Porcupine: A visual pipeline tool for neuroimaging analysis.

The field of neuroimaging is rapidly adopting a more reproducible approach to data acquisition and analysis. Data structures and formats are being standardised and data analyses are getting more automated. However, as data analysis becomes more complicated, researchers often have to write longer ana...

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Main Authors: Tim van Mourik, Lukas Snoek, Tomas Knapen, David G Norris
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2018-05-01
Series:PLoS Computational Biology
Online Access:http://europepmc.org/articles/PMC5963801?pdf=render
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spelling doaj-36188ad3b4c842cc97747dad37ed15dc2020-11-25T01:53:40ZengPublic Library of Science (PLoS)PLoS Computational Biology1553-734X1553-73582018-05-01145e100606410.1371/journal.pcbi.1006064Porcupine: A visual pipeline tool for neuroimaging analysis.Tim van MourikLukas SnoekTomas KnapenDavid G NorrisThe field of neuroimaging is rapidly adopting a more reproducible approach to data acquisition and analysis. Data structures and formats are being standardised and data analyses are getting more automated. However, as data analysis becomes more complicated, researchers often have to write longer analysis scripts, spanning different tools across multiple programming languages. This makes it more difficult to share or recreate code, reducing the reproducibility of the analysis. We present a tool, Porcupine, that constructs one's analysis visually and automatically produces analysis code. The graphical representation improves understanding of the performed analysis, while retaining the flexibility of modifying the produced code manually to custom needs. Not only does Porcupine produce the analysis code, it also creates a shareable environment for running the code in the form of a Docker image. Together, this forms a reproducible way of constructing, visualising and sharing one's analysis. Currently, Porcupine links to Nipype functionalities, which in turn accesses most standard neuroimaging analysis tools. Our goal is to release researchers from the constraints of specific implementation details, thereby freeing them to think about novel and creative ways to solve a given problem. Porcupine improves the overview researchers have of their processing pipelines, and facilitates both the development and communication of their work. This will reduce the threshold at which less expert users can generate reusable pipelines. With Porcupine, we bridge the gap between a conceptual and an implementational level of analysis and make it easier for researchers to create reproducible and shareable science. We provide a wide range of examples and documentation, as well as installer files for all platforms on our website: https://timvanmourik.github.io/Porcupine. Porcupine is free, open source, and released under the GNU General Public License v3.0.http://europepmc.org/articles/PMC5963801?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Tim van Mourik
Lukas Snoek
Tomas Knapen
David G Norris
spellingShingle Tim van Mourik
Lukas Snoek
Tomas Knapen
David G Norris
Porcupine: A visual pipeline tool for neuroimaging analysis.
PLoS Computational Biology
author_facet Tim van Mourik
Lukas Snoek
Tomas Knapen
David G Norris
author_sort Tim van Mourik
title Porcupine: A visual pipeline tool for neuroimaging analysis.
title_short Porcupine: A visual pipeline tool for neuroimaging analysis.
title_full Porcupine: A visual pipeline tool for neuroimaging analysis.
title_fullStr Porcupine: A visual pipeline tool for neuroimaging analysis.
title_full_unstemmed Porcupine: A visual pipeline tool for neuroimaging analysis.
title_sort porcupine: a visual pipeline tool for neuroimaging analysis.
publisher Public Library of Science (PLoS)
series PLoS Computational Biology
issn 1553-734X
1553-7358
publishDate 2018-05-01
description The field of neuroimaging is rapidly adopting a more reproducible approach to data acquisition and analysis. Data structures and formats are being standardised and data analyses are getting more automated. However, as data analysis becomes more complicated, researchers often have to write longer analysis scripts, spanning different tools across multiple programming languages. This makes it more difficult to share or recreate code, reducing the reproducibility of the analysis. We present a tool, Porcupine, that constructs one's analysis visually and automatically produces analysis code. The graphical representation improves understanding of the performed analysis, while retaining the flexibility of modifying the produced code manually to custom needs. Not only does Porcupine produce the analysis code, it also creates a shareable environment for running the code in the form of a Docker image. Together, this forms a reproducible way of constructing, visualising and sharing one's analysis. Currently, Porcupine links to Nipype functionalities, which in turn accesses most standard neuroimaging analysis tools. Our goal is to release researchers from the constraints of specific implementation details, thereby freeing them to think about novel and creative ways to solve a given problem. Porcupine improves the overview researchers have of their processing pipelines, and facilitates both the development and communication of their work. This will reduce the threshold at which less expert users can generate reusable pipelines. With Porcupine, we bridge the gap between a conceptual and an implementational level of analysis and make it easier for researchers to create reproducible and shareable science. We provide a wide range of examples and documentation, as well as installer files for all platforms on our website: https://timvanmourik.github.io/Porcupine. Porcupine is free, open source, and released under the GNU General Public License v3.0.
url http://europepmc.org/articles/PMC5963801?pdf=render
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AT tomasknapen porcupineavisualpipelinetoolforneuroimaginganalysis
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