| Literature DB >> 28278228 |
Krzysztof J Gorgolewski1, Fidel Alfaro-Almagro2, Tibor Auer3, Pierre Bellec4,5, Mihai Capotă6, M Mallar Chakravarty7,8, Nathan W Churchill9, Alexander Li Cohen10, R Cameron Craddock11,12, Gabriel A Devenyi7,8, Anders Eklund13,14,15, Oscar Esteban1, Guillaume Flandin16, Satrajit S Ghosh17,18, J Swaroop Guntupalli19, Mark Jenkinson2, Anisha Keshavan20, Gregory Kiar21,22, Franziskus Liem23, Pradeep Reddy Raamana24,25, David Raffelt26, Christopher J Steele7,8, Pierre-Olivier Quirion15, Robert E Smith26, Stephen C Strother24,25, Gaël Varoquaux27, Yida Wang6, Tal Yarkoni28, Russell A Poldrack1.
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.Entities:
Mesh:
Year: 2017 PMID: 28278228 PMCID: PMC5363996 DOI: 10.1371/journal.pcbi.1005209
Source DB: PubMed Journal: PLoS Comput Biol ISSN: 1553-734X Impact factor: 4.475