ORCID Profile
0000-0002-6182-6004
Current Organisations
University of Amsterdam
,
KWR Watercycle Research Institute
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Publisher: Research Square Platform LLC
Date: 22-06-2020
DOI: 10.21203/RS.3.RS-36675/V1
Abstract: Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex s les. However, current data processing software either lack functionality for environmental sciences, solve only part of the workflow, are not openly available and/or are restricted in input data formats. In this paper we present patRoon , a new R based open-source software platform, which provides comprehensive, fully tailoredand straightforwardnon-target analysis workflows. This platform makes the usage, evaluation and mixing of well-tested algorithms seamless by harmonizing various commonly (primarily open) software tools under a consistent interface. In addition, patRoon offersvarious functionality and strategies tosimplify and perform automated processing of complex (environmental) data effectively. patRoon implements several effective optimization strategies to significantly reduce computational times. The ability of patRoon to perform a straightforward and effective non-target analysis was demonstrated with real-world environmental s les, showing that patRoon makes comprehensive (environmental) non-target analysis readily accessible to a wider community of researchers.
Publisher: Springer Science and Business Media LLC
Date: 06-01-2021
DOI: 10.1186/S13321-020-00477-W
Abstract: Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex s les. However, current data processing software either lack functionality for environmental sciences, solve only part of the workflow, are not openly available and/or are restricted in input data formats. In this paper we present patRoon , a new R based open-source software platform, which provides comprehensive, fully tailored and straightforward non-target analysis workflows. This platform makes the use, evaluation and mixing of well-tested algorithms seamless by harmonizing various common (primarily open) software tools under a consistent interface. In addition, patRoon offers various functionality and strategies to simplify and perform automated processing of complex (environmental) data effectively. patRoon implements several effective optimization strategies to significantly reduce computational times. The ability of patRoon to perform time-efficient and automated non-target data annotation of environmental s les is demonstrated with a simple and reproducible workflow using open-access data of spiked s les from a drinking water treatment plant study. In addition, the ability to easily use, combine and evaluate different algorithms was demonstrated for three commonly used feature finding algorithms. This article, combined with already published works, demonstrate that patRoon helps make comprehensive (environmental) non-target analysis readily accessible to a wider community of researchers.
Publisher: Research Square Platform LLC
Date: 04-11-2020
DOI: 10.21203/RS.3.RS-36675/V2
Abstract: Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex s les. However, current data processing software either lack functionality for environmental sciences, solve only part of the workflow, are not openly available and/or are restricted in input data formats. In this paper we present patRoon , a new R based open-source software platform, which provides comprehensive, fully tailored and straightforward non-target analysis workflows. This platform makes the use, evaluation and mixing of well-tested algorithms seamless by harmonizing various common (primarily open) software tools under a consistent interface. In addition, patRoon offers various functionality and strategies to simplify and perform automated processing of complex (environmental) data effectively. patRoon implements several effective optimization strategies to significantly reduce computational times. The ability of patRoon to perform time-efficient and automated non-target data annotation of environmental s les is demonstrated with a simple and reproducible workflow using open-access data of spiked s les from a drinking water treatment plant study. In addition, the ability to easily use, combine and evaluate different algorithms was demonstrated for three commonly used feature finding algorithms. This article, combined with already published works, demonstrate that patRoon helps make comprehensive (environmental) non-target analysis readily accessible to a wider community of researchers.
Publisher: The Open Journal
Date: 12-03-2022
DOI: 10.21105/JOSS.04029
No related grants have been discovered for Thomas ter Laak.