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Rick Helmus
Universiteit van Amsterdam
Corresponding Author
ORCiD: https://orcid.org/0000-0001-9401-3133
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Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. 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 samples is demonstrated with a simple and reproducible workflow using open-access data of spiked samples 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.
Keywords
High resolution mass spectrometry, compound identification, non-target analysis, computational workflows
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CURRENT STATUS: Published
View the published article at Journal of Cheminformatics.
Version 2
Posted 04 Nov, 2020
No community comments so far
Editorial decision: Accept
On 22 Nov, 2020
Review #2 received
Received 12 Nov, 2020
Reviewer #2 agreed
On 30 Oct, 2020
Editor assigned
On 29 Oct, 2020
Reviewers invited
Invitations sent on 29 Oct, 2020
Reviewer #1 agreed
On 29 Oct, 2020
Review #1 received
Received 29 Oct, 2020
Submission checks complete
On 28 Oct, 2020
Editor invited
On 28 Oct, 2020
No comments provided
Editorial decision: Major revision
On 01 Oct, 2020
Review #2 received
Received 20 Sep, 2020
Review #1 received
Received 20 Sep, 2020
Reviewers invited
Invitations sent on 14 Sep, 2020
Reviewer #1 agreed
On 14 Sep, 2020
Reviewer #2 agreed
On 14 Sep, 2020
Editor assigned
On 20 Jun, 2020
First submitted
On 19 Jun, 2020
Submission checks complete
On 19 Jun, 2020
Editor invited
On 19 Jun, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Biomedical Engineering
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See the published version of this preprint at Journal of Cheminformatics.
This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Software
Rick Helmus
Universiteit van Amsterdam
Corresponding Author
ORCiD: https://orcid.org/0000-0001-9401-3133
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Published
View the published article at Journal of Cheminformatics.
Version 2
Posted 04 Nov, 2020
No community comments so far
Editorial decision: Accept
On 22 Nov, 2020
Review #2 received
Received 12 Nov, 2020
Reviewer #2 agreed
On 30 Oct, 2020
Editor assigned
On 29 Oct, 2020
Reviewers invited
Invitations sent on 29 Oct, 2020
Reviewer #1 agreed
On 29 Oct, 2020
Review #1 received
Received 29 Oct, 2020
Submission checks complete
On 28 Oct, 2020
Editor invited
On 28 Oct, 2020
No comments provided
Editorial decision: Major revision
On 01 Oct, 2020
Review #2 received
Received 20 Sep, 2020
Review #1 received
Received 20 Sep, 2020
Reviewers invited
Invitations sent on 14 Sep, 2020
Reviewer #1 agreed
On 14 Sep, 2020
Reviewer #2 agreed
On 14 Sep, 2020
Editor assigned
On 20 Jun, 2020
First submitted
On 19 Jun, 2020
Submission checks complete
On 19 Jun, 2020
Editor invited
On 19 Jun, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Biomedical Engineering
License:
This work is licensed under a CC BY 4.0 License. Read Full License
View the published article at Journal of Cheminformatics.
Mass spectrometry based non-target analysis is increasingly adopted in environmental sciences to screen and identify numerous chemicals simultaneously in highly complex samples. 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 samples is demonstrated with a simple and reproducible workflow using open-access data of spiked samples 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.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
The full text of this article is available to read as a PDF.
This is a list of supplementary files associated with this preprint. Click to download.
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