Fisher ratio feature selection by manual peak area calculations on comprehensive two-dimensional gas chromatography data using standard mixtures with variable composition, storage, and interferences
Fisher ratio feature selection by manual peak area calculations on comprehensive two-dimensional gas chromatography data using standard mixtures with variable composition, storage, and interferences
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使用具有可变成分、存储和干扰的标准混合物,通过对综合二维气相色谱数据进行手动峰面积计算来选择 Fisher 比特征
DOI:
10.1007/s00216-022-04484-8
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发表时间:
2022
影响因子:
4.3
通讯作者:
Perrault, Katelynn A.
中科院分区:
文献类型:
--
作者:
Oliva, Danson J.;Cheung, Cynthia;Perrault, Katelynn A.
Comprehensive two-dimensional gas chromatography (GC×GC) is becoming increasingly more common for non-targeted characterization of complex volatile mixtures. The information gained with higher peak capacity and sensitivity provides additional sample composition information when one-dimensional GC is not adequate. GC×GC generates complex multivariate data sets when using non-targeted analysis to discover analytes. Fisher ratio (FR) analysis is applied to discern class markers, limiting complex GC×GC profiles to the most discriminating compounds between classes. While many approaches for feature selection using FR analysis exist, FR can be calculated relatively easily directly on peak areas after any native software has performed peak detection. This study evaluated the success rates of manual FR calculation and comparison to a criticalF-value for samples analyzed by GC×GC with defined concentration differences. Long-term storage of samples and other spiked interferences were also investigated to examine their impact on analyzing mixtures using this FR feature selection strategy. Success rates were generally high with mostly 90–100% success rates and some instances of percentages between 80 and 90%. There were rare cases of false positives present and a low occurrence of false negatives. When errors were made in the selection of a compound, it was typically due to chromatographic artifacts present in chromatograms and not from the FR approach itself. This work provides foundational experimental data on the use of manual FR calculations for feature selection from GC×GC data.Graphical Abstract
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影响因子:
6.1
作者:
Magagna, Federico;Guglielmetti, Alessandro;Cordero, Chiara
通讯作者:
Cordero, Chiara
DOI:
10.1016/j.chroma.2015.01.031
发表时间:
2015
期刊:
Journal of chromatography. A
影响因子:
--
作者:
M. Klee;J. Cochran;Mark Merrick;L. Blumberg
通讯作者:
L. Blumberg
影响因子:
2.6
作者:
Pierre‐Hugues Stefanuto;Katelynn A. Perrault;S. Grabherr;V. Varlet;J. Focant
通讯作者:
J. Focant
影响因子:
4.3
作者:
Pierre‐Hugues Stefanuto;Katelynn A. Perrault;S. Stadler;Romain Pesesse;H. LeBlanc;S. Forbes;J. Focant
通讯作者:
J. Focant
影响因子:
4.1
作者:
Groeger, Th.;Schaeffer, M.;Zimmermann, R.
通讯作者:
Zimmermann, R.