Comprehensive two-dimensional chromatography is a powerful technique for highly effective chemical separations of complex mixtures, so GCxGC, LCxLC, and other two-dimensional techniques are increasingly popular. The data produced by comprehensive two-dimensional chromatography is rich with chemical information, but extracting that information from large complex datasets is challenging even for well-designed and executed analytical methods. The data analysis problems are even more difficult when the more complex instrument settings and conditions involving two columns are suboptimal. Regardless of the quality of data, it is important to optimize processing of that data in critical operations. Two new interactive tools that provide rapid visual feedback greatly accelerate the process of determining optimal settings for: • blob/peak detection and • analyte pattern matching. Blob/peak detection is essential for accurate quantification and analyte pattern matching is the basis for effective compound identification and cross-sample analyte comparisons. Interactive blob/peak detection implements controls in two highly visual steps. The first step allows analysts to adjust the level of smoothing, to suppress noise, in the watershed blob detection algorithm. This setting is especially important for detecting trace analytes. The second step allows analysts to construct sophisticated peak detection filters using CLIC, a language for chemical expressions, involving peak shape, size, geometry, and statistical characteristics. Each filter is implemented with an interactive slider to adjust the minimum and/ or maximum thresholds. So, for example, filters for flat shapes can be used to reject streaks. Interactive template matching provides controls and visual feedback to align a previously recorded pattern of peaks (and other features) with the same pattern of peaks (and other features) in a new chromatogram. The controls allow selection of the template transformation model (including higher-order transformations) and configuration of the parameters and thresholds for automated matching. Transformations can be applied globally or limited to a specified region. The transformed template and matches are presented in the image view and shown in a table with sortable matching-quality metrics for each matched peak. The views in the image and table have synchronized selections with automatic image zoom to focus on a selected match. The interface allows manual assignment/unassignment of matches with recomputations of the transformation model parameters.

INTERACTIVE TOOLS FOR OPTIMIZING BLOB DETECTION AND TEMPLATE MATCHING FOR COMPREHENSIVE TWO-DIMENSIONAL CHROMATOGRAPHY

CORDERO, Chiara Emilia Irma
2016-01-01

Abstract

Comprehensive two-dimensional chromatography is a powerful technique for highly effective chemical separations of complex mixtures, so GCxGC, LCxLC, and other two-dimensional techniques are increasingly popular. The data produced by comprehensive two-dimensional chromatography is rich with chemical information, but extracting that information from large complex datasets is challenging even for well-designed and executed analytical methods. The data analysis problems are even more difficult when the more complex instrument settings and conditions involving two columns are suboptimal. Regardless of the quality of data, it is important to optimize processing of that data in critical operations. Two new interactive tools that provide rapid visual feedback greatly accelerate the process of determining optimal settings for: • blob/peak detection and • analyte pattern matching. Blob/peak detection is essential for accurate quantification and analyte pattern matching is the basis for effective compound identification and cross-sample analyte comparisons. Interactive blob/peak detection implements controls in two highly visual steps. The first step allows analysts to adjust the level of smoothing, to suppress noise, in the watershed blob detection algorithm. This setting is especially important for detecting trace analytes. The second step allows analysts to construct sophisticated peak detection filters using CLIC, a language for chemical expressions, involving peak shape, size, geometry, and statistical characteristics. Each filter is implemented with an interactive slider to adjust the minimum and/ or maximum thresholds. So, for example, filters for flat shapes can be used to reject streaks. Interactive template matching provides controls and visual feedback to align a previously recorded pattern of peaks (and other features) with the same pattern of peaks (and other features) in a new chromatogram. The controls allow selection of the template transformation model (including higher-order transformations) and configuration of the parameters and thresholds for automated matching. Transformations can be applied globally or limited to a specified region. The transformed template and matches are presented in the image view and shown in a table with sortable matching-quality metrics for each matched peak. The views in the image and table have synchronized selections with automatic image zoom to focus on a selected match. The interface allows manual assignment/unassignment of matches with recomputations of the transformation model parameters.
2016
40th International Symposium on Capillary Chromatography and 13th GCxGC Symposium
Riva del Garda (TN) Italia
May 29 - June 03, 2016
40th International Symposium on Capillary Chromatography and 13th GCxGC Symposium Book of Abstract
Chromaleont
1
1
Two-dimensional comprehensive gas chromatography-mass spectrometry, reverse-inject differential flow modulation, thermal modulators, quantitative profiling; cocoa volatiles, template matching functions, polynomial and affine transform
Tao, Qingping; Heble, Chase; Reichenbach, Stephen; Cordero, Chiara
File in questo prodotto:
File Dimensione Formato  
interactivity.pdf

Accesso aperto

Descrizione: full text
Tipo di file: PDF EDITORIALE
Dimensione 20.33 kB
Formato Adobe PDF
20.33 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1589443
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact