BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods
By Krzysztof J. Gorgolewski, Fidel Alfaro-Almagro, Tibor Auer, Lune P Bellec, M. Capotă, M. Mallar Chakravarty, Nathan William Churchill, Alexander Li Cohen, R. Craddock, Gabriel A. Devenyi and 21 more. bioRxiv, 2016
311 citations recorded by the source corpus.
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 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 22 ready to use BIDS Apps, packaging a diverse set of commonly used neuroimaging algorithms. Author Summary Magnetic Resonance Imaging (MRI) is a non-invasive way to measure human brain structure and activity that has been used for over 25 years. There are thousands 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 interface with data 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.
Subfields: Health Informatics, Health, Toxicology and Mutagenesis
View Paper: https://www.semanticscholar.org/paper/379a9763b0cfcbf0a6bd9771def28ede1b318a79
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In Health, Toxicology and Mutagenesis
Citations in the corpus
- The OpenNeuro resource for sharing of neuroscience data (2021, unknown): “Interoperable: The data and metadata use the BIDS standard to ensure accessible representation and interoperation with analysis workflows, such as BIDS Apps ( Gorgolewski et al., 2017 ).”
- MRIQC: Advancing the automatic prediction of image quality in MRI from unseen sites (2016, methodology): “We provide four different installation options: 1) using the source code from the GitHub repository; 2) using the PyPI distribution system of Python; 3) using the poldracklab/mriqc Docker image; or 4) using BIDS-Apps [28].”
- Machine Learning for Precision Psychiatry: Opportunities and Challenges. (2017, background): “In general, agreement on machine-readable data structures will become increasingly useful for machine learning applications (47).”
- Singularity: Scientific containers for mobility of compute (2017, background): “Several groups across genetics [21, 22], neuroscience [23], and others [24, 25] introduced container-based scientific analyses, and this was a reflection of two things.”
- NeuroStorm: Accelerating Brain Science Discovery in the Cloud (2018, methodology): “Integration of Standards for Data and Computational Pipelines The Boutiques [15] descriptive command-line framework, supported by a Python package, has been extended to include a BIDS app [16] importer, that generates descriptors from BIDS applications.”