ClusterSculptor: Software for Expert-Steered Classification of Single Particle Mass Spectra
To take full advantage of the vast amount of highly detailed data acquired by single particle mass spectrometers requires that the data be organized according to some rules that have the potential to be insightful. Most commonly statistical tools are used to cluster the individual particle mass spectra on the basis of their similarity. Cluster analysis is a powerful strategy for the exploration of high-dimensional data in the absence of a-priori hypotheses or data classification models, and the results of cluster analysis can then be used to form such models. More often than not, when examining the data clustering results we find that many clusters contain particles of different types and that many particles of one type end up in a number of separate clusters. Our experience with cluster analysis shows that we have a vast amount of non-compiled knowledge and intuition that should be brought to bear in this effort. We will present new software we call ClusterSculptor that provides comprehensive and intuitive framework to aid scientists in data classification. ClusterSculptor uses k-means as the overall clustering engine, but allows tuning its parameters interactively, based on a non-distorted compact visual presentation of the inherent characteristics of the data in high-dimensional space. ClusterSculptor provides all the tools necessary for a high-dimensional activity we call cluster sculpting. ClusterSculptor is designed to be coupled to SpectraMiner, our data mining and visualization software package. The data are first visualized with SpectraMiner and identified problems are exported to ClusterSculptor, where the user steers the reclassification and recombination of clusters of tens of thousands particle mass spectra in real-time. The resulting sculpted clusters can be then imported back into SpectraMiner. Here we will greatly improved single particle chemical speciation in an example of application of this new tool to a number of particle types of atmospheric importance.
- Research Organization:
- Pacific Northwest National Lab. (PNNL), Richland, WA (United States). Environmental Molecular Sciences Lab. (EMSL)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC05-76RL01830
- OSTI ID:
- 943403
- Report Number(s):
- PNNL-SA-58233; 25632; 25639; KC0302020; TRN: US200902%%33
- Journal Information:
- International Journal of Mass Spectrometry, 275(1-3):1-10, Vol. 275, Issue 1-3
- Country of Publication:
- United States
- Language:
- English
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