Abstract
Ion mobility (IM) spectrometry (IMS), coupled with multi-capillary columns (MCCs), has been gaining importance for biotechnological and medical applications because of its ability to measure volatile organic compounds (VOC) at extremely low concentrations in the air or exhaled breath at ambient pressure and temperature. Ongoing miniaturization of the devices creates the need for reliable data analysis on-the-fly in small embedded low-power devices. We present the first fully automated online peak extraction method for MCC/IMS spectra. Each individual spectrum is processed as it arrives, removing the need to store a whole measurement of several thousand spectra before starting the analysis, as is currently the state of the art. Thus the analysis device can be an inexpensive low-power system such as the Raspberry Pi.
The key idea is to extract one-dimensional peak models (with four parameters) from each spectrum and then merge these into peak chains and finally two-dimensional peak models. We describe the different algorithmic steps in detail and evaluate the online method against state-of-the-art peak extraction methods using a whole measurement.
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Kopczynski, D., Rahmann, S. (2014). An Online Peak Extraction Algorithm for Ion Mobility Spectrometry Data. In: Brown, D., Morgenstern, B. (eds) Algorithms in Bioinformatics. WABI 2014. Lecture Notes in Computer Science(), vol 8701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-44753-6_18
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DOI: https://doi.org/10.1007/978-3-662-44753-6_18
Publisher Name: Springer, Berlin, Heidelberg
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