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Updated: Jul 10, 2025

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Sample Preparation Strategies for Mass Spectrometry Imaging of 3D Cell Culture Models
Published on: December 5, 2014
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Cardinal v.3: a versatile open-source software for mass spectrometry imaging analysis
Kylie Ariel Bemis1, Melanie Christine Föll1,2,3, Dan Guo1
1Khoury College of Computer Sciences, Northeastern University, Boston, MA, USA.
Nature Methods
|November 23, 2023
Summary
Cardinal v.3 is open-source software for reproducible mass spectrometry imaging analysis. This major update enhances data processing, statistical analysis, and memory efficiency for large experiments.
Area of Science:
- Computational Biology
- Analytical Chemistry
- Biotechnology
Background:
- Mass spectrometry imaging (MSI) is a powerful technique for spatial molecular analysis.
- Reproducible and efficient analysis of MSI data is crucial for scientific advancement.
- Existing software may have limitations in handling complex MSI workflows and large datasets.
Purpose of the Study:
- To introduce Cardinal v.3, a significant update to open-source software for MSI data analysis.
- To provide a comprehensive tool supporting diverse MSI experimental workflows.
- To enhance reproducibility and efficiency in MSI data analysis.
Main Methods:
- Cardinal v.3 offers advanced data processing, including mass recalibration.
- It incorporates sophisticated statistical analyses like single-ion segmentation and annotation-based classification.
- The software is designed for memory-efficient analysis of large-scale, multitissue MSI experiments.
Main Results:
- Cardinal v.3 supports a wide range of mass spectrometry imaging workflows.
- The updated software facilitates advanced data processing and statistical analysis.
- It enables efficient handling of large-scale MSI datasets, improving analytical capabilities.
Conclusions:
- Cardinal v.3 represents a major advancement in open-source software for reproducible MSI analysis.
- The software's enhanced capabilities support complex MSI workflows and large datasets.
- It is a valuable tool for researchers in computational biology and analytical chemistry.
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