The software for interactive evaluation of mass spectra stability and reproducibility
E S Zhvansky1, A A Sorokin1, D S Bormotov1
1Phystech School of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow, Russia.
Bioinformatics (Oxford, England)
|December 28, 2020
Summary
We developed Spectra Similarity Matrix (SSM) Display software for rapid visual outlier detection in mass spectrometry (MS) profiles. This tool enhances accuracy and explainability in biological and medical data analysis, reducing operator experience requirements.
Area of Science:
- Analytical Chemistry
- Biotechnology
- Computational Biology
Background:
- Mass spectrometry (MS) is crucial for biological and medical sample analysis.
- Emerging MS techniques (DESI, REIMS, NESI) offer speed but increase spectral variability.
- Machine learning and statistical analyses are sensitive to outliers and variability in MS profiles.
Purpose of the Study:
- To introduce Spectra Similarity Matrix (SSM) Display software.
- To enable fast visual outlier detection and variance estimation in mass spectrometric profiles.
- To improve the accuracy and explainability of outlier detection in MS data.
Main Methods:
- Development of SSM Display software.
- Visual analysis of spectra similarity matrices.
- Application of SSM analysis for batch effect detection and ion source tuning.
Main Results:
- SSM Display software facilitates rapid visual inspection of MS profiles.
- The tool enhances the accuracy and explainability of outlier detection.
- SSM analysis effectively reveals batch effects and aids in tuning ion sources.
Conclusions:
- SSM Display software accelerates manual spectra inspection and reduces operator dependency.
- The software improves outlier detection accuracy and explainability in MS-based analyses.
- SSM calculation is valuable for quality control of novel ion sources and identifying batch effects.
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