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BIDS Apps: Improving ease of use, accessibility and reproducibility of neuroimaging data analysis methods

View ORCID ProfileKrzysztof J. Gorgolewski, View ORCID ProfileFidel Alfaro-Almagro, Tibor Auer, View ORCID ProfilePierre Bellec, View ORCID ProfileMihai Capotă, View ORCID ProfileM. Mallar Chakravarty, Nathan W. Churchill, View ORCID ProfileR. Cameron Craddock, View ORCID ProfileGabriel A. Devenyi, View ORCID ProfileAnders Eklund, View ORCID ProfileOscar Esteban, View ORCID ProfileGuillaume Flandin, View ORCID ProfileSatrajit S. Ghosh, View ORCID ProfileJ. Swaroop Guntupalli, View ORCID ProfileMark Jenkinson, View ORCID ProfileAnisha Keshavan, View ORCID ProfileGregory Kiar, View ORCID ProfilePradeep Reddy Raamana, View ORCID ProfileDavid Raffelt, View ORCID ProfileChristopher J. Steele, Pierre-Olivier Quirion, Robert E. Smith, View ORCID ProfileStephen C. Strother, View ORCID ProfileGaël Varoquaux, View ORCID ProfileTal Yarkoni, Yida Wang, View ORCID ProfileRussell A. Poldrack
doi: https://doi.org/10.1101/079145
Krzysztof J. Gorgolewski
1Department of Psychology, Stanford University, Stanford, CA, 94305
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Fidel Alfaro-Almagro
13Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Oxford University, UK.
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Tibor Auer
15Department of Psychology, Royal Holloway University of London. Egham, UK
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Pierre Bellec
18Centre de Recherche de l’Institut Universitaire Gériatrique de Montréal
21Department of computer science and operations research, Université de Montréal, CA
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Mihai Capotă
20Parallel Computing Lab, Intel Corporation, Santa Clara, CA & Hillsboro, OR
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M. Mallar Chakravarty
22Douglas Mental Health University Institute, McGill University, Montreal, CA
23Department of Psychiatry McGill University, Montreal, CA
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Nathan W. Churchill
25Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michael’s Hospital
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R. Cameron Craddock
9Computational Neuroimaging Lab, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY
10Center for the Developing Brain, Child Mind Institute, New York, NY
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Gabriel A. Devenyi
22Douglas Mental Health University Institute, McGill University, Montreal, CA
23Department of Psychiatry McGill University, Montreal, CA
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Anders Eklund
2Department of Biomedical Engineering, Linköping University, Linköping, Sweden
3Department of Computer and Information Science, Linköping University, Linköping, Sweden
4Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden
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Oscar Esteban
1Department of Psychology, Stanford University, Stanford, CA, 94305
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Guillaume Flandin
8Wellcome Trust Centre for Neuroimaging, London, UK
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Satrajit S. Ghosh
27McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA
28Department of Otolaryngology, Harvard Medical School, Boston, MA
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J. Swaroop Guntupalli
12Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, US
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Mark Jenkinson
13Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Oxford University, UK.
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Anisha Keshavan
11UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, CA, US
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Gregory Kiar
5Center for Imaging Science, Johns Hopkins University, Baltimore, MD
6Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD
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Pradeep Reddy Raamana
16Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.
17Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
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David Raffelt
7Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
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Christopher J. Steele
22Douglas Mental Health University Institute, McGill University, Montreal, CA
23Department of Psychiatry McGill University, Montreal, CA
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Pierre-Olivier Quirion
18Centre de Recherche de l’Institut Universitaire Gériatrique de Montréal
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Robert E. Smith
7Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
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Stephen C. Strother
16Rotman Research Institute, Baycrest Health Sciences, Toronto, ON, Canada.
26Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
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Gaël Varoquaux
14Parietal team, INRIA Saclay Ile-de-France, Palaiseau, France
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Tal Yarkoni
19Department of Psychology, University of Texas at Austin, Austin, TX
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Yida Wang
20Parallel Computing Lab, Intel Corporation, Santa Clara, CA & Hillsboro, OR
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Russell A. Poldrack
1Department of Psychology, Stanford University, Stanford, CA, 94305
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Abstract

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 richness 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 20 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.

Author Summary Magnetic Resonance Imaging (MRI) is a noninvasive way to measure human brain structure and activity that has been used for over 25 years. There are hundreds MRI studies performed every year generating a substantial amount of data. At the same time, many new data analysis methods are being developed every year. The potential of using new analysis methods on the variety of existing and newly acquired data is hindered by difficulties in software deployment and lack of support for standardized input data. Here we propose to use container technology to make deployment of a wide range of data analysis techniques easy. In addition, we adapt the existing data analysis tools to understand and work with data in organized in a standardized way. We hope that this approach will enable researchers to access a wider range of methods when analyzing their data which will lead to accelerated progress in human neuroscience.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license.
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Posted October 20, 2016.
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BIDS Apps: Improving ease of use, accessibility and reproducibility of neuroimaging data analysis methods
Krzysztof J. Gorgolewski, Fidel Alfaro-Almagro, Tibor Auer, Pierre Bellec, Mihai Capotă, M. Mallar Chakravarty, Nathan W. Churchill, R. Cameron Craddock, Gabriel A. Devenyi, Anders Eklund, Oscar Esteban, Guillaume Flandin, Satrajit S. Ghosh, J. Swaroop Guntupalli, Mark Jenkinson, Anisha Keshavan, Gregory Kiar, Pradeep Reddy Raamana, David Raffelt, Christopher J. Steele, Pierre-Olivier Quirion, Robert E. Smith, Stephen C. Strother, Gaël Varoquaux, Tal Yarkoni, Yida Wang, Russell A. Poldrack
bioRxiv 079145; doi: https://doi.org/10.1101/079145
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BIDS Apps: Improving ease of use, accessibility and reproducibility of neuroimaging data analysis methods
Krzysztof J. Gorgolewski, Fidel Alfaro-Almagro, Tibor Auer, Pierre Bellec, Mihai Capotă, M. Mallar Chakravarty, Nathan W. Churchill, R. Cameron Craddock, Gabriel A. Devenyi, Anders Eklund, Oscar Esteban, Guillaume Flandin, Satrajit S. Ghosh, J. Swaroop Guntupalli, Mark Jenkinson, Anisha Keshavan, Gregory Kiar, Pradeep Reddy Raamana, David Raffelt, Christopher J. Steele, Pierre-Olivier Quirion, Robert E. Smith, Stephen C. Strother, Gaël Varoquaux, Tal Yarkoni, Yida Wang, Russell A. Poldrack
bioRxiv 079145; doi: https://doi.org/10.1101/079145

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