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@inproceedings{2262797,
author = {Bartoň, Vojtěch and Skutkova, Helena},
address = {Cham},
booktitle = {Bioinformatics and Biomedical Engineering (IWBBIO 2022) : Lecture Notes in Computer Science, vol 13347},
doi = {http://dx.doi.org/10.1007/978-3-031-07802-6_24},
editor = {Rojas I., Valenzuela O., Rojas F., Herrera L.J., Ortuño F.},
keywords = {Mass spectrometry; Clustering; Feature identification},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Cham},
isbn = {978-3-031-07801-9},
pages = {288-299},
publisher = {Springer},
title = {Data Transformation for Clustering Utilization for Feature Detection in Mass Spectrometry},
url = {https://doi.org/10.1007/978-3-031-07802-6_24},
year = {2022}
}
TY - JOUR
ID - 2262797
AU - Bartoň, Vojtěch - Skutkova, Helena
PY - 2022
TI - Data Transformation for Clustering Utilization for Feature Detection in Mass Spectrometry
PB - Springer
CY - Cham
SN - 9783031078019
KW - Mass spectrometry
KW - Clustering
KW - Feature identification
UR - https://doi.org/10.1007/978-3-031-07802-6_24
N2 - Feature detection and peak detection are one of the first steps of mass spectrometry data processing. This data comes in large volumes; thus, the processing needs to be optimized, not overloaded. State-of-the-art clustering algorithms can not perform feature detection for several reasons. First issue is the volume of the data, second is the disparity of the sampling frequency in the MZ and RT axis. Here we show the data transformation to utilize the clustering algorithms without the need to redefine its kernel. Data are first pre-clustered to obtain regions that can be processed independently. Then we transform the data so that the numerical differences between consecutive points should be the same in both space axes. We applied a set of clustering algorithms for each region to find the features, and we compared the result with the Gridmass peak detector. These findings may facilitate better utilization of the 2D clustering method as feature detectors for mass spectra.
ER -
BARTOŇ, Vojtěch and Helena SKUTKOVA. Data Transformation for Clustering Utilization for Feature Detection in Mass Spectrometry. In Rojas I., Valenzuela O., Rojas F., Herrera L.J., Ortuño F. \textit{Bioinformatics and Biomedical Engineering (IWBBIO 2022) : Lecture Notes in Computer Science, vol 13347}. Cham: Springer, 2022, p.~288-299. ISBN~978-3-031-07801-9. Available from: https://dx.doi.org/10.1007/978-3-031-07802-6\_{}24.
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