Literature DB >> 28278228

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

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


  41 in total

1.  The Extensible Neuroimaging Archive Toolkit: an informatics platform for managing, exploring, and sharing neuroimaging data.

Authors:  Daniel S Marcus; Timothy R Olsen; Mohana Ramaratnam; Randy L Buckner
Journal:  Neuroinformatics       Date:  2007

2.  Performing label-fusion-based segmentation using multiple automatically generated templates.

Authors:  M Mallar Chakravarty; Patrick Steadman; Matthijs C van Eede; Rebecca D Calcott; Victoria Gu; Philip Shaw; Armin Raznahan; D Louis Collins; Jason P Lerch
Journal:  Hum Brain Mapp       Date:  2012-05-19       Impact factor: 5.038

3.  Optimizing preprocessing and analysis pipelines for single-subject fMRI. I. Standard temporal motion and physiological noise correction methods.

Authors:  Nathan W Churchill; Anita Oder; Hervé Abdi; Fred Tam; Wayne Lee; Christopher Thomas; Jon E Ween; Simon J Graham; Stephen C Strother
Journal:  Hum Brain Mapp       Date:  2011-03-31       Impact factor: 5.038

4.  The effects of SIFT on the reproducibility and biological accuracy of the structural connectome.

Authors:  Robert E Smith; Jacques-Donald Tournier; Fernando Calamante; Alan Connelly
Journal:  Neuroimage       Date:  2014-10-12       Impact factor: 6.556

5.  Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

Authors:  Krzysztof Gorgolewski; Christopher D Burns; Cindee Madison; Dav Clark; Yaroslav O Halchenko; Michael L Waskom; Satrajit S Ghosh
Journal:  Front Neuroinform       Date:  2011-08-22       Impact factor: 4.081

6.  A test-retest fMRI dataset for motor, language and spatial attention functions.

Authors:  Krzysztof J Gorgolewski; Amos Storkey; Mark E Bastin; Ian R Whittle; Joanna M Wardlaw; Cyril R Pernet
Journal:  Gigascience       Date:  2013-04-29       Impact factor: 6.524

7.  The effects of FreeSurfer version, workstation type, and Macintosh operating system version on anatomical volume and cortical thickness measurements.

Authors:  Ed H B M Gronenschild; Petra Habets; Heidi I L Jacobs; Ron Mengelers; Nico Rozendaal; Jim van Os; Machteld Marcelis
Journal:  PLoS One       Date:  2012-06-01       Impact factor: 3.240

8.  Reproducibility of neuroimaging analyses across operating systems.

Authors:  Tristan Glatard; Lindsay B Lewis; Rafael Ferreira da Silva; Reza Adalat; Natacha Beck; Claude Lepage; Pierre Rioux; Marc-Etienne Rousseau; Tarek Sherif; Ewa Deelman; Najmeh Khalili-Mahani; Alan C Evans
Journal:  Front Neuroinform       Date:  2015-04-24       Impact factor: 4.081

9.  Automatic analysis (aa): efficient neuroimaging workflows and parallel processing using Matlab and XML.

Authors:  Rhodri Cusack; Alejandro Vicente-Grabovetsky; Daniel J Mitchell; Conor J Wild; Tibor Auer; Annika C Linke; Jonathan E Peelle
Journal:  Front Neuroinform       Date:  2015-01-15       Impact factor: 4.081

10.  The minimal preprocessing pipelines for the Human Connectome Project.

Authors:  Matthew F Glasser; Stamatios N Sotiropoulos; J Anthony Wilson; Timothy S Coalson; Bruce Fischl; Jesper L Andersson; Junqian Xu; Saad Jbabdi; Matthew Webster; Jonathan R Polimeni; David C Van Essen; Mark Jenkinson
Journal:  Neuroimage       Date:  2013-05-11       Impact factor: 6.556

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  84 in total

1.  A framework for evaluating correspondence between brain images using anatomical fiducials.

Authors:  Jonathan C Lau; Andrew G Parrent; John Demarco; Geetika Gupta; Jason Kai; Olivia W Stanley; Tristan Kuehn; Patrick J Park; Kayla Ferko; Ali R Khan; Terry M Peters
Journal:  Hum Brain Mapp       Date:  2019-06-07       Impact factor: 5.038

