Assessment of the Kernel Gram Matrix Representation of Data in Order to Avoid the Alignment of Chromatographic Signals
This article discusses the possibility of exploratory data analysis of samples described by second-order chromatographic data affected by peak shifts. In particular, the potential of the kernel Gram matrix representation as an alternative to the necessary and time-consuming alignment step is evaluat...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-01-01
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| Series: | Molecules |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1420-3049/26/3/621 |
| _version_ | 1797407466388979712 |
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| author | Ivana Stanimirova Michal Daszykowski |
| author_facet | Ivana Stanimirova Michal Daszykowski |
| author_sort | Ivana Stanimirova |
| collection | DOAJ |
| description | This article discusses the possibility of exploratory data analysis of samples described by second-order chromatographic data affected by peak shifts. In particular, the potential of the kernel Gram matrix representation as an alternative to the necessary and time-consuming alignment step is evaluated. It was demonstrated through several simulation studies and comparisons that even small peak shifts can be a substantial source of data variance, and they can easily hamper the interpretation of chromatographic data. When peak shifts are small, their negative effect is far more destructive than the impact of relatively large levels of the Gaussian noise, heteroscedastic noise, and signal’s baseline. The Gram principal component analysis approach has proven to be a well-suited tool for exploratory analysis of chromatographic signals collected using the diode-array detector in which sample-to-sample peak shifts were observed. |
| first_indexed | 2024-03-09T03:41:53Z |
| format | Article |
| id | doaj.art-d7dca4c168fd48cc85fdb37da7134863 |
| institution | Directory Open Access Journal |
| issn | 1420-3049 |
| language | English |
| last_indexed | 2024-03-09T03:41:53Z |
| publishDate | 2021-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Molecules |
| spelling | doaj.art-d7dca4c168fd48cc85fdb37da71348632023-12-03T14:40:11ZengMDPI AGMolecules1420-30492021-01-0126362110.3390/molecules26030621Assessment of the Kernel Gram Matrix Representation of Data in Order to Avoid the Alignment of Chromatographic SignalsIvana Stanimirova0Michal Daszykowski1Institute of Chemistry, University of Silesia in Katowice, 9 Szkolna Street, 40-006 Katowice, PolandInstitute of Chemistry, University of Silesia in Katowice, 9 Szkolna Street, 40-006 Katowice, PolandThis article discusses the possibility of exploratory data analysis of samples described by second-order chromatographic data affected by peak shifts. In particular, the potential of the kernel Gram matrix representation as an alternative to the necessary and time-consuming alignment step is evaluated. It was demonstrated through several simulation studies and comparisons that even small peak shifts can be a substantial source of data variance, and they can easily hamper the interpretation of chromatographic data. When peak shifts are small, their negative effect is far more destructive than the impact of relatively large levels of the Gaussian noise, heteroscedastic noise, and signal’s baseline. The Gram principal component analysis approach has proven to be a well-suited tool for exploratory analysis of chromatographic signals collected using the diode-array detector in which sample-to-sample peak shifts were observed.https://www.mdpi.com/1420-3049/26/3/621chemical fingerprintskernel trickGram PCAwarpingpreprocessingpeak shifts |
| spellingShingle | Ivana Stanimirova Michal Daszykowski Assessment of the Kernel Gram Matrix Representation of Data in Order to Avoid the Alignment of Chromatographic Signals Molecules chemical fingerprints kernel trick Gram PCA warping preprocessing peak shifts |
| title | Assessment of the Kernel Gram Matrix Representation of Data in Order to Avoid the Alignment of Chromatographic Signals |
| title_full | Assessment of the Kernel Gram Matrix Representation of Data in Order to Avoid the Alignment of Chromatographic Signals |
| title_fullStr | Assessment of the Kernel Gram Matrix Representation of Data in Order to Avoid the Alignment of Chromatographic Signals |
| title_full_unstemmed | Assessment of the Kernel Gram Matrix Representation of Data in Order to Avoid the Alignment of Chromatographic Signals |
| title_short | Assessment of the Kernel Gram Matrix Representation of Data in Order to Avoid the Alignment of Chromatographic Signals |
| title_sort | assessment of the kernel gram matrix representation of data in order to avoid the alignment of chromatographic signals |
| topic | chemical fingerprints kernel trick Gram PCA warping preprocessing peak shifts |
| url | https://www.mdpi.com/1420-3049/26/3/621 |
| work_keys_str_mv | AT ivanastanimirova assessmentofthekernelgrammatrixrepresentationofdatainordertoavoidthealignmentofchromatographicsignals AT michaldaszykowski assessmentofthekernelgrammatrixrepresentationofdatainordertoavoidthealignmentofchromatographicsignals |