RT Journal Article SR Electronic T1 BIDS Apps: Improving ease of use, accessibility and reproducibility of neuroimaging data analysis methods JF bioRxiv FD Cold Spring Harbor Laboratory SP 079145 DO 10.1101/079145 A1 Krzysztof J. Gorgolewski A1 Fidel Alfaro-Almagro A1 Tibor Auer A1 Pierre Bellec A1 Mihai Capotă A1 M. Mallar Chakravarty A1 Nathan W. Churchill A1 R. Cameron Craddock A1 Gabriel A. Devenyi A1 Anders Eklund A1 Oscar Esteban A1 Guillaume Flandin A1 Satrajit S. Ghosh A1 J. Swaroop Guntupalli A1 Mark Jenkinson A1 Anisha Keshavan A1 Gregory Kiar A1 Pradeep Reddy Raamana A1 David Raffelt A1 Christopher J. Steele A1 Pierre-Olivier Quirion A1 Robert E. Smith A1 Stephen C. Strother A1 Gaël Varoquaux A1 Tal Yarkoni A1 Yida Wang A1 Russell A. Poldrack YR 2016 UL http://biorxiv.org/content/early/2016/10/05/079145.abstract AB 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 19 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms.