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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.
Afiliação
  • Wilde MJ; School of Chemistry, University of Leicester, University Road, Leicester LE1 7RH, U.K.
  • Zhao B; Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.
  • Cordell RL; Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K.
  • Ibrahim W; School of Chemistry, University of Leicester, University Road, Leicester LE1 7RH, U.K.
  • Singapuri A; Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.
  • Greening NJ; Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K.
  • Brightling CE; Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.
  • Siddiqui S; Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K.
  • Monks PS; Department of Respiratory Sciences, University of Leicester, University Road, Leicester LE1 7RH, U.K.
  • Free RC; Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Groby Road, Leicester LE3 9QP, U.K.
Anal Chem ; 92(20): 13953-13960, 2020 10 20.
Article em En | MEDLINE | ID: mdl-32985172
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 1tR and 2tR 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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Cromatografia Gasosa Idioma: En Revista: Anal Chem Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Software / Cromatografia Gasosa Idioma: En Revista: Anal Chem Ano de publicação: 2020 Tipo de documento: Article