1. QuNex—An integrative platform for reproducible neuroimaging analytics
- Author
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Jie Lisa Ji, Jure Demšar, Clara Fonteneau, Zailyn Tamayo, Lining Pan, Aleksij Kraljič, Andraž Matkovič, Nina Purg, Markus Helmer, Shaun Warrington, Anderson Winkler, Valerio Zerbi, Timothy S. Coalson, Matthew F. Glasser, Michael P. Harms, Stamatios N. Sotiropoulos, John D. Murray, Alan Anticevic, and Grega Repovš
- Subjects
neuroimaging ,data processing ,functional MRI ,diffusion MRI ,multi-modal analyses ,containerization ,Neurosciences. Biological psychiatry. Neuropsychiatry ,RC321-571 - Abstract
IntroductionNeuroimaging technology has experienced explosive growth and transformed the study of neural mechanisms across health and disease. However, given the diversity of sophisticated tools for handling neuroimaging data, the field faces challenges in method integration, particularly across multiple modalities and species. Specifically, researchers often have to rely on siloed approaches which limit reproducibility, with idiosyncratic data organization and limited software interoperability.MethodsTo address these challenges, we have developed Quantitative Neuroimaging Environment & Toolbox (QuNex), a platform for consistent end-to-end processing and analytics. QuNex provides several novel functionalities for neuroimaging analyses, including a “turnkey” command for the reproducible deployment of custom workflows, from onboarding raw data to generating analytic features.ResultsThe platform enables interoperable integration of multi-modal, community-developed neuroimaging software through an extension framework with a software development kit (SDK) for seamless integration of community tools. Critically, it supports high-throughput, parallel processing in high-performance compute environments, either locally or in the cloud. Notably, QuNex has successfully processed over 10,000 scans across neuroimaging consortia, including multiple clinical datasets. Moreover, QuNex enables integration of human and non-human workflows via a cohesive translational platform.DiscussionCollectively, this effort stands to significantly impact neuroimaging method integration across acquisition approaches, pipelines, datasets, computational environments, and species. Building on this platform will enable more rapid, scalable, and reproducible impact of neuroimaging technology across health and disease.
- Published
- 2023
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