faculty of Technology, Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128); Bielefeld University, Center for Biotechnology (CeBiTec), Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128) 
 Bielefeld University, Center for Biotechnology (CeBiTec), Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128); Bielefeld University, Proteome and Metabolome Research, Faculty of Biology, Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128) 
 Bielefeld University, Biodata Mining Group, Faculty of Technology, Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128) 
 Bielefeld University, Biodata Mining Group, Faculty of Technology, Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128); Bielefeld University, Center for Biotechnology (CeBiTec), Bielefeld, Germany (GRID:grid.7491.b) (ISNI:0000 0001 0944 9128) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2493256811
Copyright
© The Author(s) 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.