TY - JOUR
T1 - BIDS apps
T2 - Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods
AU - Gorgolewski, Krzysztof J.
AU - Alfaro-Almagro, Fidel
AU - Auer, Tibor
AU - Bellec, Pierre
AU - Capotă, Mihai
AU - Chakravarty, M. Mallar
AU - Churchill, Nathan W.
AU - Cohen, Alexander Li
AU - Craddock, R. Cameron
AU - Devenyi, Gabriel A.
AU - Eklund, Anders
AU - Esteban, Oscar
AU - Flandin, Guillaume
AU - Ghosh, Satrajit S.
AU - Guntupalli, J. Swaroop
AU - Jenkinson, Mark
AU - Keshavan, Anisha
AU - Kiar, Gregory
AU - Liem, Franziskus
AU - Raamana, Pradeep Reddy
AU - Raffelt, David
AU - Steele, Christopher J.
AU - Quirion, Pierre Olivier
AU - Smith, Robert E.
AU - Strother, Stephen C.
AU - Varoquaux, Gaël
AU - Wang, Yida
AU - Yarkoni, Tal
AU - Poldrack, Russell A.
N1 - Publisher Copyright:
© 2017 Gorgolewski et al.
PY - 2017/3
Y1 - 2017/3
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85016747642
U2 - 10.1371/journal.pcbi.1005209
DO - 10.1371/journal.pcbi.1005209
M3 - Article
C2 - 28278228
AN - SCOPUS:85016747642
SN - 1553-734X
VL - 13
JO - PLoS Computational Biology
JF - PLoS Computational Biology
IS - 3
M1 - e1005209
ER -