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Unique ion filter—A data reduction tool for chemometric analysis of raw comprehensive two‐dimensional gas chromatography‐mass spectrometry data
Author(s) -
Adutwum Lawrence A.,
Kwao Joanna Koryo,
Harynuk James J.
Publication year - 2021
Publication title -
journal of separation science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.72
H-Index - 102
eISSN - 1615-9314
pISSN - 1615-9306
DOI - 10.1002/jssc.202001127
Subject(s) - mass spectrometry , chemometrics , chemistry , data reduction , gas chromatography , chromatography , dimensionality reduction , mass spectrum , analytical chemistry (journal) , two dimensional gas , two dimensional chromatography , dimension (graph theory) , computer science , data mining , mathematics , artificial intelligence , pure mathematics
Comprehensive gas chromatography with time of flight mass spectrometry is a powerful tool in the analysis of complex samples. Chemometric analysis of raw chromatographic data is more useful in one‐ and two‐dimensional separations relative to peak tables. The data volume from such experiments generally necessitates the use of data reduction tools. Such tools often sacrifice some of the multivariate information in the mass to charge ratio dimension. The unique ion filter reduces the over‐redundancy in two‐dimensional gas chromatography‐mass spectrometry data by limiting the data to a few unique/pseudo‐unique ions, sub‐peaks/slices in the first dimension, and spectra in the second dimension. We explore the performance of this algorithm through careful inspection of two‐dimensional gas chromatography‐mass spectrometry data before and after application of the filter. A reduction (99%) in the number of variables in a two‐dimensional gas chromatography‐mass spectrometry chromatogram passed on to subsequent analysis was observed. Feature selection times for model optimization reduced from 229 (±13) to 6.8 (±0.5) min when the filter was applied. An estimate of two unique/pseudo‐unique ions, one sub‐peak in the first dimension and five spectra in the second dimension were considered to provide a true representation of each chromatogram and provided enough information to achieve 100% model prediction accuracy.