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Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software

[Image: see text] Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful analytical tool for both nontargeted and targeted analyses. However, there is a need for more integrated workflows for processing and managing the resultant high-complexity datasets. End-to-end workflows for pro...

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Autores principales: Wilde, Michael J., Zhao, Bo, Cordell, Rebecca L., Ibrahim, Wadah, Singapuri, Amisha, Greening, Neil J., Brightling, Chris E., Siddiqui, Salman, Monks, Paul S., Free, Robert C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644112/
https://www.ncbi.nlm.nih.gov/pubmed/32985172
http://dx.doi.org/10.1021/acs.analchem.0c02844
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author Wilde, Michael J.
Zhao, Bo
Cordell, Rebecca L.
Ibrahim, Wadah
Singapuri, Amisha
Greening, Neil J.
Brightling, Chris E.
Siddiqui, Salman
Monks, Paul S.
Free, Robert C.
author_facet Wilde, Michael J.
Zhao, Bo
Cordell, Rebecca L.
Ibrahim, Wadah
Singapuri, Amisha
Greening, Neil J.
Brightling, Chris E.
Siddiqui, Salman
Monks, Paul S.
Free, Robert C.
author_sort Wilde, Michael J.
collection PubMed
description [Image: see text] Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful analytical tool for both nontargeted and targeted analyses. However, there is a need for more integrated workflows for processing and managing the resultant high-complexity datasets. End-to-end workflows for processing GC×GC data are challenging and often require multiple tools or software to process a single dataset. We describe a new approach, which uses an existing underutilized interface within commercial software to integrate free and open-source/external scripts and tools, tailoring the workflow to the needs of the individual researcher within a single software environment. To demonstrate the concept, the interface was successfully used to complete a first-pass alignment on a large-scale GC×GC metabolomics dataset. The analysis was performed by interfacing bespoke and published external algorithms within a commercial software environment to automatically correct the variation in retention times captured by a routine reference standard. Variation in (1)t(R) and (2)t(R) was reduced on average from 8 and 16% CV prealignment to less than 1 and 2% post alignment, respectively. The interface enables automation and creation of new functions and increases the interconnectivity between chemometric tools, providing a window for integrating data-processing software with larger informatics-based data management platforms.
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spelling pubmed-76441122020-11-06 Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software Wilde, Michael J. Zhao, Bo Cordell, Rebecca L. Ibrahim, Wadah Singapuri, Amisha Greening, Neil J. Brightling, Chris E. Siddiqui, Salman Monks, Paul S. Free, Robert C. Anal Chem [Image: see text] Comprehensive two-dimensional gas chromatography (GC×GC) is a powerful analytical tool for both nontargeted and targeted analyses. However, there is a need for more integrated workflows for processing and managing the resultant high-complexity datasets. End-to-end workflows for processing GC×GC data are challenging and often require multiple tools or software to process a single dataset. We describe a new approach, which uses an existing underutilized interface within commercial software to integrate free and open-source/external scripts and tools, tailoring the workflow to the needs of the individual researcher within a single software environment. To demonstrate the concept, the interface was successfully used to complete a first-pass alignment on a large-scale GC×GC metabolomics dataset. The analysis was performed by interfacing bespoke and published external algorithms within a commercial software environment to automatically correct the variation in retention times captured by a routine reference standard. Variation in (1)t(R) and (2)t(R) was reduced on average from 8 and 16% CV prealignment to less than 1 and 2% post alignment, respectively. The interface enables automation and creation of new functions and increases the interconnectivity between chemometric tools, providing a window for integrating data-processing software with larger informatics-based data management platforms. American Chemical Society 2020-09-28 2020-10-20 /pmc/articles/PMC7644112/ /pubmed/32985172 http://dx.doi.org/10.1021/acs.analchem.0c02844 Text en © 2020 American Chemical Society This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
spellingShingle Wilde, Michael J.
Zhao, Bo
Cordell, Rebecca L.
Ibrahim, Wadah
Singapuri, Amisha
Greening, Neil J.
Brightling, Chris E.
Siddiqui, Salman
Monks, Paul S.
Free, Robert C.
Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software
title Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software
title_full Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software
title_fullStr Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software
title_full_unstemmed Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software
title_short Automating and Extending Comprehensive Two-Dimensional Gas Chromatography Data Processing by Interfacing Open-Source and Commercial Software
title_sort automating and extending comprehensive two-dimensional gas chromatography data processing by interfacing open-source and commercial software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7644112/
https://www.ncbi.nlm.nih.gov/pubmed/32985172
http://dx.doi.org/10.1021/acs.analchem.0c02844
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