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From raw ion mobility measurements to disease classification : a comparison of analysis processes

  • Ion mobility spectrometry (IMS) is a technology for the detection of volatile compounds in the air of exhaled breath that is increasingly used in medical applications. One major goal is to classify patients into disease groups, for example diseased versus healthy, from simple breath samples. Raw IMS measurements are data matrices in which peak regions representing the compounds have to be identified and quantified. A typical analysis process consists of pre-processing and peak detection in single experiments, peak clustering to obtain consensus peaks across several experiments, and classification of samples based on the resulting multivariate peak intensities. Recently several automated algorithms for peak detection and peak clustering have been introduced, in order to overcome the current need for human-based analysis that is slow, subjective and sometimes not reproducible. We present an unbiased comparison of a multitude of combinations of peak processing and multivariate classification algorithms on a disease dataset. The specific combination of the algorithms for the different analysis steps determines the classification accuracy, with the encouraging result that certain fully-automated combinations perform even better than current manual approaches.

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Author of HS ReutlingenBaumbach, Jörg Ingo
Erschienen in:PeerJ Preprints
Publisher:PeerJ Inc.
Place of publication:Corte Madera, CA
Document Type:Conference proceeding
Publication year:2015
Page Number:11
First Page:1
Last Page:11
DDC classes:610 Medizin, Gesundheit
Open access?:Ja
Licence (German):License Logo  Creative Commons - Namensnennung