دورية أكاديمية
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Tile-based variance rank initiated-unsupervised sample indexing for comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.

التفاصيل البيبلوغرافية
العنوان: Tile-based variance rank initiated-unsupervised sample indexing for comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry.
المؤلفون: Sudol PE; Department of Chemistry, Box 351700, University of Washington, Seattle, WA, 98195, USA., Ochoa GS; Department of Chemistry, Box 351700, University of Washington, Seattle, WA, 98195, USA., Cain CN; Department of Chemistry, Box 351700, University of Washington, Seattle, WA, 98195, USA., Synovec RE; Department of Chemistry, Box 351700, University of Washington, Seattle, WA, 98195, USA. Electronic address: synovec@chem.washington.edu.
المصدر: Analytica chimica acta [Anal Chim Acta] 2022 May 29; Vol. 1209, pp. 339847. Date of Electronic Publication: 2022 Apr 19.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Elsevier Country of Publication: Netherlands NLM ID: 0370534 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-4324 (Electronic) Linking ISSN: 00032670 NLM ISO Abbreviation: Anal Chim Acta Subsets: MEDLINE
أسماء مطبوعة: Publication: Amsterdam : Elsevier
Original Publication: Amsterdam.
مواضيع طبية MeSH: Software* , Sulfur*, Cluster Analysis ; Gas Chromatography-Mass Spectrometry/methods
مستخلص: Tile-based variance rank initiated-unsupervised sample indexing (VRI-USI) analysis is introduced for comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS). VRI-USI analysis addresses the challenge that irrelevant variables can often obscure true chemical variation when using other unsupervised chemometric tools. Implementation of VRI-USI analysis with GC×GC-TOFMS data incorporates the tile-based Fisher ratio (F-ratio) analysis software platform that mitigates the effects of retention shifting in both separation dimensions with an unsupervised variance metric (instead of the F-ratio metric) as the initial step of ranking the hitlist. Next, implementation of k-means clustering, k, per hit using the silhouette metric, S max , is used to reveal to what extent recurring indexed sample clusters are uncovered. Finally, based upon a probability-based evaluation of how the individual samples cluster throughout the hitlist an unsupervised class membership is revealed. For a JP8 jet fuel dataset spiked with a sulfur-containing analyte mix at 30-ppm, 15-ppm, and neat, clustering by spike level at k = 3 was the most commonly re-occurring set of index assignments, occurring for 11 out of 14 spiked analytes. Upon application of these k-means index assignments to the entire hitlist, all 14 spiked hits had one way ANOVA p-values < 0.05, validating the presumption of classes. Next, application of VRI-USI to a 3-ppm spiked and neat JP8 jet fuel comparison exhibited similar performance to F-ratio analysis for analyte discovery. In the last study, for a dataset of J1800A, JP4, and JP8 jet fuel, each spiked with the sulfur-containing analyte mix at 30-ppm and neat, 453 out of 520 hits in the hitlist exhibited index assignments indicative of fuel type clustering, with the remaining 67 hits having contradictory assignments. Scrutinization of these 67 hits revealed nine hits with "split combinations" in index assignments, whereby the spiked and neat samples for a given fuel were in separate clusters. Eight of these hits were identified as spiked sulfur analytes. Interestingly, these hits also had large S max indicative of a true sub-cluster. Thus, tile-based VRI-USI analysis appears to be a promising tool for unsupervised multi-class classification studies using GC×GC-TOFMS data.
(Copyright © 2022 Elsevier B.V. All rights reserved.)
فهرسة مساهمة: Keywords: Chemometrics; Comprehensive two-dimensional gas chromatography; Multi-class classification; Unsupervised; Variance rank initiated-unsupervised sample indexing
المشرفين على المادة: 70FD1KFU70 (Sulfur)
تواريخ الأحداث: Date Created: 20220515 Date Completed: 20220519 Latest Revision: 20220519
رمز التحديث: 20221213
DOI: 10.1016/j.aca.2022.339847
PMID: 35569851
قاعدة البيانات: MEDLINE
الوصف
تدمد:1873-4324
DOI:10.1016/j.aca.2022.339847