ArticleBioinformatics (Oxford, England)2019
Unsupervised segmentation of mass spectrometric ion images characterizes morphology of tissues.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- TIMSImaging: an open and interoperable workflow for trapped ion mobility mass spectrometry imaging data processing and visualization.Bioinformatics (Oxford, England) · 2026Article
- Spatial Distribution Characterization of Hormonal Metabolites in Morphologically Diverse Jujube Fruits via MALDI-MS Imaging.Foods (Basel, Switzerland) · 2026Article
- Statistical Principles Define an Open-Source Differential Analysis Workflow for Mass Spectrometry Imaging Experiments with Complex Designs.bioRxiv : the preprint server for biology · 2026Article
- spatialstein: An Open-Source Workflow for Annotation, Deconvolution, and Spatially Aware Segmentation of Mass Spectrometry Imaging Data.Analytical chemistry · 2026Article
- LipidLocator: an open source Shiny web application for spatial lipidomics.Bioinformatics advances · 2026Article
- Multimodal landscape of atherosclerotic plaques: A spatial omics approach with mass spectrometry imaging.Analytica chimica acta · 2025Review
- Cardinal v.3: a versatile open-source software for mass spectrometry imaging analysis.Nature methods · 2023Article
- A noise-robust deep clustering of biomolecular ions improves interpretability of mass spectrometric images.Bioinformatics (Oxford, England) · 2023Article
- Emerging Computational Methods in Mass Spectrometry Imaging.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Review
- Evaluation and comparison of unsupervised methods for the extraction of spatial patterns from mass spectrometry imaging data (MSI).Scientific reports · 2022Article
- Data parsing in mass spectrometry imaging using R Studio and Cardinal: A tutorial.Journal of mass spectrometry and advances in the clinical lab · 2022Article
- The emergence of imaging mass spectrometry in drug discovery and development: Making a difference by driving decision making.Journal of mass spectrometry : JMS · 2021Article
- Spatial Segmentation of Mass Spectrometry Imaging Data by Combining Multivariate Clustering and Univariate Thresholding.Analytical chemistry · 2021Article
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Authors and funding
5 authors.
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Abstract
motivationMass spectrometry imaging (MSI) characterizes the spatial distribution of ions in complex biological samples such as tissues. Since many tissues have complex morphology, treatments and conditions often affect the spatial distribution of the ions in morphology-specific ways. Evaluating the selectivity and the specificity of ion localization and regulation across morphology types is biologically important. However, MSI lacks algorithms for segmenting images at both single-ion and spatial resolution.
resultsThis article contributes spatial-Dirichlet Gaussian mixture model (DGMM), an algorithm and a workflow for the analyses of MSI experiments, that detects components of single-ion images with homogeneous spatial composition. The approach extends DGMMs to account for the spatial structure of MSI. Evaluations on simulated and experimental datasets with diverse MSI workflows demonstrated that spatial-DGMM accurately segments ion images, and can distinguish ions with homogeneous and heterogeneous spatial distribution. We also demonstrated that the extracted spatial information is useful for downstream analyses, such as detecting morphology-specific ions, finding groups of ions with similar spatial patterns, and detecting changes in chemical composition of tissues between conditions. AVAILABILITY AND IMPLEMENTATION: The data and code are available at https://github.com/Vitek-Lab/IonSpattern. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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