BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods
Name
Gorgolewski-2017-BIDS apps_ Improving ease of.pdf
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1.59 MB
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Checksum (MD5)
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Author(s)
Gorgolewski, Krzysztof J.
Alfaro-Almagro, Fidel
Auer, Tibor
Bellec, Pierre
Chakravarty, M. Mallar
Churchill, Nathan W.
Cohen, Alexander Li
Craddock, R. Cameron
Devenyi, Gabriel A.
Eklund, Anders
Date Issued
March 2017
Journal
PLoS Computational Biology
Publisher
Public Library of Science
Citation
Gorgolewski, Krzysztof J.; Alfaro-Almagro, Fidel; Auer, Tibor; Bellec, Pierre; Capotă, Mihai; Chakravarty, M. Mallar; Churchill, Nathan W. et al. “BIDS Apps: Improving Ease of Use, Accessibility, and Reproducibility of Neuroimaging Data Analysis Methods.” Edited by Dina Schneidman. PLOS Computational Biology 13, no. 3 (March 2017): e1005209 © 2017 Gorgolewski et al
Version
Final published version
Abstract
The rate of progress in human neurosciences is limited by the inability to easily apply a wide range of analysis methods to the plethora of different datasets acquired in labs around the world. In this work, we introduce a framework for creating, testing, versioning and archiving portable applications for analyzing neuroimaging data organized and described in compliance with the Brain Imaging Data Structure (BIDS). The portability of these applications (BIDS Apps) is achieved by using container technologies that encapsulate all binary and other dependencies in one convenient package. BIDS Apps run on all three major operating systems with no need for complex setup and configuration and thanks to the comprehensiveness of the BIDS standard they require little manual user input. Previous containerized data processing solutions were limited to single user environments and not compatible with most multi-tenant High Performance Computing systems. BIDS Apps overcome this limitation by taking advantage of the Singularity container technology. As a proof of concept, this work is accompanied by 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.
MIT Department
McGovern Institute for Brain Research at MIT
Terms of Use
Creative Commons Attribution 4.0 International License
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DOI of Published Version
https://doi.org/10.1371/journal.pcbi.1005209