2.  Good practice in food-related neuroimaging.

Authors:  Paul A M Smeets; Alain Dagher; Todd A Hare; Stephanie Kullmann; Laura N van der Laan; Russell A Poldrack; Hubert Preissl; Dana Small; Eric Stice; Maria G Veldhuizen
Journal:  Am J Clin Nutr       Date:  2019-03-01       Impact factor: 7.045

3.  Reply to Brown and Behrmann, Cox, et al., and Kessler et al.: Data and code sharing is the way forward for fMRI.

Authors:  Anders Eklund; Thomas E Nichols; Hans Knutsson
Journal:  Proc Natl Acad Sci U S A       Date:  2017-04-18       Impact factor: 11.205

4.  The open diffusion data derivatives, brain data upcycling via integrated publishing of derivatives and reproducible open cloud services.

Authors:  Paolo Avesani; Brent McPherson; Soichi Hayashi; Cesar F Caiafa; Robert Henschel; Eleftherios Garyfallidis; Lindsey Kitchell; Daniel Bullock; Andrew Patterson; Emanuele Olivetti; Olaf Sporns; Andrew J Saykin; Lei Wang; Ivo Dinov; David Hancock; Bradley Caron; Yiming Qian; Franco Pestilli
Journal:  Sci Data       Date:  2019-05-23       Impact factor: 6.444

5.  NAPR: a Cloud-Based Framework for Neuroanatomical Age Prediction.

Authors:  Heath R Pardoe; Ruben Kuzniecky
Journal:  Neuroinformatics       Date:  2018-01

6.  Getting to know me better: An fMRI study of intimate and superficial self-disclosure to friends during adolescence.

Authors:  Nandita Vijayakumar; John C Flournoy; Kathryn L Mills; Theresa W Cheng; Arian Mobasser; Jessica E Flannery; Nicholas B Allen; Jennifer H Pfeifer
Journal:  J Pers Soc Psychol       Date:  2020-02-10

7.  Science in the cloud (SIC): A use case in MRI connectomics.

Authors:  Gregory Kiar; Krzysztof J Gorgolewski; Dean Kleissas; William Gray Roncal; Brian Litt; Brian Wandell; Russel A Poldrack; Martin Wiener; R Jacob Vogelstein; Randal Burns; Joshua T Vogelstein
Journal:  Gigascience       Date:  2017-05-01       Impact factor: 6.524

Review 8.  Progress toward openness, transparency, and reproducibility in cognitive neuroscience.

Authors:  Rick O Gilmore; Michele T Diaz; Brad A Wyble; Tal Yarkoni
Journal:  Ann N Y Acad Sci       Date:  2017-05-02       Impact factor: 5.691

9.  Ciftify: A framework for surface-based analysis of legacy MR acquisitions.

Authors:  Erin W Dickie; Alan Anticevic; Dawn E Smith; Timothy S Coalson; Mathuvanthi Manogaran; Navona Calarco; Joseph D Viviano; Matthew F Glasser; David C Van Essen; Aristotle N Voineskos
Journal:  Neuroimage       Date:  2019-05-12       Impact factor: 6.556

10.  Analysis of task-based functional MRI data preprocessed with fMRIPrep.

Authors:  Oscar Esteban; Rastko Ciric; Karolina Finc; Ross W Blair; Christopher J Markiewicz; Craig A Moodie; James D Kent; Mathias Goncalves; Elizabeth DuPre; Daniel E P Gomez; Zhifang Ye; Taylor Salo; Romain Valabregue; Inge K Amlien; Franziskus Liem; Nir Jacoby; Hrvoje Stojić; Matthew Cieslak; Sebastian Urchs; Yaroslav O Halchenko; Satrajit S Ghosh; Alejandro De La Vega; Tal Yarkoni; Jessey Wright; William H Thompson; Russell A Poldrack; Krzysztof J Gorgolewski
Journal:  Nat Protoc       Date:  2020-06-08       Impact factor: 13.491

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