Limits...
An online peak extraction algorithm for ion mobility spectrometry data.

Kopczynski D, Rahmann S - Algorithms Mol Biol (2015)

Bottom Line: Each individual spectrum is processed as it arrives, removing the need to store the measurement 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.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics for High-Throughput Technologies, Computer Science XI, and Collaborative Research Center SFB 876, TU Dortmund, Dortmund, Germany.

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 detect and quantify volatile organic compounds (VOC) at low concentrations in the air or in exhaled breath at ambient pressure and temperature. Ongoing miniaturization of spectrometers 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 measurements consisting of several thousand individual spectra. Each individual spectrum is processed as it arrives, removing the need to store the measurement 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.

No MeSH data available.


Time series of discovered intensities of two peaks. Left: A peak with agreement between manual and automated online annotation. Right: A peak where the online method fails to extract the peak in several measurements. If one treated zeros as missing data, the overall trend would still be visible.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
getmorefigures.php?uid=PMC4495807&req=5

Fig6: Time series of discovered intensities of two peaks. Left: A peak with agreement between manual and automated online annotation. Right: A peak where the online method fails to extract the peak in several measurements. If one treated zeros as missing data, the overall trend would still be visible.

Mentions: As an example, Figure 6 shows time series of intensities of two peaks detected by computer-assisted manual annotation and using our online algorithm. The example shows that there are cases where the sensitivity of the online algorithm is not perfect; this is mainly true for peaks whose intensity only slightly exceeds the background noise.Figure 6


An online peak extraction algorithm for ion mobility spectrometry data.

Kopczynski D, Rahmann S - Algorithms Mol Biol (2015)

Time series of discovered intensities of two peaks. Left: A peak with agreement between manual and automated online annotation. Right: A peak where the online method fails to extract the peak in several measurements. If one treated zeros as missing data, the overall trend would still be visible.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4495807&req=5

Fig6: Time series of discovered intensities of two peaks. Left: A peak with agreement between manual and automated online annotation. Right: A peak where the online method fails to extract the peak in several measurements. If one treated zeros as missing data, the overall trend would still be visible.
Mentions: As an example, Figure 6 shows time series of intensities of two peaks detected by computer-assisted manual annotation and using our online algorithm. The example shows that there are cases where the sensitivity of the online algorithm is not perfect; this is mainly true for peaks whose intensity only slightly exceeds the background noise.Figure 6

Bottom Line: Each individual spectrum is processed as it arrives, removing the need to store the measurement 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.

View Article: PubMed Central - PubMed

Affiliation: Bioinformatics for High-Throughput Technologies, Computer Science XI, and Collaborative Research Center SFB 876, TU Dortmund, Dortmund, Germany.

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 detect and quantify volatile organic compounds (VOC) at low concentrations in the air or in exhaled breath at ambient pressure and temperature. Ongoing miniaturization of spectrometers 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 measurements consisting of several thousand individual spectra. Each individual spectrum is processed as it arrives, removing the need to store the measurement 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.

No MeSH data available.