Cordero, Chiara Emilia Irma

Heble, Chase

Reichenbach, Stephen

Tao, Qingping

English

Institutional Research Information System University of Turin

INTERACTIVE TOOLS FOR OPTIMIZING BLOB DETECTION AND TEMPLATEMATCHING FOR COMPREHENSIVE TWO-DIMENSIONAL CHROMATOGRAPHYQingping Tao1, Chase Heble1, Stephen Reichenbach2,1, Chiara Cordero31 GC Image, LLC, PO Box 57403, 68505-7403 Lincoln, United States2 Computer Science & Engineering - University of Nebraska, 260 Avery, 68588-0115 Lincoln, UnitedStates3 Universita degli Studi di Torino, Via Pietro Giuria, 9, I-10125 Torino, ItalyComprehensive two-dimensional chromatography is a powerful technique for highly effectivechemical separations of complex mixtures, so GCxGC, LCxLC, and other two-dimensionaltechniques are increasingly popular.  The data produced by comprehensive two-dimensionalchromatography is rich with chemical information, but extracting that information from largecomplex datasets is challenging even for well-designed and executed analytical methods.  Thedata analysis problems are even more difficult when the more complex instrument settings andconditions involving two columns are suboptimal.  Regardless of the quality of data, it isimportant to optimize processing of that data in critical operations. Two new interactive tools that provide rapid visual feedback greatly accelerate the process ofdetermining optimal settings for:    • blob/peak detection and    • analyte pattern matching.Blob/peak detection is essential for accurate quantification and analyte pattern matching is thebasis for effective compound identification and cross-sample analyte comparisons. Interactive blob/peak detection implements controls in two highly visual steps.  The first stepallows analysts to adjust the level of smoothing, to suppress noise, in the watershed blobdetection algorithm.  This setting is especially important for detecting trace analytes.  Thesecond step allows analysts to construct sophisticated peak detection filters using CLIC, alanguage for chemical expressions, involving peak shape, size, geometry, and statisticalcharacteristics.  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 previouslyrecorded pattern of peaks (and other features) with the same pattern of peaks (and otherfeatures) in a new chromatogram.  The controls allow selection of the template transformationmodel (including higher-order transformations) and configuration of the parameters andthresholds for automated matching.  Transformations can be applied globally or limited to aspecified region.  The transformed template and matches are presented in the image view andshown in a table with sortable matching-quality metrics for each matched peak.  The views inthe image and table have synchronized selections with automatic image zoom to focus on aselected match.  The interface allows manual assignment/unassignment of matcheswith recomputations of the transformation model parameters.

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

https://iris.unito.it/bitstream/2318/1589443/1/interactivity.pdf

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

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Institutional Research Information System University of Turin