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PLoS Comput Biol. 2017 Mar 9;13(3):e1005209. doi: 10.1371/journal.pcbi.1005209. eCollection 2017 Mar.

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

Author information

1
Department of Psychology, Stanford University, Stanford, California, United States of America.
2
Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Oxford University, Oxford, United Kingdom.
3
Department of Psychology, Royal Holloway University of London, Egham, United Kingdom.
4
Centre de Recherche de l'Institut Universitaire Gériatrique de Montréal, Montreal, Canada.
5
Department of computer science and operations research, Université de Montréal, Montreal, Canada.
6
Parallel Computing Lab, Intel Corporation, Santa Clara, CA & Hillsboro, Oregon, United States of America.
7
Douglas Mental Health University Institute, McGill University, Montreal, Canada.
8
Department of Psychiatry McGill University, Montreal, Canada.
9
Keenan Research Centre of the Li Ka Shing Knowledge Institute, St. Michael's Hospital, Ontario, Canada.
10
Department of Neurology, Boston Children's Hospital, Boston, Massachusetts, United States of America.
11
Computational Neuroimaging Lab, Center for Biomedical Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, New York, United States of America.
12
Center for the Developing Brain, Child Mind Institute, New York, New York, United States of America.
13
Department of Biomedical Engineering, Linköping University, Linköping, Sweden.
14
Department of Computer and Information Science, Linköping University, Linköping, Sweden.
15
Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
16
Wellcome Trust Centre for Neuroimaging, London, United Kingdom.
17
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.
18
Department of Otolaryngology, Harvard Medical School, Boston, Massachusetts, United States of America.
19
Department of Psychological and Brain Sciences, Dartmouth College, Hanover, New Hampshire, United States of America.
20
UC Berkeley-UCSF Graduate Program in Bioengineering, San Francisco, California, United States of America.
21
Center for Imaging Science, Johns Hopkins University, Baltimore, Maryland, United States of America.
22
Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America.
23
University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Zurich, Switzerland.
24
Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada.
25
Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.
26
Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia.
27
Parietal team, INRIA Saclay Ile-de-France, Palaiseau, France.
28
Department of Psychology, University of Texas at Austin, Austin, Texas, United States of America.

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.

PMID:
28278228
PMCID:
PMC5363996
DOI:
10.1371/journal.pcbi.1005209
[Indexed for MEDLINE]
Free PMC Article

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